Simulation and Robust Optimization Design for Electromagnetic Railgun Performance

Abstract

Energy efficiency is a critical quantity of interest in the performance of electromagnetic railgun (EMRG). To improve the energy efficiency of EMRG with the presence of uncertainty, a hybrid robust optimization method is proposed. EMRG simulation model is developed to simulate the behavior of exterior ballistics and the corresponding robust optimization issue is formulated. With the help of the impact factor analysis, several significant factors of energy efficiency are selected as the design variables while the insignificant ones are not taken into account. In the robust optimization, the polynomial chaos expansion approach coupled with Latin hypercube design is proposed to propagate the uncertainty for alleviating the computational burden of fitness function (energy efficiency) evaluation. Then, the genetic algorithm is employed to solve the EMRG energy efficiency optimization problem with the constraint of mean miss distance. The optimization results illustrate that the hybrid robust optimization method is an efficient approach to improve the energy efficiency, which can be applied in the practical application of EMRG projectile design.