Robust Optimization Design of Gun Turret Structure for Lightweight

Abstract

Aiming at the structural optimization problem of a gun turret, the robust optimization model of the turret structure is established. This model takes the thickness of structural rib plate as the design variable, the minimization of the structural mass of the turret as the objective, the maximum displacement and the lowest natural frequency as the constraints. It also considers the influence of the structural instabilities and employs the 6σ robust optimization design method. The samples are obtained by the experimental design method. The radial basis function neural network is used to construct the surrogate model of the turret structure. The precision of the surrogate model is measured by the determination coefficient R2 and the Mean of Normalized Absolute Error MNAE. Finally, the robust optimization results are obtained by using the combinatorial optimization algorithm composed of Particle Swarm Optimization (PSO) algorithm and Sequential Quadratic Programming-NLPQL. The calculation results show that the 6σ robust optimization design method can effectively ensure the robustness of the optimization results. The accuracy of the radial basis function neural network surrogate model can meet the optimization requirements. The mass of structure is reduced by 9.85% after optimization.