He, Y, Gardy, J orcid.org/0000-0003-1806-4056, Hassanpour, A orcid.org/0000-0002-7756-1506 et al. (1 more author) (2020) A digital-based approach for characterising spread powder layer in additive manufacturing. Materials & Design, 196. 109102. ISSN 0261-3069
Abstract
Assessing the quality of a spread powder layer is critical to understanding powder spreadability in additive manufacturing. However, the small layer thickness presents a great challenge for a systematic and consistent characterisation of the spread layer. In this study, a novel digital-based characterisation approach is proposed based on space discretization, with an emphasis on the characteristics that is important to powder-bed-based additive manufacturing. With the developed approach, the spread powder layer can be qualitatively illustrated by contour maps and quantified by statistical distributions of packing density, surface profile and pore characteristics. For the first time, two types of pores are proposed for the spread powder layer. The density pore can identify those less populated areas while the chamber pore is able to quantify the size of empty patches observed in the spread powder bed. Applicability of this approach is demonstrated via both simulation-generated and experimentally spread powder layers. Sensitivity tests on the sampling parameters are conducted. This digital-based characterisation method is general and can be applied to both polydisperse and non-spherical particle systems, not only enriching detailed structural analysis of the spread layer but also allowing us to quantitatively evaluate powder spreadability in additive manufacturing.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Powder spreading; Additive manufacturing; Discrete element method; Chamber pore; Density pore |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/P006566/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 07 Sep 2020 11:26 |
Last Modified: | 25 Jun 2023 22:24 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.matdes.2020.109102 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:165153 |