Fluid Dynamics Of Turbulent Fluidized Beds For Geldart S Group B Particles
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Fluid Dynamics of Turbulent Fluidized Beds for Geldart’s Group B Particles
An in-depth experimental study of the fluid dynamics of turbulent fluidized beds with particles of Geldart’s Group B was carried out. For this purpose, fluidization behavior was investigated in different fluidized bed plants having diameters in the range of 0.05 m to 1 m. Pressure fluctuation analysis has been used as an identification tool for the turbulent fluidized bed regime. Different fluidization conditions have been investigated by variation of the fluidized bed properties, the bed material properties, and the gas properties. Based on the measured data, a correlation predicting the transition velocity from bubbling to turbulent fluidization is introduced. To investigate the local flow structure, capacitance probe measurements have been carried out. Using this measurement technique, local solids concentrations and properties of rising bubbles have been determined and analyzed. Finally, an empiric fluid dynamic model was developed using the local measurement data. It is mainly based on capacitance probe measurements and shows high accuracy in comparison to pressure data.
Role of Mathematical Modeling in Advanced Power Generation Systems
Energy demands throughout the globe has been increasing and the detrimental effects of carbon emissions on the environment by use of non-renewable resources has impacted life on the planet. The changing climate has caused an increase in natural calamities all over the globe. Many countries in the world have started to produce power using renewable resources like solar, biomass, wind energy, nuclear energy and green fuels. Though there are several technologies for power generation using the above sources, efficient design of these systems still needs lot of research. Mathematical modeling would play a vital role in design of state of the art technologies. Advanced nuclear power plants need special mention since they involve naturally driven safety systems where the complex phenomena of boiling, condensation and thermal stratification take place. These are difficult to model as there is more than one phase coupled with turbulence models, near wall phenomena, coalescence and break up, etc. Scaling up of such systems and their innovative design to reduce stratification requires the help of mathematical modeling. Other opportunities include Computational Fluid Dynamics (CFD) modeling for design of wind turbines for power generation using wind energy. Power generation from biomass involves use of gasifiers which has complex set of reactions and mostly two or three phases which are difficult to model using CFD at industrial scales.
Computational Transport Phenomena of Multiphase Systems and Fluidization
This book focuses on the modeling of gas-solid, liquid-solid, non-Newtonian fluid-solid, and supercritical fluid-solid fluidized beds and multiphase flows. Simulation techniques are categorized into Euler–Euler with kinetic theory of granular flow (KTGF) and Euler–Lagrange with discrete element method (DEM) approaches. Both the governing equations and numerical implementations are presented. A new CFD-KTGF-DEM approach describes phase interactions, free from the empirical restitution coefficient used in KTGF, and accounts for turbulence effects on discrete particle motion, which DEM cannot achieve. Additionally, a low Stokes number KTGF model is introduced, incorporating the interstitial fluid's effect, unlike the classical KTGF, which assumes vacuum conditions. Special attention is given to momentum exchange between heterogeneous and homogeneous flows in fluidized beds and multiphase systems, and various multiscale drag models are presented. The book also discusses the application of these approaches in fluid-solid fluidized bed reactors and oil-gas drilling processes.