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arXiv · 2209.05873

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

Nils Meyer·Sebastian Gajek·Johannes Görthofer·Andrew Hrymak·Luise Kärger·Frank Henning·Matti Schneider·Thomas Böhlke
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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.

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Nils Meyer, Sebastian Gajek, Johannes Görthofer, Andrew Hrymak, Luise Kärger, Frank Henning, Matti Schneider, Thomas Böhlke. 2022-09-13. A probabilistic virtual process chain to quantify process-induced uncertainties in Sheet Molding Compounds. https://doi.org/10.1016/j.compositesb.2022.110380

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