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A probabilistic virtual process chain to quantify process-induced uncertainties in Sheet Molding Compounds

Authors :
Meyer, Nils
Gajek, Sebastian
Görthofer, Johannes
Hrymak, Andrew
Kärger, Luise
Henning, Frank
Schneider, Matti
Böhlke, Thomas
Source :
A probabilistic virtual process chain to quantify process-induced uncertainties in Sheet Molding Compounds, Composites Part B: Engineering, Volume 249, 15 January 2023, 110380
Publication Year :
2022

Abstract

The manufacturing process of Sheet Molding Compound (SMC) influences the properties of a component in a non-deterministic fashion. To predict this influence on the mechanical performance, we develop a virtual process chain acting as a digital twin for SMC specimens from compounding to failure. More specifically, we inform a structural simulation with individual fields for orientation and volume fraction computed from a direct bundle simulation of the manufacturing process. The structural simulation employs an interpolated direct deep material network to upscale a tailored SMC damage model. We evaluate hundreds of virtual specimens and conduct a probabilistic analysis of the mechanical performance. We estimate the contribution to uncertainty originating from the process-induced inherent random microstructure and from varying initial SMC stack configurations. Our predicted results are in good agreement with experimental tensile tests and thermogravimetric analysis.

Details

Database :
arXiv
Journal :
A probabilistic virtual process chain to quantify process-induced uncertainties in Sheet Molding Compounds, Composites Part B: Engineering, Volume 249, 15 January 2023, 110380
Publication Type :
Report
Accession number :
edsarx.2209.05873
Document Type :
Working Paper
Full Text :
https://doi.org/10.1016/j.compositesb.2022.110380