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Dense Discrete Phase Model Coupled with Kinetic Theory of Granular Flow to Improve Predictions of Bubbling Fluidized Bed Hydrodynamics
Formation, expansion, and breakage of bubbles in single bubble and freely bubbling fluidized beds were studied using an improved hybrid Lagrangian-Eulerian computational fluid dynamics (CFD) approach. Dense Discrete Phase Model (DDPM) is a novel approach to simulate industrial scale fluidized bed reactors with polydispersed particles. The model uses a hybrid Lagrangian-Eulerian approach to track the particle parcels (lumping several particles in one computational cell) in a Lagrangian framework according to Newton’s laws of motion. The interactions between particles are estimated by the gradient of solids stress solved in Eulerian grid. In this work, a single bubble fluidized bed and a freely bubbling fluidized bed were simulated using DDPM coupled with kinetic theory of granular flows (KTGF). The solid stress was improved to include both tangential and normal forces compared to current hybrid methods with the consideration of only normal stress or solid pressure. The results showed that solid pressure (normal forces) as the only contributor in solid stress would lead to overprediction of bubble size and overlooking of bubble breakage in a single bubble bed. Also, the results showed the improved model had a good prediction of bubble path in a freely bubbling bed compared to solid pressure-based model. It was shown that increasing the restitution coefficient increased the particle content of the bubbles and it lead to less breakage during the formation of the bubble. The probability of formation of bubbles was compared with experimental results and solid stress model showed less discrepancies compared to the solid pressure-based model.
Dense Discrete Phase Model Coupled with Kinetic Theory of Granular Flow to Improve Predictions of Bubbling Fluidized Bed Hydrodynamics
Formation, expansion, and breakage of bubbles in single bubble and freely bubbling fluidized beds were studied using an improved hybrid Lagrangian-Eulerian computational fluid dynamics (CFD) approach. Dense Discrete Phase Model (DDPM) is a novel approach to simulate industrial scale fluidized bed reactors with polydispersed particles. The model uses a hybrid Lagrangian-Eulerian approach to track the particle parcels (lumping several particles in one computational cell) in a Lagrangian framework according to Newton’s laws of motion. The interactions between particles are estimated by the gradient of solids stress solved in Eulerian grid. In this work, a single bubble fluidized bed and a freely bubbling fluidized bed were simulated using DDPM coupled with kinetic theory of granular flows (KTGF). The solid stress was improved to include both tangential and normal forces compared to current hybrid methods with the consideration of only normal stress or solid pressure. The results showed that solid pressure (normal forces) as the only contributor in solid stress would lead to overprediction of bubble size and overlooking of bubble breakage in a single bubble bed. Also, the results showed the improved model had a good prediction of bubble path in a freely bubbling bed compared to solid pressure-based model. It was shown that increasing the restitution coefficient increased the particle content of the bubbles and it lead to less breakage during the formation of the bubble. The probability of formation of bubbles was compared with experimental results and solid stress model showed less discrepancies compared to the solid pressure-based model.
Dense Discrete Phase Model Coupled with Kinetic Theory of Granular Flow to Improve Predictions of Bubbling Fluidized Bed Hydrodynamics
Abolhasan Hashemisohi (author) / Lijun Wang (author) / Abolghasem Shahbazi (author)
2018
Article (Journal)
Electronic Resource
Unknown
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