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所属单位：能源与动力学院
发表刊物：Appl Therm Eng
摘要：Uncertainty on operating and manufacturing conditions for gas turbines leads to a reduced knowledge of their behavior along with high risk of unexpected failures. This study presents quantification analysis of the impacts of geometric uncertainty on film cooling performance at the blowing ratio of 0.5 and 1.5, and a classical flat-plate model with trench hole is used for test case. Four geometric parameters including fillet radiuses and deviation angles of trench are selected as uncertain inputs, and it is assumed that these inputs follow truncated Gaussian distributions. Radial basis function neural network is used for surrogate model based on the CFD (Computational fluid dynamics) calculation results, and Monte Carlo simulation is applied to investigate statistical characteristics of the outputs. The uncertain analysis results show that the increase of the blowing ratio results in the increase of uncertain degree of adiabatic film cooling effectiveness, especially in the near-filed region. Furthermore, by sensitivity analysis, the impact of fillet radius of trench-trailing corner on film cooling performance is the greatest, while the impact of deviation angle of trench-leading edge is the weakest. It illustrates that uncertainty of fillet radius of trench-trailing corner should be paid extra attention in design and manufacturing processes. © 2019
ISSN号：1359-4311
是否译文：否
发表时间：2019-01-01
合写作者：Sun, Xiaokai,张靖周
通讯作者：王春华