Aero-Engine Inlet Vane Structure Optimization for Anti-Icing with Hot Air Film Using Neural Network and Genetic Algorithm

An improved anti-icing design with film heating ejection slot and cover for the inlet part of aero-engine was brought out, which combines the interior jet impingement with the exterior hot air film heating and shows promising application for those parts manufactured with composite materials. A hybrid method based on the combination of the Back Propagation Neural Network (BPNN) and Genetic Algorithm (GA) is developed to optimize the anti-icing design for a typical aero-engine inlet vane in two dimensions. The optimization aims to maximize the heating performance of the hot air film, which is assessed by the heating effectiveness. The film-heating ejection angle and the cover opening angle are the two geometric variables to be optimized. Numerical model was established and validated to generate training and testing samples for BPNN, which was used to predict the objective function and find the optimal design variables in conjunction with the GA. The optimal values of the film-heating ejection angle and the cover opening angle were 24.3° and 5°, respectively, which were achieved at a given heat flow rate of 0.0429 kg/s. Compared with the previous result obtained by other researchers, the film heating performance of the optimal structure in this study has been improved by 16.73%. Besides, the effects of film-heating ejection angle and cover opening angle on the heating effectiveness were further analysed. The optimal result shows that this coupled method using BPNN and GA is significantly time-efficient as well as meeting the accuracy requirements for optimization of the inlet vane.