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Study of the Influence of Cutting Edge on Micro Cutting of Hardened Steel Using FE and SPH Modeling
Micromachining allows the production of micro-components with complex geometries in various materials. However, it presents several scientific issues due to scale reduction compared to conventional machining. These issues are called size effects. At this level, micromachining experiments raise techn...
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/PMC9317438/ https://www.ncbi.nlm.nih.gov/pubmed/35888896 http://dx.doi.org/10.3390/mi13071079 |
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author | Chaabani, Lobna Piquard, Romain Abnay, Radouane Fontaine, Michaël Gilbin, Alexandre Picart, Philippe Thibaud, Sébastien D’Acunto, Alain Dudzinski, Daniel |
author_facet | Chaabani, Lobna Piquard, Romain Abnay, Radouane Fontaine, Michaël Gilbin, Alexandre Picart, Philippe Thibaud, Sébastien D’Acunto, Alain Dudzinski, Daniel |
author_sort | Chaabani, Lobna |
collection | PubMed |
description | Micromachining allows the production of micro-components with complex geometries in various materials. However, it presents several scientific issues due to scale reduction compared to conventional machining. These issues are called size effects. At this level, micromachining experiments raise technical difficulties and significant costs. In this context, numerical modeling is widely used in order to study these different size effects. This article presents four different numerical models of micro-cutting of hardened steel, a Smooth Particle Hydrodynamics (SPH) model and three finite element (FE) models using three different formulations: Lagrangian, Arbitrary Eulerian–Lagrangian (ALE) and Coupled Eulerian–Lagrangian (CEL). The objective is to study the effect of tool edge radius on the micro-cutting process through the evolution of cutting forces, chip morphology and stress distribution in different areas and to compare the relevance of the different models. First, results obtained from two models using FE (Lagrangian) and SPH method were compared with experimental data obtained in previous work. It shows that the different numerical methods are relevant for studying geometrical size effects because cutting force and stress distribution correlate with experimental data. However, they present limits due to the calculation approaches. For a second time, this paper presents a comparison between the four different numerical models cited previously in order to choose which method of modeling can present the micro-cutting process. |
format | Online Article Text |
id | pubmed-9317438 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93174382022-07-27 Study of the Influence of Cutting Edge on Micro Cutting of Hardened Steel Using FE and SPH Modeling Chaabani, Lobna Piquard, Romain Abnay, Radouane Fontaine, Michaël Gilbin, Alexandre Picart, Philippe Thibaud, Sébastien D’Acunto, Alain Dudzinski, Daniel Micromachines (Basel) Article Micromachining allows the production of micro-components with complex geometries in various materials. However, it presents several scientific issues due to scale reduction compared to conventional machining. These issues are called size effects. At this level, micromachining experiments raise technical difficulties and significant costs. In this context, numerical modeling is widely used in order to study these different size effects. This article presents four different numerical models of micro-cutting of hardened steel, a Smooth Particle Hydrodynamics (SPH) model and three finite element (FE) models using three different formulations: Lagrangian, Arbitrary Eulerian–Lagrangian (ALE) and Coupled Eulerian–Lagrangian (CEL). The objective is to study the effect of tool edge radius on the micro-cutting process through the evolution of cutting forces, chip morphology and stress distribution in different areas and to compare the relevance of the different models. First, results obtained from two models using FE (Lagrangian) and SPH method were compared with experimental data obtained in previous work. It shows that the different numerical methods are relevant for studying geometrical size effects because cutting force and stress distribution correlate with experimental data. However, they present limits due to the calculation approaches. For a second time, this paper presents a comparison between the four different numerical models cited previously in order to choose which method of modeling can present the micro-cutting process. MDPI 2022-07-07 /pmc/articles/PMC9317438/ /pubmed/35888896 http://dx.doi.org/10.3390/mi13071079 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 Chaabani, Lobna Piquard, Romain Abnay, Radouane Fontaine, Michaël Gilbin, Alexandre Picart, Philippe Thibaud, Sébastien D’Acunto, Alain Dudzinski, Daniel Study of the Influence of Cutting Edge on Micro Cutting of Hardened Steel Using FE and SPH Modeling |
title | Study of the Influence of Cutting Edge on Micro Cutting of Hardened Steel Using FE and SPH Modeling |
title_full | Study of the Influence of Cutting Edge on Micro Cutting of Hardened Steel Using FE and SPH Modeling |
title_fullStr | Study of the Influence of Cutting Edge on Micro Cutting of Hardened Steel Using FE and SPH Modeling |
title_full_unstemmed | Study of the Influence of Cutting Edge on Micro Cutting of Hardened Steel Using FE and SPH Modeling |
title_short | Study of the Influence of Cutting Edge on Micro Cutting of Hardened Steel Using FE and SPH Modeling |
title_sort | study of the influence of cutting edge on micro cutting of hardened steel using fe and sph modeling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317438/ https://www.ncbi.nlm.nih.gov/pubmed/35888896 http://dx.doi.org/10.3390/mi13071079 |
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