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Research on 3D-Print Design Method of Spatial Node Topology Optimization Based on Improved Material Interpolation

Designing a high-strength node is significant for space structures. Topological optimization can optimally allocate the material distribution of components to meet performance requirements. Although the material distribution after topology optimization is optimum, the structure becomes complicated t...

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Autores principales: Wang, Xianjie, Zhang, Fan, Zhao, Yang, Wang, Zhaoyi, Zhou, Guangen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182439/
https://www.ncbi.nlm.nih.gov/pubmed/35683174
http://dx.doi.org/10.3390/ma15113874
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author Wang, Xianjie
Zhang, Fan
Zhao, Yang
Wang, Zhaoyi
Zhou, Guangen
author_facet Wang, Xianjie
Zhang, Fan
Zhao, Yang
Wang, Zhaoyi
Zhou, Guangen
author_sort Wang, Xianjie
collection PubMed
description Designing a high-strength node is significant for space structures. Topological optimization can optimally allocate the material distribution of components to meet performance requirements. Although the material distribution after topology optimization is optimum, the structure becomes complicated to manufacture. By using additive manufacturing technology, this problem can be well solved. At present, both topology optimization technology and additive manufacturing technology are quite mature, but their application in the design of spatial nodes is very recent and less researched. This paper involves the study and improvement of the node optimization design–manufacturing integrated method. This study used the BESO optimization algorithm as the research algorithm. Through a reasonable improvement of the material interpolation method, the algorithm’s dependence on the experience of selecting the material penalty index P was reduced. On this basis, the secondary development was carried out, and a multisoftware integration was carried out for optimization and manufacturing. The spatial node was taken as the research object, and the calculation results of the commercial finite element software were compared. The comparison showed that the algorithm used in this paper was better. Not only was it not trapped in a local optimum, but the maximum stress was also lower. In addition, this paper proposed a practical finite element geometric model extraction method and smoothing of the optimized nodes, completing the experiment of the additive manufacturing forming of the nodes. It provides ideas for processing jagged edges brought by the BESO algorithm. This paper verified the feasibility of the multisoftware integration method of optimized manufacturing.
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spelling pubmed-91824392022-06-10 Research on 3D-Print Design Method of Spatial Node Topology Optimization Based on Improved Material Interpolation Wang, Xianjie Zhang, Fan Zhao, Yang Wang, Zhaoyi Zhou, Guangen Materials (Basel) Article Designing a high-strength node is significant for space structures. Topological optimization can optimally allocate the material distribution of components to meet performance requirements. Although the material distribution after topology optimization is optimum, the structure becomes complicated to manufacture. By using additive manufacturing technology, this problem can be well solved. At present, both topology optimization technology and additive manufacturing technology are quite mature, but their application in the design of spatial nodes is very recent and less researched. This paper involves the study and improvement of the node optimization design–manufacturing integrated method. This study used the BESO optimization algorithm as the research algorithm. Through a reasonable improvement of the material interpolation method, the algorithm’s dependence on the experience of selecting the material penalty index P was reduced. On this basis, the secondary development was carried out, and a multisoftware integration was carried out for optimization and manufacturing. The spatial node was taken as the research object, and the calculation results of the commercial finite element software were compared. The comparison showed that the algorithm used in this paper was better. Not only was it not trapped in a local optimum, but the maximum stress was also lower. In addition, this paper proposed a practical finite element geometric model extraction method and smoothing of the optimized nodes, completing the experiment of the additive manufacturing forming of the nodes. It provides ideas for processing jagged edges brought by the BESO algorithm. This paper verified the feasibility of the multisoftware integration method of optimized manufacturing. MDPI 2022-05-29 /pmc/articles/PMC9182439/ /pubmed/35683174 http://dx.doi.org/10.3390/ma15113874 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
Wang, Xianjie
Zhang, Fan
Zhao, Yang
Wang, Zhaoyi
Zhou, Guangen
Research on 3D-Print Design Method of Spatial Node Topology Optimization Based on Improved Material Interpolation
title Research on 3D-Print Design Method of Spatial Node Topology Optimization Based on Improved Material Interpolation
title_full Research on 3D-Print Design Method of Spatial Node Topology Optimization Based on Improved Material Interpolation
title_fullStr Research on 3D-Print Design Method of Spatial Node Topology Optimization Based on Improved Material Interpolation
title_full_unstemmed Research on 3D-Print Design Method of Spatial Node Topology Optimization Based on Improved Material Interpolation
title_short Research on 3D-Print Design Method of Spatial Node Topology Optimization Based on Improved Material Interpolation
title_sort research on 3d-print design method of spatial node topology optimization based on improved material interpolation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182439/
https://www.ncbi.nlm.nih.gov/pubmed/35683174
http://dx.doi.org/10.3390/ma15113874
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