PROCEEDINGS OF THE AMERICAN SOCIETY FOR COMPOSITES-THIRTY-EIGHTH TECHNICAL CONFERENCE
Reduction in Computational Cost of Progressive Failure Analysis
Designing aircraft structures requires efficient modeling approaches to iterate on multiple structural configurations to achieve an optimal design. Typically, damage tolerance is not considered at the design stage because of the high computational cost in its implementation within a finite element modeling approach. Therefore, analytical or empirical approaches are often used to size critical damage-tolerant structures once an optimal design is determined. In this study, the Progressive Release eXplicit Virtual Crack-Closure Technique (PRX-VCCT) is assessed for its capability to costeffectively evaluate skin-stringer separation of a blade-stiffened panel that is subjected to seven-point bend loads. An initial verification study was performed to evaluate PRX-VCCT to accurately simulate skin-stringer separation with respect to existing cohesive element approaches. Furthermore, the influence of element size, ranging from 0.10 in. to 0.40 in., on the total computational time using the PRX-VCCT is investigated. The results indicate that the PRX-VCCT can be used to accurately simulate skin-stringer separation using large element lengths (0.40 in.). Additionally, a significant reduction in the computational time to simulate skin-stringer separation is observed using the PRX-VCCT. Large-scale progressive damage analysis using PRXVCCT can be implemented early in the design cycle of composite structures without requiring a global-to-local modeling approach.
Tailored Fiber Placements for Notch Sensitivity Study Using 3D Printing
Due to uninterrupted load transfer, continuous fiber composites have greater strength, stiffness, and toughness than nano, micro, and short fiber composites. Recent developments in 3D printing facilitated rapid manufacturing of thermoplastic composites with continuous fiber reinforcements. Such composites manufactured for primary structural applications are frequently subjected to perforations, notches, and fillets during joining and assembly processes, resulting in stress concentrations and, consequently, premature failure. As such, tailoring/steering the continuous fibers around the notch is anticipated to deliver better performance in strength and toughness as the fiber are not cut during the drilling process. In this investigation, three different cases were studied namely (i) Un-notched continuous glass fiber reinforced nylon composite (ii) Notched continuous glass fiber reinforced nylon composite and (iii) Steered continuous glass fiber around the notch. It was observed that drilling a circular notch size of size 0.3 (notch diameter/width of sample) can reduce the strength and strain to failure by 48 and 39 percent respectively. Nevertheless, samples with steered fiber around the notch manifested 22 percent improvement in strength and 38 percent improvement in toughness compared to the drilled samples. Overall, this technique provides an initial thumb-rule in enhancing the mechanical performance of continuous fiber reinforced composites.
Experimental-Computational Characterization of Fiber-to-Fiber Interactions in Glass Macro Fiber Composites
Effects of inter-fiber distance and angular orientation on the fiber-matrix interface debonding are investigated using a hybrid experimental-computational approach. Model composite samples are fabricated using two glass macro fibers embedded in a clear epoxy resin and then subjected to remote tensile loads. The distance and angular position between the two fibers in the epoxy are varied systematically to cover a wide range of inter-fiber distances and orientations. Specifically, the model composites are designed to include fiber-to-fiber angles ranging from 0° to 90° in 15° increments. Displacement and strain fields developed in the vicinity of the fiber-matrix interface are measured by high-magnification digital image correlation (DIC). The initiation and propagation of debonding at the fiber-matrix interface are characterized as a function of far-field stress, inter-fiber distance and angle. A finite element simulation framework is established and calibrated by the experimental measurements first. Correlations between local and global stress-strain fields are then identified from the experimental measurements supplemented by finite element simulations. Results obtained herein indicate that the spacing and angular orientation between adjacent fibers affect the interface debonding initiation and propagation. However, the interfiber distance has a more consequential effect on the debonding process, i.e., the smaller the distance the larger the fields intensity. The results obtained from the hybrid approach here are further analyzed to identify the sources of uncertainty quantification. The hybrid approach proposed and discussed in this work provides a systematic methodology for the quantitative analysis of fiber-matrix interface debonding mechanisms leading to transverse cracking in unidirectional composites.
Weight Effect of Buckled Composite Stiffened Panels Under Pure Shear Loading
Composite hat-stiffened skin panels are of great interest to modern aircraft design because of their high strength and stiffness. This work aims to computationally predict damage within hatstiffened composite panels under pure shear loading. As the panels enter the post-buckling regime, matrix cracking, fiber rupture and delamination are crucial. The Enhanced Schapery Theory can capture the intraply damage while the Cohesive Zone Model delamination between the skin plies and debonding between skin-hat interfaces. For hat-stiffened panels, the four, three, and two stringers configurations experienced damage initiation at 166.6%, 295.0%, and 739.6% of the buckling load, respectively. Matrix cracking initiated in the panels least stiff to transverse loading, while panels more resistant to shear see debonding at the skin-hat interface initiated first. All configurations predicted delamination at the skin ply 1-ply 2 interface as the last damage mode before penetrating deeper into the skin. Debonding between the stringers and the skin was predicted as the primary driver for ultimate failure.
3D Printing of Thermally Curable Resin/Continuous Carbon Fiber Composites with Interpenetrating Polymer Interlayer
3D printing of continuous carbon fiber composites has been a popular research focus in recent years, since it enables the design freedom and the tuning of structural properties. Currently, the existing 3D printing methods of composites with thermoplastics and photocurable resins lack comparable mechanical performances to the thermally curable thermoset resins. But the thermally curable thermoset resin as a matrix is also limited in the long thermal curing time and the difficulty in maintaining structures without mold or high pressure. In this work, we proposed our own 3D printing strategy of the thermally curable thermoset resin based continuous carbon fiber composites, which is capable of producing rapidly and maintaining the geometrical stability. It is achieved by coating dual-cure resin on the surfaces of the fiber/resin laminates during 3D printing, and forming the interpenetrating polymer network (IPN) at interlayers between the laminates after post-thermal treatment. This strategy was demonstrated in our self-developed robotic-based 3D printer, which contains the functions of thermoset resin impregnation, dual-cure resin coating, and compaction. The current level of mechanical properties of the printed composites has achieved tensile strength of 1132.69 MPa, flexural strength of 1080.37 MPa, and interlaminar shear strength of 48.75 MPa.
Enhanced Lightning Strike Protection using Vertically Oriented Carbon Fiber Melded with Conventional Carbon Fiber-Reinforced Composite and its Validation Through Damage Analysis
Lightning strike protection (LSP) is one of the prime factors in aerospace and wind industries concerning safety, enhanced service life, and reduced downtime. To ensure better LSP, high electrical conductivity is required to dissipate the current, which is always a challenge for polymer composites due to the inherent insulating nature of the polymer matrix. Conventional carbon fiber-reinforced composites (CFRP) offer electrical conductivity in the planar direction while the vertical i.e. through-thickness conductivity still remains a challenge. Having been motivated by this fact, we have fabricated CFRP interleaved with vertically oriented CF (Z-fiber) for the lightning strike test (100 kA). A paint was applied to mimic the actual service condition of the composite laminates. We have prepared two Z-fiber composites: (a) Z-1 containing one Z-fiber layer on the top along with conventional CF layers and (b) Z-5 containing five interleaved Z-fiber layers and compared the properties with conventional CFRP (Z-0). Interestingly, even a single Z-fiber layer (Z-1) showed lower damage (visual damage diameter 22 mm) than Z-0 (visual damage diameter 26 mm). Z-5 displayed the lowest damage (visual damage diameter 16.7 mm), which was further confirmed by cross-sectional optical microscopy. Improved LSP was attributed to the higher through-thickness electrical conductivity in the case of Z-5 (9 times with respect to Z-0) reflecting a lower electrical anisotropy for Z-fiber composites. The residual mechanical property after the lightning test was analyzed through the flexural test, and the retention of flexural strength and modulus was 66% and 86%, respectively for Z-5 showing a significant improvement in comparison to Z-0 (>40% for both).
Predicting Deformation Response and Failure of 3D Textile Composites Using Realistic Micromechanical Models
3D woven composites are increasingly being utilized to construct structural components due to their ability to obtain high fiber volume fractions, potential for improved interlaminar properties, and ability to reduce manufacturing time via automated formation of component-shaped preforms. Properties of the 3D woven composite are determined by weaving architecture and the constituent material system. A detailed representation of its woven unit cell architecture is thus sought to closely capture local variations and imperfections arising during the weaving process, in order to predict mechanical properties with greater accuracy. Accurate mechanical property prediction can reduce the material selection cost and cycle time by minimizing coupon fabrication and testing. In this paper, a complex 3D woven angle interlock (3DWAI) unit cell is first modeled using DEA Fabric and Composite Analyzer (DFCA). Cross-section slices from the numerical model are compared to micrographs from the corresponding test sample to highlight the important meso-scale features that are captured by the model in a detailed fashion. Then a progressive damage model based on a gradual stiffness reduction technique is implemented to predict the tensile, compressive and shear stress-strain responses as well as failure strengths of the 3DWAI unit cell. The numerical predictions are compared to the test results and a discussion on the failure mechanisms is presented. The results demonstrate that the proposed modeling methodology not only captures the actual microstructures, but also predicts properties of 3D woven composites with a high degree of accuracy.
The Effect of Apparent Crack-Tip on Predictive Capabilities of Resin Infused Composite Elements Under Pull-Off Loading
It is often seen that the nature of delamination and disbond in composite structures is different than that observed within coupon-level experiments that are used to design the structure. These effects are exacerbated in non-unidirectional tape composite laminates in which the local architectures can influence the crack growth behavior. For these materials, the assumptions of linear elastic fracture mechanics (LEFM) are challenged by the influence of the hierarchical nature of the material resulting in disparate apparent crack growth behavior. In this paper, resin infused and stitched resin infused sub-element models are compared to experimental data to study the effects of apparent crack tip behavior on predictive capability of the model.
Effect of Heat Curing Temperature for CFRP Fabricated by Electrodeposition Resin Molding Method
The new electrodeposition resin molding (EDRM) technique is regarded as a rapid and effective way to produce composite materials. In this study, the composite preparation was done using this technique. The heat curing stage is one of the key steps in this process. The optimization of the many conditions was required because it is a new method. The major objective of this study is to establish the ideal heat curing temperature and time for producing CFRP of the highest grade. In this investigation, two alternative temperature profiles were used. One measured 215°C, the other 230°C. Three different heat curing times—4 hours, 6 hours, and 8 hours—were used for each profile. Static and dynamic characteristics of the prepared CFRP were assessed to determine the impact of these heat curing temperatures and treatment times. Fourpoint bending tests were done for the static properties, and vibration tests were done for the dynamic qualities to determine the natural frequency and damping. Even though the various heat treatment methods had little impact on vibration characteristics, they had a big impact on bending qualities. The specimens that were held in the oven for 8 hours at 215°C to produce the highest bending strength, however at 230°C, the maximum bending strength was found when it was kept for 6 hours in the oven for treatment.
Mechanical Properties of Composites Containing Exfoliated-Graphite/Epoxy Sensors
One structural health monitoring (SHM) approach involves the embedding of sensors within a composite. However, embedded sensors may act as defects and could affect the composite’s mechanical properties. The objective of this study is to determine the effects of embedding exfoliated graphite (EG)/epoxy sensors on the mechanical properties of the hosting composite system. EG/epoxy composite sensor strips with two different volume fractions were fabricated. Two sets of tensile test specimens were fabricated by embedding the sensors in the epoxy system along the length and width directions of the test specimens. To develop a data baseline, EG/epoxy tensile test specimens were also fabricated. Tensile tests were performed on the samples and the results were analyzed to determine the effects of the embedded sensors on the composite material’s elastic modulus and tensile strength. The addition of EG slightly increased the elastic modulus and tensile strength of the samples. For test samples containing the sensor strips, the orientation of the sensors has a significant effect on the composite’s mechanical properties. Samples containing sensors along the widthwise direction were observed to have a lower tensile strength, and this is attributed to the observed delamination along the edge of the sensors.
Matrix Crack Detection in Cross-ply CFRP Laminates with an FBG Sensor Based on Optical Frequency Domain Reflectometry
Carbon Fiber Reinforced Plastic (CFRP) composites are expected to be used in liquid hydrogen (LH2) tanks for hydrogen-powered aircraft and reusable launch vehicles due to their superior specific strength and specific stiffness and their suitability for weight reduction. However, in cryogenic environments such as LH2 temperature, large thermal stresses occur due to the difference in coefficient of thermal expansion (CTE) between 0° and 90° layers as well as between carbon fiber and matrix resin. In addition, low temperature embrittlement occurs at the fiber/resin interface and in the resin itself. Therefore, matrix cracks propagate at much lower tensile strains than at room temperature condition. Since matrix cracks are pathways for gas leakage, it is important to monitor their initiation and evolution. Fiber optic sensors are lightweight, small in diameter, and flexible, making them easy to embed in CFRP. They have the advantage of having little effect on the mechanical properties when embedded in CFRP. Fiber Bragg Grating (FBG) sensors can measure strain with high accuracy, and their application to structural health monitoring is being investigated. In general, FBG sensors are used for single-point measurement or quasi-distribution measurement by multiplexing multiple FBGs on a single optical fiber. On the other hand, a distribution measurement method that applies optical frequency domain reflectometry (OFDR) to FBG sensors has been developed. However, previous studies have been limited to measuring the spatial distribution of strain, and there are no examples of detailed measurements of the location of matrix cracks in CFRP. This study investigates the applicability of the OFDR-FBG method for the detection of matrix cracks in CFRP laminates. An FBG sensor of 100 mm gauge length is embedded in a cross-ply CFRP specimen. The specimens are subjected to tensile loading. Transverse matrix cracks in the 90° ply are observed at the edge of thespecimen using an optical microscope and an X-ray inspection system. The results confirm that matrix crack propagation can be successfully detected as a strain change at low matrix crack densities. The matrix crack positions detected by the FBG sensor are directly compared with those obtained from the microscopic observation, and the difference is generally less than 2%. It is demonstrated that the matrix cracks can be detected with high accuracy using FBG sensors based on the OFDR method. The OFDR-FBG system can detect cracks with high accuracy in areas where the crack density is relatively low. On the other hand, when a large number of cracks are generated, it is difficult to distinguish individual cracks due to the flattening of the measured strain.
Ultrasonic Welding of Glass Fiber Reinforced Vitrimer Composites
The welding of composites has become a crucial step in the production of complex composite parts. Typically, various welding and joining techniques are used to manufacture composite assemblies. However, ultrasonic welding is one of the most popular methods for welding thermoplastic composites and cannot be used for composites with a thermosetting matrix. This study employed ultrasonic welding process for fiber-reinforced polymer composites with a dynamic covalent adaptive network (CAN). We used a thermosetting polymeric network with an associative dynamic CAN, commonly known as vitrimers; the dynamic nature of these polymers makes them reprocessable, recyclable, and reusable. These polymers can be crosslinked like thermosets but flow as thermoplastics at elevated temperatures. Thin composites were fabricated by reinforcing glass fibers into the vitrimer polymeric matrix and then welded together using ultrasonic welding. This work represents the first demonstration of welding vitrimer glass fiber-reinforced composites (vGFRC). The vGFRC matrix employed transesterification molecular exchange reactions to initiate chain mobility, leading to interlocking and rearrangement reactions on the bondline during the welding process. We evaluated the mechanical, chemical, and morphological properties of welded lap joints before and after mechanical testing. Shear strengths of 10 MPa were observed for vGFRC, indicating good weldability properties of vitrimer surfaces. The reprocessable nature of these composites was evaluated by repeated testing of lap shear strength followed by ultrasonic welding over five cycles. Additionally, we evaluated the surface functionality and atomic percentage on the fractured surface using FTIR and XPS, respectively. This exciting discovery shows that high frequency and pressure can be used to weld and reprocess polymers with dynamic molecular networks by exploiting molecular fusion and rearrangement reactions at the bondline.
Critical Progressive Damage Analysis Model Features for Low-Velocity Impact on Thermoset and Thermoplastic Panels
A previous verification and validation framework evaluated the ability of various progressive damage analysis (PDA) tools to predict the mechanical response and damage state in post-buckled stiffened aerospace structures composed of fiberreinforced thermoset composite materials. Herein, the ability of PDA tools to predict damage in thermoplastic composite materials subject to low-velocity impact (LVI) loading has been assessed. LVI tests and analyses have been conducted for similar panels, comprising thermoset or thermoplastic composite materials. Preliminary test/analysis correlations revealed that using the same combination of PDA model features and finite element model-building guidelines for the thermoset and thermoplastic LVI specimens resulted in underprediction of matrix crack lengths and delaminated area in the thermoplastic analyses despite yielding good correlations for the thermoset specimens. In this paper, the quality of the test/analysis correlations for analyses of thermoplastic LVI specimens performed with different combinations of PDA model features using the NASA CompDam material model are presented. Model features that were assessed in terms of effect on the quality of the test/analysis correlation include the representation of damageable interfaces, residual thermal stresses, and fiber damage.
Properties of Deconstructable Frontally Cured Fiber-Reinforced Thermoset Composites
Fiber-reinforced thermoset polymer matrix composites (FRPCs) possess the chemical, physical, and mechanical properties required for applications in critical industries such as defense, transportation, and energy. However, thermoset FRPCs lack sustainable end-of-life management strategies that recapture their desirable thermomechanical properties. Frontal curing with cleavable comonomers is a promising strategy to extend the lifecycle of constituent materials used in FRPCs by decreasing manufacturing cost and improving end-of-life management with little impact on thermomechanical performance. Here, we demonstrate energy efficient, out-of-autoclave manufacturing and fiber reclamation in high-performance carbonfiber/ poly(dicyclopentadiene) (CF/pDCPD) FRPCs. Through vacuum assisted resin transfer molding (VARTM) and through thickness frontal curing, we produce deconstructable high-performance (Vf ~ 50 %, Vv < 2 %) FRPCs with glass transition temperatures over 140°C using four orders of magnitude less energy than conventional bulk curing. We achieve chemical deconstruction by cleaving silyl-ether-containing comonomers and crosslinkers incorporated in the matrix. We recover the oligomeric fragments of the matrix and the in-tact woven fibers. The reclaimed fibers have excellent integrity and show minimal visual evidence of matrix residue. The thermomechanical performance of the deconstructable FRPCs presented is a step towards efficiently manufacturing sustainable FRPCs that do not compromise performance.
Experimental and Numerical Study for Hat-Stiffener Separation During Low Velocity Impact
Barely Visible Impact Damage (BVID) is known to be a potential hazard to composite structures which are prevalent in the aerospace industry. Low Velocity Impact (LVI) events can cause composite structures to undergo large deformations and experience delamination between laminae which reduces their compression load carrying capability. Understanding the driving factors for this damage event is essential for safe design of composite structures. Physical experiments on complex composite structures are expensive and there is a constant effort in the industry to develop accurate numeric models that capture delamination events. In addition to LVI events that cause interlaminar delamination, it is also important to study the failure that occurs between composite structures that are bonded together. In this study, the interface delamination between a hat stiffener and a composite skin coupon under impact loading will be investigated. The hat stiffener and skin are made of IM7/977-3 material and are co-cured during the manufacturing process. The goal of the experiments is to understand the method in which debonding occurs in a physical sense to assist numerical modeling efforts. Dynamic tests are compared to static tests to observe the effect of force oscillations during the experiment. A finite element model was developed to recreate both static and dynamic experiments. The numerical model serves to provide additional insights regarding the failure events occurring in the hat stiffened coupon.
A Theory-Guided Machine Learning Method for Cure Cycle Optimization to Minimize Process-Induced Deformations in Composites
One of the most prevalent challenges faced in aerospace manufacturing is the accurate prediction, control, and mitigation of residual stresses and resulting process-induced deformations (PIDs) in composites. Unwanted dimensional changes in composite parts can cause significant geometry mismatches during aerostructure assembly, leading to decreased throughput and a loss of structural performance. In recent decades, process simulation tools have been developed to facilitate predictions and mitigations of PIDs through process optimization as well as methods such as tool compensation. However, such numerical approaches often rely on time-consuming, expensive, and deterministic characterization and modelfitting techniques. As a result, simulation tools may be error-prone in industrial settings, making PID predictions unreliable. Therefore, manufacturers rely on laborintensive methods, such as shimming, to compensate for geometry mismatches during the assembly process. This paper presents an alternative methodology to predict and minimize PIDs in composites without using process simulation. The proposed method is solely based on a limited amount of element-level experimental tests and theory-guided machine learning (TGML). Experimental methods include autoclave-curing of L-shaped laminates with different cure cycles and quantifying the resulting PIDs using laser profilometry. Probabilistic ML models are then built to correlate temperature cycles directly to PIDs using Gaussian Process Regression (GPR) guided by the closed-form theory available for PID predictions. Finally, the theory-guided ML models are iteratively calibrated using additional targeted tests specified by the GPR algorithm to efficiently converge on an optimal cycle that minimizes PIDs and satisfies cost specifications. The proposed ML-based approach is a generalizable probabilistic method to optimize process parameters and mitigate PIDs without using expensive process simulations or conducting exhaustive characterization experiments.
Overall Properties of Polymer Matrix Composites at High Temperatures: Modeling and Application to the Lightning Strike Problem
In this work, a micromechanics-based model for determining high-temperature thermophysical properties of carbon fiber reinforced polymer (CFRP) composites undergoing pyrolysis is presented. The model accounts for the mass loss and material phase changes. Material phase changes include emergence of the secondary char and gas phases in the polymer matrix. First-order Arrhenius kinetics is used to model polymer pyrolysis. The model also accounts for the temperatureand heating rate-dependent volume fractions of the polymer, char, and pyrolysis gas phases. Temperature- and heating rate-dependent representative volume elements (RVEs) of evolving microstructures were generated and numerical homogenization was performed to determine overall thermophysical properties of the CFRP composites. The micromechanics-based models were embedded into the finite element analysis (FEA)-based multiphysics modeling of lightning strike damage in CFRP composites. Computational studies were performed to analyze lightning strike induced thermal damage in a CFRP composite.
This study presents the derivation of the three-dimensional elastic stress field is derived for an elastic medium that contains a spherical inclusion composed of a functionally graded material (FGM). The material properties for the matrix phase are uniform, while those for the FGM inclusion are assumed to vary linearly. The FGM-matrix medium is subject to constant strain at the far fields. First, the elastic field subject to uniform hydrostatic strains at the far-field is analytically solved. Subsequently, the elastic field subject to uniform deviatoric strains at the far-field is sought and is solved semi-analytically by converting the Navier equation for the displacement into a set of two ordinary differential equations which can be solved using the method of weighted residuals. Numerical examples show that the stress distribution is continuous at the FGM-matrix interface.
Local Deformation and Fracture Mechanisms in Methacrylic Composites at the Fiber-Matrix Level: Insights from Nanoscale Digital Image Correlation
Unidirectional glass fiber-reinforced methacrylic composite specimens were subjected to transverse compression testing within a scanning electron microscope (SEM). Strain localization phenomena occurring at the fiber-matrix level were analyzed via nanoscale digital image correlation (nano-DIC). A finite number of 2- fiber arrangements were identified in the composite in terms of the orientation of the fiber pair with respect to the uniaxially-applied load. Two of these were characterized experimentally by nano-DIC. Consistent and repeatable deformation patterns were observed within both test configurations, giving confidence in the relevance of focusing on the orientation of fiber pairs with respect to the macroscopic loading direction for predicting the deformation (and failure) behavior of fiber-reinforced polymer composites at the constituent level.
Experimental Study of the Pure Bypass Structural Response of Composite Structure when Subjected to Electrically Induced Damage
In modern aircraft, the design of lightning damage tolerant composite structure is an area of continued interest. In this work, a filled hole compression (FHC) experimental data set was created to demonstrate the impact that electrically induced damage has on the pure bypass residual strength of composite laminates. A scaled ARP5412 A-waveform current-pulse is used to induce electrical damage in the coupons. Following the electrical test, the articles underwent a series of inspections and structural testing. Inspection data is shown at various points in the test plan and normalized test data and trends are discussed. Multiphysics models were created and normalized comparisons to test data are made.
Prediction of a Failure Envelope of Short Fiber Reinforced Polymer Composites (SFRPs) Using Artificial Neural Network
Short fiber reinforced polymer composites (SFRPs) have become a material of interest due to their high stiffness-to-density ratio, durability, and cost-effective manufacturing of intricate parts. The modeling of an SFRP at the microscale involves complex homogenization techniques and sophisticated algorithmic implementations. The failure envelope of an SFRP gives a decision boundary for safety and failure under multiaxial loading. Additionally, the expansion and translation of the failure envelope describe the plastic behavior under monotonic and cyclic loading. Unlike isotropic materials, the stress tensor cannot be split into hydrostatic and deviatoric parts. It limits a formal mathematical theory for failure criteria for SFRPs. In the present work, an artificial neural network (ANN) is used to predict the failure envelope for a polyamide-glass SFRP specimen under biaxial loading. The data sets for training and validation are taken from the First Pseudo grain Failure (FPGF) model implemented using commercial finite element software. A noise in terms of randomly generated points near the failure curve is used as the test data. The stress or the strain values corresponding to the ANN predictions falling within a defined threshold range are plotted to obtain the failure envelope.
Enhancing Polylactic Acid (PLA) for 3D Printing with Cellulose Nanofibers via Twin Screw Melt Extrusion
In this study, cellulose nanofiber (CNF) reinforced polylactic acid (PLA) filaments were made via melt extrusion for 3D printing applications. The use of CNF reinforcement may enhance the PLA's mechanical attributes, making it a better material for a variety of 3D printing applications. In order to create the nanocomposites, a master batch of PLA and CNFs was premixed, and the CNFs were subsequently diluted throughout the extrusion process to final concentrations of 1, 3, and 5 wt%. The dilution was done to evaluate how the morphological and mechanical characteristics of the composites would be affected by different CNF concentrations. The findings demonstrated that adding 3 wt. % CNF greatly improved the mechanical characteristics of the PLA composites. In particular, the flexural strength rose by 60.2%, the compressive strength rose by 62.7%, and the tensile strength rose by 77.7%. These results show that the melt extrusion of PLA filaments reinforced with CNF is a practical method for creating nanocomposites with enhanced mechanical characteristics for 3D printing applications. The study's conclusion emphasizes how CNF reinforcement may be used to enhance the mechanical characteristics of PLA for 3D printing applications. The findings may be useful for researchers and businesses in the 3D printing and materials science fields, and they may also aid in the creation of more sophisticated and environmentally friendly 3D printing materials.
Processing Temperature Effect on Failure Behavior of Unidirectional Thermoplastic Polymer-fiber-reinforced Polymers (PFRPs)
This study aimed to investigate the influence of processing temperature on the mechanical and morphological properties of unidirectional (UD) thermoplastic polymer-fiber-reinforced polymers (PFRPs). These composites are known for their high recyclability and sustainability. The research focused on UD UHMWPE-polymer-fiber-reinforced HDPE composites as a specific example. To achieve this objective, UD thermoplastic PFRPs were produced through filament winding and hot-pressing techniques, employing five distinct processing temperatures within the range spanning from the melting onset temperature of the polymer matrix to the melting peak temperature of the reinforcing polymer fiber. By conducting the uni-axial tensile tests on the UD UHMWPE-polymer-fiberreinforced HDPE composites fabricated at different processing temperatures, it was shown that the optimal longitudinal tensile properties of the composites, comparable with glassfiber- reinforced thermoset or thermoplastic polymers (GFRPs or GFRTPs), can be achieved when the processing temperature does not significantly exceed the melting onset temperature of the reinforcing polymer fiber. However, when the processing temperature exceeds this threshold, the mechanical properties of the composites are significantly reduced, as evidenced by the transition in the failure morphology from the presence of significant splitting cracks to the occurrence of plastic necking due to the complete melting of the reinforcing polymer fibers in a composite. Particularly, the ductile behavior of the optimal thermoplastic PFRPs investigated in this study is superior than that of carbon-fiberreinforced thermoset or thermoplastic polymers (CFRPs or CFRTPs) and even GFRPs and GFRTPs. This study not only provides valuable insights into the proper fabrication of highperformance thermoplastic PFRPs but also offers useful experimental data that can aid in the validation and development of computational models, particularly those related to processing modeling.
Progressive Failure Analysis of Fiber Steering Composite Structures with a Hole
The application of fiber steering to composite structures is expected to reduce the stress concentration around a hole and to improve overall strength. The objective of this study is to establish an optimal design method for fiber steering composite structures with an open hole, with the consideration of damage progression. In this study, fiber steering is applied to 0° layers of a panel with an open hole under uniaxial tensile load by aligning the fiber steering direction to the maximum principal stress direction. Parametric studies of 1500 panel models with different hole geometries are performed by finite element analysis for both quasi-isotropic models and fiber steered models. The effect of the geometry change of the hole on failure load of the composite structure is investigated with progressive failure analysis based on Hashin’s failure criteria. In addition, the effect of hole geometry on performance of the fiber steering is also investigated. In most models, two stages of damage progression are observed. Result of the parametric study shows that failure load has increased with decreasing curvature of the hole. The smaller curvature of the hole around the point of origin of the failure reduces stress concentration and increases the maximum load. When fiber steering is applied, models with high strength are less sensitive to fiber steering. This is because the curvature of the hole around the stress concentration area is small, and the fiber orientation is straight. It is suggested that the curvature of the hole may influence the strength enhancement effect of fiber steering.
Two Step Chemical Treatment on Flax Fibers for Enhanced Interfacial Adhesion and Moisture Repulsion
Due to their reversible and sustainable properties, natural fiber thermoplastic composites are gaining popularity. The widespread use of natural fibers as reinforcements in structural components is hindered by their moisture adsorption and poor mechanical properties. In this investigation, alkaline treated and untreated flaxbased high-density polyethylene (HDPE) composites were manufactured and exposed to accelerated weathering tests in accordance with ASTM G154-23, to examine their moisture absorption behavior and rate of degradation. The tensile strength of alkalinetreated samples increased by 36 percent prior to accelerated ageing, but the elastic modulus and strain to failure remain unchanged. The post-ageing tests estimated a small increase in the fracture energy of the alkaline treated samples. However, no significant difference was obtained in elastic modulus, tensile strength and strain to failure. Further, the elastic modulus of both treated and untreated samples increased due to embrittlement, which shows the ineffectiveness of alkaline treatment on flax fibers under extreme weathering conditions.
Incremental Element-level Model Calibration and Verification of Composite Pi Joints
A finite element modeling approach previously calibrated using experimental data from narrow element pi joints was extended to wide element joint specimens allowing for the assessment of predictive capabilities through comparisons to experimental data. The progressive failure modeling approach uses a novel cohesive formulation to include intra- and inter-laminar damage modes and their interactions. Properties defining the cohesive responses were calibrated at the narrow element level and subsequently used in the wide element model to establish blind predictions prior to experimental testing. Pi joint specimens were tested in pull-off loading. Experimental and numerical comparisons were made in terms of load-displacement response, critical loads, damage modes, and failure progression. Comparisons between the experimental results and blind predictions were found to be in good agreement overall. Following the initial comparisons, a recalibration effort was performed to improve correlation between experimental and numerical results.
