Quantitative full-field data fusion for evaluation of complex structures

Jack S Callaghan, D.A. Crump, Anette S Nielsen, Ole Thomsen, Janice M Dulieu-Barton *

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

2 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)1095-1115
Number of pages21
JournalExperimental Mechanics
Issue number7
Early online date28 Jun 2023
Publication statusPublished - 1 Sept 2023

Bibliographical note

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).


Dive into the research topics of 'Quantitative full-field data fusion for evaluation of complex structures'. Together they form a unique fingerprint.

Cite this