PERFORMANCE ANALYSIS AND THE EFFECTS OF KEY PARAMETERS IN SOLID PARTICLE BEDS

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dc.contributor.advisorMetcalfe, Ralph W.
dc.contributor.committeeMemberOstilla-Mónico, Rodolfo
dc.contributor.committeeMemberEhlig-Economides, Christine
dc.contributor.committeeMemberAlba, Kamran
dc.contributor.committeeMemberYang, Di
dc.creatorHossain, Nazmul
dc.creator.orcid0000-0001-5332-0786
dc.date.accessioned2022-09-08T15:02:55Z
dc.date.createdDecember 2021
dc.date.issued2021-12
dc.date.updated2022-09-08T15:02:56Z
dc.description.abstractFluid-solid particle beds have a broad range of industrial applications as packed and fluidized beds. The particle-particle collision, particle-wall interaction, and virtual mass force which initiates from particle motion influencing neighboring particles make it very difficult to analyze the problem experimentally and numerically. This work is focused on assessing the performance of the existing numerical models for determining minimum fluidization velocity (u_mf), the effects of the key parameters in bed optimization, the turbulence-like behavior initiating from three-dimensionality, quantification of bed performance, and jet-like patterns in uniform inflow. The Eulerian 2D model overestimates pressure drop near fluidization, and thus the U_mf from pressure drop slope cannot be determined accurately. We investigated the 2D TFM (Two-Fluid Model) abnormal pressure drop near minimum fluidization and proposed an Euler number as a more accurate alternative determining u_mf. From our research, the Kinetic Theory of Granular Flow (KTGF) model for particle interaction is more impactful near fluidization, and the drag model is more influential at velocities above u_mf. Our simulations have shown that wall effects on the particle bed including frictional losses and wall-particle collision are the dominant reasons for abnormal pressure drop near minimum fluidization. In an annular fluidized bed, 3D TFM showed that particle size is the most dominant factor in u_mf, followed by the particle bed height or overburden. Bed thickness does not influence u_mf for this type of fluidized bed. Our CFD-DEM simulations showed that there is an increase in recirculation zones for increasing bed thickness to particle ratio. An approach to quantifying the effectiveness of solid particle beds has been proposed with heat transfer between fluid and particles using the CFD-DEM approach. A more efficient capped fluidized bed design has been proposed, and the numerical results show the significant advantage of capped beds over packed, and fluidized beds. We also observed repeating cellular patterns in particle motion for very small size particles in large elongated fluidized beds, and jet-like patterns for uniform inflow under periodic boundary conditions. This will help us in understanding chaotic particle motion and in optimizing bed heat transfer in the future.
dc.description.departmentMechanical Engineering, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10657/11008
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectFluidized Bed
dc.subjectMinimum fluidization Velocity
dc.subjectBed Efficiency
dc.subjectPatterns in particle motion
dc.subjectEulerian
dc.subjectCFD-DEM
dc.titlePERFORMANCE ANALYSIS AND THE EFFECTS OF KEY PARAMETERS IN SOLID PARTICLE BEDS
dc.type.dcmiText
dc.type.genreThesis
dcterms.accessRightsThe full text of this item is not available at this time because the student has placed this item under an embargo for a period of time. The Libraries are not authorized to provide a copy of this work during the embargo period.
local.embargo.lift2023-12-01
local.embargo.terms2023-12-01
thesis.degree.collegeCullen College of Engineering
thesis.degree.departmentMechanical Engineering, Department of
thesis.degree.disciplineMechanical Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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