Bayesian Transfer Learning–Based Aerodynamic Robust Optimization of Ultrahigh-Lift Turbine BladesSource: Journal of Aerospace Engineering:;2026:;Volume ( 039 ):;issue: 004::page 04026018-1Author:Wang, Xiaojing
,
Chen, Hao
,
Jiang, Qifeng
,
Wu, Yifei
,
Yao, Lichao
,
Wang, Yifan
,
Zou, Zhengping
DOI: 10.1061/JAEEEZ.ASENG-6769Publisher: American Society of Civil Engineers
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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| contributor author | Wang, Xiaojing | |
| contributor author | Chen, Hao | |
| contributor author | Jiang, Qifeng | |
| contributor author | Wu, Yifei | |
| contributor author | Yao, Lichao | |
| contributor author | Wang, Yifan | |
| contributor author | Zou, Zhengping | |
| date accessioned | 2026-08-20T21:15:43Z | |
| date available | 2026-08-20T21:15:43Z | |
| date copyright | 2026/04/08 | |
| date issued | 2026 | |
| identifier other | JAEEEZ.ASENG-6769.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314197 | |
| description 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 ... | |
| publisher | American Society of Civil Engineers | |
| title | Bayesian Transfer Learning–Based Aerodynamic Robust Optimization of Ultrahigh-Lift Turbine Blades | |
| type | Journal Article | |
| journal volume | 39 | |
| journal issue | 4 | |
| journal title | Journal of Aerospace Engineering | |
| identifier doi | 10.1061/JAEEEZ.ASENG-6769 | |
| journal fristpage | 04026018-1 | |
| journal lastpage | 04026018-15 | |
| page | 15 | |
| tree | Journal of Aerospace Engineering:;2026:;Volume ( 039 ):;issue: 004 | |
| contenttype | Fulltext |