单兵武器协同仿真与系统优化设计研究
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摘要
以单兵综合作战系统武器分系统为研究对象,针对其研制过程中涉及多个学科领域知识的特点,从系统角度出发,运用协同仿真与多学科设计优化等现代设计理论与方法,对其展开研究。
结合单兵武器系统的战术技术要求,从结构、弹道和动力学三个方面对单兵武器系统进行多学科分解,将其分解为榴弹结构、武器结构、内弹道、外弹道、终点弹道、武器自动机动力学、弹丸-身管耦合运动、人枪相互作用等八个学科,结合各学科领域的知识,建立了各单学科仿真分析模型；在此基础上,为从全局角度对单兵武器系统的整体性能进行研究,构建了单兵武器系统协同仿真与多学科设计优化框架。
对多学科设计优化搜索策略展开研究,重点研究了遗传算法,为提高其优化效率,对遗传算法的并行性进行了研究,并对其交叉和变异算子进行了自适应改造,结合免疫学理论,在遗传算法中引入了免疫算子,形成了自适应并行免疫遗传算法。运用该算法对三个复杂多峰函数进行了优化求解,在保证收敛精度的情况下,大幅提高了收敛速度。
根据单兵武器系统协同仿真框架,基于协同仿真理论与方法,建立了单兵武器系统全弹道协同仿真、弹道-武器协同仿真和人枪系统协同仿真三个模型。对各协同仿真模型进行了仿真研究与参数影响分析,将仿真结果与试验结果进行对比,验证了单兵武器系统各协同仿真模型的有效性及准确性。
根据单兵武器系统多学科设计优化框架,针对单兵步榴合一武器发射的小口径榴弹,建立了包含榴弹结构、内弹道、外弹道、终点弹道和武器动力学五个学科的小口径榴弹多学科设计优化模型,分别以最大杀伤面积、弹丸最短飞行时间、杀伤威力与武器后坐力的综合性能为优化目标,对其进行了多学科设计优化研究,与原设计相比,优化设计后榴弹性能目标性能得到显著提高。对杀伤威力和武器后坐力综合性能进行优化设计时,分别采用了模拟退火算法和自适应并行免疫遗传算法,从优化结果上看,自适应并行免疫遗传算法寻优能力及寻优效率更强。
建立了弹丸在膛内运动的弹丸-身管耦合运动参数化有限元仿真模型,验证了该模型的有效性和正确性；考虑到弹丸-身管耦合运动模型在进行优化求解时的计算效率,基于正交试验设计构建了弹丸-身管耦合运动的Kriging近似模型。建立了包含内弹道、身管质量、身管强度和弹丸-身管耦合运动四个学科的弹丸-身管耦合系统多学科设计优化模型,以身管质量最轻以及弹丸在膛内运动时期身管纵向振动角速度最小为优化目标,对其进行了优化研究,获得了弹丸-身管耦合系统的优化方案。
针对武器发射时人枪间的相互作用,建立了包含武器结构、内弹道、外弹道和人枪相互作用的单兵人枪系统多学科设计优化模型,以武器质量最轻、弹丸飞行时间最短及人枪相互作用力最小为优化目标,分别对其进行了单目标和多目标的优化设计,与原设计相比,优化后单兵人枪系统的目标性能得到有效提高。对比单目标和多目标优化结果,多目标优化结果避免了因某个目标性能的优化而导致其它性能严重劣化的现象。
开发了单兵武器协同仿真与系统优化设计软件平台,对单兵武器系统研制中涉及的各仿真与优化模型、支撑软件进行了集成和封装；基于网络与数据库技术,实现了各设计参数与模型的统一管理,以及各设计终端之间的分布式运行。该软件平台为单兵武器系统设计人员提供了实用、简便、高效、安全的设计支撑环境,提升了其建模、仿真与优化的能力。
The research and development process of the weapon subsystem which belongs to integrated individual solider combat system involves multiple disciplinary knowledge. In allusion to the characteristic, the individual weapon system is studied from the perspective of system, using the modern design theory and method of collaborative simulation and multidisciplinary design optimization(MDO).
Combined with the tactical and technical requirements, and from the three aspects of structure, ballistics, dynamics, the individual weapon system is decomposed into eight disciplinary fields, which are grenade structure, weapon structure, interior ballistics, exterior ballistics, terminal ballistics, automatic mechanism dynamics, projectile-barrel dynamics and human-gun interaction. The single field simulation models are build according to their own knowledge. On this basis, in order to study the overall performance of the individual weapon system for the global perspective, the framework of collaborative simulation and MDO is build.
The search strategy of MDO and especially the genetic algorithm(GA) is studied. In order to improve the optimization efficiency of GA, some improvement measures are taken, and the adaptive parallel immune genetic algorithm(APIGA) is proposed. The algorithm is parallelized and the crossover and mutation operator are adaptively changed during the optimization. Combined with the immunology theory, the immune operator is brought into the algorithm. With the APIGA, three complex multimodal function are optimized. The results show that the convergence rate is greatly improved under the condition of enough convergence precision.
