Mechanics & Industry
Volume 23, 2022
|Number of page(s)||8|
|Published online||20 January 2022|
An indicator of porosity through simulation of melt pool volume in aluminum wire arc additive manufacturing
Univ. Grenoble Alpes, CNRS, Grenoble INP, G-SCOP, 38000 Grenoble, France
2 S.mart Grenoble Alpes, 38000 Grenoble, France
* e-mail: firstname.lastname@example.org
Accepted: 30 December 2021
Managing the quality of functional parts is a key challenge in wire arc additive manufacturing. In case of additive production of aluminum parts, porosity is one of the main limitations of this process. This paper provides an indicator of porosity through the simulation of melt pool volume in aluminum wire arc additive manufacturing. First, a review of porosity formation during WAAM process is presented. This review leads to the proposal of this article: monitoring the porosity inside produced part can be achieved through the melt pool volume monitoring. An adapted Finite Element model is then proposed to determine the evolution of the melt pool volume throughout the manufacturing process of the part. This model is validated by experimental temperature measurement. Then, in order to study the link between the porosity and the melt pool volume, two test parts are chosen to access to two different pore distributions. These two parts are simulated and produced. The porosity rates of produced parts are then measured by X-ray tomography and compared to the simulated melt pool volumes. The analysis of the results highlights the interest of the melt pool volume as a predictive indicator of the porosity rate.
Key words: Additive manufacturing / wire arc additive manufacturing / quality / porosity / process simulation
© N. Béraud et al., Published by EDP Sciences 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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