Optimization design of shaped charge based on improved genetic algorithm

• Published in: IOP conference series. Materials Science and Engineering Vol. 1043; no. 4; pp. 42034 - 42040
• Main Authors: Tang, Cheng, Xue, Biao, Wang, Li-Xia
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.01.2021
• Subjects: Charge efficiency; Crossovers; Design improvements; Design optimization; Genetic algorithms; Mathematical analysis; Optimization
• ISSN: 1757-8981; 1757-899X
• DOI: 10.1088/1757-899X/1043/4/042034

In order to improve the design efficiency of shaped charge, reduce the number of tests and shorten the development period, an improved genetic algorithm is introduced in the design process of shaped charge. Compared with the design scheme in the iterative process of traditional optimization design, the improved genetic algorithm introduces the multi parent crossover operator, randomly selects N individuals, forms the subspace, and hybridizes N individuals in the subspace to form a new individual. Because of the number of individuals involved in the hybridization, it is easier to calculate the optimal solution, and has stronger optimization ability. Taking a shaped charge as an example, the structural parameters of shaped charge are optimized by the improved genetic algorithm. After the optimization, it is verified by the vertical static armor breaking test of shaped charge, The results show that the optimization design method of shaped charge structure based on the improved genetic algorithm is reasonable and feasible, and the operational and technical indexes of the optimization scheme meet the requirements.