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应用自动优化方法进行大涵道比风扇叶片三维气动设计,数值最优化采用遗传算法,并利用网络通讯协议实现多CPU并行优化,大幅度缩短优化耗时.对风扇叶片型面、叶片积叠线、子午面流道、叶型安装角和叶型弦长采用基于修改量的参数化方法、结合遗传算法设计参数范围限制,以达到优化过程生成个体的可控制、合理性.采用Denton黏性体积力方法进行流场计算,较大程度减少流场计算耗时,进一步缩短优化时间.以提高设计点风扇效率、保持设计点总压比和流量不变为优化目标,并对非设计点性能进行全工况校核.通过两次不同设计参数设置的优化,最终优化风扇效率由0.9463提高到0.9560;稳定裕度由11.2%增加到21.9%.最终优化风扇叶尖处激波前马赫数略有下降,且激波向通道内倾斜,因此激波及激波造成的附面层损失下降,且稳定裕度增加.
Application of automatic optimization method for large bypass ratio three-dimensional aerodynamic design of fan blades, the numerical optimization using genetic algorithms and network communication protocol to achieve multi-CPU parallel optimization, greatly reducing the optimization time-consuming. Fan blade surface, , Meridional flow channel, leaf mounting angle and leaf chord length are based on the modified parameter-based method, combined with genetic algorithm design parameter range limits, in order to achieve the process of optimization of individual controllable and reasonable .Denton viscous volume Force method to calculate the flow field to reduce the flow field calculation time to a great extent and further shorten the optimization time.To improve the design point fan efficiency and maintain the design point total pressure ratio and flow rate unchanged for the optimization goal and to non-design point performance Through the optimization of two different design parameters, the final optimized fan efficiency increased from 0.9463 to 0.9560 and the stability margin increased from 11.2% to 21.9%. The final Mach number of the final optimized fan tip was slightly And the shock wave is inclined to the inside of the channel, the loss of the surface layer due to the shock wave and the shock wave decreases, and the stability margin increases.