Parallel Numerical Simulation of 3D High-Speed Penetration Based on the SPH Method

doi:10.12382/bgxb.2025.0427

Abstract

Abstract:

Based on the Smoothed Particle Hydrodynamics (SPH) method, a parallel numerical simulation method was developed for projectile penetration into thin metal targets to address complex physical phenomena such as large deformation, damage, and fracture involved in high-velocity penetration. To accurately describe the material’s mechanical response under high-speed loading, a simplified Johnson-Cook damage model was adopted. To tackle the high computational cost caused by the rapid increase in particle numbers in SPH simulations, the computational domain was divided into subdomains, and an MPI-based CPU parallel solver was developed and implemented to exchange particle information between them. The accuracy of the numerical method in predicting residual velocity and the penetration process was validated by comparing the simulation results with experimental data from the literature. For the 8mm and 10mm thick target plates, the maximum prediction errors were 7.86% and 5.44%, respectively. A systematic evaluation of the parallel framework's acceleration performance showed a significant improvement in computational efficiency. For a medium-scale problem involving approximately 1.79 million particles, a parallel speedup efficiency of 0.76 was achieved using 54 CPU cores. While ensuring simulation accuracy, this parallel SPH framework successfully extends the computational capability to a higher order of magnitude, enabling large-scale simulations with over 100 million particles.

Key words: high-velocity penetration, smoothed particle hydrodynamics, CPU-based parallel computing, subdomain partitioning, particle migration

DENG Minjie, SONG Weidong, XIAO Lijun. Parallel Numerical Simulation of 3D High-Speed Penetration Based on the SPH Method[J]. Acta Armamentarii, 2025, 46(10): 250427-.

Figures/Tables 17

References 27

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算法1:动态负载平衡算法
1.	if (负载不平衡度>阈值){
2.	ParMetis重新图划分,生成新Cube分配方案;
3.	计算需迁移的Cube列表;
4.	for每个目标进程in迁移目标列表{
5.	打包待发送Cube数据;
6.	MPI_Isend(数据大小,目标进程, tag1, &requests); }
7.	for每个源进程in迁移源列表{
8.	MPI_Irecv(接收数据大小,源进程, tag1, &requests); }
9.	MPI_Waitall(requests);
10.	for每个目标进程in迁移目标列表{
11.	MPI_Isend(实际数据,目标进程, tag2, &requests); }
12.	for每个源进程in迁移源列表{
13.	分配接收缓冲区(根据接收大小);
14.	MPI_Irecv(实际数据,源进程, tag2, &requests); }
15.	MPI_Waitall(requests); }

算法1:动态负载平衡算法
1.	if (负载不平衡度>阈值){
2.	ParMetis重新图划分,生成新Cube分配方案;
3.	计算需迁移的Cube列表;
4.	for每个目标进程in迁移目标列表{
5.	打包待发送Cube数据;
6.	MPI_Isend(数据大小,目标进程, tag1, &requests); }
7.	for每个源进程in迁移源列表{
8.	MPI_Irecv(接收数据大小,源进程, tag1, &requests); }
9.	MPI_Waitall(requests);
10.	for每个目标进程in迁移目标列表{
11.	MPI_Isend(实际数据,目标进程, tag2, &requests); }
12.	for每个源进程in迁移源列表{
13.	分配接收缓冲区(根据接收大小);
14.	MPI_Irecv(实际数据,源进程, tag2, &requests); }
15.	MPI_Waitall(requests); }

序号	v₀/(m·s^-1)	t/mm	序号	v₀/(m·s^-1)	t/mm
1	298.0	8	11	296.0	10
2	250.8	8	12	277.5	10
3	190.7	8	13	241.5	10
4	182.2	8	14	204.0	10
5	173.7	8	15	192.9	10
6	165.2	8	16	184.9	10
7	160.7	8	17	172.6	10
8	156.0	8	18	169.3	10
9	152.5	8	19	161.2	10
10	137.4	8	20	131.3	10

序号	v₀/(m·s^-1)	t/mm	序号	v₀/(m·s^-1)	t/mm
1	298.0	8	11	296.0	10
2	250.8	8	12	277.5	10
3	190.7	8	13	241.5	10
4	182.2	8	14	204.0	10
5	173.7	8	15	192.9	10
6	165.2	8	16	184.9	10
7	160.7	8	17	172.6	10
8	156.0	8	18	169.3	10
9	152.5	8	19	161.2	10
10	137.4	8	20	131.3	10

参数	靶板	弹丸
密度ρ/(kg·m^-3)	7850	7850
弹性模量E/GPa	200	205
泊松比ν	0.33	0.33
A/MPa	490	1900
B/MPa	807	0
n	0.73	0
C	0.0114	0
k	0.94	0