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Numerical investigation of a cold bubbling bed throughout a dense discrete phase model with KTGF collisional closure

Numerical investigation of a cold bubbling bed throughout a dense discrete phase model with KTGF... AbstractA hybrid Euleran-Lagrangian Dense Discrete Particle Model (DDPM) was used to numerically simulate the bubbling behavior of a fluidized bed reactor. The model exploits the parcels concept to reduce the number of particles to simulate while exploiting the Kinetic Theory of Granular Flow (KTGF) to account for their repulsive interactions. The DDPM-KTGF was explored throughout a model sensitivity analysis to identify the most influent parameters impacting on the numerical accuracy and performances to ultimately assess its potential use for industrial purposes. Because of the measurement simplicity as well as its strong connection with the bed fluid-dynamic, pressure-drop data was used and processed to obtain the power spectral density (PSD) distribution to empirically and numerically characterize the behavior of this system under a bubbling fluidization regime. The DDPM-KTGF model was found to be sensitive to mesh size, restitution coefficients but mostly to the drag law. However, poor sensitivity to the kinetic viscosity, solid pressure, radial distribution function as well as to the number of parcels was revealed. Besides having an effect on the physical outputs, the mesh refinement was also required to numerically verify the model which also had a significant impact on the simulation time-performance. Moreover, a major barrier was found when using this model to simulate fixed bed regime, showing the limitation of the KTGF approach to high particle density regions as a result of a poor estimation of particles force interactions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biofuels Engineering de Gruyter

Numerical investigation of a cold bubbling bed throughout a dense discrete phase model with KTGF collisional closure

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Publisher
de Gruyter
Copyright
© 2018
ISSN
2084-7181
eISSN
2084-7181
DOI
10.1515/bfuel-2017-0003
Publisher site
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Abstract

AbstractA hybrid Euleran-Lagrangian Dense Discrete Particle Model (DDPM) was used to numerically simulate the bubbling behavior of a fluidized bed reactor. The model exploits the parcels concept to reduce the number of particles to simulate while exploiting the Kinetic Theory of Granular Flow (KTGF) to account for their repulsive interactions. The DDPM-KTGF was explored throughout a model sensitivity analysis to identify the most influent parameters impacting on the numerical accuracy and performances to ultimately assess its potential use for industrial purposes. Because of the measurement simplicity as well as its strong connection with the bed fluid-dynamic, pressure-drop data was used and processed to obtain the power spectral density (PSD) distribution to empirically and numerically characterize the behavior of this system under a bubbling fluidization regime. The DDPM-KTGF model was found to be sensitive to mesh size, restitution coefficients but mostly to the drag law. However, poor sensitivity to the kinetic viscosity, solid pressure, radial distribution function as well as to the number of parcels was revealed. Besides having an effect on the physical outputs, the mesh refinement was also required to numerically verify the model which also had a significant impact on the simulation time-performance. Moreover, a major barrier was found when using this model to simulate fixed bed regime, showing the limitation of the KTGF approach to high particle density regions as a result of a poor estimation of particles force interactions.

Journal

Biofuels Engineering – de Gruyter

Published: Dec 29, 2017

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