Wing structural design of supersonic civil aircraft based on deep neural network

Abstract

At present, the research on supersonic civil aircraft wings mainly focuses on the low sonic boom design and supersonic drag reduction technologies. There are relatively few studies on the wing structural design. Therefore, a multi-level optimization method for the wing structural design in the preliminary design stage of supersonic civil aircrafts was proposed. It included the parametric modeling of the wing structural layout, the automatic generation of the finite element model for the structural size optimization, construction and training of a surrogate model for the deep neural network. And the optimization was solved based on the deep neural network. The analysis results show that the proposed optimization strategy could quickly design the wing structure of the supersonic civil aircraft. The deep neural network model has higher prediction accuracy than the traditional surrogate model. Thus, the proposed approach can improve the efficiency of the preliminary design for wing structure.

Keywords

• Supersonic civil aircraft
• Parameterization
• Deep neural network
• Surrogate model
• Structural design