Integrated Proxy Micromechanical Models in Multiscale Analysis Using Deep Learning for Laminated Composites Subject to Low-Velocity Impact
Multiscale nonlinear micromechanical approaches can analyze laminated composite structures. In contrast, current classical macromechanical modeling approaches depict composite materials as anisotropic homogenized media. This research proposes alternative refined micromechanics that can generate the local mechanical behavior of fiber and matrix constituents and accurately depict the microstructure. The parametric high-fidelity generalized method of cells (PHFGMC) is an advanced micromechanical method that can be used for the nonlinear and failure analysis of different composite material systems. The computational effort required for generating the nonlinear multiaxial behavior is relatively small, depending on the size of the discretized repeating unit cell (RUC). However, it is computationally challenging, if not impossible, to integrate refined nonlinear micromechanical models within a multiscale finite element (FE) analysis of composite structures. To that end, we propose a new artificial neural network (ANN) based micromechanical modeling framework, termed ANN-PHFGMC, for depicting the nonlinear behavior of fiber-reinforced polymeric (FRP) materials. Pre-simulated mechanical stress-strain responses and behaviors are determined using the PHFGMC to generate a multiaxial training database for the ANN micromodel. The PHFGMC effective stress-strain responses for different applied multiaxial strain paths are divided into two sets of data; one for the training and the other for verifying the trained ANN-PHFGMC model. The resulting trained ANN-PHFGMC is accurate, with less than a 5% error in the verified predictions. Next, the ANN-PHFGMC model can be integrated within a commercial explicit FE code for multiscale low-velocity impact (LVI) analysis of laminated composite plates.
High-Order Embedded Finite Elements for the Component-Wise Analysis of Composite Laminated Structures
In commercial software, the accurate modeling of multi-component multilayered structures, such as aircraft wings, commonly requires the consideration of different structural finite element types for the various constituents, e.g., stringers, spars, skins, etc. The Component-Wise (CW) approach eliminated the necessity of utilizing different modeling approaches per structural component by modeling them as unique one-dimensional (1D) finite elements with conforming meshes. However, when considering intricate geometries, using a conforming mesh may lead to a vast increment in degrees of freedom. To reduce the computational cost, the embedded CW approach is proposed in this paper. The results shown in the document present a good agreement with reference solutions of previous CW works with savings in terms of degrees of freedom. This reduction can be helpful when more intricate geometries are considered.1
Simulating the Pyrolysis of Phenolic Resin Using Reactive Molecular Dynamics
Phenolic resin is a thermosetting polymer that has historically been used as a carbon matrix precursor for carbon-carbon composite manufacturing due to its relatively high char yield. However, the complex structural and chemical changes occurring during pyrolysis are difficult to characterize in situ. This work presents a novel method for modeling the pyrolysis processes for a polymerized phenolic resin using reactive molecular dynamics. The characteristics of the pyrolyzed model structures agree with experimental X-ray diffraction studies on glassy carbon matrices, with interplanar spacings of 3.80 ± 0.06 Å and crystallite heights of 10.98 ± 0.35 Å. The resulting structures are free of defects, and the mass densities of 2.01 ± 0.03 g/cm3 and Young’s moduli of 123.29 ± 22 GPa are found to be in reasonable agreement when compared to skeletal mass densities of glassy carbon and Young’s moduli of nanoscale glassy carbon thin films, respectively
Process Modeling of Toray 3900 Epoxy Resin Using Molecular Dynamics
This article details the modeling of Toray epoxy system using Molecular Dynamics to predict the volumetric shrinkage as a function of crosslinking density. The “Reacter” utility in LAMMPS is used to virtually simulate the curing of the epoxy. The results for the shrinkage showed good agreement with other modeling data in the literature. These physical properties and thermo-mechanical properties will be utilized for process modeling of composite laminates of the epoxy system.
The Effect of Fiber-angle Fidelity on the Linear Response of Tow-steered Composite Plates
Composite laminate tailoring is traditionally performed by uniformly changing the in-plane ply orientation to obtain the desired mechanical performance. The emergence of tow-steered plies, where the fibers follow a prescribed curvilinear path, have increased the tailorability of composite laminates. However, characterizing the behavior of tow-steered laminates using finite element analysis is challenging because additional, and often numerous, orientation definitions may be required. The additional orientation definitions detrimentally increase the computational cost and hinder the use of advanced analysis techniques, such as Monte Carlo or uncertainty quantification, in the design process. To reduce computational cost without adversely affecting mechanics-based performance, the results of a parametric study that was used to investigate the effects of fiber-angle fidelity, element size, and tow-steered radius-of-curvature on various loading scenarios for tow-steered composite plates are presented. The three loading scenarios that were analyzed using finite element analysis included an axial tension load, an applied constant through-thickness-direction pressure load, and an axial compression load. Results for mechanics-based metrics of interest are presented and discussed for each loading scenario. Little sensitivity (less than one percent difference) to the effect of fiber-angle fidelity is observed in the mechanics-based metrics until the coarse-end of the considered range. Sensitivity to element size generally dominates the observed results for the mechanics-based metrics. Notable reductions in the preprocessing time are observed for increasingly coarse element size and fiber-rounding parameters. The preprocessing times decreased up to three orders of magnitude from a few thousand seconds to a few seconds without loss of accuracy in the mechanics-based metrics. Such increased computational performance is of particular interest to the structural design and analysis communities that may be conducting large counts of finite-element analyses, such as in other parametric studies, Monte-Carlo analyses, uncertainty quantification, or tow-steered optimization.
Experimental Investigation of Helium Gas Leakage Behavior of CFRP Laminates with Partially Thin-Ply Laminates under Biaxial Stress at 20 K
Carbon fiber reinforced plastic (CFRP) has superior specific strength and stiffness compared to aluminum alloys. Therefore, it is a promising material for cryogenic propellant tanks of rockets and hydrogen aircrafts. One of the technical challenges in realizing a cryogenic tank made of CFRP is the prevention of gas leakage due to microscopic damage evolution. To prevent gas leakage, applying thin-ply CFRP (ply thickness is 0.1 mm or less) is devised. It is reported that thin-ply CFRP is effective in suppressing microscopic damage and reducing gas leakage. However, since the cost of thin-ply CFRP increases due to the increase in the number of layers, methods to apply thin-ply CFRP to only some of the layers (partial thin-ply) have been proposed. Earlier study by Hamori et al. Composite Structures 2019 reported that inserting thin-ply CFRP in the middle of the stacking sequence improved onset strain of leakage and leak rate. They focused only on cross-ply laminates, and the effect of off-axis (±45°) thin-plies on gas leakage behavior has not been investigated. The purpose of this study is to experimentally investigate the leakage behavior of off-axis partial thin-ply under cryogenic environment and biaxial stress. The specimens were [04/904/04/904]s cross-ply laminates with [45/-45]s and [45/0/-45]s offaxis partial thin-ply inserted. The specimens were subjected to biaxial tensile loading using bi-axial loading rig while the center of the specimen was locally cooled to -246 ±5°C by a GM type cryogenic refrigerator. The helium gas leak rate in the thicknessdirection was then measured at room temperature (25°C) with no load. The results showed that there was small difference in the onset strain of leakage and leak rate between the cross-ply and off-axis partial thin-ply. We assumed that the reason for this was the reduction of damage at the crack intersection and the decrease in crack length due to the thinning.
A Comparative Study of the Effect of Compounding Methods and Processing of PLA/GNPs on the Micromorphology and Electrical Conductivity
In this work, the effects of different compounding and processing techniques on the DC electrical conductivity and density of polylactic acid (PLA)/ graphene nanoplatelets (GNPs) composites were studied. It is found from the study that compounding by solution mixing via an ultrasonication technique can provide slightly higher DC electrical conductivity after compression molding than mixing through a twin-screw extruder due to better dispersion quality. In addition, a composite pellet from twin screw extrusion showed a slight increase in DC electrical conductivity and anisotropy when processed by filament extrusion due to the shear alignment of GNPs during the extrusion. The fused deposition modeling (FDM) process yields high anisotropy because the crystallization along the printing path allows gaps and polymer coating between the extruded lines and layers. It was found that the 7.5 wt% GNPs composites exhibited the best properties because it provides the best dispersion quality to meet the percolation threshold. Furthermore, the micromorphology of each sample was also studied to observe the dispersion and porosity inside the composite provided by each fabrication technique. This study can be used as a reference for compounding and processing techniques.
A Study on Thermal Characterization of Honeycomb Sandwich Panels with GFRP Facesheets
The thermal characterization of honeycomb and foam core sandwich panels is studied by both experimental (guarded hot plate apparatus, and transient laser flash technique), and theoretical (Swann Pittman model, and composite theory) means to analyze and modify their thermophysical properties. Then, the fabric’s structural attributes and their effects on the thermal conductivity of the GFRP facesheets were studied by metallographic techniques, polynomial curve fitting of the longitudinal fibers, Procrustes analysis and subsequent modelling in TexGen (open-source software) and ABAQUS/CAE 2022, Dassault Syst??̀mes Simulia Corp. Initially, the sandwich panels were dismantled into their constituent parts i.e., facesheets and cores and then the graphite & gold coated samples were subjected to transient laser flash thermal analysis technique and guarded hot plate apparatus per the ASTM E1461, ASTM C177 and ASTM C1058 standards. Though thermal diffusivity is not applicable to heterogeneous GFRPs, good accordance between analytical solution for homogeneous material and experimental results for composites allowed us to calculate the “effective thermal diffusivity”. These results were then utilized in the composite theory to compute the overall thermal conductivity of the sandwich panels. Moreover, with regards to other theoretical approaches, the thermal emissivity values of the facesheet and core were measured by emissivity compensation in FLIR thermal camera. Later, the epoxy mounted metallographic samples were subjected to dark field, bright field, and polarized microscopy to extract various attributes of the fibers that are obscured in all the techniques but one. For instance, to enhance the contrast between the glass fibers and the polypropylene matrix dark field microscopy was utilized but this technique is not of much help in studying the fibers from an angle orthogonal to the weave plane of the fabric; polarized light technique had to be used.
Development of Simplified Methods to Characterize Plasticity Parameters for LS-DYNA MAT213
A material model which incorporates several key capabilities which have been identified as lacking in currently available composite material models has been developed. The material model utilizes experimentally based tabulated input to define the evolution of plasticity, damage, and failure as opposed to specifying discrete input parameters (such as modulus and strength). It has been implemented into the commercially available transient dynamic finite element code LS-DYNA® as MAT 213. The model can simulate the nonlinear deformation, damage and failure that take place in a composite under dynamic loading conditions. One challenge that has been encountered by users of MAT 213 is that several of the parameters in the orthotropic plasticity model are extremely difficult to characterize experimentally or data may not be available to characterize them. To simplify this process, a toolset and methodology are being developed which can be implemented as a stand-alone in MATLAB® application. A key part of this toolset will utilize a simplified version of the orthotropic plasticity model. Specifically, the orthotropic plasticity model utilized in MAT 213 has been simplified to simulate the stress-strain response of a composite ply with an arbitrary fiber orientation subjected to uniaxial loading or the shear response of a composite ply subject to pure shear loading. These simplified models will allow a user to simultaneously simulate the longitudinal and transverse tensile and compressive stress-strain responses, the shear stress-shear strain responses, and the off-axis tensile (or compressive) stress-strain responses of a composite ply in a highly efficient manner. By using this toolset, particularly when combined with a suitable optimizer, a user can quickly determine the required plasticity model parameters required for a MAT 213 analysis.⋅
Dynamic Crush Performance of Thermoplastic and Resin Infused Thermoset Triaxially Braided Composite Structures
Dynamic crush tests were conducted on triaxially braided composite tubes and Cchannel structural elements to measure their relative energy absorbing characteristics. The elements were manufactured from triaxially braided [0/+60/-60] T700 fiber preforms with two different resin systems, a PR520 thermoset resin and a LM-PAEK thermoplastic resin. T700S/PR520 composite tubes and C-channel elements were manufactured using a resin infusion process. T700GC/LMPAEK composite tubes were manufactured by braiding slit tape prepreg onto cylindrical mandrels. Consolidation pressure was applied through thermally activated shrink tape in an oven. The energy absorbing characteristics of the composite elements were measured using a pneumatically actuated sled with a flat-faced impacting mass, which provided several independent measurements of force, displacement, and energy absorption. The parameter primarily used for comparison between the systems was the specific energy absorption (SEA), a measure of energy absorbed per unit crushed mass. The T700GC/LMPAEK tubes performed slightly better than T700S/PR520 tubes, with an approximately 8% higher SEA. T700S/PR520 tubes had over 20% higher SEA than Cchannels made from the same material. Additional tests were conducted on tubes using a tapered-conical impactor to force the tubes to fail in circumferential tension. This type of impact significantly reduced the energy absorption.
High-Energy Dynamic Impact Modeling of an AS4D/PEKK-FC Composite Using LS-DYNA MAT213
As part of the NASA Hi-Rate Composite Aircraft Manufacturing (HiCAM) Project, multiple thermoplastic composite systems are being considered as candidates for enabling a more rapid production of composite aircraft components. Various analysis methods are being explored to evaluate their capabilities and applicability to simulating the progressive failure of thermoplastic composites. One of these approaches is based on using the MAT213 material model, a tabulated composite material model recently integrated into the commercial release of Ansys LS-DYNA. For this study, a Solvay APC AS4D/PEKK-FC unidirectional tape composite system was analyzed. A MAT213 input deck was generated for this composite utilizing data from standard composite coupon tests. A series of singleelement verification exercises were performed to evaluate the correct performance of MAT213. These model inputs were then implemented into a high energy dynamic impact (HEDI) ply-by-ply model of a flat 32-ply quasi-isotropic specimen. A tie-break contact model, implemented separately from MAT213, was used to simulate delamination between individual plies. Comparisons, including deformations, damage/delamination sizes, and penetration threshold, are made to test data for a variety of impact velocities. The results demonstrate that MAT213 is a viable option for simulating progressive failure in thermoplastic composite systems under HEDI loads.
Thermomechanical Property Prediction of a Bismaleimide Resin Using Molecular Dynamics
Bismaleimide (BMI) resins have seen increased use as a thermoset polymer matrix material in structural aerospace composites as a result of their excellent thermomechanical properties and low specific weight that arise from the complex structural features of the BMI matrix. Since the development of high-performance composites has increasingly relied on molecular modeling to predict polymer processing characteristics, the ability to effectively model these materials is imperative. Molecular models offer insights into residual stresses and bulk properties of the composite matrix polymer, which directly impact the laminate’s durability and performance when subject to thermal and mechanical loads. Unfortunately, its complex crosslink structure has limited the structure-property understanding of BMI at the molecular level, complicating modeling attempts at all length scales. This study utilizes molecular-scale simulations to model a BMI thermoset resin commonly used in aerospace composites at the nanoscale to predict the properties of the bulk thermoset. Molecular dynamics (MD) simulations using the interface force field (IFF) are performed on BMI resins to describe a likely crosslink structure and to evaluate thermomechanical properties as a function of temperature and crosslink density. These properties are then validated against experimental data to ascertain the model accuracy and demonstrate that molecular modeling methods can be successfully used to predict the evolution of properties in the BMI resin during its curing.
Nano-Porous Networks Enabled Out-of-Autoclave Curing of Carbon Fiber Reinforced Plastic Aerospace Composites
Large-scale aerospace composite parts utilizing autoclave-required carbon fiber reinforced plastic (CFRP) epoxy prepreg were manufactured with a novel Nano- Porous Network (NPN) enabled and CNT-heater based out-of-oven (OoO) for a combined out-of-autoclave (OoA) approach. While prior work has established open porosity carbon nanotube films as effective NPN materials, here we utilize electrospun polymer nanofiber veils to provide capillary pressure in the inerlaminar region during curing, thus enabling void elimination without requiring an autoclave. A CNT-based surface heater was used to cure a 0.6 m  0.6 m plate. Utilizing the fast rate of the CNT heaters, an accelerated cure cycle was developed to shorten the cure cycle by 35% compared to the manufacturer-recommended cure cycle (MRCC). X-ray microcomputed tomography (μCT) inspections showed that the cured parts (autoclave baseline and combined OoA approach) were void-free. The mechanical tests (shortbeam shear, tension, and compression) revealed that the accelerated-cure combined OoA approach composites were equivalent to the autoclave cured parts. Having attributes of reducing capital cost and increasing manufacturing efficiency intrinsic to OoA, this scaled fabrication method is a facile alternative to conventional autoclave fabrication, and future work will study a broader array of mechanical testing.
Deep Learning-Based Automated Segmentation of Fiber Breaks in Advanced Composites
The heterogeneity of the microstructure and the anisotropy of the mechanical properties of carbon fiber reinforced polymer composites (CFRP) are associated with complex damage mechanisms that make failure prediction highly challenging. Typical damage mechanisms for CFRP include: (i) interlaminar cracking (delamination), (ii) matrix cracking, and (iii) fiber breakage. X-ray computed tomography (CT) has been utilized recently to identify the complex damage in progressive failure of CFRP in 3D and 4D (3D spatial and 1D temporal). However, these scans contain a large amount of data (≈10 GB/mm3), which makes it challenging to extract mechanistic insights in a reasonable time frame. In previous work, we presented the first deep learning (DL) convolutional neural network (CNN) segmentation of multiclass microscale matrix damage in CFRP. The trained CNN segments complex and sparse composite matrix damage mechanism to ≈ 99.99% agreement, with nearly 100% of human time eliminated, providing higher accuracy compared to human segmentation. In this work, we developed CNN-based method for the automated segmentation of fiber breaks using synchrotron radiation-based CT (SRCT) scans that have been human-labeled. The model employed a U-Net full CNN as the high-level encoder (feature extraction)-decoder (feature localization) structure, and VGG16 as the deep CNN backbone via the publicly available Segmentation Models GitHub repository. An unbiased evaluation was performed comparing the machine vs. the human-labeled ground truth. Finally, active learning was presented for the machine-assisted relabeling of datasets containing fiber breaks. The deep learning-based automated segmentation method demonstrated accurate identification (> 90%) of fiber breakage for CFRP.
Rapid Manufacture of Thin Composites via Infrared-Assisted Frontal Polymerization
State-of-the-art technologies for manufacture of fiber-reinforced polymer composites (FRPCs) rely on bulk polymerization of matrix thermoset resins at elevated temperatures for several hours (up to 24 h) in an autoclave or oven. This process is energy- and time-intensive, generates a significant carbon footprint, and requires expensive equipment. In recent years, frontal polymerization (FP) has emerged as an alternative approach for rapid and energy-efficient curing of FRPCs. However, widespread and practical adoption of this curing technique at industrial scale is limited by the low front velocities (<10 cm min-1), the need for using highly thermally insulating tooling materials (e.g., polymer foams), and low degree of cure of resin in produced composites. In addition, frontal curing of thin composite laminates is quite challenging even on highly thermally insulating tooling materials due to the high rate of heat loss through boundaries compared to the generated heat, resulting in quenching of reaction and incomplete cure. Here, we present a new approach for rapid curing (~50 cm min-1) of FRPC panels via FP by supporting the underlying thermal curing reaction using a moving infrared heating source. In our approach, following the infusion of a carbon fiber composite layup by an FP resin system, an infrared heating source is linearly moved along the length of the layup to not only initiate the FP reaction via photothermal energy conversion effect but also locally pre-heat the resin and increase its frontal reactivity and front velocity. We successfully cure a 5 Å~ 15 cm2 composite panel on a glass tool plate within 24 s with a total energy consumption of 8.3 kJ as a proof of concept. Differential scanning calorimetry measurements are also conducted on produced laminates to determine the degree of cure of produced FRPCs. Finally, a thin laminate, consisting of a single ply of carbon fabric is fabricated as a proof-of-concept to further demonstrate the capability of our technique for rapid manufacturing of thin composites, which is promising for use in space and aerospace applications.
Characterization of Low-Velocity Impact Damage in Thermoplastic Laminated Composites
The impact damage response of two thermoplastic material systems were compared over a range of impact energies. Eight-inch-square impact specimens with a 24-ply quasi-isotropic layup were manufactured from TC1225 LMPAEK T700G from Toray Industries and APC AS4D/PEKK-FC from Solvay. The effect of the degree of crystallinity (DOC) on the damage response was also investigated using a third set of specimens from the Toray material manufactured with reduced crystallinity. Using a combination of data obtained from X-ray computed tomography (CT) scans and ultrasonic testing (UT), detailed damage maps were created for every interface and ply for selected specimens. Using these damage maps, the delamination size, shape, and area were evaluated at each interface. The presence of fractured fibers was also identified on each ply. The LMPAEK material was found to have fewer and smaller delaminations than the PEKK specimens for impacts at the same energy. However, the LMPAEK specimens contained a larger number of fiber breaks. A similar trend was observed when comparing the baseline LMPAEK specimens with the low-crystallinity LMPAEK specimens. The low-crystallinity specimens had very little delamination but had a large number of plies with fiber breaks. In addition, the LMPAEK specimens often contained lines of fiber fractures in near-surface plies emanating from the contact region that were not present in the PEKK specimens.
Multiscale Thermal-Mechanical Analysis of Tow-Steered Composite Plate Structures Using a Mixed-Fidelity Neural Network Model
One challenge of design optimization of tow-steered composites is the significantly increased computational cost with more design variables in realistic structures. Emerging machine learning models, such as artificial neural network (ANN) models, offer an efficient alternative to expensive finite element analysis (FEA). However, the requirement for extensive training data can limit the application of ANN models in structural design using tow-steered composites. In this paper, we will utilize a recently developed Design Tool for Advanced Tailorable Composites (DATC) to generate training data. Single-fidelity ANN models will be developed to take design parameters of tow-steered composites and predict the critical buckling load of structures. The accuracy and efficiency of the ANN models will be validated with high-fidelity FEA. To reduce the cost of generating training data, we propose a composite ANN model to take mixed-fidelity data from simulations at different mesh densities. Two examples of tow-steered composite structures will be employed to develop the single-fidelity and mixed-fidelity ANN models. The results show that the proposed mixed-fidelity ANN model delivers accuracy comparable to high-fidelity FEA, while also significantly enhancing efficiency in comparison to the single-fidelity ANN model.
A Performance Comparison of Low-Cost NIR Nano to NIR Microphazir for Polymer Composite Characterization
Polymer composites are increasingly adopted to complement or replace their metal counterparts used in aerospace, wind turbine, automotive, and other safety-critical structures. However, these structures are susceptible to the development of undetected sub-surface damage, such as low velocity impact damage (LVI), that limits their performance and utility in certain cases. The ability to detect and monitor the progression of this type of damage from the micron level prior to growth to the macroscale is critical to ensuring the long-term safety and reliability of these structures. Near Infrared Spectroscopy (NIRS) is a promising technique for detecting LVI damage because it can probe the internal structure of the material and identify subtle changes in its properties. This study compared the performance of a low-cost NIR Nano (a Texas Instruments NIR Nano evaluation model) to a commercial NIR Microphazir instrument for the detection of LVI damage in glass fiber reinforced polymer composites. We evaluated the two instruments for their ability to detect and measure different levels of impact damage at increasing moisture absorbed by weight. Forty-eight fiberglass laminates consisting of e-glass and epoxy were subjected to either 0J (no damage), 1J, 1.5J, and 2J impact energy using a drop tower outfitted with a 9mm radius hemispherical striker tip impactor. Spectral scans were collected between wavelengths of 900-1700 nm (NIR Nano) and 1600-2400 nm (Microphazir) for all samples prior to moisture absorption. Following moisture contamination, spectral scans were taken at regular intervals of gravimetric moisture gain from 0.05% to 0.15% by weight. Multivariate data analysis methods were used to assess the spatial variation of the absorbance parameter at various amounts of absorbed moisture. The results and discussion emphasize the importance of rigorous calibration and technique selection for reliable and accurate NIR spectroscopy investigation in polymer composites, especially in situations where mobility,
Low Velocity Impact of Woven GFRP/ CFRP Composites: Numerical Analysis and Experimentation
Low-velocity impact (LVI) of laminated composites is commonly used in aerospace industry certification as part of a durability and damage tolerance assessment (e.g., barely visible impact damage, compression after impact, etc.). In certain situations, the puncture resistance of an impacted composite structure is of interest. To study the behavior of composite plates near perforation, this work focusses on LVI of composites at relatively high impact energies. An experimental test campaign was conducted wherein composite laminates composed of layers of woven glass fiber-reinforced polymer (GFRP) and woven carbon fiber-reinforced polymer (CFRP) plies were impacted in a drop tower using a standard LVI setup with a hemispherical indenter tip. The stacking sequence contained blocked plies of the same material, yielding a glass-carbon-glass layup. A range of impact energies were selected to produce widespread damage, including delamination, fiber fracture, and shear failure, and to fully perforate the panels in some instances. These tests are distinguished from other such impact experiments in that substantial damage and perforation are observed at low velocities. The interface between dissimilar materials showed large delaminations, which could propagate to the edge of the plate at the highest tested impact energies. Numerical modelling was performed using the explicit transient dynamics solver of Sierra/Solid Mechanics, a finite element code developed at Sandia National Laboratories. Continuum damage mechanics (CDM) and cohesive zone modelling (CZM) were utilized for the intra- and interlaminar failure, respectively. Pseudo-ply-by-ply meshing with one element through the thickness of every two blocked plies was used, and delamination planes were modelled with cohesive zone elements (CZE) inserted between every two layers. The main quantities of interest, including the energy dissipation, force-displacement curve, peak force, and damage patterns, were used to compare the numerical simulations with the experiments. These data are useful for validating computational simulations and provide insight into the impact resistance and energy dissipation capability of hybrid GFRP/CFRP composites.
Progressive Damage and Failure Analysis of Thermoplastic Composites in Low Velocity Impact Using MAT299
As part of NASA’s Hi-Rate Composite Aircraft Manufacturing (HiCAM) Project, state-of-the-art progressive damage and failure analysis (PDFA) tools developed for use with thermosets are being evaluated for use in modeling alternative material systems, like thermoplastics. This work presents experimental low-velocity impact data of a thermoplastic material system, AS4D/PEKK-FC, including characterization of the impact damage mechanisms as well as associated load and displacement data from testing. Following the presentation of experimental results, two simulation approaches using the PDFA tool MAT299 in the commercial off-the-shelf finite element software LS-DYNA are employed to predict damage area and forcedisplacement responses of thermoplastic panels subjected to various impact energies. The first modeling method uses solid elements with a high-density mesh and a ply-byply modeling approach similar to previously published work for thermosets. This method has the capability of capturing individual crack development, progression, and delamination on a per ply basis. The second modeling method uses TSHELL elements that have in-plane dimensions that are an order of magnitude larger than the elements used in the solid element approach and reduces the number of elements through the thickness of the laminate. This produces a lower-fidelity model with reduced run times that is incapable of monitoring every delamination plane and damage within each ply. Results from both simulation methods are compared to experiment, and limitations of the methods are discussed.
Simulation of Mixed-Mode I/II Debond Using VCCT and Cohesive Elements
This paper presents a modelling strategy for the simulation of quasi-static mixedmode I/II debond propagation in a bonded unidirectional composite specimen configuration. The previous test data sets were re-examined to validate the modelling, i.e., measured debond lengths were assessed and updated based on a correlation between the stiffness and the debond length. The correlation was obtained via a series of two-dimensional (2D) finite element (FE) analyses with different debond lengths. With the resulting “effective” initial debond lengths, finite element (FE) analyses of mixed-mode debonding was carried out with the virtual crack closure technique (VCCT) and cohesive zone modelling (CZM). The performance of VCCT and cohesive elements in the debonding simulation was assessed for a mode mixity of 0.2. Good agreement in the load-displacement relationship was obtained between experimental and numerical results. Discussion on the test data evaluation and the modelling strategy over a wide range of mode mixities is presented.
Accelerating Composite Cure Cycle Optimization with Combined Probabilistic Machine Learning and Finite Element Process Simulation
Advanced composites are widely used in industries such as aerospace. To certify aerospace structures, the manufacturing process of composites is tightly controlled to ensure compliance with process specifications (i.e., process specs). For example, in autoclave curing of thermoset composites, process specs often limit the maximum temperature in the composite part due to exothermic reaction, maximum thermal lag between the part and autoclave temperature cycle, as well as maximum part porosity and minimum degree of cure. Given all the requirements in process specs, optimizing the temperature cycle in autoclave curing to reduce cycle time and hence increase production throughput is often challenging. While Finite Element (FE) process simulation is used for coupled analysis of heat transfer and thermo-chemical curing reaction of composites during the curing process, due to the long simulation time of high-fidelity simulation models, optimization in the entire design spectrum is not feasible, and most often relies on trial-and-error and engineering insights. In this study, we present a novel framework based on combined probabilistic Machine Learning (ML) and FE to accelerate the process optimization of composites. The probabilistic ML is developed based on the underlying theory of curing and a mathematical foundation of Gaussian Process Regression (GPR). Instead of trial-and-error or time-consuming grid search, this approach relies on targeted FE evaluation of selected cure cycles by the ML model, such that in a step-by-step simulation approach, an optimized solution is obtained. While this approach minimizes the effort to optimize cure processing conditions, it also enables the evaluation of non-traditional cycles such as multi-ramps and holds to minimize the autoclave cycle time. For validation, the framework is applied to optimize the cure cycle of a thick HEXECL AS4/8552 composite laminate cured on a typical Invar tool. A validated FE model is used for process simulation along with the ML model for targeted evaluation. Results show that with only a few analysis steps, an optimized solution can be obtained to satisfy process specs while minimizing cycle time.
FastDM4C: A Fast and Efficient Discrete Model for Composites
The adoption of composite materials in the aerospace industry has enabled the achievement of structural performance levels and weight savings unimaginable even just twenty years ago. Yet only a fraction of the true potential of these materials has been expressed to date due to lack of high-fidelity models which has resulted in the adoption of extremely conservative designs compared to metallic counterparts. In part this is because, in contrast to high performance metallic alloys, the damaging and fracturing behaviors of composites are way more complex and difficult to simulate. Fiber reinforced composites feature many interacting mechanisms spanning several material and structural length scales, from the fiber scale of a few microns to the structural scale of a composite wing with a span of several meters. This makes the development of computational models for the design and optimization of composite structures extremely challenging due to the conflicting need of being able to capture microdamage events at the fiber scale while still being efficient enough to simulate structures that are at least six orders of magnitude larger. This work attempts to address this challenging problem by formulating a novel discrete, sub-lamina-scale model aimed at providing an effective description of damage at the microscale while maintaining computational costs comparable to continuum, homogenized formulations. In this new approach, composites are simulated as an assembly of Representative Unit Cells of roughly the same dimensions of the average distance between splitting cracks and their arrangements are designed to replicate the orthotropic behavior of the lamina. One distinct regularized strain-softening constitutive law is utilized to describe the behavior of the fibers using a new element called Discrete Fiber Model (DFM).
Effect of Crack Length on Fracture Toughness in Epoxy Polymers using Atomistic-Continuum Coupling of MD with FEM
Developing fundamental methodologies for predicting material properties, such as strength and toughness, is one of the core objectives of Integrated Computational Materials Engineering (ICME). For this purpose, a generalized framework for anchor point based concurrent coupling of FEM and MD domains, encompassing previous related methods, is presented in this paper. The motivation for this work comes from the fact that the crack length and fracture process zone size required to simulate brittle fracture in certain materials, such as epoxy polymers, often exceed the computational size limit needed for pure MD simulation. The proposed concurrent coupling framework is robust and is agnostic of material crystallinity and atomistic description. Two distinct forms of the method are discussed in detail, both of which are able to make use of specialized MD solvers such as LAMMPS with little or no modification. One of the two forms has the added advantage of being able to couple to specialized FEM solvers as well, such as ABAQUS. The two methods are tested against each other in a uniaxial tension test using a graphene monolayer at 300 K temperature and a block of thermosetting polymer EPON862 at 1 K temperature, showing comparable results. Convergence behavior of the two coupling methods are studied. The methods are then applied to study the fracture of a center-cracked graphene monolayer and compared with results from an identical pure MD simulation, using the atomistic Jintegral. Their good agreement corroborates the effectiveness of the developed method and potential use as a plug-and-play tool to couple commercial FEM and MD solvers. Future work will entail applying these methods to simulate elevated-temperature amorphous polymer models and their brittle fracture, and the effect of crack length and process zone size.
