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Estimation of Composite Laminate Ply Angles Using an Inverse Bayesian Approach Based on Surrogate Models

Published online by Cambridge University Press:  26 May 2022

M. Franz ,
S. Pfingstl ,
M. Zimmermann  and
S. Wartzack
M. Franz*
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
S. Pfingstl
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany Technical University of Munich, Germany
M. Zimmermann
Affiliation:
Technical University of Munich, Germany
S. Wartzack
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
*
franz@mfk.fau.de

Abstract

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A digital twin (DT) relies on a detailed, virtual representation of a physical product. Since uncertainties and deviations can lead to significant changes in the functionality and quality of products, they should be considered in the DT. However, valuable product properties are often hidden and thus difficult to integrate into a DT. In this work, a Bayesian inverse approach based on surrogate models is applied to infer hidden composite laminate ply angles from strain measurements. The approach is able to find the true values even for ill-posed problems and shows good results up to 6 plies.

Keywords

digital twininverse problemsimulation-based designdata-driven designstructural analysis
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 1569 - 1578
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2022.

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