Authors:
O. Schenk (1), Y.Deng (1), A. Kaletsch (1), A. Şelte (2), C. Broeckmann (1)
1- RWTH Aachen University, Institute for Materials Applications in Mechanical Engineering (IWM), Augustinerbach 4, 52062 Aachen, Germany
2- Uddeholms AB, SE-683 85 Hagfors, Sweden
Abstract:
Powder compaction is an essential part of the powder metallurgical (PM) process chain, being mainly responsible for the shape and distribution of the inherent porosity of a sintered component. While the significant effects of the porosity and the pore morphology on the fatigue behavior of PM components have been widely investigated, their numerical prediction during PM process has rarely been performed. In this work, a multiscale model of powder compaction of Astaloy 85Mo is presented, which provides information on both density distribution and pore morphology. A modified Drucker-Prager model and a friction model were experimentally derived to simulate the compaction process for different tool steels on macroscale, providing information on the density distribution. Using machine learning, artificial microstructural images of the powder compact were generated depending on local density. Both models were combined and applied to the compaction of a gear, which delivered promising results that agree well with experiments.
DOI:
https://doi.org/10.59499/EP235763805