基于随机规划的火炮膛内发射性能不确定性优化

Uncertain Optimization of In-bore Launching Performance ofArtillery Based on Stochastic Programming

In order to study the uncertainty optimization of the launching performance of large-caliber artillery,the internal ballistic program was compiled and embedded in ABAQUS finite element software for secondary development,and the dynamic model of in-bore launching was built. The uncertainties of the internal structure parameters of artillery,the parameters of projectile and the parameters of launching charge were completely considered,and the random characteristics were simulated through the distribution parameters. The BP neural network was used to construct the surrogate model of the in-bore launching dynamic model. Based on the Monte-Carlo simulation,the probability distribution of the uncertain constrained function was obtained,and the probability constraint function was constructed by the internal ballistic performance index. The uncertain objective function was constructed by the mean and standard deviation of initial disturbance,and the stochastic uncertainty optimization model of the launch performance was established. The multi-objective genetic algorithm was used to solve the optimization problem. The reasonable interval of the optimal solution and the uncertain parameters of the problem was obtained. The proposed method is effective.