Optimization Design of Curved Wing Box Based on BP-Multi-Objective Genetic Algorithm

To address the conflict issues among structural mass, maximum deformation, and equivalent stress in traditional lightweight design of aircraft structures, and to improve optimization efficiency while reducing complexity, a multi-objective genetic algorithm optimization mechanism based on a BP neural network surrogate model was proposed. Additionally, to explore new internal structural layouts for wings, a curved beam rib configuration was adopted. The feasibility of this method was validated using the wing box of a specific aircraft as the research subject. Compared to the original wing box, the optimization mechanism achieved an 8.16% reduction in mass, a 0.42% decrease in structural deformation, and a 12.75% reduction in maximum equivalent stress, significantly enhancing structural performance. The established optimization mechanism can serve as a reference for the lightweight design of aircraft structures.