A numerical model for predicting powder characteristics in LMD considering particle interaction

GUNER, Ahmet, BIDARE, Prveen, JIMÉNEZ, Amaia, SHU, Chang, KOVACEV, Nikolina and ESSA, Khamis (2024). A numerical model for predicting powder characteristics in LMD considering particle interaction. Advanced Powder Technology, 35 (3): 104348.

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Official URL: http://dx.doi.org/10.1016/j.apt.2024.104348
Open Access URL: https://www.sciencedirect.com/science/article/pii/... (Published version)
Link to published version:: https://doi.org/10.1016/j.apt.2024.104348


In this work, a numerical model is proposed to analyze the influence of particle–particle interaction in laser directed energy deposition or LMD (laser metal deposition) of CM247 Ni-based superalloy. The model is based on the analysis of contact between particles and the potential agglomeration of powder to predict powder conditions at the nozzle exit. Simulation results were experimentally validated and a good agreement was observed. At the nozzle exit mainly large particles (>100 lm) are found and small ones (<10 lm) tend to flow away from this region. This was also observed in the experimental PSD. Additionally, based on the relative velocity of particles, simulations are able to predict the formation of dents. In comparing virgin powder PSD and the one at the nozzle exit, it was observed that largest particles are collected at the exit. In order to explain this phenomena, particle agglomeration was analysed numerically. It was seen that small particles tend to adhere to the big ones due to their higher adhesive forces, which would explain the change in PSD.

Item Type: Article
Uncontrolled Keywords: 0904 Chemical Engineering; 0913 Mechanical Engineering; 0914 Resources Engineering and Extractive Metallurgy; Chemical Engineering; 4004 Chemical engineering; 4016 Materials engineering
Identification Number: https://doi.org/10.1016/j.apt.2024.104348
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 06 Feb 2024 14:26
Last Modified: 06 Feb 2024 14:30
URI: https://shura.shu.ac.uk/id/eprint/33135

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