A blade robustness optimization platform was built based on Isight software,and with the constructed RBF neural network model and by Monte Carlo method,the robustness optimization of Rotor37 was carried out.The optimization results show that the overall performance curve moves to the left and up with nearly no change of margin,the average efficiency increases by 0.24%and 0.46%,and the variance decreases by 16.3%and 15%respectively at the two selected optimization conditions.
关键词
压气机/叶片/鲁棒性优化/RBF神经网络/蒙特卡罗方法/效率/裕度
Key words
compressor/blade/robustness optimization/RBF neural network/Monte Carlo method/efficiency/margin
维普
万方数据