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CFD Modeling of Cavitation for Fine Particle Flotation Open Access


Other title
Type of item
Degree grantor
University of Alberta
Author or creator
Hosseininejad, Seyed Shaham Aldin
Supervisor and department
Hayes,Robert E. (Chemical and Materials Engineering)
Examining committee member and department
Fradette, Louis (Chemical Engineering)
Xu, Zhenghe (Chemical and Materials Engineering)
Liu, Qingxia (Chemical and Materials Engineering)
Yeung, Tony (Chemical and Materials Engineering)
Department of Chemical and Materials Engineering
Chemical Engineering
Date accepted
Graduation date
Doctor of Philosophy
Degree level
To overcome the challenges of low recovery of fine particles in flotation processes, designing a cavitating device that can enhance the recovery has been a major topic of study. In the design of a cavitating device, the bubble/bubble interactions, bubble response to the change of local pressure, and the effect of dissolved gas in the liquid are the points of interest. In this study, CFD is used to develop cavitation models that include the physical models related to these phenomena. From existing cavitation models, Singhal cavitation model is the only model that accounts for the effect of non-condensable gasses in the flow regime without including the bubble/bubble interactions. In this study, furthermore to the Singhal model being used to study the cavitation inception, two Lagrangian and Eulerian approaches for modeling of the bubbly flow are implemented in Ansys-Fluent to measure the bubble size distribution. The Eulerian method (PBM) implements a population balance equation to study the changes of bubble size distribution due to pressure, coalescence, breakage, gas diffusion and nucleation. The Lagrangian method (DBM) implements discrete particle tracking method to track each bubble individually, with the bubble dynamics, bubble coalescence/breakage, and gas diffusion models being implemented in three-way coupling. For verification, each implemented model is, separately, compared to the experimental results from literature. Some challenges in the procedure of model development are investigated and solutions are found to the model application process. Then, the two developed models, with the Singhal cavitation model, are compared to the in-house experimental results of cavitation inception and the bubble size distribution in a venturi tube. Acceptable agreement between the modeling and the experimental results is observed. Finally, the Population Balance Model (PBM) and Discrete Bubble Model (DBM) are implemented in a case study of investigating the best location of the air injection into the studied venturi. The objective is to maximize the collection of upstream nuclei by the bubble injected in the middle of the flow in the venturi.
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