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Simulation of Work Hardening in Machining Inconel 718 with Multiscale Grain Size

Machining nickel-based alloys always exhibits significant work-hardening behavior, which may help to improve the part quality by building a hardened layer on the surface, while also causing severe tool wear during machining. Hence, modeling the work-hardening phenomenon plays a critical role in the...

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Autores principales: Zhuang, Kejia, Wang, Zhuo, Zou, Linli, Fu, Changni, Weng, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10180194/
https://www.ncbi.nlm.nih.gov/pubmed/37176444
http://dx.doi.org/10.3390/ma16093562
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author Zhuang, Kejia
Wang, Zhuo
Zou, Linli
Fu, Changni
Weng, Jian
author_facet Zhuang, Kejia
Wang, Zhuo
Zou, Linli
Fu, Changni
Weng, Jian
author_sort Zhuang, Kejia
collection PubMed
description Machining nickel-based alloys always exhibits significant work-hardening behavior, which may help to improve the part quality by building a hardened layer on the surface, while also causing severe tool wear during machining. Hence, modeling the work-hardening phenomenon plays a critical role in the evaluation of tool wear and part quality. This paper aims to propose a numerical model to estimate the work-hardening layer for a deeper understanding of this behavior, employing both recrystallization-based and dislocation-based models to cover workpieces with multiscale grain sizes. Different user routines are implemented in the finite element method to simulate the increase in hardness in the deformed area due to recrystallization or changes in the dislocation density. The validation of the proposed model is performed with both literature and experimental data for Inconel 718 with small or large grain sizes. It is found that the recrystallization-based model is more suitable for predicting the work-hardening behavior of small-grain-size Inconel 718 and the dislocation-based model is better for that of large-grain-size Inconel 718. Further, as an important type of cutting tool in machining Inconel 718, the chamfered tools with different edge geometries are employed in the simulations of machining-induced work hardening. The results illustrate that the uncut chip thickness and chamfer angle have a significant influence on the work-hardening behavior.
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spelling pubmed-101801942023-05-13 Simulation of Work Hardening in Machining Inconel 718 with Multiscale Grain Size Zhuang, Kejia Wang, Zhuo Zou, Linli Fu, Changni Weng, Jian Materials (Basel) Article Machining nickel-based alloys always exhibits significant work-hardening behavior, which may help to improve the part quality by building a hardened layer on the surface, while also causing severe tool wear during machining. Hence, modeling the work-hardening phenomenon plays a critical role in the evaluation of tool wear and part quality. This paper aims to propose a numerical model to estimate the work-hardening layer for a deeper understanding of this behavior, employing both recrystallization-based and dislocation-based models to cover workpieces with multiscale grain sizes. Different user routines are implemented in the finite element method to simulate the increase in hardness in the deformed area due to recrystallization or changes in the dislocation density. The validation of the proposed model is performed with both literature and experimental data for Inconel 718 with small or large grain sizes. It is found that the recrystallization-based model is more suitable for predicting the work-hardening behavior of small-grain-size Inconel 718 and the dislocation-based model is better for that of large-grain-size Inconel 718. Further, as an important type of cutting tool in machining Inconel 718, the chamfered tools with different edge geometries are employed in the simulations of machining-induced work hardening. The results illustrate that the uncut chip thickness and chamfer angle have a significant influence on the work-hardening behavior. MDPI 2023-05-06 /pmc/articles/PMC10180194/ /pubmed/37176444 http://dx.doi.org/10.3390/ma16093562 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
Zhuang, Kejia
Wang, Zhuo
Zou, Linli
Fu, Changni
Weng, Jian
Simulation of Work Hardening in Machining Inconel 718 with Multiscale Grain Size
title Simulation of Work Hardening in Machining Inconel 718 with Multiscale Grain Size
title_full Simulation of Work Hardening in Machining Inconel 718 with Multiscale Grain Size
title_fullStr Simulation of Work Hardening in Machining Inconel 718 with Multiscale Grain Size
title_full_unstemmed Simulation of Work Hardening in Machining Inconel 718 with Multiscale Grain Size
title_short Simulation of Work Hardening in Machining Inconel 718 with Multiscale Grain Size
title_sort simulation of work hardening in machining inconel 718 with multiscale grain size
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10180194/
https://www.ncbi.nlm.nih.gov/pubmed/37176444
http://dx.doi.org/10.3390/ma16093562
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