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

DS 116: Proceedings of the DESIGN2022 17th International Design Conference

Year: 2022
Editor: Mario Štorga, Stanko Škec, Tomislav Martinec, Dorian Marjanović
Author: Michael Franz (1), Simon Pfingstl (2), Markus Zimmermann (2), Sandro Wartzack (1)
Series: DESIGN
Institution: 1: Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany; 2: Technical University of Munich, Germany
Section: Artificial Intelligence and Data-Driven Design
Page(s): 1569-1578
DOI number:
ISSN: 2732-527X (Online)


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 twin, inverse problem, simulation-based design, data-driven design, structural analysis

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