Based on the collaborative simulation framework of individual weapon system and the collaborative simulation theory and method, the simulation models of the whole trajectory, trajectory-weapon system and human-gun system are built. The simulation models are executed and the effects of design parameters are analyzed. The validity and accuracy of the collaborative simulation models are verified by comparing the simulation and experimental results.
According to the MDO framework of individual weapon system, the optimization model of small caliber grenade which involves structure, interior ballistics, exterior ballistics, terminal ballistics and dynamics is set up. Separately aimed at the maximum lethal power, the minimum time of the grenade flying, the combination properties of lethal power and recoil force, the model is optimized and the target performances enhanced remarkably after the optimization compared to the original design. The simulated annealing algorithm and APIGA are used respectively when the combination properties of lethal power and recoil force is optimized. Judging from the optimization results, the optimization ability and efficiency of the APIGA is much better.
To study the process of the projectile moving inner the barrel, the parametric dynamics finite element model of projectile-barrel is built, and it's validity and accuracy is verified. Considering the compute efficiency of the optimization which contains the finite element model, the Kriging approximation model of the projectile-barrel dynamics model is built based on the orthogonal designs. The MDO model of projectile-barrel coupling system which involves interiors ballistics, barrel mass, barrel strength and projectile-barrel dynamics model is set up. Aiming at the lightest mass and the minimum angular velocity of barrel vertical vibration, the model is optimized and the optimal scheme of the system is obtained.
In allusion to the interaction of human and gun when the weapon is firing, the MDO model of human-gun system which involves weapon structure, interior ballistics, exterior ballistics and interaction of human-gun is build. Considering the minimum recoil force, the lightest mass and the shortest time of the bullet flying as the objectives, single objective and multi-objectives optimization are carried out. In comparison with the original design, the performance of the individual weapon system is improved efficiently after the optimization. Compared to the single objective optimization, the multi-objective optimization avoids the phenomenon that a single objective is optimized and the others are degraded seriously simultaneously.
The collaborative simulation and MDO platform is developed. All the simulation&optimization models, and the supporting software are integrated and packaged in the platform. Based on the technique of network and database, the design parameters and the models are managed unified and the design terminals are distributed performed. The platform provides a practical, convenient, efficiency and safe design supporting environment, and it improves the modeling, simulation and optimization ability of the designers.
结合单兵武器系统的战术技术要求,从结构、弹道和动力学三个方面对单兵武器系统进行多学科分解,将其分解为榴弹结构、武器结构、内弹道、外弹道、终点弹道、武器自动机动力学、弹丸-身管耦合运动、人枪相互作用等八个学科,结合各学科领域的知识,建立了各单学科仿真分析模型；在此基础上,为从全局角度对单兵武器系统的整体性能进行研究,构建了单兵武器系统协同仿真与多学科设计优化框架。
对多学科设计优化搜索策略展开研究,重点研究了遗传算法,为提高其优化效率,对遗传算法的并行性进行了研究,并对其交叉和变异算子进行了自适应改造,结合免疫学理论,在遗传算法中引入了免疫算子,形成了自适应并行免疫遗传算法。运用该算法对三个复杂多峰函数进行了优化求解,在保证收敛精度的情况下,大幅提高了收敛速度。
根据单兵武器系统协同仿真框架,基于协同仿真理论与方法,建立了单兵武器系统全弹道协同仿真、弹道-武器协同仿真和人枪系统协同仿真三个模型。对各协同仿真模型进行了仿真研究与参数影响分析,将仿真结果与试验结果进行对比,验证了单兵武器系统各协同仿真模型的有效性及准确性。
根据单兵武器系统多学科设计优化框架,针对单兵步榴合一武器发射的小口径榴弹,建立了包含榴弹结构、内弹道、外弹道、终点弹道和武器动力学五个学科的小口径榴弹多学科设计优化模型,分别以最大杀伤面积、弹丸最短飞行时间、杀伤威力与武器后坐力的综合性能为优化目标,对其进行了多学科设计优化研究,与原设计相比,优化设计后榴弹性能目标性能得到显著提高。对杀伤威力和武器后坐力综合性能进行优化设计时,分别采用了模拟退火算法和自适应并行免疫遗传算法,从优化结果上看,自适应并行免疫遗传算法寻优能力及寻优效率更强。
建立了弹丸在膛内运动的弹丸-身管耦合运动参数化有限元仿真模型,验证了该模型的有效性和正确性；考虑到弹丸-身管耦合运动模型在进行优化求解时的计算效率,基于正交试验设计构建了弹丸-身管耦合运动的Kriging近似模型。建立了包含内弹道、身管质量、身管强度和弹丸-身管耦合运动四个学科的弹丸-身管耦合系统多学科设计优化模型,以身管质量最轻以及弹丸在膛内运动时期身管纵向振动角速度最小为优化目标,对其进行了优化研究,获得了弹丸-身管耦合系统的优化方案。
针对武器发射时人枪间的相互作用,建立了包含武器结构、内弹道、外弹道和人枪相互作用的单兵人枪系统多学科设计优化模型,以武器质量最轻、弹丸飞行时间最短及人枪相互作用力最小为优化目标,分别对其进行了单目标和多目标的优化设计,与原设计相比,优化后单兵人枪系统的目标性能得到有效提高。对比单目标和多目标优化结果,多目标优化结果避免了因某个目标性能的优化而导致其它性能严重劣化的现象。
开发了单兵武器协同仿真与系统优化设计软件平台,对单兵武器系统研制中涉及的各仿真与优化模型、支撑软件进行了集成和封装；基于网络与数据库技术,实现了各设计参数与模型的统一管理,以及各设计终端之间的分布式运行。该软件平台为单兵武器系统设计人员提供了实用、简便、高效、安全的设计支撑环境,提升了其建模、仿真与优化的能力。
The research and development process of the weapon subsystem which belongs to integrated individual solider combat system involves multiple disciplinary knowledge. In allusion to the characteristic, the individual weapon system is studied from the perspective of system, using the modern design theory and method of collaborative simulation and multidisciplinary design optimization(MDO).
