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Establishing the Optimal Density of the Michell Truss Members

Topology optimization is a dynamically developing area of industrial engineering. One of the optimization tasks is to create new part shapes, while maintaining the highest possible stiffness and reliability and minimizing weight. Thanks to computer technology and 3D printers, this path of developmen...

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Autores principales: Stejskal, Tomáš, Dovica, Miroslav, Svetlík, Jozef, Demeč, Peter, Hrivniak, Lukáš, Šašala, Michal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7504592/
https://www.ncbi.nlm.nih.gov/pubmed/32883038
http://dx.doi.org/10.3390/ma13173867
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author Stejskal, Tomáš
Dovica, Miroslav
Svetlík, Jozef
Demeč, Peter
Hrivniak, Lukáš
Šašala, Michal
author_facet Stejskal, Tomáš
Dovica, Miroslav
Svetlík, Jozef
Demeč, Peter
Hrivniak, Lukáš
Šašala, Michal
author_sort Stejskal, Tomáš
collection PubMed
description Topology optimization is a dynamically developing area of industrial engineering. One of the optimization tasks is to create new part shapes, while maintaining the highest possible stiffness and reliability and minimizing weight. Thanks to computer technology and 3D printers, this path of development is becoming more and more topical. Two optimization conditions are often used in topology optimization. The first is to achieve the highest possible structure stiffness. The second is to reduce the total weight of the structure. These conditions do not have a direct effect on the number of elements in the resulting structure. This paper proposes a geometric method that modifies topological structures in terms of the number of truss elements but is not based on the optimization conditions. The method is based on natural patterns and further streamlines the optimization strategies used so far. The method’s efficiency is shown on an ideal Michell truss.
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spelling pubmed-75045922020-09-24 Establishing the Optimal Density of the Michell Truss Members Stejskal, Tomáš Dovica, Miroslav Svetlík, Jozef Demeč, Peter Hrivniak, Lukáš Šašala, Michal Materials (Basel) Article Topology optimization is a dynamically developing area of industrial engineering. One of the optimization tasks is to create new part shapes, while maintaining the highest possible stiffness and reliability and minimizing weight. Thanks to computer technology and 3D printers, this path of development is becoming more and more topical. Two optimization conditions are often used in topology optimization. The first is to achieve the highest possible structure stiffness. The second is to reduce the total weight of the structure. These conditions do not have a direct effect on the number of elements in the resulting structure. This paper proposes a geometric method that modifies topological structures in terms of the number of truss elements but is not based on the optimization conditions. The method is based on natural patterns and further streamlines the optimization strategies used so far. The method’s efficiency is shown on an ideal Michell truss. MDPI 2020-09-01 /pmc/articles/PMC7504592/ /pubmed/32883038 http://dx.doi.org/10.3390/ma13173867 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Stejskal, Tomáš
Dovica, Miroslav
Svetlík, Jozef
Demeč, Peter
Hrivniak, Lukáš
Šašala, Michal
Establishing the Optimal Density of the Michell Truss Members
title Establishing the Optimal Density of the Michell Truss Members
title_full Establishing the Optimal Density of the Michell Truss Members
title_fullStr Establishing the Optimal Density of the Michell Truss Members
title_full_unstemmed Establishing the Optimal Density of the Michell Truss Members
title_short Establishing the Optimal Density of the Michell Truss Members
title_sort establishing the optimal density of the michell truss members
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7504592/
https://www.ncbi.nlm.nih.gov/pubmed/32883038
http://dx.doi.org/10.3390/ma13173867
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