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Numerical simulation and analytical modelling of temperature and morphology of melt pool in electron beam powder bed fusion of copper

融合 材料科学 阴极射线 形态学(生物学) 计算机模拟 电子 机械 机械工程 冶金 地质学 工程类 物理 核物理学 哲学 语言学 古生物学
作者
Elmira Sharabian,Mahyar Khorasani,Stefan Gulizia,Amir Hossein Ghasemi,Eric MacDonald,David Downing,Bernard Rolfe,Milan Brandt,Martin Leary
出处
期刊:Rapid Prototyping Journal [Emerald Publishing Limited]
卷期号:31 (1): 127-144 被引量:3
标识
DOI:10.1108/rpj-03-2024-0141
摘要

Purpose This study aims to comprehensively investigate the electron beam powder bed fusion (EB-PBF) process for copper, offering validated estimations of melt pool temperature and morphology through numerical and analytical approaches. This work also assesses how process parameters influence the temperature fluctuations and the morphological changes of the melt pool. Design/methodology/approach Two distinct methods, an analytical model and a numerical simulation, were used to assess temperature profiles, melt pool morphology and associated heat transfer mechanisms, including conduction and keyhole mode. The analytical model considers conduction as the dominant heat transfer mechanism; the numerical model also includes convection and radiation, incorporating specific parameters such as beam power, scan speed, thermophysical material properties and powder interactions. Findings Both the analytical model and numerical simulations are highly correlated. Results indicated that the analytical model, emphasising material conduction, exhibited exceptional precision, although at substantially reduced cost. Statistical analysis of numerical outcomes underscored the substantial impact of beam power and scan speed on melt pool morphology and temperature in EB-PBF of copper. Originality/value This numerical simulation of copper in EB-PBF is the first high-fidelity model to consider the interaction between powder and substrate comprehensively. It accurately captures material properties, powder size distribution, thermal dynamics (including heat transfer between powder and substrate), phase changes and fluid dynamics. The model also integrates advanced computational methods such as computational fluid dynamics and discrete element method. The proposed model and simulation offer a valuable predictive tool for melt pool temperature, heat transfer processes and morphology. These insights are critical for ensuring the bonding quality of subsequent layers and, consequently, influencing the overall quality of the printed parts.
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