A dynamic Gaussian process surrogate model based on the grasshopper optimization algorithm for non-probabilistic reliability analysis of complex structures-Reference-Cited by-同舟云学术

A dynamic Gaussian process surrogate model based on the grasshopper optimization algorithm for non-probabilistic reliability analysis of complex structures

Published:2023-06-26 Issue: Volume: Page:1-12
ISSN:1573-2479
Container-title:Structure and Infrastructure Engineering
language:en
Short-container-title:Structure and Infrastructure Engineering

Author:

Wang Junmu¹,Su Guoshao¹²³,Hao Junmeng¹

Affiliation:

1. Key Laboratory of Disaster Prevention and Structural Safety of Ministry of Education, School of Civil and Architecture Engineering, Guangxi University, Nanning, China

2. Guangxi Provincial Engineering Research Center of Water Security and Intelligent Control for Karst Region, Guangxi University, Nanning, China

3. Guangxi Key Laboratory of Disaster Prevention and Engineering Safety, Guangxi University, Nanning, China

Funder

National Natural Science Foundation of China

High Level Innovation Team and Outstanding Scholar Program of Universities in Guangxi Province

Interdisciplinary Scientific Research Foundation of Guangxi University

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Ocean Engineering,Geotechnical Engineering and Engineering Geology,Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15732479.2023.2225509

Reference41 articles.

1. A response-surface-based structural reliability analysis method by using non-probability convex model

2. Convex Models of Uncertainty in Radial Pulse Buckling of Shells

3. A non-probabilistic concept of reliability

4. A non-probabilistic measure of reliability of linear systems based on expansion of convex models

5. Discussion on: A non-probabilistic concept of reliability

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