Reliability analysis method of coupling optimal importance sampling density and multi-fidelity Kriging model

• Autorzy: Xie Jiayu , Tian Zongrui , Zhi Pengpeng , Zhao Yadong

Identyfikatory

DOI

10.17531/ein/161893

• Języki publikacji: EN

Abstrakty

EN

The commonly used reliability analysis approaches for Kriging-based models are usually conducted based on high-fidelity Kriging models. However, high-fidelity surrogate models are commonly costly. Therefore, in order to balance the calculation expense and calculation time of the surrogate model, this paper proposes a multi-fidelity Kriging model reliability analysis approach with coupled optimal important sampling density (OISD+MFK). First, the MEI learning function is proposed considering the training sample distance, model computation cost, expected improvement function, and model relevance. Second, a dynamic stopping condition is proposed that takes into account the failure probability estimation error. Finally, the optimal importance sampling density is incorporated into the reliability analysis process, which can effectively reduce failure probability estimation error. The results of the study show that the approach proposed in this paper can reduce the calculation cost while outputting relatively accurate failure probability evaluation results.

Słowa kluczowe

EN

reliability analysis; multifidelity model; learning function; stopping condition

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2023
• Tom: Vol. 25, no. 2
• Strony: art. no. 161893
• Opis fizyczny: Bibliogr. 36 poz., rys., tab., wykr.

Twórcy

autor

Xie Jiayu

• Aeronautical Engineering College, Civil Aviation Flight University of China, Guanghan 618307, Sichuan, China

• https://orcid.org/0000-0002-4790-8265

autor

Tian Zongrui

• Anyang Key Laboratory of Advanced Aeronautical Materials and Processing Technology, Anyang Institute of Technology, Anyang 455099, China

• https://orcid.org/0000-0001-7225-1050

autor

Zhi Pengpeng

• Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou 313001, Zhejiang, China
• Institute of Electronic and Information Engineering in Guangdong, University of Electronic Science and Technology of China, Dongguan 523808, Guangdong, China
• School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China

• https://orcid.org/0000-0003-1537-8455

autor

Zhao Yadong

• Anyang Key Laboratory of Advanced Aeronautical Materials and Processing Technology, Anyang Institute of Technology, Anyang 455099, China
• School of Mechanical Engineering, Anyang Institute of Technology, Anyang 455099, China

• https://orcid.org/0000-0002-3774-1289

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