Fatigue reliability analysis of aeroengine blade-disc systems using physics-informed ensemble learning.

Li, Xue-Qin; Song, Lu-Kai; Choy, Yat-Sze; Bai, Guang-Chen

Li, Xue-Qin; Song, Lu-Kai; Choy, Yat-Sze; Bai, Guang-Chen.

Afiliación

Li XQ; School of Energy and Power Engineering, Beihang University, Beijing 102206, People's Republic of China.
Song LK; Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, People's Republic of China.
Choy YS; Research Institute of Aero-Engine, Beihang University, Beijing 100191, People's Republic of China.
Bai GC; Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, People's Republic of China.

Philos Trans A Math Phys Eng Sci ; 381(2260): 20220384, 2023 Nov 13.

Article en En | MEDLINE | ID: mdl-37742710

Palabras clave

blade-disc; low-cycle fatigue; physics-informed; reliability analysis; surrogate model

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Philos Trans A Math Phys Eng Sci Asunto de la revista: BIOFISICA / ENGENHARIA BIOMEDICA Año: 2023 Tipo del documento: Article Pais de publicación: Reino Unido

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