Impact Damage and Failure Mechanisms of Hybrid Facesheet Sandwich Composites under Low Temperature Conditions
In this study, we experimentally investigate the impact damage and failure mechanisms of foam-core sandwich composites with carbon fiber reinforced polymer (CFRP) and/or glass fiber reinforced polymer (GFRP) face sheets. Specimens are conditioned and impacted over a wide temperature range (from room temperature of 23°C down to -70°C) using Instron CEAST 9350 impact test machine. This work also explores the use of hybrid composite face sheets, with various configurations of layering CFRP and GFRP in the face sheets of foam-core sandwich composites. Results show that exposure to low temperature causes more severe damage, particularly in specimens with CFRP face sheets, due to their extreme brittleness. GFRP face sheet specimens are able to achieve larger deformation and absorb greater impact energy even at low temperature conditions. There is a significant benefit in using hybrid configurations, by striking a balance between brittle (CFRP) and ductile (GFRP) materials and harnessing their mechanical advantages of high strength and high fracture toughness, respectively. Results also demonstrate that hybridization is a solution to reduce temperature effects in impact deformation. Careful placement of CFRP and GFRP in layup order can harness the best impact performance. X-ray micro-computed tomography (μCT) images reveal substantial delamination at the interfaces between CFRP and GFRP layers. It is also observed that CFRP layers fail by brittle fracture, while delamination is the major damage mode within GFRP layers. Other complex failure mechanisms in the composite face sheets (such as matrix crack and fiber breakage) and foam core (core crushing, core shearing and interfacial debonding) are also presented.
Measurement, Interpretation and Application of R-Curves for Translaminar Fracture Toughness of Composite Laminates
The reasons for the large variation of reported values of translaminar fracture toughness are considered, both for initiation and propagation. The effects of ply thickness, layup, the development of the fracture process zone and the implications for predicting response of notched structures are discussed.
Equi-energetic Low-velocity Impact Effects on the Compression After Impact Strength of Carbon Fiber Composite Tube Structures
This study explores the effect of equi-energetic low-velocity impact on the compression after impact (CAI) strength of tubular composite structures. The effects of equi-energetic impact energies are explored, where high-mass-low-velocity (HMLV) and low-mass-high-velocity (LMHV) test configurations are used at three impact energy levels using Instron CEAST 9350 impact test machine. Various tube diameters (76.2 mm and 101.6 mm) are also considered to achieve a better understanding of tube geometries on CAI residual strength. The impact force-time graphs and force-displacement curves are used to analyze the impact responses and damage mechanisms. The results indicate that impact energy, impactor mass, and tube diameter play a significant role in impact response. The larger diameter tubes can withstand higher compressive loads regardless of impact damage, showing significant drops for smaller UT tubes while the larger diameter tube can maintain more of their compressive strength. This study provides insights into the behavior of composite tubes under LVI and highlights the importance of considering impact effects when evaluating the structural integrity and strength of composite materials.
Experimental and Computational Verification of Additively Manufactured Carbon Fiber and Nanoreinforced Filaments for Automotive Applications
In this study, the mechanical behavior of implementing both continuous and short carbon fiber within Nylon and investigated for its effectiveness within additively manufactured prints. 0.1wt% of pure nylon was combined with carbon nanotubes through both dry and heat mixing to determine the best method and used to create printable filaments. Compression, tensile and short beam shear (SBS) samples were created and tested to determine maximum deformation and were simulated using ANSYS and its ACP Pre tool. SEM imaging was used to analyze CNT integration within the nylon filament, as well as the fractography of tested samples. Experimental testing shows that compressive strength increased by 28%, and the average SBS samples increased by 8% with minimal impacts on the tensile strength. The simulated results for Nylon/CF tensile samples were compared to experimental results and showed that lower amounts of carbon fiber samples tend to have lower errors.
Effect of Layer Material Properties on the Radial Stress at the Interface in Hybrid Tubes Made of Many Layers
Composite cylinders possess characteristics not seen in other types of structures. First they are light weight as compared to metallic cylinders due to the light weight of composite materials. Secondly they do not have free edges (along the circumferential direction) which prevents delamination along free edges like that in composite plates or panels. Thirdly, they can be manufactured using automated fiber placement which provides good repeatability and high speed of production. Fourthly, they are corrosion resistant which makes them applicable for making pipes, or undersea transmission cables for electrical lines. Due to these characteristics, composite cylinders have found applications in pipes, and potentially as cross piece for landing gears for helicopters. Nonetheless, when subjected to bending loads, composite cylinders exhibit failure on the compression side. The failure is due to buckling of the material. The buckling seems to be caused first by delamination, which in turn depends on the radial stress at the interface between the layers. This paper examines cylinders made of two different isotropic layers. The effect of different elastic moduli and Poisson ratios on the development of the radial stresses throughout the thickness, particularly at the interface of the layers, is examined.
Improvement of Damping in Carbon/Epoxy Beams with Externally Bonded, Aligned Carbon Nanotubes
Adding multiwalled carbon nanotubes (CNTs) to polymer composites such carbon fiber reinforced epoxies (c/ep) has the potential to add beneficial damping in vibration prone structures, such as rotorcraft blades, because of slip at the CNT/epoxy interface and between the multiple walls of the CNTs themselves. Recent research has demonstrated remarkable damping improvement by incorporating CNT-rich interlayers into c/ep laminates, and there is current interest in flight testing this damping approach in rotorcraft blades. In order to avoid the time and cost of developing and flight-certifying an entirely new blade material with CNT interlayers, it has been proposed to bond a CNT-rich patch onto the surface of an existing blade. Thus, this investigation compares and analyzes damping in three types of cantilevered [±45/0]s c/ep beams: without any CNTs; with CNT interlayers; and with CNT layers co-bonded to the surface. The CNT layers were used in 64 g/m2 pairs, covering 20% of the length of the beam near the clamped end, and comprising about 1 vol% of the cantilevered portion of the beam. Damping ratio, , was measured during free vibration in a vacuum chamber. The damping ratio increased from 0.65% in a plain c/ep beam to 0.93 (+43%) and 1.24% (+91%) by adding CNT interlayers and externally bonded CNTs, respectively. Dynamic finite element (FE) analysis of the beams confirmed these results and was further used to parametrically investigate the damping attainable with CNT surface films covering higher lengths of the beam or stacked to higher thicknesses at the root of the beam. The parametric investigation showed that increasing the length of the CNT surface film is the most efficient use of CNTs and that a damping ratio 277% greater than that of the beam without CNTs could be realized. In conclusion, externally bonded CNT layers offer a promising avenue for the rapid, cost-effective flight testing of CNT-augmented damping in composite rotorcraft blades.
Multiscale Prediction of Yarn Pullout Failure Mode in Unreinforced Textile Fabrics
Unreinforced woven fabrics have been implemented in a variety of high performance applications, including body armor, deployable structures, and as the reinforcement material in composites. Multiscale modeling techniques have significantly improved the capabilities of simulation-based tools to capture fabric mechanics efficiently and accurately, but often lack in their prediction of failure and require pairing with finite element analysis (FEA) software, limiting their application to the design of ‘fit-for-purpose’ materials. NASA’s Multiscale Analysis Tool (NASMAT) is a standalone multiscale program that has been traditionally used in the analysis of reinforced composites materials. More recently, it has been amended to simulate unreinforced fabric behavior by allowing the geometric state of the tows to change with applied loading due to the lack of a reinforcement material, such as the matrix seen in composites. Previous work has shown the ability of NASMAT to capture nonlinear macroscale behavior by predicting geometric changes in the state of each subcell as a function of the applied loading and allowing each subcell in the analysis to rotate according to these predicted changes, as well as predict nonlinear behavior due to the fiber breakage failure mode. In this work, the capability of predicting the onset and propagation of failure in plain woven fabrics in NASMAT is presented for the yarn pullout failure mode, which occurs when a fabric is loaded at an off-axis angle relative to the warp of weft tow direction. Yarn pullout behavior is initiated by determining the applied load in which the shear resistance of the contact area between yarn families is overcome. When failure is initiated, yarn pullout is determined to have occurred when the applied displacement, calculated from global strain, exceeds the deformed position of a given contact points between yarn families, determined from pin-joint kinematics. Contact points where pullout has occurred contribute to a global damage parameter used to modify the homogenized stiffness of the fabric, resulting in nonlinear behavior observed at the macroscale. The off-axis loading behavior and yarn pullout failure theory have been developed and implemented into NASMAT such that users can simulate off-axis tensile behavior of fabrics in a single, standalone multiscale tool. Simulations are compared to uniaxial tensile tests at various off-axis angles to demonstrate the capability of the tool in its prediction of both the onset of failure at each off-axis angles and the stress-strain behavior as failure progresses.
Efficient Residual Stress Modeling for Large- Format Polymer Composite Extrusion-Based Additive Manufacturing
Residual stresses are generated in thermoplastic composite parts produced using extrusion-based additive manufacturing (AM). The layer-by-layer deposition of molten thermoplastic composite material and the subsequent cooldown results in the differential thermal contraction of the deposited layers, giving rise to residual stress in the additively manufactured parts. These residual stresses depend on the material properties of the polymer composite and the processing parameters used during the AM process. The residual stresses affect the mechanical performance and the final printed shape of the manufactured part. Efficient numerical modeling methods can predict residual stresses for AM parts and hence help design geometrically accurate and mechanically reliable parts. However, large-scale AM introduces computational challenges for evaluating residual stresses due to the large number of degrees of freedom in the numerical models. This research work explores the use of an explicit thermal model and a mesh merging technique to expedite the numerical analysis of thermal history and residual stresses in large-scale additively manufactured thermoplastic composite parts. The goal of the research is to develop an efficient modeling method for aiding the design of AM polymer composite parts.*
Reactive Molecular Dynamics Simulations of the Furan Pyrolysis Process for Carbon- Carbon Composite Fabrication
Carbon-Carbon composites (C/C composites) are an excellent thermal protection system for aerospace vehicles. The matrix material of most C/C composites, glassy carbon (GC), demonstrates excellent thermal stability and mechanical response with low mass densities. Although GC materials have been in development and use for decades, molecular simulation protocols need to be developed to accelerate the optimization of processing cycles and to drive the development of the next generation of C/C composites. This research aims to establish molecular dynamics (MD) simulation protocols to accurately predict the evolution of the molecular structure and properties of furan resin during the pyrolysis processes that convert the polymer into a GC material. MD workflows are developed using a reactive force field to simulate the evolution of the molecular structure, mass density, and elastic properties of furan resin-derived GC. MD simulation parameters are optimized, and the predicted structures and properties are shown to agree with experimental measurements from the literature. The modeling methodology established in this work can provide guidance in driving the development of the next-generation C/C composite precursor chemistries.
Failure Analysis of Composite C-Spars Under Inter-Laminar Tensile (ILT) Configurations: An Experimental & Numerical Evaluation
In designing composite structures, it is fundamental to understand critical areas of structural deficiencies that lead to failures. One such critical design element is the failure caused by out-of-plane loads propagating through the bending of a composite laminate. In such cases, load offsets and element heights are generally the primary contributors to moments and forces leading to the degree of bending. In curved beams, these load conditions result in inter-laminar tension (ILT) type failures between plies, resulting in delamination and eventual failure. This work investigates such an ILT failure mechanism on composite C-Spars. The C-Spar specimen was constructed entirely of a quasi-isotropic [45/0/-45/90]4S layup and consisted of two 90-degree radii along with straight web sections defining the height of the element. To examine the contribution of the bending moment, resultant force, and rotation on the unfolding radii, varying loading arm configurations were investigated with a pinned load applicator. High-fidelity finite element (FE) analysis using B-Spline Analysis Method (BSAM), developed under the Air Force Research Laboratories (AFRL), was also utilized to predict failure of the C-Spars. The FE models showed good agreement with that of the experimental data and predicted failure loads within 10% on multiple configurations while also mimicking the geometric nonlinearity under larger deformation. Having successfully modeled the rotation and failure of the C-Spar configuration, this enables further investigation into the critical inter-laminar stresses induced within the design of such structures.
Tuning Load Bearing Capacities of Flexible Honeycomb with Poisson’s Ratio Modulation
Polymeric honeycomb structures are used in impact mitigation applications due to their high specific strain energy dissipation capacity at extended strains. The load bearing and energy absorption capacities of honeycomb lattices can be concurrently improved by tuning their Poisson's ratio. For instance, the inward-facing cavities in reentrant honeycomb geometries result in an auxetic behavior, effectively increasing the impact energy absorption performance. This study investigates the interrelationship between cell wall thickness, the Poisson effect, and load-bearing capacities of hexagonal and reentrant honeycomb lattices fabricated from thermoplastic polyurethane (TPU) by fused filament fabrication (FFF) additive manufacturing technique. The wall thickness of the samples is varied to investigate its effect on the mechanical performance of the honeycomb structures. The fabricated samples are characterized under quasi-static compression. The results indicate that the load-bearing responses of conventional and reentrant honeycomb structures improve with increasing wall thicknesses, while the energy absorption efficiency is inversely related to the cell wall thickness. Hexagonal honeycomb lattices exhibit superior stiffness and strength compared with their reentrant counterparts, whereas reentrant lattices are lighter and show a more compliant nature due to their more open geometry and inward-facing cavities. We observe that the reentrant lattices tend to fail due to shear deformation while honeycomb lattices fail by the bending and stretching of the cell walls. The findings suggest that the honeycomb lattice structure can be optimized by tuning the wall thickness based on the desired mechanical properties informed by a particular application.
Effects of Impact Damage on the Energy Absorption Capabilities of Composite Materials
In the current investigation, the effects of in-service impact damage on the energy absorption capabilities, and damage evolution of two different geometries, corrugated beams, and c-channel stanchions, have been presented. Both the energy absorber geometries were manufactured using two composite material systems, Hexcel IM7/8552 and Hexcel AS4 PW/8552. Two different stacking sequences evaluated were: [90o/0o]2S and [45o/90o/-45o/0o]s. The pristine specimens were secured in a nonstandard fixture and impacted at the center using a drop tower [1]. The specimens were impacted at different energy levels to introduce varying levels of damage. Postdamage introduction, compression tests were performed at 1 in/s using a high-speed servo-hydraulic test frame. All the tests were supported with high-speed Digital Image Correlation (DIC) to obtain damage evolution and surface strains. A comparison of the energy absorption capabilities and damage modes between the pristine specimens and specimens with impact damage has been reported.
Effect of Ultrasonic Welding Process Parameters on the Crystallinity of GF/MWCNT/PP Composites
Ultrasonic welding (USW) is a rapid and efficient joining method for thermoplastic polymer composites. This joining technique offers a high bonding strength between composite materials to form lightweight, durable structures in a costeffective way, compared to other traditional joining methods. Crystallinity at the bond line can influence mechanical properties and chemical resistance. However, despite technological development of the USW process, the underlying crystallization mechanisms at the welded interface are still insufficiently understood. This paper explores the use of polypropylene (PP) and multifunctional multi-walled carbon nanotube (MWCNT/PP) films to perform USW between glass fiber (GF)/PP adherends and the resulting effect of welding parameters on the crystallinity degree at the bonded interface. After the USW process, PP and MWCNT films were isolated from glass fiber laminates using Kapton tapes. The effect of MWCNT content (0, 5, 10, 15, 20, 25 wt.%) and welding parameters on the crystallinity of the films and the welded interface was analyzed using differential scanning calorimetry (DSC) and Scanning electron microscopy (SEM), respectively. It was found that increasing MWCNT percentage resulted in a lower degree of crystallinity (44-34%) for the films and for the welded composite interface (23-9%). Four sets of different parameters (welding force and vibration amplitude) were used in this experiment, (500N, 38.1μm), (500N, 54.0μm), (1500N, 38.1μm), and (1500N, 54.0μm), representing different welding times. It was found that increasing force and amplitude resulted in a higher and lower degree of crystallinity, respectively, at the welded interface. Thus, it is expected that the change of crystallinity during USW may be partially attributed to strain-induced crystallization mechanisms.
Accelerated Pyrolysis Analysis of Thick High-Temperature Composite Parts Using Theory-Guided Probabilistic Machine Learning And Finite Element Analysis
Fabrication of advanced composites for high-temperature applications typically involves a complex, multi-step process. This process includes an initial lay-up step, curing, high-temperature pyrolysis to transform the cured resin into a carbonized amorphous structure, several resin-backfilling steps to fill voids and cracks formed during pyrolysis, additional pyrolysis-densification cycles to further increase the carbon content, and a final graphitization step to achieve the desired crystalline structure of carbon atoms. The processing parameters in each step, as well as the layup and overall thickness of the part, directly impact the kinetics of reactions, phase transformations, and the resulting end-part properties. During pyrolysis, the resin undergoes a complex system of degradation reactions affected by heat and mass transfer through the part thickness. To achieve optimal performance of hightemperature composites, it is crucial to accurately establish the relationship between processing conditions, part geometry, and end-part properties. Current process optimization relies heavily on time-consuming and resource-intensive testing campaigns to characterize pyrolysis kinetics, followed by trial-and-error efforts. This is further complicated by complex temperature cycles, gradients of pyrolysis rate across thick composite parts, uncertainties, and variabilities of the material and process. This paper introduces a novel framework combining theory-guided probabilistic machine learning (ML) and finite element (FE) process simulation to address these challenges. Limited targeted experiments are used to characterize pyrolysis kinetics using an in-house developed ML code while quantifying uncertainty at each testing step. The kinetics model is then used by an FE model to simulate heat transfer and rate of pyrolysis, allowing the gradient of degree of pyrolysis across the thickness of a laminate to be simulated. For validation, laminates of varying thicknesses were fabricated and pyrolyzed using different temperature cycles. Imaging techniques including light microscopy and scanning electron microscopy (SEM) were utilized to capture the resulting microstructures.
Modeling of the Impact Response of Thermoplastic Composites
This work investigates simulation of the global deformation and damage progression response of a thermoplastic panel under high energy ballistic impact. The composite material system is a carbon fiber reinforced low melt semi-crystalline resin TC1225 LMPAEK T700G (T700/LMPAEK†). Several high energy dynamic impact tests were performed where an aluminum projectile impacted various panels at different impact velocities. For this work, the test performed at an impact velocity of 73.2 m/s was investigated. The projectile rebounded upon impact, and the damage to the panel was characterized through ultrasonic C-scanning. Response of the panel under impact and the associated damage is discussed. Numerical simulation of the impact process was performed using the LS-DYNA® computer code [1] with a new material model MAT_COMPOSITE_DAMAGE_DGD (MAT 299), a modification to the MAT 261 material model in terms of an improved representation of damage coupling and additional capability for strain rate effects. Delaminations were modeled using cohesive zone contact formulation in LS-DYNA®, wherein the mixed-mode fracture is captured via the Benzegaggh-Kenane (B-K) [2] mode-dependent fracture energy interpolation law. Simulation of this impact test demonstrates a good match of experimental and simulations results in terms of panel deflection and panel-projectile interactions. The overall extent of delaminations was under-predicted by the simulation. This work forms the basis to model tests performed at higher velocities, involving projectile penetration of the panel.
Interlaminar R-Curve Effects in Thermoplastic Composites: Experiments and Model Correlations
The interlaminar fracture behavior of thermoplastic composites under Mode-I and Mode-II static loading is investigated in this research. The material system under consideration is a carbon fiber reinforced low melt semi-crystalline resin TC1225 LMPAEK T700G (T700/LMPAEK)†. Characterization experiments were conducted to measure the load-displacement response, peak load, and propagation of delamination from a pre-implanted Kapton® insert. The Mode-I response was characterized using a double cantilever beam (DCB) test according to the ASTM D5528-22 standard. It was observed that the propagation exhibited significant resistance to delamination growth, i.e., an R-Curve effect. The test data indicated that the steady-state fracture toughness, ? ?? ? ????, was approximately twice the mean initiation fracture toughness, ??????. The Mode-II response of an end notch flexure (ENF) specimen tested according to the ASTM D7905- 19 standard exhibited an unexpected stable behavior upon attaining peak load. Prior to attaining peak load, the Mode-II response exhibited some non-linearity, which may be attributed to nonlinear bulk material response, e.g., hyper-elasticity, viscoelasticity, plasticity, etc., and potentially friction at the load/support rollers and R-Curve effects. Finite element models based on the cohesive zone method (CZM) and the virtual crack closure technique (VCCT) were used to predict the DCB and ENF specimen responses. DCB analysis results obtained using ?????? predicted propagation consistent with experimental data. However, results obtained with the as characterized ?????? were inaccurate in predicting delamination growth onset and peak load. ENF analysis results obtained with the as-characterized Mode-II fracture toughness, ????????, were inaccurate in predicting the peak load and propagation. Hence, R-Curve effects were included in both DCB and ENF simulations, which enabled improved predictions. The experimentally determined Mode-I R-Curve was used for the DCB simulations, whereas an R-Curve was derived for Mode-II assuming that the change in compliance of the specimen was associated with crack growth only.
Hydrothermal Aging of Glass Fiber Reinforced Thermoplastic Composites
Continuous fiber-reinforced polymer composites (FRPC) are commonly made with a thermoset polymer matrix; however, thermoplastic matrix materials are increasingly employed as an effective substitute in recent years. FRPC used in structural applications are often exposed to water and humid environments, which may deteriorate their mechanical performance. Both thermoset and thermoplastic matrices offer considerable resistance to water ingress, yet, moisture exposure may significantly affect material performance during long-term exposure. These situations become more severe at higher temperatures, where degradation phenomena will be accelerated. Thus, knowledge of the extent of strength reduction under these conditions is a vital input to the engineering design of durable structures. The present study investigates the durability of unidirectional glass fiber reinforced composite tapes made with either a polypropylene or high-density polyethylene matrix, by conditioning samples in deionized water for up to 8 weeks at 60°C and 95°C. Water uptake behavior and tensile strength were measured. The focus of this work is to increase the understanding of damage effects that occur to the fiber matrix interphase and the glass fibers, as these components chiefly dictate the performance of the composite. Mechanical testing was performed on dried material samples after aging. Chemical elements that may have leached into the aging fluid during conditioning were analyzed, and virgin and aged samples were characterized to explore the responsible mechanism for fiber degradation by environmental aging.
Damage Assessment and Classification of Glass Fiber-Reinforced Composite Materials During Tensile Tests Based on Acoustic Emission and Unsupervised Learning Approaches
Advancements in composite materials design have rendered glass fiber-reinforced polymer composites (GFRPC) an effective candidate for various engineering and industrial applications. Some attractive characteristics of GFRPC are low specific mass and high specific mechanical stiffness and strength. Identifying and classifying damage mechanisms is difficult for these types of materials. Several scientific works investigated the failure mechanisms of GFRPC considering different approaches, such as non-destructive techniques and various learning algorithms. However, studies to reliably identify mechanical failures in GFRPC are ongoing. Therefore, the present work investigates non-destructive testing (NDT) combined with unsupervised learning algorithms to identify damage mechanisms in GFRPC during tensile tests. The NDT used for this study is the acoustic emission (AE) technique that detects the waveforms of the different failure mechanisms during testing. Therefore, these waveforms are classified based on unsupervised learning algorithms such as principal component analysis (PCA) and self-organizing maps. The PCA method selects the most suitable AE descriptors to identify the different damage mechanisms. Thus, the self-organizing maps algorithm performs the clustering analysis and classification of the failure mechanisms. The obtained information from the AE descriptors is compared to AE data from the technical literature associated with specific damage mechanisms, matrix cracking, matrix/fiber debonding, delamination, and fiber breaking. Electron microscope images of the failures are presented to validate the results.
Failure Prediction in Large Scale Composite Laminates Containing Bonded Repairs
A finite element (FE) based predictive framework, incorporating NASA’s CompDam composite damage model, has been developed to simulate damage initiation and progression in large carbon fiber reinforced polymer (CFRP) composite laminates containing various scarfed hole configurations. The framework was applied to a CFRP panel with a centrally located double-sided scarf hole. The CFRP laminate is made of carbon/epoxy with layup sequences comparable to transport category aircraft wing skin panels. The experimental work was previously conducted using the Airframe Beam Structural Test (ABST) fixture at the FAA William J. Hughes Technical Center, which can apply combinations of loads simulating various service loading conditions of an aircraft. Results show good correlation between FE analysis and experiment.
Mesoscale Modeling and Homogenization of Woven Carbon Fiber Composites
In this study, we investigated the impact of varying boundary conditions and simulation domain size on the calculation of homogenized elastic moduli, Poisson’s ratio, thermal expansion, and cure shrinkage for woven carbon composites. The boundary conditions of interest included kinematically uniform (KUBC), statically uniform (SUBC), and periodic (PBC). Stress and strain distributions were compared across the entire simulation domain and for sub-volume regions of interest when the domain size was increased. Additionally, homogenized properties were quantified and compared across varying domain sizes. Key results show that effective moduli determined using KUBCs and SUBCs provide upper and lower limits that bounded values determined using PBCs. However, for out-of-plane thermal expansion and cure shrinkage, the effective values were not bounded by the values determined using KUBCs and SUBCs. Thermal expansion coefficients determined using KUBCs and SUBCs were underpredicted compared to values obtained from PBCs. Similarly, cure shrinkage determined using KUBCs and SUBCs were overpredicted compared to values obtain from PBCs. Lastly, it was shown that homogenized values obtain using PBCs could be well approximated using KUBCs or SUBCs with an increased domain size. Specifically, homogenized properties determined using KUBCs or SUBCs exhibited fast convergence to the periodic solution when the simulation domain size was increase both in-plane and out-of-plane, followed by calculation of properties from the centrally located unit cell within the domain.
Fire Performance of Short and Long Glass Fiber Polypropylene Composites for Electric Vehicle Battery Enclosures
In response to the significant need to identify damage and failure modes occurring in lithium-ion (LI) electric vehicle (EV) battery packs under mechanical loading and external fire exposure, this research is designed to evaluate the fire performance of new injection-molded, flame-retarded polypropylenes (PP) with 30% long and short glass fiber, STAMAX30YH570 and PPc-H1030, respectively, for battery pack enclosures. This effort includes a series of experiments to quantify the mechanically loaded composite material plates' thermal, physical, and structural behavior under a one-sided fire exposure. A non-contact thermal digital image correlation (TDIC) method was implemented to measure full-field, transient 3D deformations and temperature distribution over the unexposed surface of the composite plates. The effect of plate thickness, fire exposure size, and glass fiber-reinforcement length were studied experimentally. It was found that the occurrence of intumescence slowed down the spread of heat through the plastic plate thickness, as it created a thermal shield. No significant intumescence was observed in thin plates before failure, and it was found that increasing the plate thickness delayed the failure time by a factor of approximately six, while having no significant impact on the unexposed surface failure temperatures. The fire performance of the composite plates under extremely large fire exposure was characterized, and the coupled impacts of thermal expansion and intumescence on the failure of long- and short-fiber composites was studied. Some perspectives and outlooks on the enhancement of the complex interaction of the composite plate and the simulated mechanical loading are proposed for future development.
Molecular Dynamics Modeling of PEEK Resin Properties for Processing Modeling
The remarkable properties of Thermoplastic Matrix Composites (TMCs) including their ability to tolerate damage, low weight, high resistance to impact, and mechanical toughness, make them highly desirable for use in aerospace structures. TMCs undergo various cooling and heating cycles at elevated temperatures during the processing, which triggers the formation of crystalline regions resulting in matrix shrinkage and the generation of residual stresses in the final composite. To minimize the development cycle time and cost of future applications of TMCs, it is crucial to optimize materials manufacturing parameters, and component design. Manufacturing process of TMCs has a significant impact on their microstructure, which plays a critical role in controlling their in-service performance. Given that the thermo-mechanical properties of composite materials are influenced by phenomena at various length scales, a multiscale computational approach is necessary to predict manufacturing parameter-property relationships accurately and efficiently. Also, thermomechanical properties in semi-crystalline thermoplastics are closely linked to their crystallinity content, which is precisely regulated by both material properties such as melting and crystallization temperatures, and processing parameters like crystallization temperature and temperature holding time. Therefore, molecular-level material properties should be determined across a broad range of crystallinity levels to facilitate the multi-scale process modeling of thermoplastic composites. This study implemented molecular dynamics (MD) modeling to predict the thermo-mechanical properties and volumetric shrinkage of PolyEther Ether Ketone (PEEK) resin, a thermoplastic material, as a function of temperature and crystallinity content. The thermo-mechanical properties are linked to processing time and temperature via crystallization-kinetics models.
Hypervelocity Impact Investigations of Composite Truss Tubes for In Orbit Assembly Risk Assessment
The number of threats to space structures due to micrometeoroid and orbital debris (MMOD) impact continues to increase as the density of structures in orbit increases. Upon impact from (MMOD), the structure will have significantly reduced strength, however additionally; the debris shed post-impact causes a compounding risk of damage to the in-orbit assembly field [1]. MMOD impacts have an average velocity envelope between 9 and 10 km/s in the orbit of the International Space Station (ISS). Still, they can range between 3 and 20 km/s depending on the position of the space vehicle at the time of impact [1]. Many space structures, like that of the James Webb space telescope (JWST), and the in-space assembled telescope (ISAT), utilize fibermatrix composites consisting of various shapes and sizes [2]. In particular, the ISAT is designed to use composite truss members to connect instruments to the rest of the telescope and structurally serve as the telescope's backbone [3]. Hypervelocity impact (HVI) damage to flat plate composites has been widely discussed. However little to no research has been published on the effect of HVI on composite tubes. Understanding the effect of the localized damage caused by MMOD impact on the overall strength of the individual truss member and structure as a whole is crucial to providing insight into the state of current structures and aiding in the design of future structures. To simulate MMOD impact, a unique two-stage light-gas gas gun, designed for impact velocities between 2 and 7 km/s is used [4]. Investigating the postmortem inlet and exit diameters, residual compression strength, and in situ debris cloud tracking of characteristic carbon fiber reinforced polymer (CFRP) tubes will provide data used to reinforce current computational models of the event. Combining the results from the Lagrangian finite element (FE) model with the Eulerian hydrodynamic model will allow the verification of damage effects only seen due to hypervelocity impact. These results will be used to aid in understanding the risk of MMOD impact on current structures and assist in developing systems more resilient to HVI.
Cross Scale Simulation of Fiber-Reinforced Composites with Uncertainty in Machine Learning
Cross scale simulation aims to develop computational models that can capture the behavior of a system at multiple scales, from microscopic to macroscopic level. To explore the constitutive relationship of materials, a widely used conceptual and numerical tool called Representative Volume Element (RVE) is introduced to solicit information from their subscales in finite element analysis. It characterizes the behavior at one quadrature point of a physical device by homogenizing the local behavior over finer scales. By replicating the RVE throughout the analysis domain, a homogeneous finite element model can be synthesized, simplifying the analysis of a heterogeneous material in the presence of uncertainty, such as variations in loading, material properties of micro-constituents, and modeling physical behavior. Moreover, the generation of many similar data at subscale introduced by homogenization in RVE is usually tackled by statistical methods. In this work, we explore the mechanical behavior of a hybrid composite material, consisting of glass and carbon fibers embedded in an epoxy resin for use as a battery enclosure, using a novel energy density informed neural network architecture. We model the material properties of fiber tows and resin as random variables and use input strain tensors from a macro-scale three-point bend test simulation. History of stress tensors and strain energy density are extracted as outputs for supervise learning. In the neural network architecture, Physical constraints are implemented by introducing a novel energy density layer for the prediction of stress along the direction of tows. A long-short-term-memory (LSTM) neural network training on the same dataset is also conducted for comparison. Elimination of spurious discontinuities is obtained by PCA (Principal Components Analysis) in the stress-strain curve when predicting stresses in directions transverse to the tows, YY and ZZ directions. We develop a user-defined subroutine in LS-Dyna and conduct a mesoscale simulation to verify its accuracy.
