Steps towards Industrial Validation Experiments

Proceedings

Siebert, Thorsten¹  Szigeti, Eszter²  Patterson, Eann³  Hack, Erwin⁴  Lampeas, George⁵  Burguete, Richard⁶  Dvurecenska, Ksenija⁷ 

[1] Airbus Operations Ltd., Filton, Bristol BS99 7AR, UK;Author to whom correspondence should be addressed.;Dantec Dynamics GmbH, D-89077 Ulm, Germany;Empa, Materials Science and Technology, CH-8600 Dübendorf, Switzerland;Industrial Systems Institute, Athena Research and Innovation Center, 265 04 Patras, Greece;National Physical Laboratory, Teddington TW11 0LW, UK;School of Engineering, University of Liverpool, Liverpool L69 3GH, UK

关键词: validation;    validation metric;    Digital Image Correlation;    DIC;    image decomposition;   

DOI  :  10.3390/ICEM18-05216

学科分类：社会科学、人文和艺术（综合）

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY