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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 :
Composites: Part B, Engineering. Jan2023, Vol. 249, pN.PAG-N.PAG. 1p.
Publication Year :
2023

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. [Display omitted] [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13598368
Volume :
249
Database :
Academic Search Index
Journal :
Composites: Part B, Engineering
Publication Type :
Academic Journal
Accession number :
160397904
Full Text :
https://doi.org/10.1016/j.compositesb.2022.110380