Experimental validation of the sensitivity-based virtual fields for identification of anisotropic plasticity models
Experimental validation of the sensitivity-based virtual fields for identification of anisotropic plasticity models
In this work, the sensitivity-based virtual fields have been applied to identify two anisotropic plasticity models (Hill48, Yld2000-2D) using a deep-notched tensile test performed on flat samples of cold-rolled sheet of DC04 steel. The material was characterised using the standard protocol to obtain the reference sets of parameters. Deformation data was obtained during deep-notched tests using stereo digital image correlation and the virtual fields method was employed to identify material parameters. It was found that the sensitivity-based virtual fields outperform the standard user-defined virtual fields in terms of accuracy.
Anisotropic plasticity, Digital image correlation, Inverse identification, Sensitivity-based virtual fields, The virtual fields method
639-664
Marek, A.
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Davis, F.M.
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Kim, J.-H.
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Pierron, F.
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June 2020
Marek, A.
7cfb1c40-2e95-4e2b-81e5-c515674bece6
Davis, F.M.
20f89066-bbac-42dc-908d-d89a747dc399
Kim, J.-H.
a9999993-21c2-4bf9-b98a-ac14e49a0440
Pierron, F.
a1fb4a70-6f34-4625-bc23-fcb6996b79b4
Marek, A., Davis, F.M., Kim, J.-H. and Pierron, F.
(2020)
Experimental validation of the sensitivity-based virtual fields for identification of anisotropic plasticity models.
Experimental Mechanics, 60 (5), .
(doi:10.1007/s11340-019-00575-3).
Abstract
In this work, the sensitivity-based virtual fields have been applied to identify two anisotropic plasticity models (Hill48, Yld2000-2D) using a deep-notched tensile test performed on flat samples of cold-rolled sheet of DC04 steel. The material was characterised using the standard protocol to obtain the reference sets of parameters. Deformation data was obtained during deep-notched tests using stereo digital image correlation and the virtual fields method was employed to identify material parameters. It was found that the sensitivity-based virtual fields outperform the standard user-defined virtual fields in terms of accuracy.
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Experimental validation of SBVFs_reviewed2
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Marek 2020 Article Experimental Validation
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More information
Accepted/In Press date: 30 December 2019
e-pub ahead of print date: 19 February 2020
Published date: June 2020
Additional Information:
Funding Information:
Dr Frances Davis and Prof. Fabrice Pierron acknowledge support from Engineering and Physical Sciences Research Council (EPSRC) through grant EP/L026910/1. Prof. Fabrice Pierron also expresses gratitude to the Wolfson Foundation for support through a Royal Society Wolfson Research Merit Award. Dr Aleksander Marek acknowledges funding from EPSRC through a Doctoral Training Grant studentship. Dr Davis also acknowledges support from the Leverhulme Early Career Fellowship. Dr Marek would also like to thank Dr Georges Limbert and Prof. Sandrine Thuillier for useful suggestions during his PhD examination.
Publisher Copyright:
© 2020, The Author(s).
Keywords:
Anisotropic plasticity, Digital image correlation, Inverse identification, Sensitivity-based virtual fields, The virtual fields method
Identifiers
Local EPrints ID: 438058
URI: http://eprints.soton.ac.uk/id/eprint/438058
ISSN: 1741-2765
PURE UUID: aa3b7de8-c53a-4148-8416-c8c361abcb79
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Date deposited: 27 Feb 2020 17:30
Last modified: 17 Mar 2024 05:15
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Author:
F.M. Davis
Author:
J.-H. Kim
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