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A Fast Prediction Model for Liquid Metal Transfer Modes during the Wire Arc Additive Manufacturing Process
The liquid metal transfer mode in wire arc additive manufacturing (WAAM), plays an important role in determining the build quality. In this study, a fast prediction model based on the Young–Laplace equation, momentum equation, and energy conservation, is proposed, to identify the metal transfer mode...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10096320/ https://www.ncbi.nlm.nih.gov/pubmed/37049203 http://dx.doi.org/10.3390/ma16072911 |
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author | Ouyang, Jiaqi Li, Mingjian Lian, Yanping Peng, Siyi Liu, Changmeng |
author_facet | Ouyang, Jiaqi Li, Mingjian Lian, Yanping Peng, Siyi Liu, Changmeng |
author_sort | Ouyang, Jiaqi |
collection | PubMed |
description | The liquid metal transfer mode in wire arc additive manufacturing (WAAM), plays an important role in determining the build quality. In this study, a fast prediction model based on the Young–Laplace equation, momentum equation, and energy conservation, is proposed, to identify the metal transfer modes, including droplet, liquid bridge, and wire stubbing, for a given combination of process parameters. To close the proposed model, high-fidelity numerical simulations are applied, to obtain the necessary inputs required by the former. The proposed model’s accuracy and effectiveness are validated by using experimental data and high-fidelity simulation results. It is proved that the model can effectively predict the transition from liquid bridge, to droplet and wire stubbing modes. In addition, its errors in dripping frequency and liquid bridge height range from 6% to 18%. Moreover, the process parameter windows about transitions of liquid transfer modes have been established based on the model, considering wire feed speed, travel speed, heat source power, and material parameters. The proposed model is expected to serve as a powerful tool for the guidance of process parameter optimization, to achieve high-quality builds. |
format | Online Article Text |
id | pubmed-10096320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100963202023-04-13 A Fast Prediction Model for Liquid Metal Transfer Modes during the Wire Arc Additive Manufacturing Process Ouyang, Jiaqi Li, Mingjian Lian, Yanping Peng, Siyi Liu, Changmeng Materials (Basel) Article The liquid metal transfer mode in wire arc additive manufacturing (WAAM), plays an important role in determining the build quality. In this study, a fast prediction model based on the Young–Laplace equation, momentum equation, and energy conservation, is proposed, to identify the metal transfer modes, including droplet, liquid bridge, and wire stubbing, for a given combination of process parameters. To close the proposed model, high-fidelity numerical simulations are applied, to obtain the necessary inputs required by the former. The proposed model’s accuracy and effectiveness are validated by using experimental data and high-fidelity simulation results. It is proved that the model can effectively predict the transition from liquid bridge, to droplet and wire stubbing modes. In addition, its errors in dripping frequency and liquid bridge height range from 6% to 18%. Moreover, the process parameter windows about transitions of liquid transfer modes have been established based on the model, considering wire feed speed, travel speed, heat source power, and material parameters. The proposed model is expected to serve as a powerful tool for the guidance of process parameter optimization, to achieve high-quality builds. MDPI 2023-04-06 /pmc/articles/PMC10096320/ /pubmed/37049203 http://dx.doi.org/10.3390/ma16072911 Text en © 2023 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 Ouyang, Jiaqi Li, Mingjian Lian, Yanping Peng, Siyi Liu, Changmeng A Fast Prediction Model for Liquid Metal Transfer Modes during the Wire Arc Additive Manufacturing Process |
title | A Fast Prediction Model for Liquid Metal Transfer Modes during the Wire Arc Additive Manufacturing Process |
title_full | A Fast Prediction Model for Liquid Metal Transfer Modes during the Wire Arc Additive Manufacturing Process |
title_fullStr | A Fast Prediction Model for Liquid Metal Transfer Modes during the Wire Arc Additive Manufacturing Process |
title_full_unstemmed | A Fast Prediction Model for Liquid Metal Transfer Modes during the Wire Arc Additive Manufacturing Process |
title_short | A Fast Prediction Model for Liquid Metal Transfer Modes during the Wire Arc Additive Manufacturing Process |
title_sort | fast prediction model for liquid metal transfer modes during the wire arc additive manufacturing process |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10096320/ https://www.ncbi.nlm.nih.gov/pubmed/37049203 http://dx.doi.org/10.3390/ma16072911 |
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