TITLE:
Optimization Design of Curved Wing Box Based on BP-Multi-Objective Genetic Algorithm
AUTHORS:
Zechi Yu, Qi Wang
KEYWORDS:
Genetic Algorithm, Structural Optimization, Neural Network, Lightweight Design
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.15 No.4,
March
27,
2025
ABSTRACT: 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.