AI BASED INTERIOR BALLISTICS MODEL FOR A 155 MM PILOTED GUIDED AMMUNITION, EXPERIMENTAL VALIDATION AND COMPLIANCE TO STANAG 4110

Abstract

KATANA® is a 155 mm long-range, high-accuracy, precision-guided artillery projectile. Guiding ammunition requires controlling roll in flight at values much lower than those induced by the barrel rifling. A slipping band is a technical solution to meet this requirement but it results in leakages at the interface between the projectile and the barrel, making conventional interior ballistics models inaccurate. An interior ballistics model is important for several reasons during development and qualification but it is even more important for high added-value projectiles to reduce the number of rounds fired in order to establish compliance with standards such as AAS3P20 and STANAG 4110. A model based on machine learning using firing data was downselected. Experimental interior ballistics data are recorded on every firing occasion, using chamber pressure gauges and strain measurements along the barrel. This methodology is used to avoid formal SoPc firing and save projectiles.