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A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting

FEATURED APPLICATION: Mathematical tool for tuning Selective Laser Melting process parameters for achieving highly dense components. ABSTRACT: In this work, dimensional analysis is used to develop a general mathematical model to predict bulk density of SLMed components taking volumetric energy densi...

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Autores principales: Estrada-Díaz, Jorge A., Elías-Zúñiga, Alex, Martínez-Romero, Oscar, Rodríguez-Salinas, J., Olvera-Trejo, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7865268/
https://www.ncbi.nlm.nih.gov/pubmed/33494386
http://dx.doi.org/10.3390/ma14030512
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author Estrada-Díaz, Jorge A.
Elías-Zúñiga, Alex
Martínez-Romero, Oscar
Rodríguez-Salinas, J.
Olvera-Trejo, Daniel
author_facet Estrada-Díaz, Jorge A.
Elías-Zúñiga, Alex
Martínez-Romero, Oscar
Rodríguez-Salinas, J.
Olvera-Trejo, Daniel
author_sort Estrada-Díaz, Jorge A.
collection PubMed
description FEATURED APPLICATION: Mathematical tool for tuning Selective Laser Melting process parameters for achieving highly dense components. ABSTRACT: In this work, dimensional analysis is used to develop a general mathematical model to predict bulk density of SLMed components taking volumetric energy density, scanning speed, powder’s thermal conductivity, specific heat capacity, and average grain diameter as independent variables. Strong relation between dependent and independent dimensionless products is observed. Inconel 718 samples were additively manufactured and a particular expression, in the form of a power-law polynomial, for its bulk density, in the working domain of the independent dimensionless product, was obtained. It is found that with longer laser exposure time, and lower scanning speed, better densification is attained. Likewise, volumetric energy density has a positive influence on bulk density. The negative effect of laser power in bulk density is attributed to improper process conditions leading to powder particle sublimation and ejection. A maximum error percentage between experimental and predicted bulk density of 3.7119% is achieved, which corroborates the accuracy of our proposed model. A general expression for determining the scanning speed, with respect to laser power, needed to achieve highly dense components, was derived. The model’s applicability was further validated considering SLMed samples produced by AlSi10Mg and Ti6Al4V alloys. This article elucidates how to tune relevant manufacturing parameters to produce highly dense SLM parts using mathematical expressions derived from Buckingham’s π- theorem.
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spelling pubmed-78652682021-02-07 A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting Estrada-Díaz, Jorge A. Elías-Zúñiga, Alex Martínez-Romero, Oscar Rodríguez-Salinas, J. Olvera-Trejo, Daniel Materials (Basel) Article FEATURED APPLICATION: Mathematical tool for tuning Selective Laser Melting process parameters for achieving highly dense components. ABSTRACT: In this work, dimensional analysis is used to develop a general mathematical model to predict bulk density of SLMed components taking volumetric energy density, scanning speed, powder’s thermal conductivity, specific heat capacity, and average grain diameter as independent variables. Strong relation between dependent and independent dimensionless products is observed. Inconel 718 samples were additively manufactured and a particular expression, in the form of a power-law polynomial, for its bulk density, in the working domain of the independent dimensionless product, was obtained. It is found that with longer laser exposure time, and lower scanning speed, better densification is attained. Likewise, volumetric energy density has a positive influence on bulk density. The negative effect of laser power in bulk density is attributed to improper process conditions leading to powder particle sublimation and ejection. A maximum error percentage between experimental and predicted bulk density of 3.7119% is achieved, which corroborates the accuracy of our proposed model. A general expression for determining the scanning speed, with respect to laser power, needed to achieve highly dense components, was derived. The model’s applicability was further validated considering SLMed samples produced by AlSi10Mg and Ti6Al4V alloys. This article elucidates how to tune relevant manufacturing parameters to produce highly dense SLM parts using mathematical expressions derived from Buckingham’s π- theorem. MDPI 2021-01-21 /pmc/articles/PMC7865268/ /pubmed/33494386 http://dx.doi.org/10.3390/ma14030512 Text en © 2021 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
Estrada-Díaz, Jorge A.
Elías-Zúñiga, Alex
Martínez-Romero, Oscar
Rodríguez-Salinas, J.
Olvera-Trejo, Daniel
A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting
title A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting
title_full A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting
title_fullStr A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting
title_full_unstemmed A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting
title_short A Mathematical Dimensional Model for Predicting Bulk Density of Inconel 718 Parts Produced by Selective Laser Melting
title_sort mathematical dimensional model for predicting bulk density of inconel 718 parts produced by selective laser melting
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7865268/
https://www.ncbi.nlm.nih.gov/pubmed/33494386
http://dx.doi.org/10.3390/ma14030512
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