Zhang Yuyi, Logachev Andrey, Smirnov Aleksandr, Kazarinov Nikita
Faculty of Mathematics and Mechanics, Saint Petersburg State University, Saint Petersburg 199034, Russia.
Research Center of Dynamics, Institute of Problems of Mechanical Engineering, Saint Petersburg 199178, Russia.
Materials (Basel). 2025 Jun 24;18(13):3001. doi: 10.3390/ma18133001.
This study considers the impact and penetration of composite targets by steel projectiles. Firstly, experiments on the impact of homogeneous polymethyl methacrylate (PMMA) targets were simulated using the finite element method (FEM) and the incubation time fracture criterion (ITFC). Next, targets were assumed to be composed of cells with weakened mechanical properties, forming a composite barrier. The composite impact problems were then used to demonstrate an approach, which can be applied to overcome the typical difficulties for impact simulations-high demands on computing resources, long computation times, and potential numerical instabilities arising from high stresses in the contact zone and high strain rates. The approach is based on the use of artificial neural networks (ANNs) trained on arrays of numerical results obtained via finite element method.
本研究考虑了钢质射弹对复合靶标的侵彻及影响。首先，采用有限元法（FEM）和孕育期断裂准则（ITFC）对均质聚甲基丙烯酸甲酯（PMMA）靶标的撞击实验进行了模拟。接下来，假设靶标由力学性能减弱的单元组成，形成一个复合屏障。然后，利用复合撞击问题来演示一种方法，该方法可用于克服撞击模拟中的典型困难——对计算资源的高要求、较长的计算时间，以及因接触区域的高应力和高应变率而产生的潜在数值不稳定性。该方法基于对通过有限元法获得的数值结果阵列进行训练的人工神经网络（ANN）的应用。
