Lopez-Botello, O., Martinez-Hernandez, U., Ramírez, J. et al. (2 more authors) (2017) Two-dimensional simulation of grain structure growth within selective laser melted AA-2024. Materials and Design, 113. pp. 369-376. ISSN 0261-3069
Abstract
A two-dimensional Cellular Automata (CA) – Finite Element (FE) (CA-FE) coupled model has been developed to predict the microstructures formed during the laser melting of a powdered AA-2024 feedstock using the Additive Manufacturing (AM) process Selective Laser Melting (SLM). The presented CA model is coupled with a thermal FE model, which computes the heat flow characteristics of the SLM process. The developed model considers the powder-to-liquid-to-solid transformation, tracks the interaction between several melt pools within a melted track, and several tracks within various layers. It was found that the calculated temperature profiles as well as the simulated microstructures bared close resemblance with SLM fabricated AA-2024 samples. The developed model was capable of predicting melt pool cooling and solidification rates, the type of microstructure obtained, the size of the melt pool (with 14% error) and the heat affected zone, level of porosity, average grain size number (with 12% error) and the growth competition present in microstructures of components manufactured via SLM.
Metadata
Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/). | ||||
Keywords: | Grain Structure; Cellular Automata; Finite Element; Selective Laser Melting; Additive Manufacturing | ||||
Dates: |
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Institution: | The University of Sheffield | ||||
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) | ||||
Funding Information: |
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Depositing User: | Symplectic Sheffield | ||||
Date Deposited: | 19 Oct 2016 09:07 | ||||
Last Modified: | 28 Nov 2016 13:49 | ||||
Published Version: | http://dx.doi.org/10.1016/j.matdes.2016.10.031 | ||||
Status: | Published | ||||
Publisher: | Elsevier | ||||
Refereed: | Yes | ||||
Identification Number: | https://doi.org/10.1016/j.matdes.2016.10.031 |