Fiber Orientation Prediction at Multiple Thicknesses in a PPMC Tensile Coupon
This study evaluated the ability of artificial intelligence tools to reconstruct local fiber orientation distribution (FOD) at multiple thicknesses of a prepreg platelet molded composite (PPMC) specimen. A deep convolutional neural network (DCNN) was employed to accurately predict FOD at three thickness regions and the total thickness of a molded specimen by using thermally induced strain on the surfaces of the specimen. The developed DCNN architecture was trained with thousands of synthetic finite element morphologies of PPMC plates. The DCNN performed well on the synthetic data and predicted the FOD in the specimen with a 0.071 mean absolute error (MAE) for the entire specimen thickness and 0.128, 0.145 and 0.125 MAE for the top, middle and bottom thirds of the specimen thickness, respectively. The proposed methodology predicted the spatially varying FOD at multiple thickness levels in PPMC parts and can be used for a nondestructive evaluation process to detect erroneous fiber orientation in PPMC components.
Experimental and Computational Investigation into the Use of Discontinuous Fiber Composites to Manufacture a Bracket
In this study, Discontinuous Fiber Composites (DFCs) are used to manufacture a bracket with two platelet sizes, a narrow and square platelet. X-ray CT scans were performed in order to obtain the exact mesostructure of the bracket. From this, areas of low and high flow of platelets are observed and the effects of this are studied. The exact orientations are obtained and mapped onto a digital twin of the bracket for Finite Element (FE) simulations. The model is validated against uniaxial tension experiments. The FE model can precisely predict the apparent stiffness, strength, and match the failure locations seen in experiments. By making a one-to-one copy of the brackets, a better understanding of the failure mechanisms of complex DFC systems can be obtained.
Evaluating Rate Dependent Behavior of Silane Molecules with Molecular Dynamics Simulations and Machine Learning
In this study, silane molecules of different functionalities and molecular weights are evaluated for their performance under different strain rates 109, 1010, and 1011 1/s in Mode I. loading. Molecular Dynamics simulations are performed over the systems made of a single silane molecule bound to the glass surface via one or two bonds and are simulated in the extended or relaxed position resting on the fiber surface. The silane molecules are categorized into three classes based on these three bond failure mechanism within the silane molecule: (1) Silicon-Oxygen/Silicon-Carbon, (2) Nitrogen-Carbon, and (3) Oxygen-Carbon. For all the configurations of silane molecules simulated, the peak strength demonstrated by the silanes which failed with the 1st bond failure mechanism was higher than those failing with the 2nd and 3rd mechanisms. For each failure mechanism, it is observed that the energy absorbed at failure increases with the chain length of the molecule. The non-bonded interactions between silane molecules and the glass surface contributed to the overall energy absorption. 16 to 29 % of the total energy absorbed was due to non-bonded interactions by different silane molecules. In the end, a methodology to develop and implement a Machine Learning model of Variational Auto-encoder is presented to utilize the MD simulations performed at different strain rates and configurations to predict new silanes with improved rate-dependent strength and energy absorption.
Computational Modeling of Radiation Effects in Carbon Fiber-Reinforced Polyethylene Composites
Radiation effect in carbon fiber-filled polyethylene composites are of importance in space and aircraft applications. A two-fold approach is employed to study radiation effects in carbon nanotube polyethylene as the exemplar. First, a radiation transport model is created with a single-wall carbon nanotube (SWCNT) as thin carbon slab superimposed on a slab of medium-density polyethylene matrix. Different weight fractions of SWCNT are examined and compared with an integrated model for the shielding abilities of galactic cosmic radiation. Second, molecular dynamics simulation with bond-order force field are conducted for 350 eV carbon recoil cascade simulation. Preliminary results discuss the effect of SWCNT on the radiation damage of crystalline polyethylene. Transport simulation demonstrate the efficacy of the slab model in predicting the shielding abilities and concluded that the dose increases with increasing SWCNT filler. Molecular dynamics simulations demonstrate that adding SWCNT enhances the radiation resistance with fewer free molecules produced.
Integrating Deep Learning with Guided Wave-based Simulation to Predict Delamination Location in Composite Structures
In the present study, a numerical framework integrating deep learning with guidedwave- based finite element (FE) simulation is developed to accurately predict the delamination location in a composite structure. In the FE model, composite structure is modeled as an 8 layer [02/902]2 laminate. Elliptical delamination with randomly selected orientations and in-plane locations, is placed at the interface between top 0° and 90° layers. The guided wave is excited by a piezoelectric transducer, and the out-of-plane displacement signals are collected at eight prescribed sensor locations. The initial sensor signal is processed using continuous wavelet transform (CWT), and the convolutional neural network (CNN) is utilized to predict the delamination location. With the baseline model trained, the CNN model is extended to predict the location for circular shaped delamination. The use of transfer learning to minimize data needed for CNN model in predicting the location of delamination of a different shape is also investigated. The results show that the CNN-based framework can accurately identify delamination location given the sensor signal. Furthermore, the combination of modeling randomly distributed and oriented elliptical delamination, along with transfer learning, proves to be an effective strategy for reducing the additional data required for a new delamination shape.
Investigation of Carbon Black/Ultra-High- Molecular-Weight-Polyethylene Nanocomposites Manufactured by Compression Molding and Equal Channel Angular Extrusion
Conductive carbon black (CCB) reinforced ultra-high molecular weight polyethylene (UHMWPE) polymers are investigated by micro-computed tomography, scanning electron microscope, and mechanical testing. The composites are manufactured by two techniques: compression molding (CM) and equal channel angular extrusion (ECAE). It is observed that electrical conductivity increases for the composites with the higher concentration of CCB inclusions without significant loss of tensile toughness. At the same time, ECAE procedure decreases the observed thickness of the CCB-rich layer and decreases electrical conductivity of the UHMWPE composites as compared to CM. Concentration of carbon inclusions in CCB-rich layer was evaluated for different weight fractions of CCB in the overall composite. Preliminary studies indicate that ECAE doesn’t change the orientation and elongation of UHMWPE particles in the CM consolidated composites.
Effect of Polymer/Fiber Affinity on the Performance of Silk Composite Laminates
Aerospace industry is intensely shifting towards the usage of composite materials, as the new Airbus and Boeing aircrafts, among others, comprise increasing percentages of these materials. Beyond their higher specific mechanical properties, fiber reinforced polymer composites are non-magnetic, and thus do not interfere with the magnetic compass of the aircraft, making them particularly suitable for the aircraft’s skin. Recent sustainability concerns and environmental awareness has led to the popularity of natural fibers as eco-friendly reinforcements in polymer composites. Among natural fibers with established potential applications, silk fibers have recently received considerable attention from researchers due to their remarkable properties. Strong, lightweight and flexible, silk is a viable natural reinforcement that can be repurposed for composite industrial use. However, silk composite laminates are hardly used in aerospace products due, in part, to a lack of affinity between the silk fibers and epoxy, the polymeric resin often used to manufacture silk composites. This paper investigates the effect of polymer/fiber affinity on the performance of silk composite laminates. To this effect, the silk/resin contact angle is measured for different resins, and correlated with the mechanical properties of the silk composite laminates fabricated by vacuum assisted resin transfer molding (VARTM). The ability of the resin to impregnate the woven silk fiber preform is observed to affect the mechanical performance of these laminates as well as their overall quality.
Adaptation of the Microplane Constitutive Model for Brittle-Plastic Glassy Polymers
This paper presents a microplane constitutive model for the tensile and compressive damaging behavior of brittle-plastic glassy polymers. The model is formulated and validated using experimental data on such polymers and is an adaptation of the previous microplane model formulation developed for concrete. The model considers a material point as a Gaussian approximation of a unit sphere, discretized into several “microplanes”. The macroscopic strain tensor is projected onto these microplanes yielding various micro-strain vectors. The various damage mechanisms such as tensile microcracking, shear microplasticity, and micro-crack friction are formulated in terms of the microplane level strain vectors, yielding corresponding stress vectors. These are then homogenized via the principle of virtual work yielding the macroscopic stress tensor. One of the salient features of the present adaptation includes a volumetric-deviatoric (V-D) split in the microplane level stresses and strains. This enables properly capturing a Poisson’s ratio greater than 0.25, which happens to be the case with most polymers. On the other hand, a normal stress comparison algorithm is implemented to alleviate the overestimation of stresses which can happen due to the V-D split. The proposed adaptation is validated using experimental data from uniaxial tension and compression tests on two different polymers, which includes post-peak inelastic behaviors such as hardening and softening or both. The model shows excellent agreement with the experimental data, demonstrating its ability and applicability to accurately capture the various damage mechanisms in brittle-plastic glassy polymers. The results presented here are at the material point level, and the application to structure level problems via a user material subroutine in a finite element software is in progress.
Characterizing Thermal Degradation in Semi-Crystalline Thermoplastic Composites
Semi-crystalline thermoplastic composites, such as carbon fiber-reinforced polyetheretherketone (PEEK) and polyetherketoneketone (PEKK), are processed and consolidated while melted at high temperatures. During cool-down, polymer chains fold into lamellar structures at the nanoscale to form crystalline morphology. These lamellar structures radiate from a nucleus, creating spherulitic structures in bulk polymers, and transcrystallinity in fiber reinforced polymers. A certain amount of thermal degradation occurs when the thermoplastic matrix is melted, and the amount of degradation is a factor of several parameters such as melting temperature, time at melt, and whether the material is processed in an inert environment such as nitrogen. One form of degradation that occurs in the matrix is cross-linking and oxidation. In this case, the polymer chain breaks and new bonds form between chains or within the chain. Moreover, thermal degradation affects crystallization, the lamellar thickness and spacing, and overall degree of crystallinity. The spacing between lamellar structures can be measured through Small Angle X-ray Scattering (SAXS) at nanoscale, while the degree of crystallinity can be found using Wide Angle X-ray Scattering (WAXS). To study thermal degradation, the effect of melting temperature, environmental condition, and reprocessing was investigated on samples of neat PEEK, as well as carbon-fiber PEKK prepreg. Additionally, these samples were thermally cycled multiple times, and repeats were performed for each condition. Degree of crystallinity, spacing, and lamellar thickness were measured using an x-ray scattering system. To study underlying physics and correlations, a probabilistic Machine Learning (ML) framework was used for regression. Using this approach, different thermal degradation mechanisms for neat resin and prepreg samples were demonstrated at the nanoscale. The differences were explained in terms of crystallinity and nucleation around fibers in prepreg. This framework provides a unique holistic understanding of crystal formation and degradation, which affects the reprocessability and end-part properties of semicrystalline thermoplastic composites.
Shape Control for Thermoplastic Composites Made by Automated Fiber Placement Using Annealing
The goal of this research is to undo the visible warping and relieve the residual stresses of thermoplastic composite parts manufactured using automated fiber placement (AFP) technology by designing an annealing cycle. AFP is an automated process that allows for the manufacturing of flat and round parts from various materials, including thermoplastic composites. The samples were made from carbon fiber reinforced polyether ether ketone (PEEK) tape and were manufactured on a 6- axis AFP system with a hot gas torch. The residual stresses arise due to the large temperature gradients in manufacturing and the subsequent uneven cooling. The warping is problematic because finished parts vary significantly from their intended geometry. The curvature of samples with 4, 12, and 15 layers were measured using a laser measuring system that is comprised of a platen that allows users to pinpoint x-y coordinates and a laser to provide the elevation. MATLAB was used to compute the second order polynomial that best represents this surface. The curvature at any point on this surface can be calculated using partial derivatives. Annealing in an oven and using a heat blanket were explored as out-of-autoclave options. A reduction in the mean curvature of 86%-90% was observed in unidirectional samples with an annealing cycle comprised of a three-hour hold at 200°C and vacuum pressure of 15 torr. The sample with a symmetric unbalanced layup sequence only had a 17%-19% improvement to its mean curvature.
Optimized Core Geometry for Energy Absorption in 3D-Printing Sandwich Panels: A Comparative Study
The demand for lightweight and durable materials is continuously increasing, leading to the escalated utilization of sandwich structures across various engineering applications, including biomedical, automotive, renewable energy, aircraft, and transportation. This preference is driven by the unique mechanical properties of sandwich materials including superior energy absorption, reduced density, higher stiffness-to-weight, and strength-to-weight ratios, Consequently, this demand has driven the development of advanced composite materials with multifunctional performance. Sandwich panels encompass a wide range of designs, including Triply Periodic Minimal Surfaces (TPMS), commonly observed in diverse natural systems. This study aimed to assess the mechanical properties of sandwich structures with different core geometries through a combination of numerical simulation and experimental impact testing. Specifically, the investigation focused on a type of TPMS sheet structure and its comparison with a typical honeycomb structure to identify the most suitable core geometry for 3D-printed lightweight sandwich panels with high energy absorption capacity. The architected sandwich panels firstly were fabricated using the 3D printing technique and PLA filaments. A numerical simulation was performed to assess the response of sandwich structures when subjected to impact testing. Furthermore, the experimental impact test was carried out to estimate the mechanical behavior. Both experimental and numerical results clearly demonstrated the significant impact of meta-sandwich structure topology and geometrical parameters on the energy absorption capabilities of the panels.
Analysis of the Influence of Drilling Parameters and Monitoring of the Delamination Phenomenon in Thermoplastic CFRP Machining
Carbon fiber reinforced Polyamide 6 (Nylon 6) composites have a high potential for use in the aerospace, automotive, and energy industries. Parts of polymeric composites are generally manufactured in dimensions close to those used by the hot compression molding process. However, the assembly of these components in manufacturing a product occurs by riveting or screwing, which makes it necessary to drill holes. The central hole quality problem during the machining of carbon fiber-reinforced polymeric composites (CFRP) is the delamination phenomenon. Separating the composite layers at the entrance of the cutting tool (peel-up delamination) and exit (push-out delamination) harms the resistance, stiffness, and reliability of the components. Many strategies are used to suppress the occurrence of delamination, including the selection of suitable machining parameters, the use of specific tool geometries, and the use of different materials for making drills. Ways of monitoring the drilling process to prevent delamination are also researched. The present study aimed to analyze the drilling process of a thermoplastic polymeric composite reinforced with carbon fibers, verifying the influence of the variation in the drilling parameters of cutting speed and feed rate in the thrust force and push-out delamination factor. It was carried out through two different 32 full factorial matrices, testing cutting speed from 35.95 to 133.12 m/min and feed rate from 0.018 to 0.118 mm/rev. It also investigated the potential use of thrust force signals for monitoring delamination formation during the drilling process.
A Novel Design of Elliptical S-Chiral MetaComposite: The Finite Element/Experimental Data Approach
This paper addresses a new concept of chiral metastructure the so-called elliptical S-shape chiral. All five groups of metamaterials studied exhibited large anisotropy. This the anisotropic behavior is controlled by the ellipses’ eccentricities. Moreover, the anisotropic response is also more evident when the loading axes are considered. For x-axis compressive loading conditions, the stiffness decreases as the ellipse eccentricity increases. The Poisson ratio's magnitude increases with the increase of a/b aspect ratio, showing a very high auxeticity when the ellipse is close to a flat configuration. In this case, the Poisson ratio was near to -18. For y-axis compressive loadings, the stiffness increases with the decrease of a/b aspect ratio leading to a flexible metastructure. The Poisson ratio's values decreases with the increasing of a/b aspect ratio, but all values were near zero (between -0.35 and -0.05). It seems that the transversal section practically does not change when the metastructure is compressed through y-direction.
Homogenization Methods for Multiscale Process Modeling Through Full Factorial Design
Crucial to developing the next generation of high-performance composites are multiscale process models which have the capacity to predict in-service performance affecting residual stresses and deformations generated during manufacturing. Length scale and geometrical complexity of composites increase in tandem; thus, process models must rely upon methods for homogenization of the curing process. This work proposes a novel, high-fidelity computational approach which leverages finite element (FE) analysis at the microscale to predict effective composite properties at arbitrary cure and temperature states. The approach is applied to a high-fidelity representative volume element (RVE) and low-fidelity repeating unit cell (RUC) that models a 75% fiber volume fraction AS4-carbon fiber/epoxy composite microstructure. Elastic properties of the composite are characterized across several temperature and cure states for each FE model. Two classical closed-form composite homogenization approaches are also used to predict effective properties at each cure state. Predictions obtained by each method are compared against those of the RVE on a state-by-state and property-to-property basis.
High Buckling Strength of Auxetic Carbon Fiber Composite Laminates
This research focused on testing the effect of the negative Poisson’s ratio of a carbon fiber composite on its critical buckling load. A secondary goal was to determine the accuracy of simulation compared to the experimental results for carbon fiber composites. In order to accomplish these two goals, both simulation and experimental testing were employed. For the simulation, ABAQUS software was used to determine predicted values for the critical buckling loads of auxetic and nonauxetic composites as well as the respective nonlinear force behavior of these composites. These results were then compared to experimental results of four auxetic and four non-auxetic specimens each experiencing uniaxial compressive tests. The results of simulation and experimentation showed that the critical buckling loads, and force sustained in general, of the auxetic composites were about three times higher than those of non-auxetic composites. While it appears that the negative Poisson’s ratio has a significant impact on the buckling strength of composite materials, further testing is required to determine the effects of other factors on the critical buckling loads. Along with this, the simulation was more accurate for the auxetic composites than for the non-auxetic composites. Therefore, further testing and simulation are required to determine the limits of simulation accuracy for composite structures.
Mechanical Characterization of Epoxy Resin Manufactured Using Frontal Polymerization
Frontal polymerization (FP) is a promising alternative manufacturing method for thermoset-based fiber-reinforced polymer composites (FRP) in comparison with the traditional autoclave/oven-curing method, due to its rapid curing process, low energy consumption, and low cost. Optimizing the weight contents of initiators relative to the resin’s mass is needed to adjust the mechanical properties of FRPs in industrial applications. This study investigates the effect of varying the photoinitiator (PI) weight content on tensile properties and the frontal polymerization characteristics, including the front velocity, front temperature, and degree of cure, in the FP process of the epoxy resin. Specifically, a dual-initiator system, including PI and thermal-initiator (TI), is used to initiate the polymerization process by ultraviolent (UV) light. The weight content of the TI is fixed at 1 w%, and the relative PI concentration is varied from 0.2 w% to 0.5 wt%. Results show that increasing the PI amount from 0.2 wt% to 0.3 wt% significantly improves the front velocity and the degree of cure by about two times. Increasing the PI content from 0.3 wt% to 0.4 wt% results in 15% and 26% higher degree of cure and front velocity, respectively. Moreover, due to the different front velocity in the top and bottom regions of the specimen, the specimens with 0.4 wt% PI exhibited a curved shape. The specimen with 0.5 wt% PI is thermally degraded and foamed. By comparing tensile properties, it is found that increasing the PI concentration from 0.2 wt% to 0.3 wt% improves the tensile strength and Young’s modulus by 3.91% and 7%, respectively, while the tensile strength and the Young’s modulus of frontal polymerized specimens are on average 8% and 14% higher than traditionally ovencured ones, respectively.
Multiscale FE Modelling and ANN to Predict Mechanical Properties of Non-Crimp Fabric Composites With Manufacturing Induced Defects
Fiber-reinforced plastic (FRP) composites comprising unidirectional non-crimp fabrics (UD-NCFs) have recently gained considerable traction for fabrication of liquid composite molded parts. However, the variations in the microstructure of UD-NCF composites poses challenges in predicting and optimizing their properties. Additionally, their mechanical properties are influenced by process-induced defects, including variations in the relative position and shape of the tows, in-plane tow misalignment, out-of-plane tow crimping, and non-uniform fiber volume fraction. Thus, there is a need to develop robust tools to predict the mechanical properties of NCF composites that capture the critical manufacturing-induced defects. In this study, a multiscale finite element (FE) modelling approach is proposed to predict the in-tow (micro) and lamina-level (meso) effective properties of UD-NCF composites in order to support the use of artificial neural networks (ANNs) for the same purpose. First, a microscopic analysis was conducted to capture the material micro and mesoscale structure and process-induced defects. Second, microscale and mesoscale FE models were constructed based on the microscopic analysis, where process-induced defects were included within the associated representative volume elements (RVEs). The developed multiscale modeling approach was intended to generate an adequate amount of reliable training and testing data for ANN models. Finally, micro and mesoscale ANN models were developed, trained, and tested to predict the relations between inputs (i.e., constituent properties and material structure parameters) and outputs (i.e., in-tow and lamina-level effective properties). The trained ANN models reduced the calculation time from hours in multiscale FE modeling to seconds without sacrificing accuracy.
Effect of Fabric Stabilization Medium on the Interlaminar Shear Strength of Unidirectional Carbon/Epoxy Laminates
Dry unidirectional fiber preforms need to be stabilized by stitched or adhesively bonded materials to maintain a fixed fiber position and alignment during infiltration, compaction, and cure processes for composite laminates. However, these stitching and binding materials can have deleterious effects on the quality of manufactured laminates, such as in-plane-wavy fibers, resin rich areas, and a weak interface between the stabilization material and the matrix of the composite. Little information is available on the interlaminar shear strength (ILSS) of unidirectional carbon/epoxy composites with various types of stabilizing materials within individual plies. The objective of the current investigation is to experimentally evaluate the effect of plywise stitching and thermoplastic adhesive binding on the ILSS of unidirectional carbon/epoxy composites. One stitched fabric and two thermoplastic-bound fabrics were evaluated. Four laminates of two different sizes were manufactured using resin film infusion (RFI). Laminate quality was evaluated based on void and fiber volume fractions and ILSS from short beam shear (SBS) testing. Laminates with stitches demonstrated a lower ILSS (34.3 MPa) than those with binder (49.6 MPa). Manual removal of the binder before processing provided the highest ILSS (52.7 MPa). Laminates manufactured with stitched and bound fabrics had interlaminar failure modes connected to the stabilization materials. Laminates fabricated with the stitched fabric exhibited lower fiber volume fractions (55-56%) than those fabricated with binder (62%) and removed binder (66%). This result is attributed to the greater resistance of the stitched fabrics to compaction, in comparison to the binder and no binder fabrics. Void volume content was nearly the same in all four laminates— between 1% and 2%.
Effect of Representative Volume Element Size for Creating Statistically Equivalent Composite Microstructures
Micromechanical models of fiber reinforced composites often need to have fiber arrangements which are equivalent to manufacture samples to capture local features such as fiber clusters or matrix pockets which may impact failure. These features can vary in size, requiring that models must be large enough to capture features which may be most important. In this study, different size windows of larger composite scans were sampled, and descriptors were measured which characterize fiber and matrix dense regions. Statistically equivalent microstructures to these windows were generated and simulated for transverse strength and stiffness using a reduced order micromechanical model. Results showed that certain statistics could be captured by smaller window sizes compared to larger, and that some statistics could not be captured by the largest window size. Also shown is how transverse strength and stiffness varied depending on microstructure size.
Molecular Dynamics Investigation of the Effects of Defects and Transverse Pressure on the Axial Tensile Behaviors of Polyethylene Crystals and Fibrils
Experimental AFM images have revealed that the structure of ultra-high molecular weight polyethylene (UHMWPE) is porous at the fibril length scale. However, the effects of voids on the mechanical properties of PE fibers are not well understood. We employ molecular dynamics (MD) simulations to investigate the behavior of porous PE crystals under transverse pressure, which can be manifested during processing or transverse impact. We first focused on investigating the influence of the cut-off function in the Reactive Empirical Bond Order potential on the predicted properties of polyethylene crystals. Our objective was to identify the most accurate and computationally efficient implementation of the cut-off function. Through our investigation, we discovered that modifying the lower cut-off radius of the existing cutoff function yields reliable results while maintaining computational efficiency. Building upon this, we conducted MD simulations to analyze the behavior of polyethylene crystals with voids under transverse compression. Our simulations revealed that the collapse of voids is influenced by their state, whether they are vented or closed. Moreover, the strain rate significantly influences the process of void collapse. The outcomes of this study lay a solid foundation for future research endeavors, particularly in exploring the response of porous UHMWPE structures to transverse compression and axial tensile loading.
Tensile Properties of Unidirectional Polymer Composites Reinforced by Aligned Carbon Nanotube Yarns
Carbon nanotubes (CNTs), as they possess outstanding mechanical properties and low density, are considered as one of the most promising reinforcements in composite structures. Due to their capability of transferring loads, CNTs in long continuous forms such as yarns and tapes can withstand 20 times as much load as steel can do at the same weight. In this research, carbon nanotube yarns were wound onto an aluminum plate using a custom-built fixture to fabricate a unidirectional strip. Then, by brushing epoxy resin on the strip and laminating four layers, the unidirectional CNT reinforced epoxy resin composite beam specimens were produced. The mechanical properties of the unidirectional CNT-reinforced composite (CNTRC) were determined using standard tensile tests. This study presents a method for manufacturing CNTRC out of CNT yarns, determining the CNTRC’s Young’s modulus as well as the tensile strength, and obtaining its strain field via digital image correlation (DIC) method. It is observed that the pressure due to sandwiching of the aluminum plates during the manufacturing process leads to nonuniformity of the specimen in the width along midspan of the longitudinal direction which results in the specimen’s not being perfectly unidirectional. This phenomenon can cause the matrix cracking in tensile test and reduce the ultimate tensile strength up to 78% in comparison with perfectly unidirectional specimens. However, the Young’s modulus of such composites is comparable with those obtained from previously existing research. Also, Results from DIC showed the possible failure prone areas in the specimens, as it presents a up to 64% difference between the highest and lowest strain in the tensile loading direction through the specimens. This study will serve as a foundation for future research involving CNT composites, particularly the use of their high anisotropy to produce auxetic composites with large negative Poisson’s ratios.
Improving Uniaxial Dynamic Tension Testing of Composite Specimens
Validation of composite specimens on the order of a few millimeters in length in tension can be examined dynamically via uniaxial test rigs and split Hopkinson pressure bars. For compression testing, hydraulic/gravity drop towers and the Hopkinson bar are permissible for larger specimens (on the order of centimeters in length) and up to 1,000 1/s. Uniaxial tension test methods for composite specimens enabling both configurations, i.e., several centimeters in length and at strain rates up to 1,000 1/s, is much more limited. The goal of this research investigation is to test precisely in this regime by optimizing the composite coupon specimen for dynamic material characterization. For this project, a tension setup using a single Hopkins on bar was adapted to enable up to 6 cm long specimens tested at the requisite strain rates. Coupon specimens were then optimized using machine learning to promote stress in the gage region thereby minimizing testing failures if the specimen were to break near the grips. Using these two systems, we may have a proof of concept for high strain rate tension testing of composites that is optimized for validation studies using machine learning based geometries.
Generating Woven Textile Models with Induced Fiber Entanglement for Controlling Composite Thickness
Generating realistic tow geometries is important for making effective models for textile composite materials. The geometry of the tows is controlled by the compaction response of the textile during manufacturing. Attaining a realistic compaction response from a textile model has been difficult due to the representation of fibers as unentangled. These tows containing idealized, parallel fibers without fiber entanglement or meandering compact with less resistance than tows with the entanglement found in manufactured textile composites. In this study, a method of introducing entanglement to the tows within a textile was created which selectively swapped fiber positions at different cross sections along the length of the tow. This method introduces entanglement and meandering into a textile while ensuring the fibers do not cross into the bounds of the surrounding tows. The entanglement was controlled by varying the frequency (probability of swapping) and distance (swapping radius standard deviation) of fiber path pairs being swapped within each tow at cross sections separated by the swapping plane spacing along the length of the tow. When applied to a plain weave textile, it was found that the greater the entanglement, the greater the compaction pressure vs composite thickness of the plain weave textile. While examining the ability for entanglement to control the compaction response of the textile, it was found that the compaction pressure-composite thickness response of a manufactured specimen was able to be replicated.
Effects of Consolidation Process on the Tensile Strength of UHMWPE Filaments Extracted from Composite Panels
This research focuses on the investigation of damage mechanisms induced through the processing and consolidation of UHMWPE composites (HB210). The HB210 composites consist of Dyneema® fibers and thermoplastic polyurethane resin. The composite panel consisting of 72 sheets was processed following the manufacturer’s recommended temperature and pressure profile of 100°C and 2 MPa (290 psi) for 10 minutes, followed by 125°C and 20.7MPa (3ksi) for 30 minutes. Each sheet consists of 0/90/0/90 ply orientation with an average sheet thickness of 200 μm. To quantify the effects of consolidation pressure on fiber deformation and tensile strength distribution, a technique for extracting fibers from the processed panels was developed. Specimens (11 x 19 x 152 mm) were cut from the panel and immersed in tetrahydrafuran (THF) fluid for 7-20 days (dependent on the specimen thickness). The THF effectively dissolved the matrix enabling UHMWPE fibers to be extracted at different locations through the thickness. The baseline tensile strength distribution was based on testing virgin fibers from the spool and fibers extracted using the THF method from a single as-received layer of HB210. The two baselines exhibited statistically equivalent tensile strength distributions proving the THF extraction method did not affect the fiber properties and that degradation of tensile strength is a result of the consolidation process. From tensile test data, strength distributions for extracted fibers from consolidated panel were generated, and strength at 50% failure probability was evaluated. Compared to the baseline, the fibers extracted from the processed panel showed a 15% reduction in the average tensile strength. SEM microscopy of the extracted fibers from the consolidated panel exhibits different damage modes. Surface cracking and flattening damage modes were induced by the consolidation pressure (20.7 MPa) applied in the thickness direction of the panel. Additionally, axial kinking was observed along the length of the fibers. The possible mechanisms for the formation of these kinks are – viscous forces from the resin during the consolidation process, where fibers loaded in compression are observed to kink into large voids between fibers, or due to the CTE mismatch between the fibers and the resin within a layer or between the 0 and 90 layers within a sheet during the cooling stage.
Effect of Surface Preparation on the Damage and Fracture Behavior of Carbon Fiber- Reinforced Polymer and Titanium Tubular Adhesive Lap-Joints
This work evaluates the bond durability for adhesive tubular lap-joints (TLJs) between titanium and CFRP using static tensile tests. Five different treatment methods are introduced to prepare the surface of the CFRP: (1) sanding, (2) air atmospheric pressure plasma treatment (APPT), (3) as-received, (4) Frekote 710NC to act as contamination, and (5) Frekote 700NC plus air APPT to understand the APPT ability to remove contamination. Characterization of the treated surface is done using X-ray Photoelectron Spectroscopy (XPS), Scanning Electron Microscope (SEM), and Water Contact Angle (WCA) to examine surface energy. Results show that air APPT produces the lowest WCA compared to the other treatment methods, indicating high surface energy and wettability. When the CFRP surface is prepared by sanding, it causes breakage to the underlying fibers, exposing them to the environment. As a result, asreceived CFRP has better bond strength than when prepared with sanding. This study evaluates the durability of adhesive TLJ and builds a relationship between surface characteristics and performance, providing insight into their behavior and knowledge of optimal surface preparation principles.
Effect of Fiber-Matrix Interface on Fiber-Direction Compressive Strength of Carbon Fiber Composites
The rotorcraft industry has shown a strong interest in High-modulus (HM) carbon fiber-reinforced polymers (CFRPs) due to their potential to create lightweight airframes and rotor components, resulting in significant weight reduction. However, a major drawback of HM CFRPs has been their very low compressive strength in the fiber direction compared to the currently used intermediate-modulus (IM) CFRPs in primary structures. This weakness has been delaying the implementation of HM CFRPs in aircraft structures. Microstructural tailoring may provide an innovative means for breaking through the fiber-direction compressive strength barrier of the HM CFRPs. The primary failure mechanism in both HM and IM CFRPs under fiber-direction compression is shear microbucking, which is significantly influenced by fiber-matrix interface strength. In-depth analysis using in-situ scanning electron microscopy (SEM) experiments has revealed significant differences in the surface characteristics of the carbon fibers, leading to a much stronger interface for IM fibers compared to HM fibers. These findings have prompted a microstructural tailoring strategy involving the reinforcement of HM fibers with IM fibers, which enhances the overall stability of the microstructure governing the fiber-direction compressive strength performance of the material. A laboratory-scale production-quality manufacturing system has been delivered, and promising experimental results enabling HM CFRPs with adequate fiber-direction compressive strength have been achieved through hybridization of IM and HM fibers at the filament level in HM CFRP toughened with nano-silica. This new material solution not only approaches the compressive strength of IM CFRPs but also provides more than 30% higher axial modulus.
