The waverider forebody and Bump profile of aircraft are two classic cases reflecting the waverider idea in aircraft component design.They can effectively improve the overall aerodynamic performance of aircraft and have become the core technology of aircraft overall design.In order to seek the optimal design of the waverider forebody and Bump profile to improve the efficiency of aircraft design,an optimization design method for the waverider forebody and Bump profile is proposed in this paper.The initial waverider forebody and Bump profile are generated by the osculating cone theory and conical flow field,and the aerodynamic performance is quickly estimated by the panel method.The surrogate model established by the back-propagation(BP)neural network and genetic algorithm NSGA-II are used to optimize the waverider forebody and Bump profile quickly.The data mining method is used to analyze the flow mechanism of the waverider forebody and Bump profile.The lift-to-drag ratio and volume of the optimized waverider forebody are increased by 25.6%and 41.4%,respectively.The drag coefficient of the Bump profile is decreased by 10.9%,and the lateral pressure gradient is increased by 12.1%.The results show that the proposed optimization method can be applied to the design optimization of the waverider forebody and Bump aerodynamic profile,which has guiding significance for the optimization of the overall aerodynamic performance of the aircraft and has great potential in engineering applications.
关键词
乘波前体/Bump型面/NSGA-II/高超声速/优化研究
Key words
waverider forebody/Bump profile/NSGA-II/hypersonic velocity/optimization research
维普
万方数据