A novel multi-fidelity modelling-based framework for reliability-based design optimisation of composite structures
File(s)
Published version
Author(s)
Yoo, Kwangkyu
Bacarreza, Omar
Aliabadi, MH Ferri
Type
Journal Article
Abstract
A new multi-fidelity modelling-based probabilistic optimisation framework for composite structures is presented in this paper. The multi-fidelity formulation developed herein significantly reduces the required computational time, allowing for more design variables to be considered early in the design stage. Multi-fidelity models are created by the use of finite element models, surrogate models and response correction surfaces. The accuracy and computational efficiency of the proposed optimisation methodology are demonstrated in two engineering examples of composite structures: a reliability analysis, and a reliability-based design optimisation. In these two benchmark examples, each random design variable is assigned an expected level of uncertainty. Monte Carlo Simulation (MCS), the First-Order Reliability Method (FORM) and the Second-Order Reliability Method (SORM) are used within the multi-fidelity framework to calculate the probability of failure. The reliability optimisation is a multi-objective problem that finds the optimal front, which provides both the maximum linear buckling load and minimum mass. The results show that multi-fidelity models provide high levels of accuracy while reducing computation time drastically.
Date Issued
2022-02-01
Date Acceptance
2020-06-03
Citation
Engineering with Computers: an international journal for simulation-based engineering, 2022, 38, pp.595-608
ISSN
0177-0667
Publisher
Springer
Start Page
595
End Page
608
Journal / Book Title
Engineering with Computers: an international journal for simulation-based engineering
Volume
38
Copyright Statement
© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long
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copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000539904400002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Technology
Computer Science, Interdisciplinary Applications
Engineering, Mechanical
Computer Science
Engineering
Multi-fidelity
Composites
Reliability analysis
Reliability-based design optimisation
Surrogate model
Publication Status
Published
Date Publish Online
2020-06-12