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Inverse identification strategies for the characterization of transformation-based anisotropic plasticity models with the non-linear VFM

Inverse identification strategies for the characterization of transformation-based anisotropic plasticity models with the non-linear VFM
Inverse identification strategies for the characterization of transformation-based anisotropic plasticity models with the non-linear VFM
The Virtual Fields Method (VFM) is a well established inverse technique used to identify the constitutive parameters of material models using heterogeneous full-field strain data. When VFM is employed to retrieve the coefficients of advanced plasticity models, including non linear hardening and anisotropy, however, the procedure may become computationally intensive. Furthermore, the impact of experimental uncertainties is still not entirely scrutinized. In this paper, an identification strategy based on uncoupling the hardening behaviour and the anisotropic yield function is proposed. The approach, based on VFM, allows to carry on the identification with low computational time, and provides also indications on the optimal smoothing level to use in the full-field measurement.

The identification framework is applied on the linear transformation-based yield condition Yld2000-2D, employing numerical data for the validation and, afterwards, using actual experimental data on a bake-hardenable steel, i.e. BH340. Moreover, several aspects of the identification procedure are investigated in depth, namely, the effect of smoothing, the influence of VFM settings (type of virtual fields used, discretization method) and the computational time. The identification results are compared with the standard calibration process, demonstrating that the proposed strategy is capable of identifying properly the material anisotropic behaviour using only three tests on notched specimens.
Anisotropic plasticity, Digital Image Correlation, Inverse Identifcation, Large deformations, Virtual Fields Method
0020-7403
Lattanzi, Attilio
93d7ad5d-91ae-49d3-b959-55413824df9f
Barlat, Frederic
48bfc27a-f489-42b4-987c-76c6f84d0714
Pierron, Fabrice
a1fb4a70-6f34-4625-bc23-fcb6996b79b4
Marek, Aleksander
7cfb1c40-2e95-4e2b-81e5-c515674bece6
Rossi, Marco
bfeecd16-516a-414d-b97d-a4c03ca384ac
Lattanzi, Attilio
93d7ad5d-91ae-49d3-b959-55413824df9f
Barlat, Frederic
48bfc27a-f489-42b4-987c-76c6f84d0714
Pierron, Fabrice
a1fb4a70-6f34-4625-bc23-fcb6996b79b4
Marek, Aleksander
7cfb1c40-2e95-4e2b-81e5-c515674bece6
Rossi, Marco
bfeecd16-516a-414d-b97d-a4c03ca384ac

Lattanzi, Attilio, Barlat, Frederic, Pierron, Fabrice, Marek, Aleksander and Rossi, Marco (2020) Inverse identification strategies for the characterization of transformation-based anisotropic plasticity models with the non-linear VFM. International Journal of Mechanical Sciences, 173, [105422]. (doi:10.1016/j.ijmecsci.2020.105422).

Record type: Article

Abstract

The Virtual Fields Method (VFM) is a well established inverse technique used to identify the constitutive parameters of material models using heterogeneous full-field strain data. When VFM is employed to retrieve the coefficients of advanced plasticity models, including non linear hardening and anisotropy, however, the procedure may become computationally intensive. Furthermore, the impact of experimental uncertainties is still not entirely scrutinized. In this paper, an identification strategy based on uncoupling the hardening behaviour and the anisotropic yield function is proposed. The approach, based on VFM, allows to carry on the identification with low computational time, and provides also indications on the optimal smoothing level to use in the full-field measurement.

The identification framework is applied on the linear transformation-based yield condition Yld2000-2D, employing numerical data for the validation and, afterwards, using actual experimental data on a bake-hardenable steel, i.e. BH340. Moreover, several aspects of the identification procedure are investigated in depth, namely, the effect of smoothing, the influence of VFM settings (type of virtual fields used, discretization method) and the computational time. The identification results are compared with the standard calibration process, demonstrating that the proposed strategy is capable of identifying properly the material anisotropic behaviour using only three tests on notched specimens.

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Accepted/In Press date: 5 January 2020
e-pub ahead of print date: 7 January 2020
Published date: 1 May 2020
Keywords: Anisotropic plasticity, Digital Image Correlation, Inverse Identifcation, Large deformations, Virtual Fields Method

Identifiers

Local EPrints ID: 436945
URI: http://eprints.soton.ac.uk/id/eprint/436945
ISSN: 0020-7403
PURE UUID: eb76c93c-fb48-48a1-8a54-b04f29a4dded
ORCID for Fabrice Pierron: ORCID iD orcid.org/0000-0003-2813-4994

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Date deposited: 14 Jan 2020 17:31
Last modified: 26 Nov 2021 06:32

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Contributors

Author: Attilio Lattanzi
Author: Frederic Barlat
Author: Fabrice Pierron ORCID iD
Author: Marco Rossi

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