Research on Multi-objective Optimization of Aircraft NACA Inlet Air Characteristics Based on Neural Network
摘要
In this paper, the air inlet characteristics of aircraft NACA inlet are studied, and the influence rules of structural parameters of NACA inlet (throat width-height ratio \(W/dt\) , slope angle \(\alpha\) , throat feature ratio \(t/dt\) , opening length \(L\) , expansion angle \(\beta\) , etc.) on air intake mass flow rate and aerodynamic resistance are quantitatively analyzed. BP neural network is used to establish a surrogate model for predicting air inlet performance under typical working conditions. On this basis, taking the highest mass flow rate and the lowest aerodynamic resistance of NACA intake as optimization objectives, a multi-objective optimization study is carried out for the structural parameters of NACA intake, and a Pareto solution set is obtained. Based on LINMAP decision, the optimized NACA intake structural parameters are obtained (throat width-height ratio \(W/dt\) = 3.26, slope angle \(\alpha\) = 10.19°, throat feature ratio \(t/dt\) = 0.23, opening length \(L\) = 1149 mm, expansion angle \(\beta\) = 1.68°). At this time, the air inlet mass flow rate is 6.392 kg/s, and the aerodynamic resistance is 1163.4 N. This study provides a new method and idea for the optimal design of structural parameters of aircraft NACA air intakes.