近地场景下爆炸型烟雾弹结构仿真方法

doi:10.12382/bgxb.2023.0903

摘要/Abstract

摘要：

爆炸型烟雾弹在反制红外武器、保护高价值军事目标方面具有重要意义。目前绝大多数的烟雾仿真模型未考虑到爆炸的矢量信息和近地粒子扩散效果,在壁面效应与空气湍流现象显著的近地场景下对爆炸型烟雾仿真的真实性较低。针对现有方法,在近地场景下对爆炸型烟雾弹仿真精度差的问题,提出一种近地场景下的爆炸型烟雾弹结构模型仿真方法。该方法利用粒子位置信息代替粒子模型的生命周期,以高斯烟团模型为基础,构建了基于爆弹方向和壁面效应的近地烟雾爆炸模型,以提高对近地烟雾弹爆炸场景仿真的精确性。在仿真的图像上采用结构相似度(Structural Similarity,SSIM)分析,经过最佳参数选取实验后,SSIM值达到0.9443,标准差为±0.0005。对比粒子系统-高斯烟团模型、椭球爆炸模型和爆炸型烟雾弹模型,分别高出0.0112、0.1329和0.0063。实验结果对比表明,新模型在烟雾仿真中具有明确的方向信息,对烟雾湍流和壁面效应的细节表达能力更强,对近地烟雾弹爆炸场景的仿真具有更高的精确性。

关键词: 爆炸型烟雾弹, 烟雾仿真, 粒子系统, 高斯烟团模型, 向量法

Abstract:

Explosive smoke bombs are of great significance in countering the infrared-guided weapons and protecting the high-value military targets. At present, most of the smoke simulation models do not take into account the vector information of explosion and the near-ground particle diffusion effect, and the authenticity of the explosion smoke simulation is low in the near-ground scene where the wall effect and the air turbulence phenomenon are significant. For the poor simulation accuracy of explosive smoke bomb in near-earth scene, a simulation method of explosive smoke bomb structure model in near-ground scene is proposed. This method uses the particle position information to replace the life cycle of the particle model. Based on the Gaussian puff model, a near-ground smoke explosion model considering the explosion flying direction of bomb and the wall effect is constructed to improve the simulation accuracy of near-ground smoke bomb explosion scene. The structural similarity (SSIM) analysis is used on the simulated image. After the best parameter selection experiment, the SSIM value reaches 0.9443 and the standard deviation is ±0.0005. The SSIM value of the proposed model is 0.0112, 0.1329 and 0.0063 higher than those of the particle system-Gaussian smoke model, ellipsoid explosion model and explosive smoke bomb model,respectively.The experimental results shows that the proposed model has clear direction information in smoke simulation, stronger ability to express the details of smoke turbulence and wall effect, and higher accuracy in the simulation of near-ground smoke bomb explosion scene.

Key words: explosive smoke bomb, smoke simulation, particle system, Gaussian puff model, vector method

中图分类号:

TJ417

闫鹏, 温荣臻, 盛庆红, 王博, 李俊. 近地场景下爆炸型烟雾弹结构仿真方法[J]. 兵工学报, 2024, 45(9): 3125-3134.

YAN Peng, WEN Rongzhen, SHENG Qinghong, WANG Bo, LI Jun. Structure Simulation of Explosive Smoke Bomb in Near-ground Scene[J]. Acta Armamentarii, 2024, 45(9): 3125-3134.

图/表 15

图1 粒子模型示意图

Fig.1 Schematic diagram of particle model

图2 改进生命周期后的粒子模型

Fig.2 The particle model after improving the life cycle

图3 爆炸型烟雾弹化简模型

Fig.3 Simplified model of explosive smoke bomb

表1 实验参数信息

Table 1 Experimental parameters

参数	数值
粒子位置/px	(200,200,100)
粒子数量N	3000
粒子半径r/px	40
粒子位置关系d/px	320
爆炸瞬时风速u/(px·s^-1)	1000
高斯运动协方差σ_x,σ_y,σ_z	(20,20,20)
爆弹方向n/px	(1,1,0)
时间步长Δt/s	0.02
步长总数S	50

图4 爆炸型烟雾弹近地场景结构仿真三视图

Fig.4 Three-orthographic views of explosive smoke bomb smoke model simulation

图5 参与对比的三类模型三视图

Fig.5 Three-orthographic views of three models

图6 四类模型各自的仿真结果

Fig.6 Simulated results of four types of models

表2 四类模型的SSIM评价标准比较

Table 2 Comparison of SSIM evaluation criteria for four types of models

模型	SSIM	SSIM标准差
粒子系统-高斯烟团模型	0.9335	0.0003
爆炸型烟雾弹模型	0.9389	0.0003
椭球爆炸模型	0.9347	0.0004
爆炸型烟雾弹近地场景结构仿真模型	0.9425	0.0007