Real-Time Delamination Monitoring in DCB Specimens Using MFC Sensors
Laminated composites when subjected to high-cycle fatigue loading, undergo delamination and the damage due to fatigue delamination can be detrimental to structural health. Hence, it is necessary to develop a way to detect the damage and then explore novel methods to repair it without need of mechanical fasteners. With this objective, double cantilever beam (DCB) specimens were fabricated, and macro fiber composite (MFC) elements were attached to the top and bottom surfaces. The MFC elements serve a dual purpose- First, they can be used as sensors to detect damage; secondly, they can be used to generate heat to actuate the self-healing process where damage is detected, as proven and presented in our previous studies. The main objective of this study is to detect the damage due to fatigue loading, i.e., crack size and location, with the help of MFCs so that the same network of MFCs can be used to heal the crack in situ. Tests were carried out on baseline DCB specimens with a pre-crack of 38.1 mm and specimens with crack growth in the interval of 2.5 mm beyond the pre-crack end. The DCB specimen with an array of 8 MFCs was used to perform damage detection initially with a single 5-cycle tone-burst actuation signal and then with the actuation signal as antisymmetric Lamb wave excitation. The signal difference coefficient (SDC) was used as a delamination detection metric and calculated for different actuator and sensor location combinations. The preliminary results of lamb wave actuation showed significant increase in SDC with the delamination crack growth for the selected actuator combination. The other objective of this study was to simulate the experimental results for the MFC actuator-sensor setup using the commercially available finite element (FE) analysis software ABAQUS, with fully dynamic simulation of Lamb wave propagation in the composite DCB specimens.
Evolution of Viscosity Upon Crosslinking in Epoxy Resin: An Atomistic Investigation
Adhesive materials such as epoxy resin (DGEBA/DETDA) are crucial in formation of any laminated and sandwich composites. Typically for these thermoset polymeric adhesives, crosslinking is an important step which eventually determines the thermomechanical response of the resultant composite. During this process of cross linking of epoxy resin, one observes changes in the viscosity of the resultant composite mixture of the resin and the hardener as well as change in temperature. This crosslinking of thermoset resins (DGEBA/DETDA at 2:1 ratio) is a complex chemical reaction process involving breaking of oxirane ring (C-O bond) in DGEBA, breaking of N-H bond in the amine (DETDA) and creation of N-C covalent bonds between the resin and the hardener. Apart from formation of new covalent bonds in the process, numerous non-covalent bonds such as hydrogen bonds and van der Waals interactions are also formed. This study is aimed at fundamental understanding of the correlation between viscosity changes in the composite upon crosslinking with the evolution of these non-covalent bonds. The study is primarily based upon molecular/atomistic investigations.
Extracting Damage Mode and Depth in Composite Panels Through Measured Wave Characteristics Using a Novel Mini-Impactor Excitation Source
Ultrasonic guided wave (UGW) is an established nondestructive evaluation method capable of assessing a wide area of the structure. A novel composite mini-impactor was used as a broadband excitation source for the UGW damage characterization of composite plates. Unlike the traditional impact hammers for composite structures which have an excitation frequency below 30 kHz, the unidirectional carbon/epoxy mini-impactor can excite between a range of 30-500 kHz. The excitation source was utilized to conduct basic studies on the effect of single-mode damage states such as: delamination, matrix crack, and fiber breakage. The single-mode damage states in AS4/977-3 prepreg composite plates are manufactured during layup by incorporating release film strips for delamination, and perpendicular cuts to create matrix or fiber breaks. Broadband air-coupled transducers (BATS) were used to measure the UGW structural response to the mini-impactor excitation through a pitch-catch setup. Two reception transducers are placed before and after the damage on the wave propagation path to assess the true structural transfer function (STF) through deconvolution between the signal output of both receivers. Comparisons of measured wave characteristics between pristine and damage types are conducted using extraction of damage-indicative signal features and by calculating Difference Signals. Additionally, double-sided UGW interrogations were conducted on the composite plates having non-centered flaws to determine different damage depths. Damage type and depth were distinguished based on STF statistical features and Difference Signals. STF of Damaged Signals farther from the surface of excitation were not indicative of damage but were identifiable through Difference Signals. Signals indicating fiber breakage produce a strong reduction in amplitude when breakage is closer to the surface of excitation.
Integrated Optimization Framework for Composite Manufacturing: Minimizing Spring-In Effects and Improving Cure Cycles
This study presents a structured methodology for the optimization of composite manufacturing processes, focusing specifically on autoclave techniques to mitigate issues such as the spring-in effect. The initial phase employs Sequential Quadratic Programming (SQP) in a weighted-sum approach to optimize the cure cycle, using Radford's equation for spring-in angle estimation and a multi-physics, multi-scale MATLAB model to investigate the cure and temperature-dependent laminate response. This phase underscores the efficacy of the selected optimization algorithm, demonstrating a significant reduction in spring-in while ensuring a high degree-of-cure. Subsequently, the study incorporates an integrated Finite Element Analysis (FEA) optimization framework linking ABAQUS and MATLAB. This framework utilizes the Non-dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization with an integrated composite manufacturing processing model. This second phase illustrates the framework's robust capabilities in composite cure cycle optimization, providing a well-distributed set of optimal solutions in an efficient timeframe. The study highlights the potential of the approaches and frameworks investigated to improve the efficiency, performance, and quality of composite parts.
Mapping Process Model Results to Fracture Model Initial Conditions for Adhesive Bonding
A systematic approach is proposed for mapping adhesive bonding process outcomes to initial conditions for progressive damage analysis (PDA). Herein, two mapping procedures are developed: 1) direct mapping for residual stresses, strains, and deformations obtained from a process model; and 2) functional mapping for quantities such as bondline thickness, degree of cure, and porosity that are assumed to have a functional relationship with fracture toughness but are not discretely modeled in the PDA. The spatial distribution of functionally mapped quantities may be determined by process modeling or inspection. The functional maps between the quantity of interest and fracture toughness may be obtained from independent lower-scale numerical simulations or empirical test campaigns. The proposed mapping procedure links the adhesive bonding process to the structural performance. Therefore, by accounting for the effects of bondline nonuniformities in structural analysis, analytical predictive accuracy can be improved, and off-nominal conditions can be evaluated. The mapping procedures are demonstrated and verified with example problems.
Silicon Oxycarbide Nanocomposite Laminates Reinforced with Carbon Nanotubes of High Degree of Alignment and Ultrahigh Packing Density
With properties including high stiffness, high strength, low density, and high aspect ratio, carbon nanotubes (CNTs) are ideal reinforcements for ceramic matrix composites (CMCs) for enhanced strength and toughness. However, prior studies on CNT- reinforced CMCs generally showed limited mechanical and multifunctional property enhancements due to damage, random orientation, low volume fraction, and agglomeration of the introduced CNTs. In this study, we developed a bulk nanocomposite laminating process for ceramic matrix composites (BNL4CMC) to overcome such limitations and to enable the fabrication of ceramic nanocomposite laminates reinforced with highly aligned, uniformly distributed CNTs of ultrahigh packing densities (>40 vol%). Instead of direct mixing, the polymer precursors for the ceramic can be infused into horizontally aligned CNT (HA-CNT) arrays followed by curing and pyrolysis to convert the polymer matrix to ceramic while preserving the CNTs’ high degree of alignment and packing density. Silicon oxycarbide (SiOC), which possesses high modulus, high hardness, creep resistance, and good thermal/chemical stability, is selected as the matrix for this study. Using the BNL4CM approach, we successfully fabricated 4-ply HA-CNT/SiOC laminates with ultrahigh CNT packing density (> 40 vol%), uniform distribution, and nanofiber alignment. Microstructure and morphology characterizations including X-ray micro-computed tomography (X-ray μCT) and scanning electron microscopy (SEM) are used to study the evolution of HA- CNT/SiOC laminates’ microstructure during the fabrication process. Nano-indentation was performed to obtain the elastic modulus and hardness of the fabricated HA- CNT/SiOC laminates. The process-structure-property relation obtained will inform the design and manufacturing of other HA-CNT reinforced ceramic systems for enhanced mechanical and multifunctional properties.
Optimization of Variable Thickness and Stiffness Composite Plate Buckling Load Using FEM andSemi-Analytical Method
In this study we report results on the manufacturing and response of cylindrical sandwich panels subjected to axial compressive loads. The structural panels were manufactured using Out-of-Autoclave (OOA) carbon fiber composite face sheets and aluminum hex core, using Automated Fiber Placement (AFP) manufacturing. Two types of panels were manufactured: pristine panels with straight fiber paths, and steered fiber panels, to examine the influence of fiber steering, gaps and overlaps on the compressive buckling response. Panel testing used specially designed fixtures, and digital image correlation (DIC) for diagnostics along with point wise out of plane displacement measurements using a laser scanning system. Test results indicated that sandwich panels failed due to skin compressive failure leading to disbonding, rather than global panel buckling. Steered panels showed marginal decrease in strength.
Quantification of Low Velocity Impact (LVI) Delamination from Ultrasound (UT) Inspection Data and Machine Learning
In this paper we demonstrate the use of machine learning for segmentation of raw ultrasound scan of impacted composite panels. The methodology implemented describes the use of data augmentation, where sparse real data is augmented with synthetic data, to enable use of convolutional neural network for machine learning. Initial results indicate that the approach is able to segment the delamination patter with good accuracy.
Modified Mode I Cohesive Traction-Separation Law for Z-Pinned Composite
In this study a detailed numerical analysis is conducted to determine the traction-separation curve for z-pin under mode-I loading state. A single z-pin is modeled and studied with pre-stress and friction and cohesive interface modeled, to determine the traction-separation curves in mode-I. The results show that a traditional bi-linear or tri-linear traction separation curve is insufficient to capture the bending of z-pin and consequent frictional dissipation due to z-pin. Based on this a new approach to parameterize traction-separation is proposed.
Investigation of Bending After Impact Failure Behavior in Foam-Core Hybrid Sandwich Composites at Extreme Low Temperature
In this study, we investigate the behaviour of foam-core sandwich composites, specifically with regards to bending after impact (BAI), in the presence of carbon fiber reinforced polymer (CFRP) and/or glass fiber reinforced polymer (GFRP) facesheets. To accomplish this, we utilize an Instron 5582 universal testing machine to conduct 3- point bend test on specimens that have previously undergone impact testing. The 3-point bend tests are conducted at both room temperature (23°C) and low temperature (-70°C) to evaluate the effect of low temperature (LT) on the BAI behaviour of the composite materials. Moreover, we explore the effect of different stacking sequence and layup configuration of GFRP and CFRP layers on sandwich composites under flexural loading. We analyse the force-displacement curves and compare peak stress values to gain insight into the influence of the CFRP and GFRP hybrid facesheets. Results suggest that altering the arrangement of CFRP and GFRP layers has a significant impact on the flexural strength of the hybrid composite. At LT, the specimens experience more flexural damage due to increase in brittleness. However, the peak stress at LT increases due to the increase in the compressive strength of the CFRP layers. Specimens featuring a GFRP layer on the outside (referred to as ‘glass first’ specimens) and specimens with alternating CFRP/GFRP layers, with CFRP positioned on the outermost layers (referred to as ‘CGCG’), when impacted at 15J, experience core shear and core debonding at LT flexural test. Overall, GC is found to be the optimal configuration. This configuration provides excellent strength from the inner CFRP layer and while the outer GFRP layer offers damage resistance during impact test.
Graphite Enhanced GNP/PVA Composite Piezoresistor with a Stable Loading Response
This study introduced graphite particle enhanced graphene nanoplatelet (GNP)/Polyvinyl alcohol (PVA) nanocomposite piezoresistor. The intention was to explore and use the synergy between graphite particles (GPs) and GNPs. The role of the GPs would be to create the backbone for conduction paths. Hence, they can reduce the variations in the conductive path formation as the number of cycles increases. The GNPs’ on the other hand, is to enhance the piezoresistive effect of the nanocomposite piezoresistor. Different filler ratios of the GPs and associated synergy with the GNPs were examined. As the GPs constituted the backbone for conduction, they decreased the sensitivity loss under cycling loading. The synergy assured repeatable and consistent Gauge factor over the cycles and a linear response to the applied strain. The piezoresistor was produced in ink that allows the application with a spatula or a brush on a substrate. This application method provides structural health monitoring of the materials with an easy application. In our study, plexiglass was selected as the substrate. Their response under cycling loading was examined as a function of resistance change of composite piezoresistor. The data was collected via a multimeter.
Origin and Significance of Non-Uniform Morphology in AFP Composites
Employing automated fiber placement provides a high level of control over intricate layup designs, but it introduces irregular morphology due to fiber tow deposition effects, such as tow gaps and overlaps. A confluence of elements like squeeze flow, resin bleed-out, and non-linear deformation results in morphological variation on micro and macro levels. To delve into these complex, interrelated phenomena, we developed a multiphysics finite element framework designed to simulate compaction behavior specifically around areas with fiber tow gaps. This structure integrates chemo-rheological and flow-compaction analyses. Within the compaction analysis, we incorporated a visco-hyperelastic constitutive model. This model is characterized by anisotropic tensorial prepreg viscosity, a feature that is dependent on the resin cure degree and local fiber orientation and volume fraction. Our approach considers the impact of resin bleed-out into the gap region, which results in the formation of a complex, non-uniform resin-rich pocket. The predicted morphology from the proposed finite element simulation agreed with the observed morphology in cured sample with staggered fiber tow gaps.
Comparing Characterization Methods for Investigating High-Temperature Bending Behavior of Melted Thermoplastic Prepreg Using DMA and Rheometer
With the growing popularity of thermoplastic composites, controlling and optimizing processing methods, such as in-situ Automated Fiber Placement (AFP) consolidation or continuous compression molding (CCM), has become increasingly important. These methods involve melting and deforming materials at extreme conditions, followed by consolidation and autohesion. To control these processes, the thermo-mechanical behavior of viscoplastic materials at high temperatures, such as bending response, must be well understood. This understanding enables the use of process simulation to explore optimization of processing parameters. In this work, a new characterization technique for examining the bending behavior of thin-ply thermoplastic prepreg using Dynamic Mechanical Analysis (DMA) is developed and compared with a test method that uses a rheometer and was previously developed by Convergent. Toray TC1225 LM PAEK thermoplastic prepreg was used in both methods to study the bending-relaxation behavior of the material at different temperatures and loading rates. A standard 3-point bend fixture and a custom-built 4-point bend fixture were used for DMA testing, while a custom-built pure bending fixture was used for rheometer testing. Although the initial testing with the 3-point bend fixture was promising, limitations were found due to the variable bending moment across the beam and highest bending under the loading contact point, leading to micro-buckling and formation of plastic hinges in early deformations. This was mitigated by employing a custom-built 4-point bending fixture, which enabled pure bending in a larger section of the beam. For data reduction and analysis of viscoplastic moment-curvature of the prepreg, a combination of pseudo-viscoelastic constitutive analysis and/or additional deformation measurement using a laser profiler were used. In comparison, the custom-built pure bending fixture in the rheometer was capable of directly measuring the moment-curvature at high temperatures for larger specimens to higher levels of curvature. It was shown that the 4-point bending method is an approximation as the new fixture cannot apply pure beam bending. Nevertheless, the results were found to be reliable and repeatable. Given the availability of DMA or rheometer, and the limitations of different test methods, the results of this study can be used as a guideline to characterize the bending behavior of thermoplastic composites.
Micro-Mechanical Investigation of Process-Induced Fiber Waviness in Thermoplastic Composites
Thermoplastic carbon fiber reinforced polymer (CFRPs) composite materials are attractive for their higher throughput, chemical resistance, and higher toughness compared to their thermoset counterparts. One challenge of processing these materials is controlling the process induced wrinkle/waviness formation arising from the high temperature change from process to room temperature. The process induced waviness is a significant microstructural defect that negatively affects the static and fatigue properties of the CFRP. This study offers a micromechanical approach to isolate, visualize, and monitor the development of fiber waviness as a function of process temperature, temperature dependent viscosity, and polymer crystallization. The approach utilizes a single AS4 carbon fibers (7 μm nominal diameter) in a thin film. Three different matrix polymers are studied: amorphous polyetherimide (PEI) and semi- crystalline low-melt poly-aryl-ether-ketone (LM-PAEK) and polypropylene (PP). A key observation is that fiber waviness initiates during cooling from the melt processing temperature (where all polymers are amorphous) and ceases at a temperature associated with a critical viscosity level (40,000 P) for all three matrix resins (PEI, PP, LM-PAEK) having very different ranges of temperature dependent viscosity. The magnitude of the fiber waviness was measured in a hot-stage microscope by observing fiber waviness upon cooling the micro-composites from various starting temperatures. In the case of LM-PAEK and PP, the critical viscosity (40,000 P) occurs during the onset of crystallization (cooling rate dependent). The amplitude of the fiber waviness does not increase further due to crystallization shrinkage. Amorphous PEI polymer at the recommended process temperature of 335 °C exhibits a viscosity approximately equal to the critical value of 40,000 P and the fiber remains straight through the entire cooling process to room temperature confirming the important role of viscosity on waviness The results indicate that one route to reduce fiber waviness is to reduce the melt processing temperature to achieve the critical viscosity level that stabilizes the fiber.
Effect of Fiber Reinforcement on the Process Parameters of Injection Molding Manufacturing Process
Notice: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
Modeling the In-Plane Compression Response of As-Manufactured Steered Fiber Laminated Plates
Robotic Automated Fiber Placement (RAFP) is a novel additive manufacturing modality for the production of laminated fiber reinforced composites. In addition to faster and precise manufacturing of composite structures, RAFP enables the designer to now use optimal steered fiber directions to maximize structural performance indices. The optimal solutions depend on loading and boundary conditions and are called “Variable Stiffness” (VS) laminates. Several studies have established that VS designs show significant benefits when compared to traditional laminates. A novel algorithm to derive optimal fiber paths to maximize uniaxial and biaxial buckling loads of 20 in ×20 in square VS laminates was introduced by the authors. The study utilized Bezier splines to represent the course center-lines, along with a “global manufacturing mesh” that would reduce the number of optimization variables. A surrogate model in conjunction with a multi-objective Genetic Algorithm (GA) was used to obtain a “Pareto front” of feasible solutions from which three feasible solutions were identified based on the criteria that the total gain in mass be less than 10%, the decrease in global stiffness capped at 10% and more than 25% increase in buckling load compared to a unidirectional laminate. These chosen designs were then manufactured and tested for uniaxial in-plane compression response. The proposed study presents the development of a numerical model using a pixelated FE mesh that captures manufacturing signatures like gaps and overlaps as well as the measured initial curvatures of the panels as manufactured. The load v/s load point displacement response of seven of the nine panels are well captured using the numerical model, with less than 5% error in initial stiffness and transition loads. A model with relaxed boundary conditions is used to correct for the deviation in the response curves for the rest two panels. Further, an optimization problem is introduced to examine the optimal straight fiber paths that maximizes the transition loads of the slightly curved panels and comparisons are drawn to establish that the steered fiber panels perform better than the straight fiber paths by up to 25% in terms of transition loads.
Improving Joint Strength Prediction by Accounting for Defects in Tensile Testing Specimens
Adhesively bonded joints are widely used in various industries, highlighting the importance of understanding their behavior. While fracture toughness tests provide valuable insights, they are complex and time-consuming. As a result, engineers often rely on tensile test data alone, considering its simplicity and practicality. However, the prevalence of defects in tensile specimens can lead to an underestimation of adhesive elongation at break. Tensile specimens distribute loads over a larger area, making them more susceptible to premature failure caused by localized flaws compared to bond line loads. To address this limitation and improve accuracy, this study proposes a novel approach. Tensile tests are conducted to determine the distribution of elongation at break, and inverse modeling using User Material (UMAT) in ABAQUS is employed to acquire the defect distribution in the specimens for different mesh sizes. Single Lap Joint (SLJ) tension tests are performed to compare force-displacement results from experimental data with simulation. The results highlight the significance of considering proper flaw distribution in the adhesive layer. By incorporating the defect distribution obtained from inverse modeling, the prediction of failure displacement can be enhanced compared to using adhesive with uniform properties based solely on average tensile data.
An Experimentally Validated Hyper-Viscoelastic Model for the Bending Responses of Pre-Impregnated Tapes Under Processing Conditions
Compaction of pre-impregnated fiber sheets (prepregs) is crucial to the formation of defects such as wrinkles and void. This study presents an anisotropic hyper-viscoelastic constitutive model to predict the compaction deformation and force of prepregs considering the influence of temperature on resin behaviors. The entire stack of individual prepregs is homogenized as an anisotropic continuous material whose strain energy density function is developed considering normal, shear, and coupling between normal behaviors. The proposed constitutive model integrates prepreg relaxation responses through generalized Maxwell models. The proposed novel constitutive model was implemented in the commercial Finite Element Analysis (FEA) software Abaqus as a user-defined material subroutine, UMAT. The modeling parameters were characterized by a discrete micromechanics model. The modeling approach was further applied to simulate a stepwise compaction process of carbon fiber/polyamide 6 prepregs to demonstrate the predictive capability.
Prediction of Effective Elastic Properties of Carbon/UHMWPE Nanocomposites by Combination of Numerical and Analytical Modeling
In this paper, we investigate ultra-high-molecular-weight-polyethylene (UHMWPE) doped with conductive carbon black (CCB) nanoparticles. This nanocomposite is considered a candidate for biomedical applications such as orthopedics. Micro-computed tomography (μCT) and scanning electron microscopy studies show that the composite has a complex microstructure consisting of larger particles of UHMWPE surrounded by a thin layer containing a high concentration of CCB nano inclusions. The overall mechanical properties of these composites depend on the volume fraction of CCB and the manufacturing procedures e.g., compression molding or equal channel angular extrusion. To predict the effective elastic properties of the CCB/UHMWPE nanocomposite, we propose a multiscale modeling framework based on a combined analytical-numerical approach. μCT images are processed to extract the size, shape, and orientation distributions of UHMWPE particles as well as the volume fractions and spatial distribution of CCB containing layer. These distributions are used to develop multiscale numerical models of the composite including finite element analysis of representative volume elements on the mesoscale, and micromechanical predictions of CCB containing layer on the microscale. The predictive ability of the models is confirmed by comparison with the experimental measurements obtained by dynamic mechanical analysis.
Using Machine Learning to Predict Mechanical Properties of Long Fiber Thermoplastics Based on Manufacturing Process Parameters
Long Fiber Thermoplastic Direct Extrusion Compression Molding (LFT-D) is an effective manufacturing process for semi-structural composite parts. LFT-D requires the user to know the influence each process parameter (e.g., temperature setpoints, rotational machinery speed, twin screw extruder configurations, matric flow rates, etc.) has on the resulting mechanical property of the manufactured part. This case study highlights the LFT-D manufacturing of carbon and glass fiber reinforced PA6 (CFRP, GFRP) at the Fraunhofer Innovation Platform (FIP) at the University of Western Ontario in London, Ontario, Canada. Data was collected for forty-six trials conducted over three years, varying fiber concentrations, fiber volume weights, screw configurations, temperatures, torques, forces, and pressures. The mechanical properties were measured and recorded in zero- and ninety-degree fiber directions. Machine Learning (ML) models like linear regression, random forest regression, ridge regressor, and lasso regressor were used to predict mechanical properties like Young's modulus and tensile strength of the part based on the process parameters as inputs. Data preprocessing and cleaning techniques were used to reduce the dimensionality of the dataset and to reduce the number of inputs to the model. These models were then evaluated using cross-validation to select the best model. Once the model was selected, the validation and testing datasets were used to determine the accuracy of the model. A sensitivity analysis was also conducted to determine how the variation in the output of each model can be attributed to the variation in input parameters. With this information, models can be further refined to obtain a more accurate prediction of the outputs and determine which inputs are essential when in the design phase of a product. The application of machine learning in the manufacturing process will ultimately accelerate composite product development and reduce the costly and iterative manufacturing process.
Fabrication and Characterization of Carbon Nanotube/Poly(Methyl Methacrylate) Nanocomposite Laminates
Aligned carbon nanotubes (A-CNTs) are advantageous reinforcements for polymer nanocomposites (PNCs) due to their high mass-specific physical properties, including strength, elastic modulus, thermal conductivity, and electrical conductivity, which create potential applications in both structural reinforcement and multifunctionality. To utilize these properties, the CNTs should be aligned and densely packed within the polymer matrix, similar to existing carbon microfiber composites. However, past methods to fabricate CNT-reinforced PNCs have focused on random dispersion of the nanofibers, resulting in uneven distribution and low packing density. As such, it has been difficult to fully realize the benefits of reinforcing PNCs with A-CNTs. In more recent work, the high volume fraction bulk nanocomposite laminating (BNL) process with A-CNTs has been demonstrated. PNC laminates containing uniform, aligned and highly-dense CNTs at unprecedented high volume fractions (> 50 vol%) using the aerospace-grade thermoset bismaleimide (BMI) polymer have been successfully manufactured. In this work, the BNL fabrication technique is applied to the manufacturing of the first high volume fraction aligned-CNT BNL with a thermoplastic matrix, namely poly(methyl methacrylate) (PMMA). Composites with thermoplastic matrices are used extensively in aerospace and civil structures due to their rapid processing, high ductility, improved recyclability and repairability. It is shown in this study that PMMA-matrix BNL with a high packing density and a void-free morphology have been successfully fabricated, based on assessment using micro-computed tomography (μCT). Crystallinity and glass transition temperature (Tg) are shown to be largely unaffected by the aligned CNTs using DSC. With the high specific strength, rapid manufacturing process, and multifunctionality of aligned CNTs, the thermoplastic PMMA BNL has the potential to replace conventional materials in additive manufacturing and electronic applications.
A Framework for Design Allowables Accounting for Paucity of Data and Errors in Complex Models
This work introduces a novel framework for the prediction of design allowables of composite laminates with reduced experimental cost. Building on high-fidelity simulations, polynomial chaos expansions (PCE) are first used to build probabilistic models for the material properties (input parameters). The coefficients of the models are themselves randomized by perturbing them with new stochastic degrees of freedom, thus accounting for uncertainty on the uncertainty and generating a family of distributions for these parameters. High-fidelity simulations are used to generate samples of the quantity of interest (QoI) which is then represented by a new PCE in terms of the previously described stochastic degrees of freedom. With this construction, the distribution of the QoI can be cheaply estimated and updated with experimental observations. The framework is applied to a hybrid carbon-glass fiber composite laminate under 3-point bending. We demonstrate how the updated distribution of the QoI can be used to predict the A-basis design allowable.
Analyzing the Progressive Damage of Composites Due to Manufacturing Induced Defects Through a Semi-Discrete Damage Model
During composite manufacturing processes, multiple steps are involved, each step introducing new physical and chemical processes. These processes alter the properties of the constituents (fiber and matrix), affecting the behavior of the composite materials. The changes in the properties of the fiber are not that significant. Whereas the mechanical and thermal properties of the matrix such as Young’s modulus, Poisson’s ratio, coefficient of thermal expansion etc. change significantly. Residual stresses are developed in the composite due to thermal expansion mismatch of the constituents and cure shrinkage of the resin. These resulting residual stresses have a considerable impact on the mechanical properties and performance of the composites. Also, cracks develop in the composite system during the manufacturing process which can affect the performance of the composite. When the composite system with residual stresses is mechanically loaded, the system exhibits a drop in the strength after a critical stress state is reached. To predict the critical stress at which the drop occurs we use the continuum damage method called the Smeared Crack Approach (SCA). Using SCA we can predict the stress-strain behavior of an RVE as the damage progresses. The critical stress value of the microscale RVE acts as the corresponding strength of the composite on a macro-scale level. To account for the variability in a composite system we randomly generate different RVEs. This is done by varying the number of fibers and the location of fibers using a statistic distribution for a fixed volume fraction. Then we conduct the simulations of manufacturing and progressive damage to identify the strength values of the RVEs. The strength values obtained are then used to assign to the different regions of a semi-discrete damage model of a composite laminate in macro-scale. The unique aligned meshing strategy of the model decomposes the bulk non-linearity and localization zones which provide a proper load transfer pathway. This random assignment of the strength values simulates the realistic behavior of a composite where each region has almost the same material properties but different strength values due to the uncertainties associated with the manufacturing processes.
Rapid Design and Analysis of Bonded Composite Joggle Lap Joints
Progressive failure analysis to determine the strength and damage tolerance of joggle lap joints containing pre-existing cracks was performed using the finite element method and virtual crack closure technique. Two adhesive, and four adherend, thicknesses were considered. Two pre-cracked configurations were considered that contained 0.25 in. long placed at the top adhesive/adherend interface or inside the laminate in the joggle region. The joints with the adhesive cracks exhibited stable crack growth followed by a transition into unstable crack growth. Meanwhile, the advancement of the interlaminar crack was entirely unstable. The line load strength of the joints displayed substantial sensitivity to changes in the thickness of the adherend. However, while the adhesive crack also was affected by changes in the thickness of the adhesive, the interlaminar crack was relatively insensitive to these changes.
Fatigue Performance of Highly Aligned Short Fiber IM7/LM-PAEK Thermoplastic Composites
(R=0.1, 3Hz). In comparison, this significant level of applied max strain (0.9 %) with no micro-cracking is ~50% higher than the initiation strain level for a typical carbon/epoxy having a much lower intralaminar fracture toughness (initiation strain is 0.6% and exhibits crack saturation (24 cracks/cm). The high degree of fatigue damage resistance observed for the 3mm IM7/LM-PAEK TuFF is attributed to the significant level of interface adhesion between the fiber and the resin (Interfacial Shear Strength of 120 MPa) and high matrix ductility (>40% strain to failure) and high intralaminar fracture toughness of the 90˚ layers.Tailorable universal Feedstock for Forming (TuFF) is a highly aligned short fiber composite material (fiber aspect ratio of 600) that can achieve a high fiber volume fraction (50-60%). Previous studies on unidirectional (UD) 3mm IM7/polyetherimide (PEI) have demonstrated quasi-static and tension-tension fatigue properties comparable to continuous fiber composites (57% fiber volume fraction). In this work, UD 3mm IM7/Low-Melt Polyaryletherketone (LM-PAEK) TuFF panels (Vf = 54%) were tested in the fiber direction using a tensile fatigue methodology to generate an S/N curve (R = 0.1, 3 Hz) with periodic checks for modulus loss over a minimum of 1 million cycles. The results indicate 3mm IM7/LM-PAEK is superior to other discontinuous fiber composites and equivalent to other continuous fiber composites in the literature. The comparison is based on the slope of normalized strength versus cycles on a semi-log plot with LM-PAEK exhibiting the lowest slope/strength reduction. No reduction in axial fiber tension modulus was measured. This study further looks at the tension-tension fatigue performance of [0/90/0] IM7/LM-PAEK TuFF cross-ply laminate with a thick ((240 gsm) 90˚ ply subjected to a maximum tensile strain of 0.9% (R = 0.1, 3 Hz). Typically, cross-ply composite layups exhibit transverse cracking in the transverse plies (90˚ layer) that extend across the entire thickness. Models and experimental studies show that the initiation and saturation of transverse cracking during static loading depend on several factors including mechanical loading, residual stress, and ply thickness. The effect of fatigue loading has been shown to reduce the initiation strain. In general, initiation strain for transverse cracks decreases with increases in residual stress and ply thickness (the typical range of initiation strain is 0.1 to 0.6% tensile strain). The key material property at the continuum length scale governing transverse cracking is the intralaminar fracture toughness of the 90˚ layers. In the present study, the thickest 90˚ layers (240 gsm) in the cross-ply 3mm IM7/LM-PAEK TuFF laminates exhibited no transverse micro-cracking up to ~1.5 M fatigue cycles with a 0.9% maximum strain
Interfacial Characterization of S2 Glass-Epoxy Resin Using Single Fiber Pullout Tests at Varying Temperature and Moisture Level
Due to their high specific strength, stiffness, and energy-absorbing properties, glass fiber epoxy composites are commonly used in automotive, aerospace, and other consumer applications. The Army uses these composites in ground vehicles for various structures, and they are often subjected to a wide range of environmental conditions, with varying temperature and moisture conditions. They may also be subjected to high strain rate loading. While the influence of environmental conditions on the properties of the reinforcing fibers is minimal, a fundamental understanding of its effect on the resin and interfacial adhesion is critical in evaluating the behavior of these composites. This research focuses on characterizing the effect of temperature and moisture on the interfacial bonding between S2 glass fibers (with 463 sizing) and epoxy resin using single fiber pullout testing. Epoxy resin SC-15, commonly used in these applications, is tested at room temperature, -55ºC and 76ºC. The range is chosen based on the operating temperature defined by MIL 810 standards. The embedded length is comparable for all tests, of the order of 55-60 μm. The embedded length and average diameter are measured using a scanning electron microscope image of the failed specimen to calculate the apparent IFSS. The IFSS shows a strong correlation with temperature; an increase in IFSS at -55ºC and a decrease at 76ºC. An 89% increase was measured at -55ºC and a 45% decrease at 76ºC when compared to room temperature tests. The IFSS measured is dependent on various factors such as the surface roughness of the fiber, chemical bonds between the resin and the fiber (sizing), and the residual compression forces that induce friction within debond regions due to the difference in CTE (coefficient of thermal expansion) between the fiber and the resin. Due to competing mechanisms of resin failure or interfacial failure, in some cases, a residue of the resin on the fiber may be present. A discussion of these mechanisms and a comparison with the resin properties at different temperatures is discussed.
