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Abstract
Particle shape complicates the tribocharging behavior in pneumatic conveying, and the resulting performance is complex and poorly understood. This study further develops our recent model, which combines computational fluid dynamic (CFD) and the discrete element method (DEM), to simulate particle tribocharging in horizontal pneumatic conveying of superquadric particles. Charge transfer is modeled using the condenser model, which incorporates impact and frictional charges. After validation, the CFD-DEM model is used to investigate the effect of ellipsoid aspect ratio (AR) on tribocharging, revealing the impacts of flow regime and the underlying particle-particle/wall (P-P/W) interactions on charge transfer across flat and elongated particle shapes. The results show that the specific charge increases with lower sphericities due to larger P-W contact areas. Frequent P-P/W interactions and plug formations for prolate particles lead to smooth charging curves, while induced Coulomb forces prevent oblate particles (AR = 0.455 and 0.526) from forming plugs, resulting in unsmooth charging curves. The synergic effects of tribocharging and particle shape on pressure drop, mass flow rate, and flow regime have also been unveiled. It is shown that non-spherical particle shapes lead to increased pressure drop and mass flow rate with higher fluctuations, while tribocharging decelerates particle velocity due to intensified P-W interactions caused by cohesive Coulomb force, resulting in a higher pressure drop and lower mass flow rate with reduced fluctuations. No plugs are observed for extreme oblate shapes (AR = 0.455 and 0.526) because of induced Coulomb forces, leading to decreased and stable pressure drop and mass flow rate.
Original language | English |
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Article number | 115894 |
Number of pages | 18 |
Journal | Applied Mathematical Modelling |
Volume | 140 |
DOIs | |
Publication status | Published - Apr 2025 |
Keywords
- CFD-DEM
- Non-spherical particles
- Pneumatic conveying
- Superquadric
- Tribocharging
Projects
- 1 Active
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ARC Research Hub for Smart Process Design and Control
Yu, A. (Primary Chief Investigator (PCI)), Strezov, V. (Chief Investigator (CI)), Bao, J. (Chief Investigator (CI)), Wang, G. (Chief Investigator (CI)), Shen, Y. (Chief Investigator (CI)), Rudman, M. (Chief Investigator (CI)), Zhao, D. (Chief Investigator (CI)), Yan, W. (Chief Investigator (CI)), Zou, R. (Chief Investigator (CI)), Chen, C. (Chief Investigator (CI)), Kuang, S. (Chief Investigator (CI)), Selomulya, C. (Chief Investigator (CI)), Yang, R. (Chief Investigator (CI)), Dong, K. (Chief Investigator (CI)), Zhu, H. (Chief Investigator (CI)), Zeng, Q. (Chief Investigator (CI)), Jiang, Y. (Chief Investigator (CI)), Steel, K. (Chief Investigator (CI)), Ma, X. (Chief Investigator (CI)), mingyuan, L. (Chief Investigator (CI)), Evans, T. J. (Partner Investigator (PI)), Song, S. (Partner Investigator (PI)), Mao, X. (Partner Investigator (PI)), Ye, X. (Partner Investigator (PI)), Cheng, G. (Partner Investigator (PI)), Zhou, Z. (Partner Investigator (PI)), Qiu, T. (Partner Investigator (PI)), Sakai, M. (Partner Investigator (PI)), de Ryck, A. (Partner Investigator (PI)), Luding, S. (Partner Investigator (PI)) & Ching, T. (Project Manager)
Australian Research Council (ARC), Monash University – Internal Faculty Contribution, Rio Tinto Services Limited (Australia)
10/01/24 → 10/01/29
Project: Research