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Acta Armamentarii ›› 2025, Vol. 46 ›› Issue (5): 240496-.doi: 10.12382/bgxb.2024.0496

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Optimization Design Method of the Supercavitating Projectile Based on BP Neural Network

GONG Shilong1, DANG Jianjun1, LI Shaoxing2, HUANG Chuang1,*()   

  1. 1 School of Marine Science and Technology,Northwestern Polytechnical University,Xi’an 710072,Shaanxi,China
    2 Military Representative Bureau of the Army Equipment Department in Xi’an,Xi’an 710032,Shaanxi,China
  • Received:2024-06-24 Online:2025-05-07
  • Contact: HUANG Chuang

Abstract:

Effective range is one of the most important performance indexes of supercavitating projectiles, which is influenced by the coupling of shape and weight parameters. In order to increase the effective range of supercavitating projectile, a numerical model for calculating the effective range of supercavitating projectiles is established, and a combination of four factors and five levels is designed according to the principle of orthogonal test design. The effective range data set of supercavitating projectiles under the influence of shape and weight parameters is obtained by simulation calculation, and an optimization method of design parameters of supercavitating projectiles is established by using BP(back propagation) neural network method and genetic algorithm, and the maximum effective range of supercavitating projectile and its corresponding shape and weight parameters are obtained. The results show that the underwater trajectory of supercavitating projectile has a stable tail beat characteristic. The mass has the greatest impact on the effective range through range analysis In the absence of precise mathematical model, the accuracy of the effective range prediction model trained by BP neural network based on limited data points is high with the average error of 0.735%. The optimal range of the whole domain under the influence of four-factors coupling is obtained by genetic algorithm. The range is improved by 5.01% compared with the best result of data set, and by 1.95% compared with the result of orthogonal optimization. The research results can providereference for the overall design of supercavitating projectile.

Key words: supercavitating projectile, orthogonal test, BP neural network, genetic algorithm

CLC Number: