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A Hybrid Level Set Method for the Topology Optimization of Functionally Graded Structures

This paper presents a hybrid level set method (HLSM) to design novelty functionally graded structures (FGSs) with complex macroscopic graded patterns. The hybrid level set function (HLSF) is constructed to parametrically model the macro unit cells by introducing the affine concept of convex optimiza...

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Detalles Bibliográficos
Autores principales: Fu, Junjian, Shu, Zhengtao, Gao, Liang, Zhou, Xiangman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9267375/
https://www.ncbi.nlm.nih.gov/pubmed/35806609
http://dx.doi.org/10.3390/ma15134483
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author Fu, Junjian
Shu, Zhengtao
Gao, Liang
Zhou, Xiangman
author_facet Fu, Junjian
Shu, Zhengtao
Gao, Liang
Zhou, Xiangman
author_sort Fu, Junjian
collection PubMed
description This paper presents a hybrid level set method (HLSM) to design novelty functionally graded structures (FGSs) with complex macroscopic graded patterns. The hybrid level set function (HLSF) is constructed to parametrically model the macro unit cells by introducing the affine concept of convex optimization theory. The global weight coefficients on macro unit cell nodes and the local weight coefficients within the macro unit cell are defined as master and slave design variables, respectively. The local design variables are interpolated by the global design variables to guarantee the C(0) continuity of neighboring unit cells. A HLSM-based topology optimization model for the FGSs is established to maximize structural stiffness. The optimization model is solved by the optimality criteria (OC) algorithm. Two typical FGSs design problems are investigated, including thin-walled stiffened structures (TWSSs) and functionally graded cellular structures (FGCSs). In addition, additively manufactured FGCSs with different core layers are tested for bending performance. Numerical examples show that the HLSM is effective for designing FGSs like TWSSs and FGCSs. The bending tests prove that FGSs designed using HLSM are have a high performance.
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spelling pubmed-92673752022-07-09 A Hybrid Level Set Method for the Topology Optimization of Functionally Graded Structures Fu, Junjian Shu, Zhengtao Gao, Liang Zhou, Xiangman Materials (Basel) Article This paper presents a hybrid level set method (HLSM) to design novelty functionally graded structures (FGSs) with complex macroscopic graded patterns. The hybrid level set function (HLSF) is constructed to parametrically model the macro unit cells by introducing the affine concept of convex optimization theory. The global weight coefficients on macro unit cell nodes and the local weight coefficients within the macro unit cell are defined as master and slave design variables, respectively. The local design variables are interpolated by the global design variables to guarantee the C(0) continuity of neighboring unit cells. A HLSM-based topology optimization model for the FGSs is established to maximize structural stiffness. The optimization model is solved by the optimality criteria (OC) algorithm. Two typical FGSs design problems are investigated, including thin-walled stiffened structures (TWSSs) and functionally graded cellular structures (FGCSs). In addition, additively manufactured FGCSs with different core layers are tested for bending performance. Numerical examples show that the HLSM is effective for designing FGSs like TWSSs and FGCSs. The bending tests prove that FGSs designed using HLSM are have a high performance. MDPI 2022-06-25 /pmc/articles/PMC9267375/ /pubmed/35806609 http://dx.doi.org/10.3390/ma15134483 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fu, Junjian
Shu, Zhengtao
Gao, Liang
Zhou, Xiangman
A Hybrid Level Set Method for the Topology Optimization of Functionally Graded Structures
title A Hybrid Level Set Method for the Topology Optimization of Functionally Graded Structures
title_full A Hybrid Level Set Method for the Topology Optimization of Functionally Graded Structures
title_fullStr A Hybrid Level Set Method for the Topology Optimization of Functionally Graded Structures
title_full_unstemmed A Hybrid Level Set Method for the Topology Optimization of Functionally Graded Structures
title_short A Hybrid Level Set Method for the Topology Optimization of Functionally Graded Structures
title_sort hybrid level set method for the topology optimization of functionally graded structures
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9267375/
https://www.ncbi.nlm.nih.gov/pubmed/35806609
http://dx.doi.org/10.3390/ma15134483
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