Numerical simulation of dendritic growth and porosity evolution in solidification of Al-Cu alloy with lattice Boltzmann-Cellular automata method
- Authors
- Lee, Wonjoo; Bae, Junho; Lee, Howon; Kang, Seong-hoon; Yoon, Jonghun
- Issue Date
- Dec-2022
- Publisher
- Elsevier BV
- Keywords
- Lattice Boltzmann method (LBM); Cellular automata (CA); Dendritic growth; Solidification; Gas porosity
- Citation
- Journal of Alloys and Compounds, v.929, pp 1 - 11
- Pages
- 11
- Indexed
- SCIE
SCOPUS
- Journal Title
- Journal of Alloys and Compounds
- Volume
- 929
- Start Page
- 1
- End Page
- 11
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/112645
- DOI
- 10.1016/j.jallcom.2022.167233
- ISSN
- 0925-8388
1873-4669
- Abstract
- A multi-phase lattice Boltzmann method-cellular automata (LBM-CA) model is developed for the micro -structural morphologies of dendritic growth and porosity evolution in the solidified Al-Cu alloy. The pro-posed model can simulate the dendritic growth and porosity evolution during solidification taking account for the solidification conditions such as cooling rates and initial hydrogen concentration. LB and CA were adopted to simulate the diffusion of alloy solute and hydrogen in liquid melt and phase transition during solidification, respectively. Microstructural morphologies including the formation of gas porosity and the growth of solid phase were visualized with different solidification conditions. The simulation results were validated by comparing with experiment data reported in the literature in terms of the percentage of porosity and morphology tendency with respect to the solidification conditions. The pore size decreased when applying the higher cooling rate due to the insufficient growth time. Apparently, the higher initial hydrogen concentration led to the higher percentage of the porosity. The proposed model can be utilized to optimize the solidification conditions for reducing porosity defect in solidified material including 3D printing and welding process as well as casting process. (c) 2022 Elsevier B.V. All rights reserved.
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