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    Bayesian Transfer Learning–Based Aerodynamic Robust Optimization of Ultrahigh-Lift Turbine Blades

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    JAEEEZ.ASENG-6769.pdf (7.636Mb)
    Date
    2026
    Author
    Wang, Xiaojing
    Chen, Hao
    Jiang, Qifeng
    Wu, Yifei
    Yao, Lichao
    Wang, Yifan
    Zou, Zhengping
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    Abstract
    AbstractGeometric deviations can significantly degrade the aerodynamic performance of ultrahigh-lift (UHL) low-pressure turbine (LPT) blades. Conventional uncertainty quantification and robust optimization require extensive computational fluid dynamics (...Practical ApplicationsIt is impractical to enhance product robustness to manufacturing tolerances and operating variability through thousands of CFD runs or physical tests in engineering design. This study presents a Bayesian framework that can blend ...
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    http://yetl.yabesh.ir/yetl1/handle/yetl/4314197
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