Supercritical Fluid Treatments of Flax Fibers for Improved Mechanical Properties
Global increases in CO2 levels and increasing concerns regarding the effects of climate change have encouraged the transportation sector to reduce the carbon footprint of its products. The automotive and aerospace sectors have focused on the replacement of monolithic materials with composites, which have the potential to reduce weight and optimize the properties of the materials they are replacing. Many structural composites contain fiberglass reinforcement, which has a high density and is energy intensive to produce. Natural fibers have been explored as a low density, renewable alternative, but high variability and low mechanical properties have historically prevented widespread use of natural fibers in structural composites. In prior work, flax fibers treated under a specific set of conditions in supercritical CO2 (scCO2) were shown to improve fiber tensile properties. In this work, the dynamic mechanical properties of the fibers treated in scCO2 were evaluated. Treatment resulted in an increase in storage modulus, loss modulus, and tan-delta, consistent with reductions in fiber porosity and increases in fiber density previously reported. Additional treatments of the fibers in supercritical nitrogen (scN2) and supercritical argon (scAr) were explored to understand how the fluid chemistry may affect fiber structure and fiber mechanical properties. Fibers treated in scAr exhibited similar crystallinity and mechanical properties to fibers treated in scCO2 under the same conditions. However, fibers treated in scN2 exhibited higher crystallinity than fibers treated in scCO2 and scAr, but no significant changes to mechanical performance. Overall, this work expands the understanding on how supercritical fluid treatments could be applied to natural fibers as a means of enhancing fiber mechanical performance for composite applications.
Methodology for Characterizing the Forming Limits of Highly Aligned Discontinuous Fiber Composite Laminates
Highly aligned discontinuous fiber (ADF) composite laminates have demonstrated potential to stretch form biaxially to complex geometry while retaining aerospace grade properties. This work utilizes Tailored Universal Feedstock for Forming (TuFF) [1], an ADF format that uses 3mm IM7 fibers and PEKK 7002 thermoplastic resin converted to unidirectional prepreg and multiaxial blanks. To lay the groundwork for the forming process-structure-property relations, a novel methodology is developed for defining the forming limits of an ADF composite lamina by constructing a forming limit diagram (FLD). The ADF-FLD defines the strain mode forming limits based on lamina fiber orientation and will be defined with respect to a broader set of failure criteria—which can be material uniformity, consolidation quality, or specific mechanical properties. To demonstrate the methodology, ADF TuFF blanks were stretch formed at various strain levels and strain modes (longitudinal and transverse plane strain). Surface strain on stretch formed samples was measured by photogrammetry. Preliminary failure criteria were established based on acceptable variability in strain measurements to reflect the uniformity of material deformation. This unique approach to defining forming limits will be used in studying material and process variables in forming ADF composites, as well as providing part geometry and forming process design requirements.
Microwave Heating of Functionalized Graphene-Nanoplatelet Polymer Composites: Experimental and Numerical Study
Compared with contemporary electrofusion techniques that use embedded wires for Joule heating, microwave heating may facilitate the joining of thermoplastic polymer components, promising shortened fusion periods, better heating uniformity, and reduced energy consumption. This study investigates the fabrication of multifunctional polylactide acid (PLA) composites with strong microwave absorption using functionalized graphene nanoplatelets (fGNP). Graphene nanoplatelets were treated with tannic acid to produce fGNP. The fGNP/PLA nanocomposites were fabricated using a two-step scalable manufacturing method, including solution blending and hot compression molding. The fGNP content of the composites ranged from 0 to 8% by weight. The samples were characterized for dielectric permittivity, heat capacity, and electrical and thermal conductivity. Thermal imaging was used to investigate the efficacy of microwave heating in fGNP/PLA nanocomposites as a function of microwave power and filler weight fractions. Experimental findings were contrasted with similar results for plain (non-functionalized) GNP in PLA. The produced nanocomposites were discovered to have strong microwave absorption characteristics and hence rapid heating, making this type of composite a prospective choice for gasket materials that faci
Design Optimization to Fabrication with HyperX Laminate Families for Traditional Quad 0/45/90 and Double-Double [±Φ/±Ψ] Layups
Traditional Quad and novel Double-Double laminate designs have been investigated using the HyperX design/optimization software for a panel with a large circular cutout. Parametric studies were performed based on varying the panel loading to compare the optimized masses of Quad and Double-Double designs for a uniform panel, a panel with a single buildup region around the cutout, and a fully optimized panel where the thickness and layup are varied throughout the panel. Finally, following the same optimization procedures in HyperX, a Quad demonstration test panel was designed and manufactured via hand layup and vacuum infusion.
3D Printable Flame Retardant Graphene-Polymer Nanocomposites
Polymer nanocomposites that can combine various properties, including flame retardant behavior, ElectroMagnetic Interference (EMI) shielding, as well as mechanical strength are highly desirable in the automotive and aerospace industries. Graphene is a low-dimensional material with unique properties that impart multifunctionality. In this work, we investigate the properties of graphene-reinforced high-density polyethylene produced via extrusion. We carry out complete analytical studies to investigate the physical and chemical properties of the nanocomposites. We then compare the mechanical and thermal properties of the graphene-reinforced nanocomposites to recent results from the literature, as well as benchmark values established by industry.
Experimental and Numerical Analysis of Welded Thermoplastic Joints
High-rate manufacturing technologies and processes are essential to meet the increasing global demand for lightweight, sustainable commercial aircraft. Thermoplastic materials play a key role in achieving this goal. Joining methods such as thermoplastic welding enable rapid part assembly and reduce the total weight of the structure due to minimal to no fasteners. As the aviation industry is exploring the potential to increasingly use welded thermoplastic structures, it is necessary to understand their structural performance under different loading conditions. Additionally, the industry’s need could also be addressed through well-established numerical modeling methodologies. Developing numerical methods validated with experimental data at the lower-mid building block level could help in predicting higher building block level experiments and eventually reduce the cost of the test matrix. In this research, welded thermoplastic joints are tested under single-lap shear loading conditions, and medium-fidelity modeling methodologies are developed to predict strength and weld failure mechanisms. These methods would eventually be used to validate welded thermoplastic structures under complex loading conditions at sub-component and component levels.
Characterization of Ply-Waviness Manufacturing Defect in Composite Aerospace Laminates by Ultrasonic Scattering Analysis
The use of composite materials in the aerospace industry has considerably increased in the last decades. Despite their superior mechanical performance and tailorable nature, they are hindered by their expensive manufacturing processes and complex damage evolution behavior during their lifetime. Among the manufacturing defects that particularly characterize automated methods and/or complex parts, ply waviness in Carbon Fiber Reinforced Polymer (CFRP) could lead to strength reduction and complex behavior, and needs further attention, both in its detection and understanding of damage evolution. Ultrasonic c-scanning techniques are well suited for composite inspection: they are currently used in the aerospace industry for non-destructive evaluation of newly manufactured parts, in- service inspections and maintenance, and can be tuned to detect ply waviness. In this work, CFRP laminate beams specimens with induced out-of-plane ply waviness have been inspected in a water submerged C-scan system, using ultrasonic pulse-echo technique. Data were collected for different specimen parameters and system settings, including ply waviness severity, ultrasonic transducer frequency, and C-scan resolution. A customized code was then developed to process, visualize, and analyze the waveforms collected from the tests. Front-wall, back-wall, and internal wave- packets were identified using estimated calculations of the wave velocity in composite laminates. Then, different waveform features such as time-of-flight and amplitude were extracted to visualize and analyze the ply waviness and its characteristics. It was found that internal and back-wall wave packets experienced a decrease in amplitude over the ply waviness region of the specimen. Furthermore, regions to the left and right of the ply waviness experienced noticeable differences in time-of-flight and amplitude for various wave packets. Additional features and signal processing techniques are employed to consistently characterize ply waviness defects and study their evolution under fatigue and other loads by means of ultrasonic scattering analysis.
A Coupled Experimental-Numerical Method Dedicated to the Dynamic Characterization of Composite Braids Under Drop Weight Conditions
Bird strike simulation is crucial for designing aircraft blades, but characterizing materials at high strain rates presents challenges. This study presents a Dynamic Tensile Test Device (DTTD) for characterizing composite materials usually used in blades industry. The DTTD, integrated with a drop weight tower, converts kinetic energy into tensile loading, allowing material characterization of any material. In this article, experimental results for aramid/epoxy 2D braids at different angles were obtained and load curves were analyzed. However, the effort is produced by an impact, which generates a shock wave that must pass through the system, resulting in several vibrations that makes the primary results difficult to exploit. To overcome this, a finite element (FE) model of the drop tower system was created for reverse engineering material characterization. This approach enables material characterization and strain rate analysis. Further investigations can explore additional braid angles and refine the modeling techniques.
Peridynamics for Microstructural Damage Modeling of 3D Carbon/Carbon (C/C) Composite Materials
This study presents a peridynamic model to investigate damage initiation in complex 3D C/C microstructures for optimal design and fabrication. The peridynamic theory unifies the mechanics of continuous and discontinuous media. It is a continuum approach without spatial derivatives, thus without mathematical singularities. It restores nonlocal interactions and introduces an internal length parameter (horizon of a point) which links different length scales. Because of these features, it enables autonomous multiple damage initiation sites and their complex interactions at unspecified locations along unguided paths. The numerical results concern damage initiation and growth in a complex 3D C/C microstructure. A repeating representative volume element (RVE) composed of yarns and surrounding matrix is constructed according to the periodic architecture of the 3D woven C/C composites. The analysis is conducted through a mixed implicit-explicit algorithm with GPU parallel computing. The strength properties of the constituents are used to determine the critical stretch for damage initiation and growth in the microstructure. The isolated initial micro cracks start merging as the load increases. Subsequently, the crack front reaches to the surface of a nearby fiber. However, the micro-crack cannot pass through that fiber directly. Instead, it deflects along the fiber direction and starts climbing up around the fiber lateral surface.
Comparison of Micromechanics Theories for Modeling Discontinuous Long Fiber Reinforced Composites
Two micromechanics theories, the high fidelity generalized method of cells and Carrera Unified Formulation, are used to model a repeating unit cell of a discrete long fiber composite. The models are used to predict the effective properties of a single fiber with varying fiber-to-fiber end gap lengths, as well as the local stresses in the fiber and matrix. Both models produced similar results and demonstrated that they could capture the complex local load transfer due to the shear lag effect.
Forming Simulation of a HiPerDiF PLA/Carbon Fibre Tape with a Micromechanical Model
Aligned discontinuous fibre composites (ADFRCs) have been gathering attention with the growth in both quality and available quantity of materials from HiPerDiF (High Performance Discontinuous Fibre), AFFT (Aligned Formable Fibre Technology), and TuFF (Tailored universal Feedstock for Forming). In addition to their support of sustainable solutions for the composite industry by the potential to use both thermoplastic and vitrimeric matrices and reclaimed fibres, they offer promising advantages to the manufacturing of complex structures through superior formability. To maximise these advantages, it is crucial to understand the material behaviour and by simulating the forming of complex parts it will be possible to decrease manufacturing costs and increase the quality of a product. In this study, the procedure for a forming simulation of ADFRCs is demonstrated with the help of a micromechanical model of poly (L-lactic acid) (PLA)/carbon fibre tape.
Stiffness and Fatigue Life Estimator for Polymer Composite Laminates Using Machine Learning
Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, Python-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been established. Results show that both neural net type algorithms can provide an excellent estimate of initial laminate stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminates (PMCs). RNNs are better able to capture the shape of the fatigue curve of a laminate. The resulting tool and GUI can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. Further, the associated surrogate models can also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make micromechanics-based multiscale analyses a viable industrial tool for large scale structural problems.
Cure Shrinkage Characterization of a Thermosetting Resin with Three-Dimensional Digital Image Correlation (3D-DIC)
This work presents the application of three-dimensional digital image correlation (3D-DIC) to capture pre- and post-gelation volumetric chemical shrinkage of EPON 862 thermosetting resin paired with hardener triethylenetetramine (TETA) and cured at room temperature. The manufacturer-recommended 100:14 resin-hardener mixing ratio is used for DIC experimentation. A stress-free boundary condition is employed with a thin Teflon sheet placed between the resin mixture and the specimen container. For the first time, a spray-painted speckle pattern is applied directly to the resin to record full-field strain measurements during curing. This speckle pattern is employed immediately after the resin mixture is poured on the Teflon-covered specimen container for the pre-gelation case, and after gelation has been visibly observed for the post-gelation case. Strain capture with 3D-DIC is initiated directly after speckle pattern application with stereo-images captured every 30 seconds for one hour and then every 60 seconds for two hours. Differential scanning calorimetry (DSC) is used to determine resin cure kinetics to correlate chemical shrinkage with degree of cure. The presented technique provides an innovative methodology to characterize the chemical shrinkage of thermosets during curing.
Design of Broadband Radar Absorbing Corrugated Hybrid Core SandwichNickel-Coated Glass/PEEKThermoplastic Composites
This study aims to design and manufacture a low-density hybrid corrugated core sandwich structure, employing a nickel-coated glass fiber (NCF)/polyether ether ketone (PEEK) thermoplastic matrix, which demonstrates exceptional radar absorption performance and lightning resistance within the C~Ku (4-18 GHz) band. To modify the electromagnetic (EM) characteristics of glass fibers (GF), a nickel electroless plating technique was employed to plate the surface of the GF with nickel. The complex permittivity (ε = ε' - jε'') of the GF/PEEK and NCF/PEEK composites was measured using a free space measurement (FSM) technique within the C~X-band (5.8-12.4 GHz) to assess their EM properties. The measurement results revealed that at 10 GHz, the ε of GF/PEEK was 4.69 - j0.079, whereas the ε of NCF/PEEK increased to 18.50 - j15.32, indicating improved dielectric properties. To design a broadband radar absorbing structure (RAS) with exceptional microwave absorption performance, the optimal shape of the corrugated core was determined through the utilization of CST Microwave Studio. The designed RAS demonstrated absorption performance exceeding 90% within the C~Ku band (4-18 GHz). Additionally, to improve the lightning protection effectiveness in RAS designs, a polyimide (PI) film coated with patterned silver paste was applied to the facesheet of corrugated core sandwich panel. Through lightning experiments, it was observed that the lightning protection effect was enhanced in the presence of the dedicated lightning strike protection film. The outcomes of this study indicate that the developed corrugated core sandwich structure for RAS holds potential for applications in stealth technology.
Utilizing Tailored Fiber Placement Methodology to Enhance Fracture Toughness of Wavy Composite Laminates
Polymer matrix composites can be used to design various aircraft components because of their strength-to-weight advantages and durability. However, the material must satisfy the necessary design allowable when implemented into a structural application. Tailor Fiber Placements is a process in which dry carbon fibers can be stitched into any fabric, impregnated with resin, and molded to any geometrical component. In our study, in-plane waviness was introduced to the material to enhance the fracture toughness of the laminated composite—a sinusoidal function defined by four different types of waviness. The overall objective is to develop a fracture tolerant material creating a tortuous path for damage to propagate, which could enhance impact resistance, susceptibility to extreme environments, and dissipative energy mechanisms.
AI-Assisted Statistical Analysis of Fragmentation Response of Heterogeneous Layered Media
The fracture response of materials is highly dependent on their microstructural details, especially for fragmentation problems. The fragmentation response of a ring expanding with constant radial velocity is often analyzed using the method of characteristics. While most studies assume homogeneous material properties, we treat fracture strength as a random field to elucidate the interaction of key characters of the random field, correlation length and point-wise variation, with loading rate and other fracture and elastic parameters. The output parameters include dynamic strength and macroscopic energy dissipation capacity of the material. Due to the high dimensionality of the input random fields and other types of input data, e.g., loading rate, training machine learning models for predicting output parameters is challenging. For this purpose, we consider a few neural network architectures and feature extraction techniques to predict the response accurately with only a handful of influential input parameters.
Additive Manufacturing of Frontally- Polymerizable Continuous Carbon Fiber Tow-Based Composites
Additive manufacturing (AM) of high-performance thermoset polymer-matrix composites has important applications in many fields, including the aerospace, energy and automotive industries. Current AM methods for thermoset composite often require a thermal post-cure or result in lower mechanical properties compared to conventional composite manufacturing techniques. Frontal polymerization (FP) presents an alternative curing strategy that utilizes a self-sustaining exothermic reaction that propagates through a monomer as a front to convert it to a hardened thermoset polymer. In this work, we develop an extrusion-based AM process to deposit dicyclopentadiene (DCPD)-impregnated carbon fiber tows which undergo FP. The tow is deposited on a thermally conductive, heated bed to supply the thermal energy required to initiate FP. We investigate the effect of bed temperature on the front speed, front temperature, and degree of cure of the printed composite tows. A finite-element model based on a homogenized thermo-chemical formulation is developed to capture the deposition of the tow on the substrate, the heat transfer in the tow, the cure kinetics of the matrix material, and the impact of key process parameters, including the fiber volume fraction, bed temperature and deposition speed. This numerical model is then used to predict the front properties and maximum degree of cure, and is compared to experimental results.
Relaxation Behaviors of Adhesive Bonded Carbon Fiber Reinforced Composites Using Dielectric Relaxation Spectroscopy and Thermally Stimulated Depolarization Current
Improving the reliability and durability of adhesive bonds is one of the biggest challenges in critical composite structures in industries such as Aviation, Automotive, Marine, and so on. Characterizing the interfacial region of the adhesive and composite adherends can yield vital information in this regard. Dielectric Relaxation Spectroscopy (DRS) is a technique used to investigate relaxation behaviors in terms of dielectric constant and loss tangent as a function of frequency. The material's response to polarization mechanisms at different frequencies can be captured by conducting Broadband Dielectric Spectroscopy (BbDS). Among these polarization mechanisms, interfacial polarization is most relevant to adhesively bonded joints. Thermally Stimulated Depolarization Current (TSDC) is also an effective tool that provides information about interfacial polarization and polarization of polar groups in epoxy-based polymers. The relaxation behaviors of the specimen are described by the depolarization current that is emitted as the polarized dipoles are relaxed in relation to temperature. Adhesively bonded carbon fiber composite adherends with different surface properties were manufactured and studied using TSDC and DRS techniques. Different polarization current spectra were observed with bonded specimens of varying surface characteristics. The morphological changes made to the adhesive-adherend interfaces are found to be reflected in the relaxation times and corresponding frequencies at different temperatures. These two complementary techniques portray conclusive relaxation mechanisms triggered by the external electrical fields.
Experimental Investigation of Bubble Mobility in Porous Media During Resin Transfer Molding
Liquid Composite Molding (LCM) is a class of manufacturing processes such as Resin Transfer Molding (RTM) and Vacuum Assisted Resin Transfer Molding (VARTM) used to produce composite materials. One of the challenges in LCM is elimination of voids or air pockets in the final composite part which can compromise its structural integrity. One source of voids are the bubbles that are present within the resin as it enters the closed mold and are trapped as the resin cures. The first step to eliminate such voids is to understand their flow behavior in a resin that is injected into a fabric. We have carried out an experimental study to characterize the bubble movement through the pore network formed by the fabric weave architecture. The movement of bubbles within the resin is tracked using a camera within a transparent mold for three different fabric types. The bubble diameter and its velocity are measured as it goes through the fibrous media. By introducing dimensionless numbers that characterize bubble mobility (how fast the bubble moves compared to the resin velocity) as a function of dimensionless channel within the fabric weave (ratio of bubble diameter to the spacing of fiber tows) it is demonstrated that bubble mobility is much higher for tighter weaves and larger bubbles. This can help to optimize the LCM processes and minimize the voids by tunning the bubble mobility during the manufacturing process.
Study of Microstructural Variability of Fiber Reinforced Composites Using Multi-Scale Modeling and Machine Learning
This paper presents an overview of research conducted to track the variation in fiber reinforced composites at the microscale induced from manufacturing, and determine the effect composite properties. For this effort, the microscale was first quantified using statistical descriptors. These descriptors are needed in order to determine statistical equivalency of artificially generated microstructures. The artificially generated microstructures have been made using a combination of randomly distributed fibers and simulations. Numerical parameters of the simulation can be manipulated to produce different features found in common microstructures such as fiber clusters and matrix-rich regions. Finally, reduced order structural models were used to quantify the variation in the response due to variations at the microstructure. Meso-scale simulations utilize integration point variation in material properties to simulate the overall variation in the response. Machine learning can be used to replace models at the microscale level and capture variation without having to link multi-scale models.
Assessing Damage in Composites with Acousto-Ultrasonics and Machine Learning
This work presents an approach to assessing the severity of damage consisting of delamination emanating from transverse cracks using features of ultrasonic waves and machine learning tools. Matrix cracking and delamination are two commonly observed damage mechanisms in composite laminates. Assessing the severity of these damage modes during service is important for structural safety. Structural health monitoring (SHM) methods are commonly concerned with detecting the location and extent of damage but do not provide quantitative measures to evaluate the ability of structures for continued safe operation. Ultrasonic waves based SHM methods, known as acousto-ultrasonics (AU), have shown great potential for in-field material inspections due to their ease of execution with simple portable sensors and their sensitivity toward damage. The transmitted waves in AU interact with damage, producing complex displacement patterns that cause alterations in the signals at the receiving sensor. The current work aims to utilize the features of those received wave signals to establish correlative relationships between them and the severity of damage for complex damage cases observed in composite laminates. The features extracted from the wave signals may not always provide direct and unambiguous measures reflecting the damage state, making it difficult to assess damage with a single signal. However, the advances in machine learning and pattern recognition make it possible to optimize the feature selection process, eliminating the need to inspect individual signal features. In this work, data from the finite element simulations of various realizations of delamination emanating from transverse cracks are used in machine learning models. It is found that these models successfully identify the signal features that correlate with the damage for the random test cases used and thereby give an excellent prediction tool to assess the damage severity.
Autonomous Continuous Fiber Infill Generation for Composites 3D Printing
Additive Manufacturing (AM) techniques are advantageous in manufacturing polymeric composites over traditional procedures that require molding, mounting, etching, and post-cleaning. AM is conducive to material allocation reinforcing in critical regions or directions by increasing the fiber volume fraction or by the selective orientation of the fibers. However, state-of-the-art entails fiber orientations be specified manually during the slicing and infill planning steps without any awareness of the desired material properties. In this paper, we formulate and solve the continuous fiber infilling with additively manufactured parts as a fiber path planning problem with constraints on the desired minimum fiber-volume fraction and optimal fiber orientations. The autonomous path planner maximizes the fiber-volume fraction in areas requiring high stiffness while minimizing the continuous-carbon filament in the rest of the part. The fiber orientation is also optimized to maximize the use of continuous carbon filaments. The software tools for generating continuous carbon fiber infills packaged with commercial composite 3D printers cannot automatically satisfy machine-imposed constraints, and the user is often asked to provide the infill geometries manually. The algorithms presented in this paper consider the geometry, stiffness requirements, and printing device constraints while formulating the infill structure. The algorithm was implemented into an open-source parametric 3D modeler. The implementation imports the mesh file representing the solid geometry, cleans and repairs the mesh, calculates the space between faces, and slices the part. Before creating the infill path, the algorithm obtains the face and hole contours and establishes the continuous carbon infill regions. The continuous carbon fiber placement paths are then determined within the infill region to maximize the fiber volume fraction while satisfying the machine constraints. The paper describes solutions with continuous fiber infilling using several example part geometries.
Scalable High Tensile Modulus Composite Laminates Using Continuous Carbon Nanotube Yarns and Gamma Ray Treatment
Continuous carbon nanotube (CNT) yarns are used to fabricate scalable composite laminates with high strength and stiffness for scaled-up manufacturing and potential engineering applications. CNT yarns are shown with specific tensile strengths of 1.77 N/tex due to a high degree of nanotube alignment. These properties are transferred to scalable unidirectional CNT yarn reinforced composite laminates fabricated using filament winding and aerospace resin matrices. Gamma ray treatments of 200 kGy, 700 kGy, and 1200 kGy are used to further improve the mechanical and interface properties of the constituent CNT yarns. The optimal dose is 700 kGy, yielding a specific tensile strength of 1.89 GPa/(g cm-3) and specific modulus of 258 GPa/(g cm-3), which represents a 37% and 44% improvement over the properties of the control laminate. The specific modulus exceeds current state-of-the-art unidirectional carbon fiber composite laminates. The results demonstrate an effective approach transferring high-strength CNT yarns into composites that retain the tensile performance of CNT materials at the flight article scale.
Progressive Damage Analysis of Open Hole Compression Specimens Containing Complex 3D Textile Architectures Using Discrete Damage Modeling and Independent Mesh Method
Discrete Damage Modeling (DDM) and Independent Mesh Method (IMM) are applied to progressive damage analysis in angle-interlock woven 3D textile composites with open hole loaded in uniaxial compression. The predictions were made by considering, geometrically nonlinear formulation, thermal residual stresses and compression-shear interaction in the tows in the framework of LaRC04 failure criterion. The effects of each of these consideration as well as their combinations was evaluated and concluded that while each separately has only an incremental effect it is their combined effect that resulted in accurate prediction of the warp direction open hole compression strength in angle-interlock woven 3D textile.
Effect of Silica and Mixing Time on Microstructures of Porous Polymer Composite by Emulsion Templating
Porous polymer composite with tailored porosity is applied in the myriads of areas such as energy storage, oil/water absorption, bioengineering, and advanced areas of material science. The emulsion templating technology is one of the most popular methods for synthesizing porous polymer composite. It involves solidifying a two-phase mixture of porogen and polymer, then removing porogen to create pores within the continuous emulsion phase by polymerization or curing. The surfactant plays a pivotal role in accomplishing a stable emulsion, a key factor in designing the internal porous structure. This study highlights the effect of silica filler and mixing time on pore morphology, i.e., shape, size, and distribution. on polydimethylsiloxane (PDMS) porous structure utilizing the water-in-oil emulsion templating method. Span® 80 is used as a surfactant to reduce the surface tension between water, silica, and PDMS and simultaneously create a strong foaming effect. Different weight concentrations of silica (1-10 wt%) were chosen while keeping the internal phase, i.e., water (50 wt%) constant. The designed porous structures were further characterized through scanning electron microscopy (SEM). Porous composite specimens fabricated with higher silica content and mixing time consistently exhibit smaller pore sizes than specimens fabricated with lower mixing time and silica content. A breakthrough of pore morphology is seen at silica content higher than 5wt% at 1 min mixing, however, pore morphology drastically changes when mixing time increases from 1 min to 6 min. Variation of finer mixing time beyond 1 min shows stepwise changes in pore morphology from a large single-phase porous structure to a bi-modal porous structure which eventually become a smaller single-mode porous structure. Thus, the emulsion templating technique, in combination with different filler content and mixing time, will effectively aid in designing engineered porous polymer composite with varying stiffness and pore morphology.
Simulation of Dynamic Crushing Behavior of Simulated Carbon/Epoxy Stanchions Using MAT58 and MAT213 in LS-DYNA
Carbon fiber-reinforced polymer (CFRP) composites have shown promise as a material for structures designed to absorb energy in crush-style impact loading. However, simulating the behavior of CFRP structures in dynamic, crushing-style impact loading is challenging because of the many damage and failure modes that are essential to capture in the model. For the present investigation, CFRP stanchions were tested using a crash sled experimental test rig. The stanchions were designed by the Composite Materials Handbook-17 (CMH-17) Crashworthiness Working Group for the purpose of comparing experimental crash sled tests to corresponding simulations of the tests. The stanchions are C-channel shaped and represent a geometry common in the interior of aerospace vehicle structures. Explicit simulations in LS- DYNA were performed using a well-established composite material model (MAT58) and a next-generation material model (MAT213). Simulating the crushing of the stanchions occurred in two phases. First, the material models were calibrated using flat specimens that were manufactured with the same layup as the stanchions. While the original goal was calibration of material-related properties, mesh- dependent behavior was observed in simulations with both material models, and an unstructured mesh was therefore selected to remediate undesirable mesh-dependent failure modes. Additionally, for both the MAT58 and MAT213 models, it was found that either the crush force or the failure mode could be modeled accurately, but no set of parameters could be identified to optimize both results in the same model. Once satisfactory calibration was achieved, the same material parameters were applied to the stanchion crush simulations. The stanchion simulations showed that MAT213 more accurately predicted the experimentally determined crush force, and both material models predicted key aspects of the experimentally observed failure modes.
Exploring Underlying Correlations in Multi-Fidelity Finite Element Simulations of Open-Hole Tension Tests: A Comparative Study Using Machine Learning
Certification of composite aerostructures is typically achieved via analysis supported by testing, following the building block approach. Analysis of failure and crash at different scales, as well as design iterations and optimization, require fast and validated numerical models. Given the complexity and interactions of multi-failure mechanisms in composites, high-fidelity FE models are often needed to explicitly simulate the behavior of individual layers and their interlaminar interfaces, using a mix of continuum and discrete damage models. However, high-fidelity FE models require a considerable amount of time to set up, calibrate, and perform. On the other hand, low-fidelity modeling approaches, such as laminate-based smeared models, may provide reduced accuracy in some cases, while offering shorter simulation times and thereby lower computational costs. In this study, progressive failure of Open-Hole Tension (OHT) tests on HEXCEL IM-7/8552 quasi-isotropic laminates are investigated using both low- and high-fidelity FE models. A Machine Learning (ML) technique is then employed to perform a comparative study between the inputs and outputs of these models. The ultimate goal is to identify areas in the FE parameter space where the low-fidelity model can be used as a substitute for the high-fidelity model with reasonable accuracy and to discover the relationships among main parameters to reproduce high-fidelity results from the low-fidelity model in an accelerated manner. To generate the low-fidelity model, a laminate-based FE model was created in LS-DYNA, using a continuum elastoplastic damage-based material card, MAT081. The model parameters were varied randomly, and simulations were performed to generate a large database of low-fidelity FE results. Similarly, a ply-based FE model employing MAT261 for continuum intralaminar damage modeling combined with cohesive tiebreak contacts to capture discrete interlaminar delamination was created. This high-fidelity model was also used to generate another database of simulation results. Both databases were used to create a training set for an ML model, aiming to study the correlation between low- and high-fidelity inputs that result in similar failure responses. The results enable increasing use of low-fidelity FE models to generate data for the training of ML models.
