Title page for ETD etd-06222012-133017

Type of Document Master's Thesis
Author Teaters, Lindsey Claire
Author's Email Address Linzi85@vt.edu
URN etd-06222012-133017
Title A Computational Study of the Hydrodynamics of Gas-Solid Fluidized Beds
Degree Master of Science
Department Mechanical Engineering
Advisory Committee
Advisor Name Title
Battaglia, Francine Committee Chair
Bayandor, Javid Committee Member
Lattimer, Brian Y. Committee Member
  • minimum fluidization velocity
  • pressure drop
  • fluidized beds
Date of Defense 2012-05-31
Availability unrestricted
Computational fluid dynamics (CFD) modeling was used to predict the gas-solid hydrodynamics of fluidized beds. An Eulerian-Eulerian multi-fluid model and granular kinetic theory were used to simulate fluidization and to capture the complex physics associated therewith. The commercial code ANSYS FLUENT was used to study two-dimensional single solids phase glass bead and walnut shell fluidized beds. Current modeling codes only allow for modeling of spherical, uniform-density particles. Owing to the fact that biomass material, such as walnut shell, is abnormally shaped and has non-uniform density, a study was conducted to find the best modeling approach to accurately predict pressure drop, minimum fluidization velocity, and void fraction in the bed. Furthermore, experiments have revealed that all of the bed mass does not completely fluidize due to agglomeration of material between jets in the distributor plate. It was shown that the best modeling approach to capture the physics of the biomass bed was by correcting the amount of mass present in the bed in order to match how much material truly fluidizes experimentally, whereby the initial bed height of the system is altered. The approach was referred to as the SIM approach. A flow regime identification study was also performed on a glass bead fluidized bed to show the distinction between bubbling, slugging, and turbulent flow regimes by examining void fraction contours and bubble dynamics, as well as by comparison of simulated data with an established trend of standard deviation of pressure versus inlet gas velocity. Modeling was carried out with and without turbulence modeling (k-ϵ), to show the effect of turbulence modeling on two-dimensional simulations.
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