Comparative study of orthogonal decomposition of surface deformation in composite automotive panel



Dvurecenska, K ORCID: 0000-0003-0642-1095, Hack, E, Lampeas, G, Siebert, T and Patterson, E ORCID: 0000-0003-4397-2160
(2020) Comparative study of orthogonal decomposition of surface deformation in composite automotive panel. .

[img] Text
Dvurecenska etal 2018ECCM.pdf - Published Version

Download (551kB)

Abstract

© CCM 2020 - 18th European Conference on Composite Materials. All rights reserved. Model validation is a major step in achieving computational models with good predictive capabilities. It is normal practice to validate simulation models by comparing their numerical results to experimental data. A critical issue when performing a validation procedure with information-rich data fields is the identification of effective techniques for data compression to allow the application of statistical measures to the comparison of predictions and measurements. Recently, image decomposition techniques have successfully been applied in a laboratory environment to condense data and extract features of surface deformation maps obtained with the aid of optical measurement techniques and finite element analysis. In this work, the integration of orthogonal decomposition with a validation metrics is explored and a new metric introduced. For the purpose of illustration, a case study of a composite car bonnet liner subject to impact loading has been used. Displacement fields from the entire surface of the bonnet liner were captured at equal time increments for 0.1s following the impact and then decomposed while a parallel process was applied to predictions from a finite element model. The validation metric was calculated from the resultant feature vectors and used to evaluate the quality of the predictions. It is anticipated that the outcomes of this investigation will support the development of a robust validation methodology for industrial applications.

Item Type: Conference or Workshop Item (Unspecified)
Depositing User: Symplectic Admin
Date Deposited: 16 Jan 2019 12:17
Last Modified: 09 Jan 2021 04:27
URI: https://livrepository.liverpool.ac.uk/id/eprint/3031377