Effect of Graphene Quantum Dots on the Mechanical Properties of Bisphenol F-Based Epoxy
Nanofillers have gained popularity in the composites industry to enhance the already desirable thermo-mechanical properties of the material. These fillers have been reported to generate poor bonding, agglomeration, void-formation, and similar nano-scale defects. Graphene Quantum dots (GQDs) are one of the smallest nanofiller with a diameter of ~1 nm that can mitigate the commonly seen defects in toughened composites. Molecular Dynamics (MD) is used to investigate the molecular mechanisms generated by embedding a single GQD in an epoxy matrix. Mechanical characterization of a single pristine GQD-epoxy system is reported in this study.
Quantitative Evaluation of Fiber Distribution in Discontinuous CFRP Using Dark-Field Images Derived by X-Ray Talbot-Lau Interferometer
This study proposes a new method which quantitatively evaluates distributions of carbon fiber content, mean fiber orientation, and variance of fiber orientation in CFRP. Dark-field images taken by Talbot-Lau interferometer are employed for the method. Talbot-Lau interferometer can measure X-ray scattering generated by carbon fibers in the optical path as a dark-field signal. Dark-field image visualizes the distribution of dark-field signal. The authors first describe a model that relates number of carbon fibers oriented in a certain orientation in CFRP and the dark-field signal. The model is then expanded so that it can calculate dark-field signal of CFRP laminates in which carbon fibers of different orientations are stacked in the thickness direction. Carbon fiber distribution, mean fiber orientation, and variance of fiber orientation in a given CFRP can be evaluated by using the model. The method is validated by comparing the results of the method to the results those are directly measured from the optical microscopic images. The authors believe that the proposed method has a potential to be a new nondestructive inspection method for CFRP.
Investigating Stiffness Property Matching and Homogenization of the Double-Double Family of Laminates
The investigation of stiffness property matching and homogenization of the Double-Double (DD) family of laminates is presented. DD laminates are a new layup design approach composed of repeated sub-laminates, comprising two sets of bi-angled plies, [±φ°, ±ψ°]r. The DD laminate approach simplifies the design of composite structures, reduces manufacturing complexity, and allows for rapid thickness tapering, presenting substantial prospects for reducing structural mass. An order-of-magnitude improvement in matching accuracy for both in-plane and bending stiffness properties was observed when extended DD sub-laminates, featuring additional 0°, 90° or ±φ° plies, were incorporated as options in the quad laminate matching process. Additionally, homogenization of laminates comprised of extended DD sub-laminates was examined, concluding that extended DD sub-laminates have no negative implications in terms of laminate homogenization if the correct sub-laminate permutation is selected.
Damage Initiation of Continuous Fiber Laminated Thermoplastic Composites
The use of advanced thermoplastic composites (TPC) for structural applications in the aerospace and automotive industries has grown increasingly popular due to their high performance, high manufactured part output, and sustainability. Advanced manufacturing processes of thermoplastic composites allow for the building of complex optimized structural geometries with both continuous and discontinuous fibers. With more complex parts and processes comes the need for established qualification methodologies. Characterization of damage evolution from different manufacturing processes needs to be further explored to better understand the behavior of TPC for aerospace environments. Investigation into the differences in the damage behavior of continuous and discontinuous laminated TPC in tension and compression is important for aerospace applications where impact and crush damage is likely. Experiments using continuous fiber laminated IM7/PEKK TPC, [±45]4s specimens loaded in tension and [90/0]3s specimens loaded in compression, are performed to obtain stress vs strain curves with Digital Image Correlation (DIC) and acoustic emission (AE) transducers to monitor damage initiation and evolution. Next, interrupted low-cycle mechanical tests are performed on [±45]4s laminates with optical microscopy in between cycles to support characterization and understanding of the relevant damage mechanisms needed for material models. The damage mechanisms in laminated composites are of interest to better understand the effects of different fiber architectures on the laminate scale behavior, which can be used to calibrate continuum damage mechanics models.
Rx-FEM Modeling of Fatigue Damage Growth in Composites with Local R-Ratio by Using Strength Tracking Method
A computationally efficient fatigue methodology is proposed that uses automatic cycle jump step selection algorithm within implicit framework to predict fatigue damage accumulation in laminated composites. Stress state scan within a specified load profile such as one or more cycles is performed to determine local stress ratio (R-ratio) in each integration point. S-N ply level-based strength criterion was applied for matrix Mesh Independent Crack (MIC) insertion in each ply as well as within respective Cohesive Zone Model (CZM) formulation at the damage initiation stage. Paris Law based propagation was utilized for MIC and delamination opening within CZM. The local R-ratio is implemented within CZM for initiation and propagation stages. In addition to the matrix failure modes fatigue degradation in the fiber direction under compression loading was implemented. The concept is based on shear strength degradation in the misalignment frame and LaRC failure criterion. Finite element simulations of [45/0/−45/90]3?? open hole laminate under tension-tension (T-T) and compression-compression (C-C) fatigue were performed. Fiber damage, delamination, and matrix cracks are seen to be the appropriate size and location compared with the experimental result.
Designing a Functionally Graded S-2 Glass/Epoxy Composites for Improved Energy Absorption
SC-15 epoxy while the low yield strength epoxy was a TGDDM based modified system with monoamine functionalized partially reacted structure (mPRS), synthesized by collaborators at Drexel University. Compared to the baseline VARTM panel made from plain weave S-2 glass fabric with a 463 sizing and SC-15 epoxy, the penetration resistance was improved by ~25% by using a low yield strength with a high interface strength combination of 8-harness satin with mPRS. The thin laminate samples (6 mm) showed a 14% improvement in V50 when normalized by areal weight compared to a plain weave/SC-15 baseline by using plain weave/TGDDM with 20%mPRS. These two systems were combined to make an FGM panel (1.8 cm thick, 1.2 cm DoP system on strike face and 0.6 cm thin laminate on the back surface) which allowed for a 18% % increase in energy absorption capability compared to the baseline VARTM plain weave/SC-15 system on an equivalent areal density basis. This study demonstrates that the ballistic performance of GFRP can be improved through a material by design approach where constituents are varied through the thickness for maximum energy absorption.Glass fiber reinforced polymers (GFRPs) are often used in protective-structural applications due to their high specific stiffness, strength, and energy absorption. During an impact event, GFRP laminates absorb energy at multiple length scales through fiber/matrix interphase debonding, resin plasticity, fiber failure, fabric ply delamination, and overall laminate deformation. Meanwhile, the through-thickness role and energy absorption mechanism of the GFRP going through a penetration event changes from a confined punch shear/crush under hydrostatic compression on the front face to delamination and in-plane tension failure in the layers near the back face. Traditional composite panels use a single fabric/sizing and resin which are not optimized for the different energy absorption mechanisms at the different phases of impact and penetration. This indicates a potential opportunity to improve the impact performance of GFRPs by functionally grading the constituents through-thickness of the laminate to optimize the specific properties of the constituents during to improve penetration resistance. In this study, a 1.8 cm thick functionally graded (FGM) composite was designed using the depth of penetration tests to select the strike face material system and a thin laminate ballistic perforation test for the back side material selection. Two commercially available S-2 glass fabrics, an 814 g/m2 plain weave with a 463 sizing and a 302 g/m2 8-harness satin fabric with 933 sizing, were tested with low and medium yield strength epoxy resins. The medium yield strength is the baseline
Process Modeling of the First Pyrolysis Cycle of SMP-10 Ceramic Matrix Composites
Ceramic matrix composites (CMCs) are widely used in high-temperature applications like hypersonic thermal protection systems. The polymer infiltration and pyrolysis (PIP) process is commonly employed to manufacture CMCs. The PIP process consists of repeated cycles of preceramic polymer infiltration and pyrolysis to progressively increase the density of CMCs. However, it presents challenges such as gas evolution, shrinkage of the preceramic polymer (PCP), and the formation of cracks, porosity, and internal stresses during pyrolysis. Detecting these defects is difficult, and they can lead to interlaminar delamination, reducing the CMC structure's strength, stiffness, and durability. Currently, determining the number of PIP cycles and manufacturing parameters relies heavily on experimental results due to the complex nature of CMC manufacturing. However, the high costs and time required for experiments hinder process optimization. Thus, there is a need for high- fidelity computational tools that can capture PIP process defects and analyze the effects of manufacturing parameters. This research aims to develop a multiphysicsbased model with temperature and degree of cure dependencies to simulate the first pyrolysis cycle of the PIP process and its resulting defects (pores and cracks) in CMCs. The FEA software ABAQUS and user subroutines will be used to implement this model. A comparison will be made between the predicted defects by the computational model and experimental results from AFRL. A comprehensive multiphysics model will be developed, integrating a thermo-chemical model, thermo- mechanical model, and crack initiation and propagation model. Initial findings have demonstrated encouraging agreement between the material model and thermogravimetric analysis (TGA) data, particularly concerning the impact of temperature and ceramic conversion.
A Progressive Fatigue Model on the Bearing Failure of Composite Bolted Joints
Bolted composite joints have distinctive failure mechanisms due to the bolt clamping force, which could induce a hydrostatic pressure in the bearing region. Compressive failure near a bolt hole under bearing, clamp-up pressure, and constraint from non-zero degree plies takes a variety of forms at the microscales including fiber micro-buckling, fiber kinking, fiber compressive failure, matrix cracking, delamination, and out-of-plane shear cracking. The hydrostatic pressure would cause the increase of compressive strength of the composite material and hence grant a large load-carrying capability to the bolted joint from damage initiation to ultimate failure. A physics-informed modeling approach is developed for the static bearing failure analysis by considering the residual stress along the longitudinal and transverse direction in the bearing region. However, the mechanisms become more complicated for the fatigue load when hole elongation is involved. The permanent hole elongation could be caused by the releasing of the formed debris in the bearing region during the unloading stage under fatigue load. To consider this permanent deformation, two permanent strain components in the longitudinal direction and transverse direction are introduced into the developed fatigue model and their evolution with the increase of fatigue cycles. With the evolution of permanent strain implemented, the fatigue model can be utilized in the failure prediction for the composite bolted joints of various configurations such as single shear bearing (SSB), double shear bearing (DSB), and bearing and bypass (BB) coupons. Validation studies are performed using test data from National Institute for Aviation Research (NIAR) and damage characterization results to correlate the damage progression and final failure mechanisms. The validated bearing damage and failure prediction module for CB2ATA will be used as a virtual testing tool to generate additional points on the bearing and bypass interaction curve without testing.
Towards a Digital Twin for High-Quality Curing of Multiple Composite Parts in Autoclave
Autoclave processes require a balance between the throughput and quality of the cured composite parts. The curing process is a major factor that influences the quality as well as the manufacturing time, which in turn is governed by the thermal distribution of the composite part. Developing a digital twin for composite curing in an autoclave is essential to optimize the autoclave process, which involves simultaneously curing multiple parts and improving the thermal homogeneity to obtain high-quality parts. A physics-based digital twin is created to mirror the physical composite curing process in the virtual domain. The digital twin includes a thermal CFD model, a thermo-chemo-mechanical module, and an efficient and accurate block coupling between these two modules. The customized Abaqus driven by local and spatial variation of the turbulence-induced heat transfer coefficient imposed through one-way coupling determines the thermo-mechanical response in composite parts. The accuracy of the one-way coupling strategy is demonstrated first using a benchmark problem followed by the capability demonstration with a single-part L-beam assembly. The benefits of using the digital twin tool are illustrated via the optimal placement of multiple parts in an autoclave to balance the throughput and quality.
Reconstruction of a SiC-SiC CMC Microstructure Using Deep Learning and Advanced Image Processing Technique
The paper presents a workflow for the reconstruction of a SiC-SiC ceramic matrix composite (CMC) microstructure using advanced image processing techniques and deep learning. The objective of this research is to develop highly accurate physics-based computational models for CMCs by gaining a comprehensive understanding of the microstructural features and their impact on material properties. A workflow is presented to classify voxels into individual components and extract stochastic data for establishing microstructure-property correlations. X-ray computed tomography (CT) data of the SiC/SiC CMC with a plain weave architecture and 00/900 fiber orientation are reconstructed using advanced image processing techniques. The resulting CT data is successfully segmented into three material constituents: tows, matrix, and pores. Pore segmentation is accomplished using the Otsu segmentation algorithm, while a deep learning-based U-net model is employed for accurate segmentation between SiC tows and the SiC matrix. Furthermore, an anisotropic segmentation algorithm is utilized to classify tow voxels along different directions, capturing the intricate variations within the microstructure. Geometrical and morphological attributes are extracted from the segmented data for further analysis.
Examining Cellulose-Pectin Interactions in Plant Cell Wall and Implication in Composite Design
The cell wall (CW) in plants is an anisotropic fiber-reinforced composite material made from multiple components (cellulose, hemicellulose, pectin, and lignin), with their structure and properties varying throughout the growth process to accommodate its multifunctional biological and structural needs. Revealing the architecture of plant CW and the role of its constituent and their interfaces is the key driver for this study. Here we characterized the composite-structure-mechanical response outcome of CW under component removal using enzymatic treatment, followed by instrumented indentation, optical microscopy, and Raman spectroscopy analysis to illustrate the changes. The results of the study indicate the critical role of pectin in the structure, where its breakage f1rom the cell wall leads to a maximum loss in structure and strength both for the early and later stages of plant growth. This study forms the basis of an expanded future investigation into the cell wall structure toward designing flexible fiber-reinforced composites for a broad range of applications.
Tuning Mechanical Response of Hierarchical Composite Structures
By varying the arrangements of microstructures and constituents in bodies allows for effectively tuning the mechanical performance of composite structures, i.e., increasing stiffness and toughness, maximizing energy dissipation, etc. We explore the use of programmable filaments consisting of soft and hard constituents in tuning the mechanical properties of materials used for kerf structures. Kerf structures consist of connected microstructural topology with spatially controlled flexibility enabling for easy macroscopic and microscopic shape reconfigurations. Using additive manufacturing (AM), we first fabricate programmable filaments out of Polylactic acid (PLA) and Thermoplastic polyurethane (TPU) polymers which we will then use to print kerf structures. We demonstrate the use of kerf structures with programmable filaments to enhance toughness and energy dissipation, which is driven by microstructural shape reconfigurations of kerf topology and hierarchical failure of the programmable filaments.
Low-Velocity Repeated Impact Behaviors of Polymer Fiber Reinforced Plastics (PFRPs)
Modern fiber-reinforced composites have become ubiquitous across multiple industries due to their excellent weight-to-strength ratio. Typically glass or carbon fibers are widely used. While Glass or Carbon Fiber-Reinforced Plastics (GFPRs or CFPRs) have good stiffness, strength, and fatigue life, they are expensive and difficult to recycle. Researchers are exploring Polymer Fiber-Reinforced Plastics (PFRPs) as an alternative solution. PFRPs utilize polymer fibers and a polymer matrix. A wide range of materials options is available, including low-cost thermoplastics such as polyethylene or polypropylene. These thermoplastics are easy to handle and recyclable without special methods. Manufacturing parts using thermoplastics are well-established as well. However, their mechanical performances have not been extensively studied compared to GFRPs or CFRPs. This study examines the low-velocity impact resistance of PFRPs made of different thermoplastics. The low-velocity impacts are applied through a drop-weight tower. The experiment is divided into two cases: a single perforation impact and low-energy repeated impacts. Energy absorption and the number of impacts to failure are measured. The results are compared to traditional CFRPs which have a thermoset matrix. The PFRPs demonstrate energy absorption capabilities comparable to or greater than those of CFRPs with respect to specimen thickness and density. Additionally, the PFRPs show significantly higher impacts-to-failure than the CFRPs in low-energy repeated impact tests. This is particularly noteworthy considering that the PFRPs are much simpler and more economical to manufacture than CFRPs. To further explore the advantages of PFRPs, we upcycle or heal PFRP panels after impacts. The healing process is identical to the initial panel manufacturing process. Healed PFRPs are impacted again, and their impact resistances are measured. The healed PFRPs can regain 20 to 30% of their energy absorption capability. These results are remarkable compared to the traditional CFRPs where any healing or repairing process is difficult and time-consuming.
Comparative Study of Compaction and Voids Development During the Out-of-Autoclave Curing Followed by CT-Scan: Effects Upon ILSS
The main challenges with composite parts manufacturing are related to the curing means, mainly autoclaves, the length of their cycles and their operating costs. In order to decrease this dependency, out of autoclave materials have been considered a solution for high production rate parts such as spars, flaps, etc. However, most out-of-autoclave process do not possess the same maturity as their counterpart, especially concerning achievable part quality. The absence of external pressure during cure has an impact on the part quality if the parameters such as the temperature and vacuum are not set correctly. In this work, the behaviour of 2 prepreg materials developed for out-of-autoclave curing is analysed by CT-Scan during precompaction under vacuum and during curing steps, with a focus on the manufactured laminates void content. The way mechanical properties are affected by void content is then studied by measuring the interlaminar shear stress of VBO processed parts.
Aeroelastic Analysis of Composite Plate Wings Based on a New HSDT Finite Element—MONNA
A new Multi-Order Nine-Node Advanced (MONNA) plate finite element is developed. This is a subparametric conforming 68 degree-of-freedom composite flat plate element based on the Higher Order Shear Deformation Theory (HSDT). This element may be considered h-p version, as accuracy is increased by increasing the number of elements and internal nodes are included to aid the rate of convergence. The element formulation is based on Hamilton’s principle. A computer code is written in MATLAB to perform the finite element analysis. Several static and dynamic verification runs are carried out and these demonstrate mostly superior convergence and higher accuracy of MONNA when compared to existing elements. The objective is to study the divergence and flutter characteristics of composite plate wings using HSDT by incorporating the MONNA finite element. The aerodynamic model incorporates the vortex lattice, doublet lattice, and doublet point panel method models. The higher-order plate element demonstrates better aeroelastic convergence and accuracy relative to traditional elements. Negligible difference is shown between FSDT and HSDT for a variety of composite materials and plate thicknesses.
Hygrothermal Aging of Structural Epoxy Adhesives Used in Wind Turbine Blade Composite Joints
Two different epoxy adhesives that are widely used in wind turbine blades were studied. The aim was to investigate the adhesives moisture absorption and desorption behaviors and assess their mechanical performance degradation with the environmental exposure conditions. The cured adhesives were conditioned at 50 ºC and three different relative humidity levels of 43, 75, and 96% for 17 days, followed by vacuum drying at 40 °C for another 17 days. During moisture absorption and desorption tests, periodic gravimetric measurements were conducted to obtain moisture saturation concentrations, diffusion coefficients, and residual moisture concentrations. The results revealed that the moisture saturation concentration increased 3-4 folds as the RH level was changed from 43 to 96%, while the diffusion coefficient was decreased. The permanent damage related to the environmental conditioning was then measured by tensile testing of fully conditioned samples. A significant drop in both the modulus of elasticity and the strength as well as a mild decrease in the strain at break were observed for both adhesive systems.
Effects of Bondline and Substrate Thicknesses on the Mode II Fracture Toughness of Composite/Adhesive Joints
Glass fiber reinforced plastics (GFRPs) are commonly used in wind turbine blades (WTB). The joining of several GRFP components in a WTB is usually obtained using structural adhesives. The GFRP/adhesive joint usually experiences mixed-mode loading (opening and shear) conditions, with mode II being a major phase. The experimental evaluation of the joint failure under shear is usually conducted using end-notched flexure (ENF) test, which provides the value of the fracture energy required for the onset of interlaminar crack propagation by shear forces. There are standard methods such as ASTM D7905 that have provided the procedure for the ENF test. This standard test method has been particularly developed for the evaluation of crack growth from a precrack within a fiber reinforced composite, not composite/adhesive joints. However, this method has also been used for Mode II fracture energy evaluations in composite/adhesive joints. To better understand the applicability of the standard ENF method for composite/adhesive joints of WTBs, this work focuses on the dependency of the measured mode II critical strain energy release rate (GIIc) on the specimen geometry, in particular, substrate thickness and adhesive layer thickness. The substrate effect on the fracture behavior was assessed using three different substrate thicknesses of about 3, 5, and 6.3 mm, and the bondline thickness was examined from 0.25 to 3.55 mm.Overall, it was found that both substrate thickness and the bondline thicknesssignificantly affect the fracture energy and failure mode. The results showed that withan increase in the substrate thickness, GIIc was increased, and the fracture surfaceexamination suggested a more cohesive failure behavior. Moreover, with an increase inthe bondline thickness, GIIc first was increased up to a maximum value of 6.90 kJ/m2 ata thickness of 1.05 mm beyond which it started to decline. These findings suggest thatthe measured fracture energy for composite/adhesive joints using ENF standard testmethod is strongly geometry dependent and thus the geometry should be considered inthe design for failure under crack growth.
Multiscale Modeling of Failure Mechanisms in Multidirectional Double-Edge Notch Compression Specimens
This study presents the use of a multiscale computational model for laminated composites in a double-edge notch compression (DENC) configuration. Analysis of in-situ and post-test DENC experiment results indicates the presence of multiple failure mechanisms, including ply splitting, delamination, and compression kink bands. In order to understand the onset, growth, and interplay of the critical and subcritical damage mechanisms, a nonlocal multiscale kink band model is incorporated alongside splitting and delamination models to simulate the compression behavior. The kink band model used in this study explicitly tracks the microstructural failure mechanisms that lead to the formation and propagation of kink bands. Cohesive zone models are used to describe the initiation and progression of ply splitting and delamination in the specimen. The splitting model was implemented using implicit finite element simulations and deployed with a pre-crack insertion technique to reduce simulation time while preserving prediction accuracy. Deterministic calibration of model parameters is performed using experiment measurements, and the effects of split location and growth characteristics on model predictions are also studied. The predicted positions of damage initiation and progression through the thickness of the laminate agree well with experiment results which include quantified characterization of the initiation and growth of both kink bands and surface ply splitting as a function of applied load level.
Investigating the Structure of CVD Deposited Amino Silane on Silica Substrate via High Resolution Characterization Methods
The interphase between glass fiber and an epoxy matrix is a nanometer scale region that governs the load transfer between these constituents in composites. Traditionally, sizing packages are multifunctional and are applied to a fiber surface to protect fibers during handling and weaving while improving wettability and adhesion through covalent bonds between the fiber surface and the matrix. The most conventional sizing application approach is to use epoxy emulsion of silanes and surfactants; however, it leads to non-uniform coating (i.e., coverage and thickness) and a structure that is not well understood. An adhesion promoter like organofunctionalized silanes is often a part of these sizing packages, and they can help achieve desirable interphase properties. Molecular dynamics (MD) simulation studies have shown that these glass-silane-epoxy interphase strength and energy absorption is highly dependent on bond density, interphase-coating thickness, and strain rate (monolayer and full saturation of bond density resulted in highest interphase strength). To create such thin coatings, a chemical vapor deposition (CVD) approach may be well suited since it can achieve both a uniform silane coating and control of the thickness range as low as a monolayer. A CVD method developed previously to deposit the silane coating on glass fiber surfaces, has shown improvements to the interphase strengths, though the deposited coating morphology was not well understood nor optimized. Quantifying/characterizing the uniformity and thickness of coating on a fiber surface is an experimental challenge due to its cylindrical shape. Hence, a Si substrate with an oxide layer was used as a surrogate. The current study focuses on understanding the relationship between CVD process exposure time (5 min, 30 min and 60 min) and structure of the amino silane coating on Si substrate to develop an approach for depositing a uniform and thin coatings.
Characterization of Continuous Carbon Nanotube Yarns
An approach on tensile testing is established for the mechanical characterization of two types of continuous carbon nanotube (CNT) yarns for potential aerospace-grade composite laminate applications. CNT yarns with around 80% alignment achieved a specific tensile strength of 1.66 N/tex and a specific tensile modulus of 84.64 N/tex. We studied the effects of resin cure cycles, moisture levels, and cyclical loading on the yarn’s mechanical properties. The results show that the specific strength and specific modulus of CNT yarns were unaffected by the temperature parameters of the BMI resin cure cycle. Hysteresis tests were performed to examine the resistance of CNT yarns to loading cycles, resulting in slight strain hardening and a 4-6 % increase in the specific strength and modulus of yarns. CNT yarns were moisture conditioned in wet, dry, and ambient environments to determine the effect of moisture content on mechanical performance. Yarn properties increased by up to 10% when ambient moisture was removed from the system. The results provide valuable insights to understand tensile properties and behaviors of high strength continuous CNT yarns with multiscale microstructures.
Analysis of Fiber Flow, Fiber Orientation, and Void Formation at Syringe-Nozzle Junction in Material Extrusion Additive Manufacturing of Short Carbon Fiber Epoxy Composites
Material extrusion additive manufacturing of short carbon fiber epoxy composite ink should exhibit thixotropic behavior which enables the fabrication of complex as well as simple 3D structures with controlled and tailored fiber arrangement within the composite part. This study investigates a method to automatically segregate fibers from voids and epoxy allowing fiber flow analysis and fiber orientation distribution. Validation of this method is used to present the experimental results for fiber orientation/alignment and void formation at the syringe-nozzle junction for a stitched (entire cross-section) and representative image. Further, the results were compared to assess the significance of the stitched image analysis over a representative image. Specimens were extracted as is from the syringe-nozzle juncture, followed by polishing and imaging. Qualitative visualization and quantitative analysis of the cross-section of the fibers were carried out using image-processing techniques for both images to identify the fiber orientation and alignment corresponding to the ink material flow direction at this junction. Bay and Tucker's method was used to quantitatively measure the 3D orientation and alignment of fibers. Similarly, qualitative, and quantitative analysis was carried out to identify and measure void area fraction for both the images. This study provides insight into the fiber alignment, arrangement, and dispersion within the epoxy matrix at this section as the ink material flows into the nozzle, followed by extrusion. Lastly, the experimental results reported in this study could be used to validate computational models used for analyzing flows within the ME-AM system for short fiber-reinforced epoxy composites.
3D Printed Aircraft Competition: A Framework for Learning Design for Additive Manufacture
The annual 3D Printed Aircraft Competition (3DPAC) at the University of Texas at Arlington (UTA) provides a competitive, experiential environment for undergraduate and graduate students to learn and apply design and process knowledge to innovatively design an aircraft with a 3D printed airframe. This paper provides an overview of the competition, case studies of current fixed and rotary wing aircraft designs from UTA design teams, and discussion of key observations and lessons learned from seven years of 3D printed aircraft competitions. In the competition, teams from a range of universities compete in fixed wing and rotary wing categories for prizes in design innovation and flight duration. It challenges students to apply theoretical principles for successful, lightweight vehicle design while considering 3D printing process and material constraints in order to maximize flight performance. Design freedom in terms of size, configuration, weight, and materials allows students to innovate and create to the best of their abilities. Limitations on propulsion duration and flight boundaries require teams to design effective, controllable flight vehicles and configure and size lightweight, efficient structures for maximum flight duration. Design case studies discuss the vehicle and structural design, including loads development, vehicle sizing, structural configuration and sizing, and structural and vehicle testing for aircraft printed using Fused Filament Fabrication (FFF), MultiJet Fusion (MJF), and Continuous Fiber Fabrication (CFF). The discussion emphasizes design considerations for 3D printing limitations such as wall thickness, overhangs and bridging limits, design limits to eliminate the need for supports, process-induced distortion, and printed material integrity.
Frontal Polymerization of Thermoset Composites: A Prospective Route for Additive Manufacturing
In this paper, frontal polymerization (FP) of carbon/epoxy (C/E) composites is investigated, considering FP as a promising route for additive manufacturing (AM) of thermoset composites. It is a fast and self-propagating polymerization process activated by thermal and cationic initiators. This study uses FP for neat epoxy resin, short carbon fiber (SCF), and continuous carbon fiber (CCF) reinforced composites. The evolution of exothermic reaction temperature, polymerization frontal velocity, degree of cure, and fracture surface are experimentally determined for different thermoset composites. As the FP continued, the temperature distribution and the FP path were monitored using a thermally activated infrared (IR) camera. The differential scanning calorimeter (DSC) is used to measure the degree of cure of the polymerized samples. The effects of excitation temperature and fiber contents in self-propagating reaction temperature and FP velocity are studied. FP-based thermoset composites' void contents and tensile properties are determined and compared with those manufactured through conventional methods with long-duration cure cycles. The results show increased cure time and decreased average frontal velocity with increased fiber contents in SCF-reinforced composites. This occurs because, at higher fiber contents, the resin percentage (heat source) is reduced, which primarily drives the exothermic reaction. Such a trend is primarily observed in low filler loading of SCF (1% to 3%). The FP velocity varied at different sample regions during polymerization, possibly due to the non-uniform distribution of short fiber contents. Increased tensile strength is observed in SCF-based composite in comparison to neat resin. The void contents in the 8% and 12% range were observed in neat resin and short fiber composites, respectively. The microstructure of the specimens shows large cracks due to residual thermal stresses developed during curing. Excitation temperature shows some effects on the exothermic reaction temperature and frontal velocity. The exothermic reaction temperatures range between 110 0C and 147 0C, whereas the initial excitation temperature varies from 150 0C to 270 0C. The FP velocities are seen to be 0.65 mm/sec for neat resin and 0.63 mm/sec, 0.62 mm/sec, and 0.57 mm/sec for 1%, 2%, and 3% SCF-reinforced composites, respectively. The result shows an FP velocity of 0.72 mm/sec for unidirectional continuous fiber reinforcement composites. This velocity is seen to be 28% higher in comparison to the neat resin. This is due to continuous carbon fiber-reinforced composites' faster heat flow rate. Failure strength is observed to be increased with enhanced initial excitation temperature. This is possibly due to enhanced reaction temperature, which resulted in a higher degree of cure. Finally, FP is seen to be a promising route for additive manufacturing of thermoset composites which emphasizes further studies to overcome shortcomings of the process.
A Stress-Responsive Shape Memory Polymer via Chemical Grafting Functionalized Cinnamoyl-Based Mechanophore
Due to the intrinsic mechanochemical characteristics, shape memory polymers (SMPs) with multifunctionalities are highly desirable for structural applications. The capability of self-sensing for early damage has been extensively investigated. The general fabrication technique for feature incorporation is to blend stress-responsive additives directly; however, this approach usually leads to performance tradeoffs. Here, we have developed a method to attach a cinnamoyl-based mechanophore to the backbone of the SMP matrix via a chemical grafting technique. We have varied weight ratios of mechanophore, which exerts its amine functionality to mingle with Jeaffmine D230 forming an advanced crosslinker and allowing for the fabrication of a stress-responsive polymeric network inside an SMP matrix. Dynamic mechanical analysis (DMA) and quasi-static tensile tests were performed to characterize the mechanical and thermal properties of SMP thermoset samples and investigate the optimal weight ratio. Meanwhile, the rubber elasticity plateau is utilized to calculate the crosslinking densities for the SMP samples. The storage moduli and glass transition temperatures of SMP-based thermoset samples were slightly reduced with the lower weight ratio of mechanophore on 5 wt.% and 7.5 wt.%. With increasing mechanophore loading weight to 9 wt.%, the storage modulus and glass transition temperatures of baseline SMP improved by 9.0 % and 15.7 %, respectively. Interestingly, increasing the weight ratio of mechanophore to 10 wt.% and 12.5 wt.% caused the property reduction again. This could be attributed to the over-saturation from self-polymerization or unreacted mechanophore affecting the SMP matrix negatively. Quasi-static tensile tests were performed while the instrument is coupled with in situ fluorescence detection setup to monitor the self-sensing capabilities under given loading conditions.
