Multiobjective Optimization Method of Solid Rocket Motor Finocyl Grain Based on Surrogate Model

Abstract

To improve the performance of a solid rocket motor (SRM), a multiobjective optimal design method that can consider the structural integrity, internal ballistic performance, and loading performance of the SRM was proposed based on parametric modeling and surrogate modeling technology. Firstly, the parametric modeling technology was introduced into the field of structural integrity analysis for a high-loading SRM, based on which the influences of load and geometric parameters on the maximum von Mises strain of the SRM grain were analyzed, which effectively improved the sampling speed and prediction accuracy of the surrogate model. Combining the calculation models of the combustion surface area and volume loading fraction of the SRM, the Pareto optimal solution set was obtained based on the NSGA-II algorithm. Under the constraints of the optimization model, the maximum von Mises strain can be reduced by up to 26.72% and the volume loading fraction can be increased by up to 1.83% compared with the original. In addition, the optimal design method proposed in this paper is significantly superior in efficiency, capable of reducing both the single sampling time by more than 95% and the number of numerical simulations from 20,000 to 400, and the average prediction deviation is only 1.87%.