Enriching IRA for nonlinear and low-probability failure problems: The active learning Kriging-based inverse reliability analyses-Reference-Cited by-同舟云学术

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Enriching IRA for nonlinear and low-probability failure problems: The active learning Kriging-based inverse reliability analyses

Published:2023-12-27 Issue: Volume: Page:1-16
ISSN:1537-6494
Container-title:Mechanics of Advanced Materials and Structures
language:en
Short-container-title:Mechanics of Advanced Materials and Structures

Author:

Zhang Hairui¹,Wang Yao¹,Wang Hao¹,Hong Dongpao¹,Yang Song¹,Liu Yuanda¹,Zhao Yanlin²³^ORCID

Affiliation:

1. China Academy of Launch Vehicle Technology, Beijing, China ;

2. University of Science and Technology Beijing, School of Mechanical Engineering, Beijing, China

3. Shunde Innovation School, University of Science and Technology Beijing, Guangzhou, China

Funder

Guangdong Basic and Applied Basic Research Foundation

Fundamental Research Founds for the Central Universities

International Communication Foundation of the University of Science and Technology Beijing

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science,General Mathematics,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15376494.2023.2297397

Reference33 articles.

1. First order reliability method for time-variant problems using series expansions

2. B. Keshtegar, Limited Conjugate Gradient Method for Structural Reliability Analysis, Springer, London, 2017.

3. Probabilistic sensitivity analysis for novel second-order reliability method (SORM) using generalized chi-squared distribution

4. Stochastic configuration network for structural reliability analysis;Li S.;Mech. Adv. Mater. Struct,2023

5. Structural system reliability analysis based on multi-modal optimization and saddlepoint approximation

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