A Study of Optical Surface Analysis Methods for 3D Printed Continuous Fiber Composites
Continuous fiber reinforced additive manufacturing has been growing in research and in commercial application. In this work, additively manufactured carbon fiber thermoset composites are being produced utilizing a liquid deposition modeling process with photo-curable resin. The quality and mechanical properties of additively manufactured composites is sensitive to the void concentration and distribution. The void percentage of additively manufactured composites had shown correlation with the surface quality of individual layers. Research has found that surface quality of individual layers could be controlled by process parameter adjustments such as material flow rate, speed and layer thickness. Regular monitoring of these variables becomes necessary for consistent and feasible production. To achieve this, the authors implemented a study utilizing a camera system and image processing algorithm for surface evaluation with a goal of print parameter adjustment on the fly. The resulting technology has been proven to accurately analyze each layer. This study aims to develop a surface feature extraction method for the purpose of training and deployment of a machine learning algorithm which will execute dynamic adjustment of process parameters.
The Low Velocity Dynamic Energy Absorption of Composite-Lattice Sandwich Structures
Recent advances in additive manufacturing have allowed the investigation of the static and dynamic performance of 3-dimensional cellular structures for the application of absorbing mechanical energy. The inclusion of lattice structures in energy absorbers allows lighter weight design that can sustain large elastic deformation. Structures that perform well under static loading may not perform well under dynamic loads due to kinetic energy and wave propagation effects. Thus, the complexity of the design process increases when designing energy absorbing structures through a range of strain rates and impacting inertias. In this study we investigate the dynamic performance of existing and novel lattice structures sandwiched between carbon fiber composites and Kevlar fabrics for the application of lighter weight, better protecting armor and helmets. The results of this novel sandwich design are directly compared to the performance of the material layers used in United States Army’s standard issue Advanced Combat Helmet (ACH). Dynamic low velocity impact experiments are conducted using a drop tower system. The energy absorbed by the sandwich structure is recorded based on the difference in acceleration from the top impacted surface and the base of the structure. A base-level study of the existing lattice structure energy absorption is conducted prior to the testing of composite sandwich structures. The existing structures tested include body center cubic (BCC), face center cubic (FCC), kelvin truss (KT), and diamond cubic (DC). Across all tests the BCC reduced the most acceleration followed by the DC, FCC, and KT lattice. It is observed for all tests that at constant impacting mass and strain a lower relative density allows more deformation of the lattice resulting in a higher acceleration reduction. The lower relative density structures undergo compression for a longer period yielding higher impulse or momentum change. This study provides insights into how the use of cellular materials, carbon fiber composite sheets, and Kevlar fabrics may provide enhanced energy absorption at a lighter weight compared to existing helmet material and structural systems.
Prediction of Distortion and Residual Stress Evolution in the Fused Filament Fabrication Process Using Higher-Order Finite Elements
This work presents a higher-order finite element-based process modeling framework for material extrusion additive manufacturing. The numerical modeling is based on higher-order structural theories derived via the Carrera Unified Formulation, and allows for high-fidelity modeling in a computationally efficient manner. The element activation strategy is employed to simulate the material deposition process. A thermo-mechanical analysis is performed to determine the evolving temperature field within the part during the printing process, which is subsequently used to evaluate the distortion of the printed structure. Numerical assessments are performed, and the agreement of the numerical predictions with available reference experimental data validates the proposed process modeling framework for additive manufacturing.
Recyclable Cellulose Fiber Reinforced Vitrimer Composite
Vitrimer is an innovative class of polymeric materials which demonstrates traditional thermoset-like mechanical and chemical resilience while still being able to flow on demand like a traditional thermoplastic through covalently adaptive dynamic linkages. Herein, high-performance cellulose fiber reinforced vitrimer composites are developed using an epoxy-based vitrimer and natural cellulose paper. The reinforced vitrimer composite was fabricated by impregnating the porous structure of cellulose paper with two curable monomers, followed by in-situ polymerization of the monomers inside the fibrous scaffold. The introduction of hydroxyl group present on the cellulosic framework assisted in a faster topological rearrangement of the crosslinked matrix through transesterification exchange reaction, thus imparting various sought-after properties like shape recovery and recyclability via simple thermal reprocessing. Moreover, the reinforced vitrimer composite exhibits superior tensile properties as high as 90 MPa with 15-25 volume% vitrimer loading due to the interfacial adhesion via ester exchange reaction between the epoxy matrix and functionalities on the cellulosic fibers. Noteworthily, the key ingredients of the resulting composite (i.e., epoxy-based vitrimer and cellulose fibers) can be comfortably recycled without using aggressive chemical treatment, enabling composite to be easily recycled or disposed of at the end of service life and assist in reducing the subsequent manufacturing cost. This study would shed light on the development of a recyclable polymer composite with exceptional mechanical properties while simultaneously demonstrating self-healing and shape memory capabilities.
Investigation of Tooling Geometry Using a Finite Element Simulation of UHMWPE Unidirectional Thermoforming
Thermoforming is an economical and fast process for transforming a flat sheet of thermoplastic composite material into a complex-shaped preform. A binder ring is used to induce in-plane tension to mitigate wrinkling and to drive the dominant deformation mechanism to be in-plane. The degree of shear can vary over the part, creating variations in thickness and subsequent challenges with uniform consolidation for a stack of preforms. While material attributes and processing parameters are critical in successful preforming, variations in the tool geometry may also lead to significant changes in the preform outcome. The goal of this research was to develop a virtual process simulation that can guide design changes in the processing conditions, ply blank geometries and tooling to achieve a well consolidated part. A discrete mesoscopic modeling approach was implemented in LS-DYNA using thickness-change shell elements (ELFORM25) that can incorporate 3D material properties, including through-plane thickness changes. The current state of the simulation effectively incorporates material behavior, tool/ply friction and thickness changes that reflect variations in pressure during consolidation to radius. In the current study, the simulation is used to investigate the significance of tooling geometry, including the punch/die gap size. The die fillet results were verified through comparison to experimental results with two types of tooling geometry. A parametric study was performed to investigate tooling changes in relation to the number of layers, or thickness, of a unidirectional UHMWPE material. Observations show that the radius of the die fillet has significant impact on wrinkle onset as the material passes through that juncture.
Microstructure Correlation Method for Fiber Orientation Characterization and Ply Segmentation in X-Ray CT Scans of Composite Laminates
This work is a part of an on-going effort to develop effective methods and algorithms enabling automated conversion of X-ray Computed Tomography (CT) scan data into finite element (FE) models for as-built composite parts. In particular, this paper is focused on the automated methods of segmentation of composite plies in X-ray CT scans and finding resulting ply waviness as well as local fiber directions and ply orientations, including average fiber misalignment and fiber direction variability. Sample applications of the proposed algorithm are provided for as-manufactured tape composite laminates as well as additively manufactured composites. Effects of X-ray CT scan quality on the algorithm performance are demonstrated.
Influence of Deformation of Compliant Rollers on Tape Steering During Automated Tape Placement
Automated tape placement with tape steering represents a process to manufacture lightweight composite structures. In our experimental studies, a Mikrosam Tape placement system with laser nip-point heating and a compliant consolidation roller has been used to quantify the limits of steering of continuous and highly aligned short fiber tapes (AS4/PEI with a fiber length of 3 mm). The minimum radius is typically limited by the compressive strain in the fiber direction that will buckle/wrinkle the inner radius of the tape. In the case of the aligned short fiber tapes, order of magnitude reduction in the minimum radius (50-100 mm) has been demonstrated by exploiting the in-plane extensibility of these tapes compared to inextensible continuous fiber (500-1000 mm). The tape deformation and path accuracy during steering experiments has been quantified using DIC methods. These results have indicated that the deformation of the compliant roller during compaction, placement and steering is a major factor. In this study, the deformation of the roller over the full range of consolidation forces (400-900 N) has been quantified to include load-deformation response, and pressure distribution within the contact area. In addition, DIC is used to measure the 3D deformation and strain fields within the roller across the width and circumference as well as to provide insight into the frictional interaction between the rubber surface and the substrate during static loading and constant velocity steering paths. A finite element model of the compliant roller is developed, and a parametric study is conducted investigating the effects of rubber durometer and friction within the rubber/substrate contact area. Relatively good correlation has been achieved using a rubber durometer of Shore hardness 45 in terms of load-deformation response. In the case of steering where the AFP head rotates, a torsional moment is imparted on the roller and the rubber is predicted to undergo shear deformation as well as compression deformation from the consolidation force. Steering of the deformable roller at 25 mm radius is simulated and shows centerline deviations of around 2 mm. To analyze the rubber deformation DIC is conducted during steering and shows that 1000 mm steering radius deforms differently from 25 mm. The results of this study show that the deformation of the roller is an important factor in controlling the tape deformation and critical for accurate path control during steering of the highly aligned short fiber tape with a small steering radius.
Constitutive Modeling for High-Fidelity Analysis of Bondline Failure in Polymeric Matrix Composites
Adhesively bonded Polymeric Matrix Composite (PMC) structures could offer significant cost savings and increase production rates in the fabrication and assembly of future composite airframes. In particular, bonded PMCs may eliminate the use of thousands of mechanical fasteners and allow incorporation of multiple aircraft composite primary structures into a unitized structural design. However, increased susceptibility to defects and manufacturing irregularities, including voids, disbonds, and geometry variations, as well as complex interacting failure mechanisms, hinder a widespread use of bonded PMCs. High-fidelity computational materials-based analysis methods that can capture the effect of defects and improve the understanding of failure mechanisms that govern bondline failure are needed to support qualification and certification of next-generation bonded PMCs and safely reduce redundant fasteners. The objective of this work is to contribute to such development. A continuous-discontinuous framework is considered for capturing quasi-brittle failure within the epoxy adhesive and predicting growth of arbitrary solution-dependent crack paths in presence of bondline defects. In this approach, an elasto-plastic constitutive model with isotropic damage is enhanced with the introduction of extended finite element method (XFEM) enrichments that incorporate non-local features. The implementation of the approach in commercial FE software Abaqus using built-in XFEM capabilities in combination with a set of user-defined subroutines is presented and illustrated in two-dimensional FE models representative of adhesively-bonded double-cantilever beam (DCB) specimens.
Analytical Model for Transverse Tensile Strength Prediction of Thermoset Composites
Evaluating the transverse tensile response of Polymer Matrix Composite (PMCs) is an extremely challenging problem since it is greatly influenced by the stress concentration induced within the composite microstructures by random fiber inclusions. This study presents a novel methodology to develop an analytical solution for transverse composite strength prediction. A computational micromechanical study of composite microstructures with varying fiber volume fraction is carried out to accurately predict their transverse strength. Local stress concentration in composites due to fiber inclusion is investigated and a global stress concentration factor for each analyzed microstructure is quantified using statistical descriptor. Transverse composite strengths from FE simulations are expressed as a function of the constituent properties and the global stress concentration factors to derive a material system-specific analytical relation.
To the Mesoscale and Beyond! Capturing Complex Damage Mechanisms in Composites via Simple, Physics-Based, Discrete Mathematical Models of Fibers and Matrix
Unidirectional (UD) and 2D/3D textile composites are increasingly being employed in systems acrossed many industrial sectors including aerospace, automotive, and wind energy. This is due to the excellent specific mechanical properties and tailorability of composites, paving new avenues for structural optimization and weight savings. One of the challenges with the simulation of the mechanical response of composite materials is that their damage mechanisms depend strongly on the material micro- and mesostructures. Phenomena such as fiber micro-buckling and kinking in compression or fiber scissoring and matrix microcracking in shear in UD composites are only a few examples. Homogenized continuum models that describe these mechanisms are extremely mathematically complex, lack generality, and can only be used to fit experimental data. In fact, the constitutive equations compensate for not modeling fibers and matrix explicitly by introducing several complex equations and fitting parameters of unclear physical meaning. This makes model calibration extremely cumbersome and limits the predictive capability of the model. In reality, the modeling of damage and fracture in composite materials does not have to be complex if the physics of the micro-and mesostructures is simulated explicitly. This is the goal of the Discrete Model for Composites (DM4C), a novel discrete mesoscale modeling framework that simulates the mechanical behavior of UD and textile composites. Specifically, this framework is only based on physical laws and does not depend on element erosion to simulate fracture. As it will be shown in this presentation, in DM4C, fibers, groups of fibers, and tows are simulated explicitly as Timoshenko beam elements while the matrix is described by vectorial constitutive laws defined on the facets of a tetrahedral mesh anchored to the nodes of the beam elements. These vectorial laws describe both the elastic and inelastic behavior of the matrix, including the traction-separation laws governing the fracture process and the friction between facets governing the compressive behavior. Thanks to the facet-based formulation, fracture is modeled in a discrete way and the need for element erosion can be avoided. Furthermore, since fibers and matrix are now simulated explicitly, the constitutive laws of each material can be physics-based, simple, and with clearly defined material parameters. To demonstrate the predictive capability of the proposed framework, simulations of several typical damage mechanisms in composites will be compared to experimental data such as shear band formation in transverse compression, fiber micro-buckling and kinking in longitudinal compression, and sub-critical matrix microcraking in off-axis layers.
Experimental Characterization and Numerical Modeling of ±45° Tensile Laminates
This paper investigates the combined effect of stacking sequence and interlayer toughening on the mechanical response and failure modes of ±45 carbon fiber reinforced laminates, through experimental and numerical studies. Two material systems (T800H/3631, T800S/3900) and three stacking sequences (4 double plies, 4 plies, 8 plies) have been examined. Digital Image Correlation (DIC) and a high resolution edge camera were utilized to capture the intricate crack patterns in each ply. This paper also addresses the challenge of the nonlinear in-plane shear characterization of each lamina, and proposes an amendment to the existing ASTM standard to obtain the lamina shear strength and the in-situ non- linear response. The complex progression of micro-damage, matrix cracks and delamination as well as the final two-piece failure were captured by the enhanced semi-discrete damage modeling (eSD2M) framework. A parametric study was performed to reverse-engineer the most critical parameters such as interlayer strengths and toughnesses. The obtained values reflect the difference in the interlayer composition between the two material systems.
Impact of Buckypaper on the Mechanical Properties and Failure Modes of Composites
Recently, there has been an interest in the incorporation of buckypaper (BP), or carbon nanotube (CNT) membranes, in composite laminates. Research has shown that using BP in contrast to nanotube doped resin enables the introduction of a higher CNT weight fraction which offers multiple benefits including higher piezo resistivity for health monitoring applications and enhanced mechanical response for structural applications. However, their impact on the deformation and failure mechanisms of composite laminates has not been investigated thoroughly. Understanding these issues experimentally would require a carefully executed test plan involving a multitude of design parameters such as BP geometry and placement, material anisotropy and variability, and laminate stacking sequence. Computational investigations can also be conducted to 1reduce the labor and cost associated with testing; however, for these results to be meaningful, high-fidelity physics-based simulation tools, accounting for scale-dependent variability, constitutive laws, and damage mechanisms and their evolution across the length scales, must be used. These methodologies are computationally intensive and their implementation in the analysis of complex heterogeneous structural systems can be prohibitive. This paper presents a deep learning (DL)-based surrogate model for studying the mechanical response of hybrid carbon fiber reinforced polymer (CFRP) composite laminates with BP interleaves under various mechanical loads. The surrogate model utilizes a long short-term memory (LSTM) architecture implemented within a DL framework and predicts the laminate global response for a given configuration, geometry, and loading condition. The DL framework training and cross-validation are performed via data acquisition from a series of three-point bend tests conducted through finite element analysis (FEA) and in-house experiments, respectively. The results show that the surrogate model is capable of predicting damage induced inelastic response without the computationally expensive task of solving nonlinear equations such as continuum damage mechanics and fracture mechanics-based equations. The model predictions show good agreement with FEA simulations and experimental results, where CFRP with two BP interleaves showed enhanced flexural strength and modulus over pristine samples. This enhancement can be attributed to the excellent crack retardation capabilities of CNTs, particularly in the interlaminar region. Finally, confocal microscopy images of experimentally tested specimens were analysed to interpret the predicted stress-strain response. Early damage initiation was observed in the 90° ply, resulting in the onset of nonlinearity and stiffness degradation. These micrographs also confirmed the role of BP in preventing through-thickness crack propagation.
Static and Fatigue Characterization of Mode I Fracture in Adhesively Bonded Composites Based on the J-Integral Approach
In this work, efforts are made to further develop tests for characterization of mode I quasi-static and fatigue fracture of adhesively bonded composites based on the J-integral approach using the double cantilever beam (DCB) test. This work will address the few remaining challenges that must be resolved before standardization of these test methods. Specifically presented are the attempts to: 1) establish a robust procedure for measuring JI using specimen arm rotation and the applied load, 2) determine specimen geometry that would enable accurate characterization of the traction separation law (TSL) during DCB testing, and 3) develop a protocol for J-controlled fatigue testing without explicit knowledge of crack extension.
Development and Validation of the Instrumented Traveling Wedge Test for Mode I Fracture of Adhesively Bonded PMCs
To date, methods for characterizing bondlines in adhesively bonded polymer matrix composites (PMCs) have relied on adapting tests for bonded metals or tape laminate composites. These test methods have not been accepted as standard due to the lack of quantitative information connecting the observed bondline failure (e.g., fracture growth), the specimen geometry, and applied loading. The ITW test method is a mode I fracture test designed to characterize long (>150 mm) adhesive bondlines between PMC adherends. In this work, the ITW test is further developed to allow for the extraction of fracture toughness using a J-integral approach. It is then validated by comparing ITW results to those obtained using a traditional DCB configuration where the loading is applied via hinges. In both cases, J-integral data reduction was used. Close agreement between the ITW and DCB test results suggests the ITW test is equivalent to the DCB method. Additionally, the ITW’s ability to detect bondline variability was assessed by testing specimens manufactured with variable bondline toughness. Gradual changes in bond toughness were introduced by tapering the adhesive thickness along the specimen bondline. Dramatic changes in bond toughness were produced by using two adhesives with noticeably different fracture toughness in the same bondline. The ITW was shown to be capable of detecting subtle and dramatic changes in bondline toughness.
Sources of Variability in Small-Scale Tensile Testing of Carbon Fiber Reinforced Resins
Scaling down the dimensions of standardized materials testing methods can provide opportunities for comparison between established and emerging materials. However, scaled-down testing methods can be sensitive to a variety of testing variables and may not always produce material properties that are comparable to standardized methods. In this work, we developed a method for tensile testing small fiber-reinforced composite specimens and used it to test unidirectional IM7/8552 laminates. Specimens with dimensions around one-third of the ASTM standard recommended size were loaded in tension using aluminum inserts inside hydraulic collet grips, without the need for specimen end tabs. To investigate specific variables that can lead to deviation in the measured tensile strength and modulus of the laminate, 14 different specimen sets were tested. Overall, the testing method was not sensitive to the specimen dimensions over the range of lengths, widths, and thicknesses that were investigated. The ability to fabricate very small specimens with consistent quality was the main challenge to generating accurate and precise tensile data. Uncertainty in the cross-sectional area measurement for very small specimens can also contribute significantly to the deviation in the measured tensile properties. Using an alignment jig significantly reduced the scatter in the tensile strength measurement. The developed testing method consistently and accurately measures tensile modulus but tends to report strength values that are lower than reference values. We consider the method to be a useful and reliable tool for comparing tensile properties of small composite specimens, but not a direct replacement for testing using ASTM D3039 or other established testing standards.
Experimental and Numerical Analysis of Crack Migration in Carbon-Epoxy Composites Subjected to Shear Loading
This study investigates shear-driven intralaminar crack migration and delamination in tape-laminate carbon-epoxy composites. A new test procedure is proposed using the end-loaded-split (ELS) test configuration combined with a dual actuator load frame to control the crack migration process caused by shear loading. Several experimental ELS tests were completed to gain a full understanding of the migration process, with results indicating that the crack migrations and delaminations are repeatable and can be used for numerical validation. Numerical models were able to replicate the linear elastic response of experimental specimens but had discrepancies when simulating crack growth. Migrations could be captured but transverse damage growth and delamination following migration events gave inconsistent results.
A New Test for Characterization of Interlaminar Tensile Strength of Tape-Laminate Composites
Interlaminar tensile strength (ZT) is an important property of polymer matrix composites (PMCs). Accurate characterization of ZT is critical for material screening, failure analysis, and design of laminates. However, current methods for determining ZT suffer from several drawbacks that prevent accurate and unambiguous measurement of this property. With this in mind, the aim of this study is to develop a new test specimen and method for accurate measurements of ZT. This new test is developed such that the measured ZT values can be directly compared to intralaminar tensile strength (YT) obtained using the same specimen geometry and batch of material. Consequently, the ZT test geometry is based on a three-point bend flexure configuration, which has been previously used to measure YT. The material orientation in the proposed specimen configuration begins with the configuration used for measuring YT, where the specimen is subjected to tensile flexure stresses along the transverse (in-plane) 2-direction. This geometry is subsequently modified by extracting the central portion of the specimen, rotating the resulting central core by 90° about the 1-direction, and reattaching it to the other two parts of the specimen using a paste adhesive. In the resulting configuration, the central portion of the specimen is subjected to tension along the 3-direction, which allows for characterization of ZT at the onset of beam failure during flexure loading. The proposed test is evaluated using two microstructurally distinct carbon/epoxy systems, namely Hexcel’s IM7/8552 and Toray’s T800/3900-2C. To obtain a sense of variability in ZT for each material, at least 30 specimens are tested per configuration. Additional testing is performed to determine whether the bonded core and the adhesive used affect the measurements of ZT. Overall, the experimental data demonstrates that the new configuration provides a reliable measure of ZT that is independent of the specimen manufacturing method. More importantly, a direct comparison between ZT and YT demonstrates that the two properties appear to be different, with ZT being the lower of the two. Although no direct links between lower values of ZT and the specimen microstructure are discovered, this effect is likely influenced by the local microstructure of each composite system, and specifically, by the presence and location of resin-rich regions relative to the tensile stresses.
Accurate Tension-Tension Fatigue Testing of Unidirectional Composites
The fatigue behavior of composites is generally described by the S-N curve of unidirectional (UD) composites. However, obtaining reliable fatigue data hinges on a test method that guarantees uniform stress distribution over the gauge section. The standard methods introduce stress concentrations close to the end tab edge and hence lead to premature failure. To find the method yielding the highest fatigue life, the current work examines different specimen configurations. The standards and two well-known configurations as well as a novel arrow-shape one are studied. The standard configuration, rectangular specimens with rectangular and tapered end tabs, yielded the highest fatigue life. Moreover, the effect of the test setup on fatigue life is investigated. The results show a considerable effect of specimen configuration and test setup on the fatigue life of UD composites. The results of this study assist reliable fatigue tests.
Three Common Mistakes in Mechanics of Composites
Mechanics of composite materials is a well-established subject after active research for more than fifty decades. The two most fundamental theories in the mechanics of composites are the Rules of Mixtures (ROMs) and the Classical Lamination Theory (CLT). ROMs are the simplest micromechanics theories which are used to compute the effective properties of a composite material in terms of its constituents. CLT is the simplest structural mechanics theory to model composite laminates in terms of lamina constants and layup angles. During the course of researching and teaching the mechanics of composites for over two decades, the author has discovered three common mistakes made in most textbooks and other literature related to the mechanics of composite materials. The first mistake is that most textbooks and other literature claim an incorrect upper bound. The second mistake is the in-compatibility of the plane-stress assumption and the Kirchhoff assumption used in deriving the CLT. The third mistake is the common belief that the extension-bending coupling stiffness B must be symmetric, which is only true for laminated plates. Symmetric B is not guaranteed for curved panels or panels with microstructures featuring arbitrary heterogeneity and anisotropy, such as sandwich panels with corrugated cores or 3D woven composite panels. It is the intention of this paper to disclose these mistakes so that they will not be propagated into future generations.
OpenSG: An Open-Source Multiscale Constitutive Modeling Code for Composite Structures and Materials
Mechanics of Structure Genome (MSG) represents a revolutionary approach to multiscale modeling drastically different from the conventional bottom-up multiscale modeling approaches. The principle of minimum information loss (PMIL) is used to avoid a priori assumptions in kinematics and kinetics. MSG confines all approximations to the constitutive modeling for all types of structures including 3D solids, 2D plates/shells, and 1D beams, directly linking the structural properties with microstructural details. MSG allows one to choose the starting scale and ending scale and capture details as needed and affordable without invalid scale separation and assumptions within scales. MSG has been proven to be much faster than the popular alternative, RVE analysis. MSG was implemented in a commercial code called Swift- Comp as a general-purpose constitutive modeling software that can be used by itself for virtual testing of structures and materials or as a plugin for conventional FEA packages. However, to assemble all the talents the world has to offer to realize the ICME vision, we are motivated to develop an open-source implementation of MSG so that others can easily leverage the efficient MSG theory to develop other multiscale models. In this paper, we will show how we implement MSG using FEniCS, an opensource, general-purpose FEA package. FEniCS is a popular open-source computing platform for solving partial differential equations (PDEs). FEniCS enables users to quickly translate scientific models into efficient finite element codes. Formulating the MSG theory using a variational statement suitable for FEniCS along with proper constraints, we developed OpenSG, an open-source implementation of MSG, using FEniCS. OpenSG will be used to perform homogenization and dehomogenization for heterogeneous solids, plates/shells, and beams. Applications of OpenSG to composites, 3D printed materials, metamaterials, biomaterials, and auxetic materials will be demonstrated. The performance in terms of accuracy and efficiency of OpenSG will be compared to SwiftComp. After extensive verification and validation, OpenSG will be made available globally through github.
Large Scale Additive Manufacturing of Recycled Polymer Composites
The production of large-scale products is currently undergoing a considerable shift in the manufacturing sector in favor of additive manufacturing (AM). Complex structures and elaborate designs that were previously impossible to produce using conventional manufacturing techniques are now possible thanks to the usage of additive printing technology. At the same time, using recycled materials in the production process has also risen to the top of the industry’s priority list as a result of a growing focus on sustainability. In this context, the use of recycled polymer composites in large-scale additive manufacturing (LSAM) is beginning to attract attention from both industry and research. Indeed, recycled polymer composites offer several benefits, including not only lower costs but also significantly reduced environmental impact and improved mechanical properties compared to virgin polymer materials. However, several challenges are still associated with using recycled materials in AM, including issues with material properties and compatibility with the AM process. Perhaps the most difficult polymer for AM is nylon where different grades pose different printing properties and challenges, thus printing large-scale objects in recycled nylon is a challenge that few have taken on.
Machine Learning Based Structural and Failure Characteristics of Carbon Nanotube Junction Configurations
Carbon nanotube based multi-terminal junction configurations are of great interest because of their potential aerospace and electronics applications. The performance of nanodevices based on these carbon nanotube junctions can be affected by the structural properties of the topologically accurate junction morphology like mechanical strength, thermal and electrical conductivities. It is therefore necessary to be able to investigate and characterize these properties accurately and quickly such that optimum structural configurations can be intelligently configured for the desired function. It is in this scenario that traditional atomistic simulations encounter severe limitations in terms of computational time required and hence the use of artificial intelligence techniques becomes necessary. In this work, we present a Machine Learning based characterization of structural and failure properties of carbon nanotube junction configurations. Structural and failure properties of a large set of 3D nanotube (CNT) junction configurations are first studied using molecular dynamics (MD) simulations. The stress-strain data until failure for each of the carbon nanotube junction configuration was estimated and various structural properties were used in the generation of the dataset. This dataset was used in a gradient boosting-based machine learning algorithm for the characterization of mechanical and failure properties of the nanotube junctions. Gradient boosting algorithms are prediction-based models that consists of sequential ensemble learning techniques in which the overall performance of the model is enhanced over multiple iterations. The coefficient of determination (R2) value is used to evaluate the robustness of the developed models for structural and failure parameters identified earlier. The machine learning techniques can be effective in predicting the structural properties of nanotube junction configurations with greater confidence.
Strength and Stiffness Evaluation of Aluminum-Based Open and Closed-Cell Foam Core Sandwich Panels for Comparison to AM2 Al 6061-T6 Mats: An Initial Investigation
The purpose of the present study is to explore lightweight aluminum foam-core sandwich panel materials and structural configurations in order to compare their mechanical performance to that of Marine Corps AM2 Al 6061-T6 mats. The objective is to quantify the property variations with tailoring of foam core type and base skin structure and compare them to AM2 mechanical performance of specimens of similar dimensional scale on the basis of strength, stiffness and weight, among other properties. Quasi-static tests have been conducted and the resulting analysis has yielded strength-to-weight ratio increases of 11.2% under compression and 48.9% under flexure; the data variations are observed considering that the thickness of select specimen configurations is 50% lower than that of the AM2 mat configuration. The results aim to determine potential viable material/structural alternatives to inform future aircraft landing platform designs with the goal of enhancing logistics and maintaining or exceeding current matting mechanical performance.
Effect of Particle Size on Viscoelastic and Electrical Properties of Reduced Graphene Oxide Films
Structural materials with high damping and stiffness can reduce the weight of structures in several applications, yet they do not exist yet. Films made from 2D materials such as graphene have the potential to realize this new set of material properties. This study investigates the impact of particle size on the viscoelastic and electrical properties of graphene oxide (GO) and reduced graphene oxide (rGO) films. Two types of GO films were fabricated, one using small GO sheets and the other using large GO sheets. The size difference was confirmed through electron microscopy, revealing an average lateral size of approximately 1 μm for small particles and 9 μm for large particles. Particle packing differs for the tested samples and is correlated to their storage modulus and damping. Similarly, the electrical conductivities of the reduced films are measured and explained in terms of particle size, functional groups, and packing. This study reveals the processing-structure-property relationships in GO/rGO films, a crucial step in realizing their potential for achieving simultaneous high stiffness and damping for noise, vibration, and impact damage mitigation.
Development of Novel Carbon Fiber Based Electrodes for Lithium-ion Batteries
Carbon fiber-based structural lithium-ion batteries are attracting significant attention in the automotive and aerospace industries due to their dual capability of energy storage and mechanical load-bearing, leading to weight reduction. These batteries utilize lightweight carbon fiber (CF) composites, which offer excellent stiffness, strength-to-weight ratios, and electrical conductivity. Polyacrylonitrile-based CFs, comprising graphitic and amorphous carbon, are particularly suitable for Li-ion battery applications as they allow the storage of lithium ions. However, integrating lithium iron phosphate (LFP) into CFs poses challenges due to complex lab-scale processes and the use of toxic dispersants, hindering large-scale industrial compatibility. To address this, we investigate the development of water-based LFP-integrated CF structural Li-ion batteries. Homogeneous suspensions are created using cellulose nanocrystals (CNCs) to form hybrid structures. The battery system employs LFP-modified CF as the cathode, unsized CF as the anode, and a water-based electrolyte. The LFP-CNC-graphene nanoplatelet (GNP) hybrids are coated onto CFs through immersion coating. Scanning electron microscopy (SEM) images confirm the well-dispersed and well-adhered LFP-CNC-GNP structures on the CF surface, contributing to their mechanical interlocking and electrochemical performance. The batteries demonstrate a specific energy density of 62.67 Wh/kg and a specific capacity of 72.7 mAh/g. Furthermore, the cyclic voltammetry experiments reveal the stability of the LFP-CNC-GNP-coated CF batteries over 200 cycles without degradation. This research enables the engineering of hybrid nanostructured battery laminates using novel LFP-CNC-GNP-coated CFs, opening avenues for the development of innovative Li-ion structural batteries.