Quantitative full‑field data fusion for evaluation of complex structures
Quantitative full‑field data fusion for evaluation of complex structures
Background: validation of models using full-field experimental techniques traditionally rely on local data comparisons. At present, typically selected data fields are used such as local maxima or selected line plots. Here a new approach is proposed called full-field data fusion (FFDF) that utilises the entire image, ensuring the fidelity of the techniques are fully exploited. FFDF has the potential to provide a direct means of assessing design modifications and material choices.
Objective: a FFDF methodology is defined that has the ability to combine data from a variety of experimental and numerical sources to enable quantitative comparisons and validations as well as create new parameters to assess material and structural performance. A section of a wind turbine blade (WTB) substructure of complex composite construction is used as a demonstrator for the methodology.
Methods: the experimental data are obtained using the full-field experimental techniques of Digital Image Correlation (DIC) and Thermoelastic Stress Analysis (TSA), which are then fused with each other, and with predictions made using Finite Element Analysis (FEA). In addition, the FFDF method enables a new high-fidelity validation technique for FEA utilising a precise full-field point by point similarity assessment with the experimental data, based on the fused data sets and metrics.
Results: it is shown that inaccuracies introduced because of estimation of comparable locations in the data sets are eliminated, The FFDF also enables inaccuracies in the experimental data to be mutually assessed at the same scale regardless of differences in camera sensors. For example, the effect of processing parameters in DIC such as subset size and strain window can be assessed through similarity assessment with the TSA.
Conclusions: the FFDF methodology offers a means for comparing different design configurations and material choices for complex composite substructures, as well as quantitative validation of numerical models, which may ultimately reduce dependence on expensive and time-consuming full-scale tests.
Full-field data fusion (FFDF) · Thermoelastic stress analysis (TSA) · Digital image correlation (DIC) · Substructural testing · Quantitative FEA validation
1095-1115
Callaghan, Jack S.
a8e6b689-7fe0-44a7-827b-47053b66048d
Crump, Duncan
5fa2d636-89bc-4005-a948-32554ef3d951
Thomsen, Ole
672bfbd1-8bb7-4b9e-a839-2d7360eeab9b
Barton, Janice
9e35bebb-2185-4d16-a1bc-bb8f20e06632
Nielsen, Anette
7e46fbe1-c4c4-43cf-8033-d887a46f3491
September 2023
Callaghan, Jack S.
a8e6b689-7fe0-44a7-827b-47053b66048d
Crump, Duncan
5fa2d636-89bc-4005-a948-32554ef3d951
Thomsen, Ole
672bfbd1-8bb7-4b9e-a839-2d7360eeab9b
Barton, Janice
9e35bebb-2185-4d16-a1bc-bb8f20e06632
Nielsen, Anette
7e46fbe1-c4c4-43cf-8033-d887a46f3491
Callaghan, Jack S., Crump, Duncan, Thomsen, Ole, Barton, Janice and Nielsen, Anette
(2023)
Quantitative full‑field data fusion for evaluation of complex structures.
Experimental Mechanics, 63 (5), .
(doi:10.1007/s11340-023-00973-8).
Abstract
Background: validation of models using full-field experimental techniques traditionally rely on local data comparisons. At present, typically selected data fields are used such as local maxima or selected line plots. Here a new approach is proposed called full-field data fusion (FFDF) that utilises the entire image, ensuring the fidelity of the techniques are fully exploited. FFDF has the potential to provide a direct means of assessing design modifications and material choices.
Objective: a FFDF methodology is defined that has the ability to combine data from a variety of experimental and numerical sources to enable quantitative comparisons and validations as well as create new parameters to assess material and structural performance. A section of a wind turbine blade (WTB) substructure of complex composite construction is used as a demonstrator for the methodology.
Methods: the experimental data are obtained using the full-field experimental techniques of Digital Image Correlation (DIC) and Thermoelastic Stress Analysis (TSA), which are then fused with each other, and with predictions made using Finite Element Analysis (FEA). In addition, the FFDF method enables a new high-fidelity validation technique for FEA utilising a precise full-field point by point similarity assessment with the experimental data, based on the fused data sets and metrics.
Results: it is shown that inaccuracies introduced because of estimation of comparable locations in the data sets are eliminated, The FFDF also enables inaccuracies in the experimental data to be mutually assessed at the same scale regardless of differences in camera sensors. For example, the effect of processing parameters in DIC such as subset size and strain window can be assessed through similarity assessment with the TSA.
Conclusions: the FFDF methodology offers a means for comparing different design configurations and material choices for complex composite substructures, as well as quantitative validation of numerical models, which may ultimately reduce dependence on expensive and time-consuming full-scale tests.
Text
Callaghan et al_expt Mech 2023_published paper
- Version of Record
More information
Accepted/In Press date: 26 May 2023
e-pub ahead of print date: 28 June 2023
Published date: September 2023
Additional Information:
Funding Information:
The experimental work was conducted in Testing and Structures Research Laboratory at University of Southampton and supported by the Principal Experimental Officer, Dr Andrew Robinson. The contributions of the PhD students and co-workers of Professor Dulieu-Barton are acknowledged, in particular, Dr Irene Jimenez-Fortunato for the development of the microbolometer TSA system and Dr Richard Fruehmann for the idea of lock-in processing for DIC.
Funding Information:
The work described in the paper was supported by Siemens Gamesa Renewable Energy (SGRE) as part of the UK Physical and Engineering Science Research Council (EPSRC) Centre for Doctoral Training in Sustainable Infrastructure Systems (CDT-SIS) (EP/L01582X/1). The work forms the basis of techniques developed for the “Structures 2025” facility constructed using an EPSRC Strategic Equipment Grant (EP/R008787/1) and developed for the Programme Grant “Certification for Design: Reshaping the testing pyramid” (EP/S017038/1) led by the University of Bristol.
Publisher Copyright:
© 2023, The Author(s).
Keywords:
Full-field data fusion (FFDF) · Thermoelastic stress analysis (TSA) · Digital image correlation (DIC) · Substructural testing · Quantitative FEA validation
Identifiers
Local EPrints ID: 479411
URI: http://eprints.soton.ac.uk/id/eprint/479411
ISSN: 0014-4851
PURE UUID: 0ff06dcc-4e13-429b-a00c-48cab4381997
Catalogue record
Date deposited: 21 Jul 2023 16:50
Last modified: 17 Mar 2024 03:21
Export record
Altmetrics
Contributors
Author:
Jack S. Callaghan
Author:
Duncan Crump
Author:
Ole Thomsen
Author:
Anette Nielsen
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics