Numerical Simulations of the Mesostructure Formation in Material-Extrusion Additive Manufacturing (2019-05)¶
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Journal Article - Additive Manufacturing, Vol. 28, pp. 419-429
Abstract
A computational fluid dynamics model is used to predict the mesostructure formed by the successive deposition of parallel strands in material extrusion additive manufacturing. The numerical model simulates the extrusion of the material onto the substrate. The model takes into account the effect of the presence of the previously extruded material on the shape of the subsequently deposited strands. The simulated mesostructures are compared to optical micrographs of the mesostructures of 3D-printed samples, and the predictions agree well with the experiments. In addition, the influence of the layer thickness, the strand-to-strand distance, and the deposition configuration (with aligned or skewed layers) on the formation of the mesostructure is investigated. The simulations provide detailed information about the porosity, the inter- and intra-layer bond line densities, and the surface roughness of the mesostructures, which potentially can be used in a model-based slicing software.
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BibTeX
@article{serd_comm_pede_span.2019.NSotMFiMEAM,
author = "Marcin P. Serdeczny and Raphaël Comminal and David Bue Pedersen and Jon Spangenberg",
title = "Numerical Simulations of the Mesostructure Formation in Material-Extrusion Additive Manufacturing",
doi = "10.1016/j.addma.2019.05.024",
year = "2019",
journal = "Additive Manufacturing",
volume = "28",
pages = "419--429",
}
Formatted Citation
M. P. Serdeczny, R. Comminal, D. B. Pedersen and J. Spangenberg, “Numerical Simulations of the Mesostructure Formation in Material-Extrusion Additive Manufacturing”, Additive Manufacturing, vol. 28, pp. 419–429, 2019, doi: 10.1016/j.addma.2019.05.024.
Serdeczny, Marcin P., Raphaël Comminal, David Bue Pedersen, and Jon Spangenberg. “Numerical Simulations of the Mesostructure Formation in Material-Extrusion Additive Manufacturing”. Additive Manufacturing 28 (2019): 419–29. https://doi.org/10.1016/j.addma.2019.05.024.