Discrete element simulation of powder layer spreading by blade sliding: packing factor, mechanism, and optimization

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Discrete element simulation of powder layer spreading by blade sliding: packing factor, mechanism, and optimization
Title:
Discrete element simulation of powder layer spreading by blade sliding: packing factor, mechanism, and optimization
Journal Title:
Computational Particle Mechanics
Publication Date:
12 August 2024
Citation:
Dai, L., Chan, Y. R., Vastola, G., Zhang, Y. W. (2024). Discrete element simulation of powder layer spreading by blade sliding: packing factor, mechanism, and optimization. Computational Particle Mechanics. https://doi.org/10.1007/s40571-024-00808-w
Abstract:
We utilized the Discrete Element Method (DEM) to simulate the packing of a powder layer by blade spread. Our study revealed the following findings: (1) We uncovered a hereditary relationship that exists between the pouring heap and the packing layer, which plays a significant role in the non-uniform distribution of powder in the packing layer in terms of sizes and shapes. (2) We systematically analysed the influence of sliding speed on powder packing and recommended a threshold sliding rate of 0.15 m/s for achieving a high packing quality. (3) Contrary to the conventional belief that non-spherical powders tend to reduce packing density, our study discovered that the inclusion of a small portion of non-spherical powders can create pathways for efficient gapfilling, resulting in denser packings. (4) By adjusting inter-powder interactions, we observed a transition from discrete powder packing to cluster deposition. (5) We proposed and demonstrated the efficacy of a two-step spreading technique followed by multiple shaking cycles in achieving maximum random packing density. Overall, our work provides a comprehensive understanding of mechanisms involved in the powder spreading process through blade sliding, which may lead to enhanced powder packing density and uniformity and ultimately improved outcomes in additive manufacturing.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the Agency for Science, Technology and Research, Singapore - RIE 2025 Manufacturing, Trade and Connectivity (MTC) Industry Alignment Fund- Pre- Positioning (IAF-PP) "Metal AM Powders: Reusability, Rejuvenation, Cost, Quality & Performance (RRAMP)"
Grant Reference no. : M22K7a0047

This research / project is supported by the Agency for Science, Technology and Research, Singapore - “Solid Solution, Short-range Ordering, Precipitation and Grain Boundary Strengthening Mechanisms and Their Impacts on the Mechanical and Chemical Properties of Medium Entropy Alloys: A Computational Study”
Grant Reference no. : SC23/21-1075EM

This research / project is supported by the Agency for Science, Technology and Research, Singapore - MTC Programmatic Fund “Advanced Models for Additive Manufacturing”
Grant Reference no. : M22L2b0111
Description:
This is a post-peer-review, pre-copyedit version of an article published in Computational Particle Mechanics. The final authenticated version is available online at: http://dx.doi.org/10.1007/s40571-024-00808-w
ISSN:
2196-4378
2196-4386
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