Probabilistic-based combined high and low cycle fatigue assessment for turbine blades using a substructure-based kriging surrogate model

Hai-Feng Gao; Enrico Zio; Anjenq Wang; Guang-Chen Bai; Cheng-Wei Fei

doi:10.1016/j.ast.2020.105957

Journal articles

Probabilistic-based combined high and low cycle fatigue assessment for turbine blades using a substructure-based kriging surrogate model

Hai-Feng Gao Enrico Zio ¹ Anjenq Wang Guang-Chen Bai Cheng-Wei Fei

1 CRC - Centre de recherche sur les Risques et les Crises

Document type :

Journal articles

Domain :

Engineering Sciences [physics]

Humanities and Social Sciences / Crisis and risk management

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Submitted on : Wednesday, February 10, 2021 - 11:41:52 AM
Last modification on : Friday, February 12, 2021 - 3:05:51 AM

Probabilistic-based combined high and low cycle fatigue assessment for turbine blades using a substructure-based kriging surrogate model

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Probabilistic-based combined high and low cycle fatigue assessment for turbine blades using a substructure-based kriging surrogate model

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