Journal
POWDER TECHNOLOGY
Volume 397, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.powtec.2021.11.044
Keywords
Polymer powders; Sintering; Visco-elastic kinetics; Discrete element method; Bayesian calibration
Categories
Funding
- NWO-TTW [16604]
Ask authors/readers for more resources
This study presents a novel discrete element method framework for modeling the visco-elastic sintering kinetics in polymer powders. The framework considers three distinct sintering mechanisms and is implemented in an open-source software package. Experimental data analysis confirms the accuracy of the sintering time estimation compared to a widely-used model. This research provides an efficient and reliable approach for studying strength evolution in powder-bed fusion processes.
This work provides a novel discrete element method (DEM) framework for modelling the visco-elastic sintering kinetics in virgin and aged polymer powders. The coalescence of particle pairs, over long times, is described by a combined three-stage model of the sintering process, where each stage is dominated by a different driving force: adhesive contact force, adhesive inter-surface force and surface tension. The proposed framework is implemented in MercuryDPM, an open-source package for discrete particle simulations. To quantitatively calibrate the particle-scale parameters, Bayesian filtering is used. Experimental data on Polystyrene (PS), Polyamide 12 (PA12), and PEEK powders, both virgin and aged, are analysed and confirm over a wide range of times the existence of the three distinct sintering mechanisms. In good agreement with the experimental observations, the estimation of sintering time is achieved with a significant accuracy compared to Frenkel's model. This study provides an efficient and reliable approach for future studies of strength evolution in powder-bed fusion processes.(c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available