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Sensitivity-based virtual fields for the non-linear virtual fields method

Sensitivity-based virtual fields for the non-linear virtual fields method
Sensitivity-based virtual fields for the non-linear virtual fields method
The virtual fields method (VFM) is an approach to inversely identify material parameters using full-field deformation data. In this manuscript, a new set of automatically-defined virtual fields for non- linear constitutive models has been proposed. These new sensitivity-based virtual fields reduce the influence of noise on the parameter identification. The sensitivity-based virtual fields were applied to a numerical example involving small strain plasticity; however, the general formulation derived for these virtual fields is applicable to any non-linear constitutive model. To quantify the improvement offered by these new virtual fields, they were compared with stiffness-based and manually defined virtual fields. The proposed sensitivity-based virtual fields were consistently able to identify plastic model parameters and outperform the stiffness-based and manually defined virtual fields when the data was
corrupted by noise.
0178-7675
409–431
Marek, Aleksander
7cfb1c40-2e95-4e2b-81e5-c515674bece6
Davis, Frances
20f89066-bbac-42dc-908d-d89a747dc399
Pierron, Fabrice
a1fb4a70-6f34-4625-bc23-fcb6996b79b4
Marek, Aleksander
7cfb1c40-2e95-4e2b-81e5-c515674bece6
Davis, Frances
20f89066-bbac-42dc-908d-d89a747dc399
Pierron, Fabrice
a1fb4a70-6f34-4625-bc23-fcb6996b79b4

Marek, Aleksander, Davis, Frances and Pierron, Fabrice (2017) Sensitivity-based virtual fields for the non-linear virtual fields method. Computational Mechanics, 60 (3), 409–431. (doi:10.1007/s00466-017-1411-6).

Record type: Article

Abstract

The virtual fields method (VFM) is an approach to inversely identify material parameters using full-field deformation data. In this manuscript, a new set of automatically-defined virtual fields for non- linear constitutive models has been proposed. These new sensitivity-based virtual fields reduce the influence of noise on the parameter identification. The sensitivity-based virtual fields were applied to a numerical example involving small strain plasticity; however, the general formulation derived for these virtual fields is applicable to any non-linear constitutive model. To quantify the improvement offered by these new virtual fields, they were compared with stiffness-based and manually defined virtual fields. The proposed sensitivity-based virtual fields were consistently able to identify plastic model parameters and outperform the stiffness-based and manually defined virtual fields when the data was
corrupted by noise.

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More information

Accepted/In Press date: 7 April 2017
e-pub ahead of print date: 28 April 2017
Published date: September 2017
Organisations: Engineering Mats & Surface Engineerg Gp, Education Hub

Identifiers

Local EPrints ID: 410716
URI: http://eprints.soton.ac.uk/id/eprint/410716
ISSN: 0178-7675
PURE UUID: 1c470668-e458-4935-86a2-46133fafd86d
ORCID for Fabrice Pierron: ORCID iD orcid.org/0000-0003-2813-4994

Catalogue record

Date deposited: 09 Jun 2017 09:26
Last modified: 26 Nov 2021 02:55

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Contributors

Author: Frances Davis
Author: Fabrice Pierron ORCID iD

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