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Validation of finite-element models using full-field experimental data: leveling FEA data through a DIC engine

Validation of finite-element models using full-field experimental data: leveling FEA data through a DIC engine
Validation of finite-element models using full-field experimental data: leveling FEA data through a DIC engine
Full-field data from Digital Image Correlation (DIC) provides rich information for finite element analysis (FEA) validation. However, there are several inherent inconsistencies between FEA and DIC data that must be rectified before meaningful, quantitative comparisons can be made, including: strain formulations, coordinate systems, data locations, strain calculation algorithms, spatial resolutions, and data filtering. In this paper, we investigate two full-field validation approaches: (1) the direct interpolation approach, which addresses the first three inconsistencies by interpolating the quantity of interest from one mesh to the other; and (2) the proposed DIC-leveling approach, which addresses all six inconsistencies simultaneously by processing the FEA data through a stereo-DIC simulator to "level" the FEA data to the DIC data in a regularization sense. Synthetic "experimental" DIC data was generated based on a reference FEA of an exemplar test specimen. The direct interpolation approach was applied, and significant strain errors were computed, even though there was no model form error, because the filtering effect of the DIC engine was neglected. In contrast, the leveling approach provided accurate validation results, with no strain error when no model form error was present. Next, model form error was purposefully introduced via a mismatch of boundary conditions. With the direct interpolation approach, the mismatch in boundary conditions was completely obfuscated, while with the leveling approach, it was clearly observed. Finally, the "experimental" DIC data was purposefully misaligned slightly from the FEA data. Both validation techniques suffered from the misalignment, thus motivating continued efforts to develop a robust alignment process. In summary, direct interpolation is insufficient, and the proposed leveling approach is required to ensure that the FEA and the DIC data have the same spatial resolution and data filtering. Only after the FEA data has been "leveled" to the DIC data can meaningful, quantitative error maps be computed.
Veri�cation and Validation (V&V);, Finite-Element Analysis (FEA);, Digital Image Correlation (DIC);, DIC-Leveling Approach
1475-1305
1-17
Lava, P.
66113c15-d51e-47a7-bd3e-263f25474f41
Jones, EMC
e96d2aea-20b1-4fcb-8a52-b296731c3850
Wittevrongel, L
98ef3a16-c4f5-4f27-8142-45583a5f93a3
Pierron, Fabrice
a1fb4a70-6f34-4625-bc23-fcb6996b79b4
Lava, P.
66113c15-d51e-47a7-bd3e-263f25474f41
Jones, EMC
e96d2aea-20b1-4fcb-8a52-b296731c3850
Wittevrongel, L
98ef3a16-c4f5-4f27-8142-45583a5f93a3
Pierron, Fabrice
a1fb4a70-6f34-4625-bc23-fcb6996b79b4

Lava, P., Jones, EMC, Wittevrongel, L and Pierron, Fabrice (2020) Validation of finite-element models using full-field experimental data: leveling FEA data through a DIC engine. Strain, 56 (4), 1-17, [e12350]. (doi:10.1111/str.12350).

Record type: Article

Abstract

Full-field data from Digital Image Correlation (DIC) provides rich information for finite element analysis (FEA) validation. However, there are several inherent inconsistencies between FEA and DIC data that must be rectified before meaningful, quantitative comparisons can be made, including: strain formulations, coordinate systems, data locations, strain calculation algorithms, spatial resolutions, and data filtering. In this paper, we investigate two full-field validation approaches: (1) the direct interpolation approach, which addresses the first three inconsistencies by interpolating the quantity of interest from one mesh to the other; and (2) the proposed DIC-leveling approach, which addresses all six inconsistencies simultaneously by processing the FEA data through a stereo-DIC simulator to "level" the FEA data to the DIC data in a regularization sense. Synthetic "experimental" DIC data was generated based on a reference FEA of an exemplar test specimen. The direct interpolation approach was applied, and significant strain errors were computed, even though there was no model form error, because the filtering effect of the DIC engine was neglected. In contrast, the leveling approach provided accurate validation results, with no strain error when no model form error was present. Next, model form error was purposefully introduced via a mismatch of boundary conditions. With the direct interpolation approach, the mismatch in boundary conditions was completely obfuscated, while with the leveling approach, it was clearly observed. Finally, the "experimental" DIC data was purposefully misaligned slightly from the FEA data. Both validation techniques suffered from the misalignment, thus motivating continued efforts to develop a robust alignment process. In summary, direct interpolation is insufficient, and the proposed leveling approach is required to ensure that the FEA and the DIC data have the same spatial resolution and data filtering. Only after the FEA data has been "leveled" to the DIC data can meaningful, quantitative error maps be computed.

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Validation-Part1-Synthetic_accepted - Accepted Manuscript
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More information

Accepted/In Press date: 22 March 2020
e-pub ahead of print date: 20 April 2020
Published date: August 2020
Keywords: Veri�cation and Validation (V&V);, Finite-Element Analysis (FEA);, Digital Image Correlation (DIC);, DIC-Leveling Approach

Identifiers

Local EPrints ID: 438957
URI: http://eprints.soton.ac.uk/id/eprint/438957
ISSN: 1475-1305
PURE UUID: dad62eec-c16b-476a-bda3-fbb53e1673cf
ORCID for Fabrice Pierron: ORCID iD orcid.org/0000-0003-2813-4994

Catalogue record

Date deposited: 30 Mar 2020 16:30
Last modified: 26 Nov 2021 06:15

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Contributors

Author: P. Lava
Author: EMC Jones
Author: L Wittevrongel
Author: Fabrice Pierron ORCID iD

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