Global Sensitivity Analysis for Stay Vane and Casing Design of Reaction Hydraulic Turbine

Hyunkyoo Cho, U. Shrestha, Young-Do Choi, Jungwan Park
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Abstract

Global sensitivity analysis (GSA) estimates influence of design variables in the entire design domain on performance measures. Hence, using GSA, important design variables could be found for an engineering application with high dimension which require computationally expensive analyses. Then, similar engineering applications could use selected variables to carry out design process with smaller dimension and affordable computational cost. In this study, GSA has been carried out for the performance measures in design of stay vane and casing of reaction hydraulic turbines. Global sensitivity index method is used for GSA because it can fully capture the effect of interaction between the design variables. For efficiency, genetic aggregation surrogate models are constructed using the responses of computational fluid dynamic (CFD) analysis. Global sensitivity indices for the performance measures of stay vane and casing have been evaluated using the surrogate models. It is found that less than three design variables among 12 are effective in the design process of stay vane and casing in reaction hydraulic turbines.
反力水轮机停留叶和机匣设计的全局敏感性分析
全局灵敏度分析(GSA)估计了整个设计域中设计变量对性能度量的影响。因此,使用GSA,可以为需要计算昂贵的分析的高维工程应用找到重要的设计变量。然后,类似的工程应用可以使用选定的变量以更小的尺寸和可承受的计算成本进行设计过程。本文对反式水轮机停留叶和机匣设计中的性能指标进行了GSA分析。由于全局灵敏度指数法能充分捕捉设计变量间相互作用的影响,因此采用全局灵敏度指数法进行GSA分析。为了提高效率,利用计算流体动力学(CFD)分析的响应构建了遗传聚集代理模型。使用代理模型对停留叶片和套管性能测量的全局敏感性指标进行了评估。结果表明,在反应式水轮机停留叶和机匣设计过程中,12个设计变量中有效的设计变量不足3个。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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