Multi-objective design optimization of reentrant auxetic model using Lichtenberg algorithm based on metamodel

IF 1.5 4区 工程技术 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Engineering Computations Pub Date : 2023-11-07 DOI:10.1108/ec-07-2022-0448
Matheus Francisco, João Pereira, Lucas Oliveira, Sebastião Simões Cunha, G.F. Gomes
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Abstract

Purpose The present paper aims at the multi-objective optimization of a reentrant hexagonal cell auxetic structure. In addition, a parametric analysis will be carried out to verify how each of the design factors impact each of the responses. Design/methodology/approach The multi-objective optimization of five different responses of an auxetic model was considered: mass, critical buckling load under compression effort, natural frequency, Poisson's ratio and failure load. The response surface methodology was applied, and a new meta-heuristic of optimization called the multi-objective Lichtenberg algorithm was applied to find the optimized configuration of the model. It was possible to increase the failure load by 26.75% in compression performance optimization. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively. This paper addresses something new in the scientific world to date when evaluating in a multi-objective optimization problem, the compression and modal performance of an auxetic reentrant model. Findings It was possible to find multi-objective optimized structures. It was possible to increase the critical buckling load by 42.82%, and the failure load in compression performance by 26.75%. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%, and decrease the mass by 15.97%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, increase the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively. Originality/value There is no work in the literature to date that performed the optimization of 5 responses simultaneously of a reentrant hexagonal cell auxetic structure. This paper also presents an unprecedented statistical analysis in the literature that verifies how the design factors impact each of the responses.
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基于元模型的Lichtenberg算法的可重入辅助模型多目标设计优化
目的研究可重入六边形胞体结构的多目标优化问题。此外,将进行参数分析,以验证每个设计因素如何影响每个响应。设计/方法/方法考虑了质量、压缩载荷作用下临界屈曲载荷、固有频率、泊松比和失效载荷五种不同响应的多目标优化。采用响应面法,采用一种新的元启发式优化方法——多目标Lichtenberg算法来寻找模型的优化构型。在压缩性能优化中,可以将失效载荷提高26.75%。此外,在模态性能优化中,可以将固有频率提高37.43%。最后,对同时分析的5个应答进行优化。在此情况下,临界屈曲载荷和破坏载荷分别提高42.55%和28.70%,质量和泊松比分别降低15.97%和11%。本文讨论了迄今为止科学界在多目标优化问题评估中出现的一些新问题,即辅助可重入模型的压缩和模态性能。发现可以找到多目标的优化结构。临界屈曲载荷可提高42.82%,压缩性能破坏载荷可提高26.75%。此外,在模态性能优化中,可以将固有频率提高37.43%,将质量降低15.97%。最后,对同时分析的5个应答进行优化。在此情况下,临界屈曲载荷可提高42.55%,破坏载荷可提高28.70%,质量和泊松比可分别降低15.97%和11%。到目前为止,文献中还没有对可重入的六边形细胞辅助结构同时进行5个响应的优化。本文还提出了文献中前所未有的统计分析,以验证设计因素如何影响每个响应。
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来源期刊
Engineering Computations
Engineering Computations 工程技术-工程:综合
CiteScore
3.40
自引率
6.20%
发文量
61
审稿时长
5 months
期刊介绍: The journal presents its readers with broad coverage across all branches of engineering and science of the latest development and application of new solution algorithms, innovative numerical methods and/or solution techniques directed at the utilization of computational methods in engineering analysis, engineering design and practice. For more information visit: http://www.emeraldgrouppublishing.com/ec.htm
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