journal article·2019-10

Powder-spreading mechanisms in powder-bed-based additive manufacturing: Experiments and computational modeling

Hui Chen, Qingsong Wei, Yingjie Zhang, Fan Chen, Yusheng Shi, Wentao Yan

Acta Materialia· Volume 179
Publisher page

Abstract

Abstract The packing density of the powder layer plays a key role in the final quality of the parts fabricated via powder-bed-based (PBB) additive manufacturing. This paper presents a combined experimental and computational modeling study on the scraping type of powder-spreading process, in order to understand the fundamental mechanisms of the packing of the powder layer. The deposition mechanisms at the particulate scale, including particle contact stress and particle velocity, are investigated, using the discrete element method, while the macro-scale packing density is validated by experiments. It is found that there is a stress-dip at the bottom of powder pile scraped by the rake. This stress-dip makes the powder particles uniformly deposited. Three kinds of deposition mechanisms dominating the powder-spreading process are identified: cohesion effect, wall effect, and percolation effect. The cohesion effect, which leads to particle agglomerations and thus reduces the packing density, becomes stronger with the decrease of particle size. The wall effect, which leads to more vacancies in the powder layer, becomes stronger with the decrease of layer thickness or the increase of particle size. The percolation effect exists in bimodal powder particles, which leads to particle segregation within the powder layer and thus reduces the packing density. The three kinds of deposition mechanisms compete with each other during the powder-spreading process and make combined effects on the packing density of the powder layer.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Additive Manufacturing and 3D Printing Technologies · Additive Manufacturing Materials and Processes · Fluid Dynamics and Heat Transfer

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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