Based upon the two fluid model (TFM) theory, a CFD model was implemented to investigate a cold multiphase-fluidized bubbling bed reactor. The key variable used to characterize the fluid dynamic of the experimental system, and compare it to model predictions, was the time-pressure drop induced by the bubble motion across the bed. This time signal was then processed to obtain the power spectral density (PSD) distribution of pressure fluctuations. As an important aspect of this work, the effect of the sampling time scale on the empirical power spectral density (PSD) was investigated. A time scale of 40 s was found to be a good compromise ensuring both simulation performance and numerical validation consistency. The CFD model was first numerically verified by mesh refinement process, after what it was used to investigate the sensitivity with regards to minimum fluidization velocity (as a calibration point for drag law), restitution coefficient, and solid pressure term while assessing his accuracy in matching the empirical PSD. The 2D model provided a fair match with the empirical time-averaged pressure drop, the relating fluctuations amplitude, and the signal’s energy computed as integral of the PSD. A 3D version of the TFM was also used and it improved the match with the empirical PSD in the very first part of the frequency spectrum.
A 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.
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