Robust design optimization of imperfect stiffened shells using an active learning method and a hybrid surrogate model-Reference-Cited by-同舟云学术

Robust design optimization of imperfect stiffened shells using an active learning method and a hybrid surrogate model

Published:2020-01-22 Issue:12 Volume:52 Page:2044-2061
ISSN:0305-215X
Container-title:Engineering Optimization
language:en
Short-container-title:Engineering Optimization

Author:

Meng Zeng¹^ORCID,Zhang Zhuohui¹,Zhou Huanlin¹^ORCID,Chen Hanshu¹,Yu Bo¹

Affiliation:

1. School of Civil Engineering, Hefei University of Technology, Hefei, People’s Republic of China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Anhui Province

Publisher

Informa UK Limited

Subject

Applied Mathematics,Industrial and Manufacturing Engineering,Management Science and Operations Research,Control and Optimization,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/0305215X.2019.1702978

Reference53 articles.

1. Toward a Probabilistic Preliminary Design Criterion for Buckling Critical Composite Shells

2. Collapse of axially compressed cylindrical shells with random imperfections

3. Imperfection surveys on a 10-ft-diameter shell structure

4. Robust topology optimization of structures with uncertainties in stiffness – Application to truss structures

5. Robust optimization – A comprehensive survey

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