摘要
为获得更高的冷却效率,采用两步法完成扇形气膜孔的几何优化。以扇形孔出口前缘长度L1、尾缘长度L2、出口宽度H和圆柱段长度Lm作为优化变量,构造第1轮拉丁超立方样本空间,通过敏感性分析得到目标函数对各优化变量的敏感度。选择高敏感度参数,生成第2轮参数的样本空间,构建Kriging代理模型,采用多岛遗传算法寻优。结果表明:L1、L2和Lm对面平均冷却效率的影响显著,敏感度很高,H的敏感度最小;通过敏感度分析对参数缩维后,可提高代理模型的预测精度;与无敏感性分析相比,经过敏感性分析后优化孔的面平均冷却效率更高,且优化结果的收敛性提高。
In order to obtain higher cooling efficiency,the two-step method was used to optimize the geometry of fan-shaped film holes.In the first step,taking the leading edge length L1,trailing edge length L2,exit width H and cylinder segment length Lmas optimization variables,the first round Latin hypercube sample space was constructed,and the sensitivity of the objective function to each optimization variable was obtained based on parameter sensitivity analysis.In the second step,high sensitive parameters were selected to generate the second round of parameter sample space,and the Kriging surrogate model was constructed.Finally,multi-island genetic algorithm was used for optimization.Results show that L1,L2 and Lmwould significantly affect surface average cooling efficiency with high sensitivity,while the sensitivity of His the least.After reducing dimension of parameters by sensitivity analysis,the prediction accuracy of the surrogate model can be improved.Surface average cooling efficiency of the optimized hole obtained by two-step method is higher than that of one-step optimization,and the convergence of the optimization results can be improved.
作者
管俊俊
张祎
张也平
鲍阿美
戴韧
GUAN Junjun;ZHANG Yi;ZHANG Yeping;BAO Amei;DAI Ren(School of Energy and Power Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;Headquarters of Shanghai Electric Power Generation Group,Shanghai 201199,China)
出处
《动力工程学报》
CAS
CSCD
北大核心
2021年第9期736-742,757,共8页
Journal of Chinese Society of Power Engineering
关键词
气膜冷却
参数优化
敏感性分析
冷却效率
film cooling
parameter optimization
sensitivity analysis
cooling efficiency
