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Proceeding Paper

Steps towards Industrial Validation Experiments

Empa, Materials Science and Technology, CH-8600 Dübendorf, Switzerland
National Physical Laboratory, Teddington TW11 0LW, UK
School of Engineering, University of Liverpool, Liverpool L69 3GH, UK
Industrial Systems Institute, Athena Research and Innovation Center, 265 04 Patras, Greece
Dantec Dynamics GmbH, D-89077 Ulm, Germany
Airbus Operations Ltd., Filton, Bristol BS99 7AR, UK
Author to whom correspondence should be addressed.
Presented at the 18th International Conference on Experimental Mechanics, Brussels, Belgium, 1–5 July 2018.
Proceedings 2018, 2(8), 391;
Published: 9 May 2018
(This article belongs to the Proceedings of The 18th International Conference on Experimental Mechanics)
Imaging systems for measuring surface displacement and strain fields such as stereoscopic Digital Image Correlation (DIC) are increasingly used in industry to validate model simulations. Recently, CEN has published a guideline for validation that is based on image decomposition to compare predicted and measured data fields. The CEN guideline was evaluated in an inter-laboratory study that demonstrated its usefulness in laboratory environments. This paper addresses the incorporation of the CEN methodology into an industrial environment and reports progress of the H2020 Clean Sky 2 project MOTIVATE. First, while DIC is a well-established technique, the estimation of its measurement uncertainty in an industrial environment is still being discussed, as the current approach to rely on the calibration uncertainty is insufficient. Second, in view of the push towards virtual testing it is important to harvest existing data in the course of the V&V activities before requesting a dedicated validation experiment, specifically at higher levels of the test pyramid. Finally, it is of uttermost importance to ensure compatibility and comparability of the simulation and measurement data so as to optimize the test matrix for maximum reliability and credibility of the simulations and a quantification of the model quality.
Keywords: validation; validation metric; Digital Image Correlation; DIC; image decomposition validation; validation metric; Digital Image Correlation; DIC; image decomposition
MDPI and ACS Style

Hack, E.; Burguete, R.; Dvurecenska, K.; Lampeas, G.; Patterson, E.; Siebert, T.; Szigeti, E. Steps towards Industrial Validation Experiments. Proceedings 2018, 2, 391.

AMA Style

Hack E, Burguete R, Dvurecenska K, Lampeas G, Patterson E, Siebert T, Szigeti E. Steps towards Industrial Validation Experiments. Proceedings. 2018; 2(8):391.

Chicago/Turabian Style

Hack, Erwin, Richard Burguete, Ksenija Dvurecenska, George Lampeas, Eann Patterson, Thorsten Siebert, and Eszter Szigeti. 2018. "Steps towards Industrial Validation Experiments" Proceedings 2, no. 8: 391.

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