填充式防护结构弹道极限方程的差异演化优化

There are 11 parameters in the form of domestic integrated modeling of ballistic limit equations. Theoretically, the exhaustion method can be used to obtain the numerical value, but the computation time is too long and the storage space is huge, so it is not suitable to realize. To solve this problem, differential evolution algorithm is used. Based on the domestic data of stuffed Whipple shield, the differential evolution algorithm is applied to optimize 11 undetermined parameters of the formal ballistic limit equation of the integrated modeling. The optimization results show that the totality predicted rate is 82.35%, the safety predicted rate is 100%, and the average sum of squared prediction relative errors is 0.001 3. Based on 49 experimental data from other sources for predictive testing, the prediction test shows that the totality predicted rate is raised by 1.32%, the safety predicted rate is reduced by 4.08%, and the average sum of squared prediction relative errors is increased by 0.007 3. It shows that the differential evolution algorithm is suitable for solving the ba-llistic limit equation modeling of multiple parameters and multiple targets.