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A Novel Approach to Discrete Representative Volume Element Automation and Generation-DRAGen

In this study, a novel approach for generating Representative Volume Elements (RVEs) is introduced. In contrast to common generators, the new RVE generator is based on discrete methods to reconstruct synthetic microstructures, using simple methods and a modular structure. The plain and uncomplicated...

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Detalles Bibliográficos
Autores principales: Henrich, Manuel, Pütz, Felix, Münstermann, Sebastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215640/
https://www.ncbi.nlm.nih.gov/pubmed/32316429
http://dx.doi.org/10.3390/ma13081887
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author Henrich, Manuel
Pütz, Felix
Münstermann, Sebastian
author_facet Henrich, Manuel
Pütz, Felix
Münstermann, Sebastian
author_sort Henrich, Manuel
collection PubMed
description In this study, a novel approach for generating Representative Volume Elements (RVEs) is introduced. In contrast to common generators, the new RVE generator is based on discrete methods to reconstruct synthetic microstructures, using simple methods and a modular structure. The plain and uncomplicated structure of the generator makes the extension with new features quite simple. It is discussed why certain features are essential for microstructural simulations. The discrete methods are implemented into a python tool. A Random Sequential Addition (RSA)-Algorithm for discrete volumes is developed and the tessellation is realized with a discrete tessellation function. The results show that the generator can successfully reconstruct realistic microstructures with elongated grains and martensite bands from given input data sets.
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spelling pubmed-72156402020-05-22 A Novel Approach to Discrete Representative Volume Element Automation and Generation-DRAGen Henrich, Manuel Pütz, Felix Münstermann, Sebastian Materials (Basel) Article In this study, a novel approach for generating Representative Volume Elements (RVEs) is introduced. In contrast to common generators, the new RVE generator is based on discrete methods to reconstruct synthetic microstructures, using simple methods and a modular structure. The plain and uncomplicated structure of the generator makes the extension with new features quite simple. It is discussed why certain features are essential for microstructural simulations. The discrete methods are implemented into a python tool. A Random Sequential Addition (RSA)-Algorithm for discrete volumes is developed and the tessellation is realized with a discrete tessellation function. The results show that the generator can successfully reconstruct realistic microstructures with elongated grains and martensite bands from given input data sets. MDPI 2020-04-17 /pmc/articles/PMC7215640/ /pubmed/32316429 http://dx.doi.org/10.3390/ma13081887 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
Henrich, Manuel
Pütz, Felix
Münstermann, Sebastian
A Novel Approach to Discrete Representative Volume Element Automation and Generation-DRAGen
title A Novel Approach to Discrete Representative Volume Element Automation and Generation-DRAGen
title_full A Novel Approach to Discrete Representative Volume Element Automation and Generation-DRAGen
title_fullStr A Novel Approach to Discrete Representative Volume Element Automation and Generation-DRAGen
title_full_unstemmed A Novel Approach to Discrete Representative Volume Element Automation and Generation-DRAGen
title_short A Novel Approach to Discrete Representative Volume Element Automation and Generation-DRAGen
title_sort novel approach to discrete representative volume element automation and generation-dragen
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215640/
https://www.ncbi.nlm.nih.gov/pubmed/32316429
http://dx.doi.org/10.3390/ma13081887
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