Combined with the tactical and technical requirements, and from the three aspects of structure, ballistics, dynamics, the individual weapon system is decomposed into eight disciplinary fields, which are grenade structure, weapon structure, interior ballistics, exterior ballistics, terminal ballistics, automatic mechanism dynamics, projectile-barrel dynamics and human-gun interaction. The single field simulation models are build according to their own knowledge. On this basis, in order to study the overall performance of the individual weapon system for the global perspective, the framework of collaborative simulation and MDO is build.
The search strategy of MDO and especially the genetic algorithm(GA) is studied. In order to improve the optimization efficiency of GA, some improvement measures are taken, and the adaptive parallel immune genetic algorithm(APIGA) is proposed. The algorithm is parallelized and the crossover and mutation operator are adaptively changed during the optimization. Combined with the immunology theory, the immune operator is brought into the algorithm. With the APIGA, three complex multimodal function are optimized. The results show that the convergence rate is greatly improved under the condition of enough convergence precision.
Based on the collaborative simulation framework of individual weapon system and the collaborative simulation theory and method, the simulation models of the whole trajectory, trajectory-weapon system and human-gun system are built. The simulation models are executed and the effects of design parameters are analyzed. The validity and accuracy of the collaborative simulation models are verified by comparing the simulation and experimental results.
According to the MDO framework of individual weapon system, the optimization model of small caliber grenade which involves structure, interior ballistics, exterior ballistics, terminal ballistics and dynamics is set up. Separately aimed at the maximum lethal power, the minimum time of the grenade flying, the combination properties of lethal power and recoil force, the model is optimized and the target performances enhanced remarkably after the optimization compared to the original design. The simulated annealing algorithm and APIGA are used respectively when the combination properties of lethal power and recoil force is optimized. Judging from the optimization results, the optimization ability and efficiency of the APIGA is much better.
To study the process of the projectile moving inner the barrel, the parametric dynamics finite element model of projectile-barrel is built, and it's validity and accuracy is verified. Considering the compute efficiency of the optimization which contains the finite element model, the Kriging approximation model of the projectile-barrel dynamics model is built based on the orthogonal designs. The MDO model of projectile-barrel coupling system which involves interiors ballistics, barrel mass, barrel strength and projectile-barrel dynamics model is set up. Aiming at the lightest mass and the minimum angular velocity of barrel vertical vibration, the model is optimized and the optimal scheme of the system is obtained.
In allusion to the interaction of human and gun when the weapon is firing, the MDO model of human-gun system which involves weapon structure, interior ballistics, exterior ballistics and interaction of human-gun is build. Considering the minimum recoil force, the lightest mass and the shortest time of the bullet flying as the objectives, single objective and multi-objectives optimization are carried out. In comparison with the original design, the performance of the individual weapon system is improved efficiently after the optimization. Compared to the single objective optimization, the multi-objective optimization avoids the phenomenon that a single objective is optimized and the others are degraded seriously simultaneously.
The collaborative simulation and MDO platform is developed. All the simulation&optimization models, and the supporting software are integrated and packaged in the platform. Based on the technique of network and database, the design parameters and the models are managed unified and the design terminals are distributed performed. The platform provides a practical, convenient, efficiency and safe design supporting environment, and it improves the modeling, simulation and optimization ability of the designers.
引文
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