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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Residual stresses prediction in machining: Hybrid FEM enhanced by assessment of plastic flow

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Author(s):
Rocha D' Oliveira, Andre Luiz [1] ; Rego, Ronnie Rodrigo [1] ; de Faria, Alfredo Rocha [1]
Total Authors: 3
Affiliation:
[1] Aeronaut Inst Technol ITA, Competence Ctr Mfg, Praca Marechal Eduardo Gomes 50, BR-12228900 Sao Jose Dos Campos - Brazil
Total Affiliations: 1
Document type: Journal article
Source: Journal of Materials Processing Technology; v. 275, JAN 2020.
Web of Science Citations: 0
Abstract

Manufactured components are submitted to thermo-mechanical loads that can blemish their surface integrity and change the inherent residual stress distribution. The discontinuous machining process is relevant to the integrity conception because of their potential application at the end of the manufacturing chain. In order to consolidate a method to predict the residual stress state with a reduced CPU effort, this paper addresses the prediction of residual stress fields resulting from the milling process. The approach is using the hybrid FEM approach combined with the analysis of the plastic flow. The results obtained point out to the validity of the combination of the hybrid method and the visualization of the equivalent stress and equivalent strain rates. Moreover, a direct correspondence between the references and experimental dataset was observed, even when the input data for the model is associated with macro-loads obtained by piezoelectric platform measurements. The determination of the stress state as residual stress in mainly associated to the mesh convergence and the time to equilibrate the plastic flow. A conclusion is drawn regarding the viability of applying the same combination for other manufacturing processes. (AU)

FAPESP's process: 18/09251-0 - Design for Residual Stress (DRS) on Gears Manufacturing: Industry 4.0 Approach
Grantee:Alfredo Rocha de Faria
Support type: Regular Research Grants