表3 四类模型仿真所需的时间

Table 3 The time required for simulation of four types of models

模型	所需时间(200张图像)/s
粒子系统-高斯烟团模型	130
爆炸型烟雾弹模型	203
椭球爆炸模型	213
爆炸型烟雾弹近地场景结构仿真模型	205

图7 以时间步长为单位的SSIM折线图

Fig.7 SSIM line chart in time step

图8 最优模型参数模拟的图像

Fig.8 Images simulated by optimal model parameters

表4 最优模型参数模拟的图像SSIM值

Table 4 SSIM values simulated by the optimal model parameters

SSIM	SSIM标准差	所需时间/s
0.9443	0.0005	183

表5 最优模型参数下四类模型模拟的图像SSIM值

Table 5 Image SSIM values simulated by four types of models under the condition of optimal model parameters

模型	SSIM	SSIM标准差
粒子系统-高斯烟团模型	0.9331	0.0002
爆炸型烟雾弹模型	0.9380	0.0002
椭球爆炸模型	0.8114	0.0008
爆炸型烟雾弹近地场景结构仿真模型	0.9443	0.0005

表6 不同位置的SSIM值

Table 6 SSIM values at different locations

粒子位置/px	SSIM	SSIM标准差
(200,200,50)	0.9428	0.0005
(200,200,100)	0.9443	0.0005
(200,200,150)	0.9407	0.0008
(200,200,200)	0.9320	0.0009

表7 不同粒子数量的SSIM值

Table 7 SSIM values of different particle numbers

粒子数量	SSIM	SSIM标准差
2000	0.9384	0.0007
2500	0.9400	0.0007
3000	0.9443	0.0005
3500	0.9408	0.0009

