Modern Dimensional Analysis Involved in Polymers Additive Manufacturing Optimization
The paper aims to use Modern Dimensional Analysis (MDA) to study the polymers additive manufacturing optimization. The original part of the work is represented by the application of this nonconventional method in the field of polymers additive manufacturing. The laws of the model provide the complet...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9570554/ https://www.ncbi.nlm.nih.gov/pubmed/36235943 http://dx.doi.org/10.3390/polym14193995 |
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author | Asztalos, Zsolt Száva, Ioan Vlase, Sorin Száva, Renáta-Ildikó |
author_facet | Asztalos, Zsolt Száva, Ioan Vlase, Sorin Száva, Renáta-Ildikó |
author_sort | Asztalos, Zsolt |
collection | PubMed |
description | The paper aims to use Modern Dimensional Analysis (MDA) to study the polymers additive manufacturing optimization. The original part of the work is represented by the application of this nonconventional method in the field of polymers additive manufacturing. The laws of the model provide the complete sets of dimensionless variables, which cannot be offered by any of the classical methods (such as Geometric Analogy, Theory of Similarity, and Classical Dimensional Analysis). The validation of the method was performed experimentally. The original part of the work is represented by the application of this nonconventional method in the field of polymers additive manufacturing optimization. An application is presented and the necessary steps are analyzed one by one. |
format | Online Article Text |
id | pubmed-9570554 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95705542022-10-17 Modern Dimensional Analysis Involved in Polymers Additive Manufacturing Optimization Asztalos, Zsolt Száva, Ioan Vlase, Sorin Száva, Renáta-Ildikó Polymers (Basel) Article The paper aims to use Modern Dimensional Analysis (MDA) to study the polymers additive manufacturing optimization. The original part of the work is represented by the application of this nonconventional method in the field of polymers additive manufacturing. The laws of the model provide the complete sets of dimensionless variables, which cannot be offered by any of the classical methods (such as Geometric Analogy, Theory of Similarity, and Classical Dimensional Analysis). The validation of the method was performed experimentally. The original part of the work is represented by the application of this nonconventional method in the field of polymers additive manufacturing optimization. An application is presented and the necessary steps are analyzed one by one. MDPI 2022-09-23 /pmc/articles/PMC9570554/ /pubmed/36235943 http://dx.doi.org/10.3390/polym14193995 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 Asztalos, Zsolt Száva, Ioan Vlase, Sorin Száva, Renáta-Ildikó Modern Dimensional Analysis Involved in Polymers Additive Manufacturing Optimization |
title | Modern Dimensional Analysis Involved in Polymers Additive Manufacturing Optimization |
title_full | Modern Dimensional Analysis Involved in Polymers Additive Manufacturing Optimization |
title_fullStr | Modern Dimensional Analysis Involved in Polymers Additive Manufacturing Optimization |
title_full_unstemmed | Modern Dimensional Analysis Involved in Polymers Additive Manufacturing Optimization |
title_short | Modern Dimensional Analysis Involved in Polymers Additive Manufacturing Optimization |
title_sort | modern dimensional analysis involved in polymers additive manufacturing optimization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9570554/ https://www.ncbi.nlm.nih.gov/pubmed/36235943 http://dx.doi.org/10.3390/polym14193995 |
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