4.5 Article

Finite element and artificial neural network analysis of ECAP

期刊

COMPUTATIONAL MATERIALS SCIENCE
卷 63, 期 -, 页码 127-133

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ELSEVIER
DOI: 10.1016/j.commatsci.2012.05.075

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Equal channel angular pressing; Finite element model; Artificial neural network; Strain measurements; Aluminum alloys

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Equal channel angular pressing (ECAP) is the most promising among the developed severe plastic deformation (SPD) techniques to induce strain in bulk metals. In this study finite element method (FEM) and artificial neural network (ANN) were used to simulate ECAP deformation of AA2024 aluminum alloy. The results show that the equivalent plastic strains are not uniform and the deformation inhomogeneity indexes and the location of maximum equivalent plastic strain are varied with the increasing friction coefficient. Moreover, the area over which friction acts and hence the total accumulated friction force is reduced when the billet length is reduced. The FEM and ANN results were in good agreement with experimental measurements. (C) 2012 Elsevier B.V. All rights reserved.

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