参考文献 21

[1]	SOMAYAJULU M R, GAUTAM G K, JAYARAMAN S, et al. Studies on characterization and burning of red phosphorus-based smoke compositions[J]. Journal of Energetic Materials, 2003, 21(1):15-31.
[2]	SHAW A P, BRUSNAHAN J S, PORET J C, et al. Thermodynamic modeling of pyrotechnic smoke compositions[J]. ACS Sustainable Chemistry & Engineering, 2016, 4(4):2309-2315.
[3]	周梦得, 李佳玉. 粒径对烟幕中团聚体颗粒散射特性的影响分析[J]. 兵工学报, 2020, 41(5):975-983. doi: 10.3969/j.issn.1000-1093.2020.05.017
	ZHOU M D, LI J Y. Analysis of the scattering properties of aggregate with random-sized particles in smoke screen[J]. Acta Armamentarii, 2020, 41(5):975-983. (in Chinese) doi: 10.3969/j.issn.1000-1093.2020.05.017
[4]	周迎春, 房凌晖, 郑翔玉, 等. 基于粒子系统的虚拟战场烟雾特效仿真[J] 计算机仿真, 2015, 32(7):417-420.
	ZHOU Y C, FANG L H, ZHENG X Y, et al. Virtual battlefield smoke effects simulation based on particle system[J]. Computer Simulation, 2015, 32(7):417-420. (in Chinese)
[5]	朱静远, 马惠敏, 袁坚. 基于格子玻尔兹曼方法的涡量修正高效烟雾仿真算法[J]. 信号处理, 2020, 36(9):1390-1398.
	ZHU J Y, MA H M, YUAN J. High performance vorticity refinement smoke simulation algorithm based on lattice boltzmann method[J]. Journal of Signal Processing, 2020, 36(9):1390-1398. (in Chinese)
[6]	陈国栋, 苏志鹏, 王娜. 基于涡丝模型的烟雾仿真研究[J]. 贵州大学学报(自然科学版), 2018, 35(1):57-62.
	CHEN G D, SU Z P, WANG N. The research of smoke simulation based on vortex filament method[J]. Journal of Guizhou University(Natural Sciences), 2018, 35(1):57-62. (in Chinese)
[7]	吴冀川, 余洋, 赵剑衡. 微创手术过程中的手术烟雾仿真[J]. 太赫兹科学与电子信息学报, 2020, 18(5):896-901.
	WU J C, YU Y, ZHAO J H. Physics-based simulation of surgical smoke during minimally invasive surgery[J]. Journal of Terahertz Science and Electronic Information Technology, 2020, 18(5):896-901. (in Chinese)
[8]	邹宁, 周飞, 韩庆阳, 等. 基于室内环境下火焰烟雾扩散和仿真模拟研究[J]. 无线互联科技, 2018, 15(9):111-112.
	ZOU N, ZHOU F, HAN Q Y, et al. Research on flame smoke diffusion and simulation in indoor environment[J]. Wireless Internet Technology, 2018, 15(9):111-112. (in Chinese)
[9]	汪继文, 杨贤达. 基于物理模型的实时烟雾模拟[J]. 计算机技术与发展, 2014, 24(1):122-125.
	WANG J W, YANG X D. Real-time smoke simulation based on physics model[J]. Computer Technolocy and Development, 2014, 24(1):122-125. (in Chinese)
[10]	张作宇, 廖守亿, 张金城, 等. 基于物理模型的战场烟幕实时红外仿真[J]. 红外与激光工程, 2016, 45(4):116-123.
	ZHANG Z Y, LIAO S Y, ZHANG J C, et al. Real-time battlefield smoke IR simulation based on physical model[J]. Infrared and Laser Engineering, 2016, 45(4):116-123. (in Chinese)
[11]	李宏宁, 白廷柱, 王贺, 等. 用于场景仿真的红外烟幕模型及其特性分析[J]. 系统仿真学报, 2011, 23(10):2248-2253.
	LI H N, BAI T Z, WANG H, et al. Smoke model for infrared scene imaging simulation and characteristic analysis[J]. Journal of System Simulation, 2011, 23(10):2248-2253.( in Chinese)
[12]	杨尚贤, 陈慧敏, 高丽娟, 等. 发烟罐烟雾质量浓度时空分布特性[J]. 兵工学报, 2020, 41(9):1772-1782.
	YANG S X, CHEN H M, GAO L J, et al. Spatiotemporal distribution characteristics of smoke mass concentration of smoke pot[J]. Acta Armamentarii, 2020, 41(9):1772-1782. (in Chinese) doi: 10.3969/j.issn.1000-1093.2020.09.009
[13]	曹力子, 张志刚, 葛涛, 等. 烟幕扩散与遮蔽效能的动态仿真研究[J]. 兵器装备工程学报, 2022, 43(8):223-229.
	CAO L Z, ZHANG Z G, GE T, et al. Study on dynamic simulation of smoke diffusion and obscuring efficiency[J]. Journal of Ordnance Equipment Engineering, 2022, 43(8):223-229. (in Chinese)
[14]	王志刚, 郭三学. 催泪弹非致命效能分析计算[J]. 兵工学报, 2017, 38(1):59-63. doi: 10.3969/j.issn.1000-1093.2017.01.008
	WANG Z G, GUO S X. Analysis and calculation of non-lethal efficiency of tear bomb[J]. Acta Armamentarii, 2017, 38(1):59-63. (in Chinese)
[15]	马超, 陈慧敏, 王凤杰, 等. 基于高斯烟团模式的爆炸烟雾浓度分布特性仿真[J]. 制导与引信, 2017, 38(3):4-9.
	MA C, CHEN H M, WANG F J, et al. Simulation of explosive smoke concentration distribution characteristic based on Gaussian puff model[J]. Guidance & Fuze, 2017, 38(3):4-9. (in Chinese)
[16]	何宁, 吴宗之, 郑伟. 一种改进的有毒气体扩散高斯模型算法及仿真(英文)[J]. 应用基础与工程科学学报, 2010, 18(4):571-580.
	HE N, WU Z Z, ZHENG W. Simulation of an improved Gaussian model for hazardous gas diffusion[J]. Journal of Basic Science and Engineering, 2010, 18(4):571-580. (in Chinese)
[17]	陈欣星, 黄剑. 基于粒子滤波的烟雾羽流路径追踪算法[J]. 华中科技大学学报(自然科学版), 2020, 48(1):66-70.
	CHEN X X, HUANG J. Particle filter-based algorithm for smoke plume path tracking[J]. Journal of Huazhong Universityof Science & Technology(Natural Science Edition), 2020, 48(1):66-70. (in Chinese)
[18]	唐勇, 甄志华, 汪新宇, 等. 烟雾扩散与气体污染的动态仿真研究[J]. 燕山大学学报, 2021, 45(6):523-528.
	TANG Y, ZHEN Z H, WANG X Y, et al. Dynamic simulation of smoke diffusion and gas pollution[J]. Journal of Yanshan University, 2021, 45(6):523-528. (in Chinese)
[19]	王志刚, 郭三学. 基于高斯扩散模型的催泪弹气溶胶烟雾非致命效能仿真[J]. 含能材料, 2019, 27(2):113-118.
	WANG Z G, GUO S X. Simulation of non-lethal efficiency of tear bomb aerosol smoke based on Gaussian diffusion model[J]. Chinese Journal of Energetic Materials, 2019, 27(2):113-118. (in Chinese)
[20]	徐路程, 郝雪颖, 肖凯涛, 等. 爆炸型烟幕弹遮蔽效能仿真研究[J]. 兵工学报, 2020, 41(7):1299-1306. doi: 10.3969/j.issn.1000-1093.2020.07.006
	XU L C, HAO X Y, XIAO K T, et al. Simulation study of screening efficiency of explosive smoke bomb[J]. Acta Armamentarii, 2020, 41(7):1299-1306. (in Chinese) doi: 10.3969/j.issn.1000-1093.2020.07.006
[21]	秦军超, 宋磊. 基于粒子系统的气垫船气液介质特效仿真[J]. 信息通信, 2018(2):17-18.
	QIN J C, SONG L. Special effect simulation of gas-liquid medium of hovercraft based on particle system[J]. Information & Communications, 2018(2):17-18. (in Chinese)