Experimental and numerical investigation of liquid-solid binary fluidized beds： Radioactive particle tracking technique and dense discrete phase model simulations

Liquid-solid binary fluidized beds are widely used in many industries. However, the flow behavior of such beds is not well understood due to the lack of accurate experimental and numerical data. In the current study, the behavior of monodisperse and binary liquid-solid fluidized beds of the same density but dif- ferent sizes is investigated using radioactive particle tracking （RPT） technique and a dense discrete phase model （DDPM）. Experiments and simulations are performed in monodisperse fluidized beds containing two different sizes of glass beads （0.6 and I mm） and a binary fluidized bed of the same particles for vari- ous bed compositions. The results show that both RPT and DDPM can predict the mixing and segregation pattern in liquid-solid binary fluidized beds. The mean velocity predictions of DDPM are in good agree- ment with the experimental findings for both monodisperse and binary fluidized beds. However, the axial root mean square velocity predictions are only reasonable for bigger particles. Particle-particle interac- tions are found to be critical for predicting the flow behavior of solids in liquid-solid binary fluidized beds.

Agglomerate behavior in a recirculating fluidized bed with sheds： Effect of ring baffles

The radioactive particle tracking technique was used to study the effect of internal ring baffles on wet agglomerate motion inside a cold flow recirculating fluidized bed. The study found that using such a baffle on its own or above the regular sheds helps reduce the fouling of the stripper section by increasing the residence time that the agglomerates spend above the baffle, thereby reducing the release of the vapors below the baffles that cause fouling of the sheds. Adding down-comers, or flux tubes, to the ring baffles degrades the performance of the baffles, Reducing the length of the flux tubes, so that they do not reach the bottom of the baffle lip results in a further degradation in baffle performance.

Validation of CFD-DEM simulation of a liquid-solid fluidized bed by dynamic analysis of time series

Liquid-solid fluidized beds(LSFB)modeling validation is crucial for establishing design rules and monitor-ing tools.However,it generally relies on comparing global variables,which overlook dynamic features that influence reaction outputs.This work aims to implement time series analysis tools to compare Radioactive Particle Tracking data with a simulation consisting of Computational Fluid Dynamics cou-pled with Discrete-Element Method.Experiments have been performed in a pilot-scale LSFB of calcium alginate spheres fluidized with a calcium chloride solution.The Diks'test indicates that the simulation can capture the LSFB behavior.It also allows diagnosing flow regime transitions from the simulation.Trends of solid dispersion coefficients and mixing times predicted by the simulation are in good agreement with the experiments.

Ensuring adequate statistics in particle tracking experiments

Particle tracking techniques such as magnetic particle tracking,radioactive particle tracking and positron emission particle tracking are widely used in academia and industry to image the dynamics of particulate and multiphase systems.These techniques can provide detailed data concerning a range of important,whole-field quantities based only on the time-averaged dynamics of a small number of tracer particles.However,in order for this data to be reliable,the duration over which these time-averages are taken must be suitably long.Further,the‘minimum averaging time’required to produce good statistics depends sensitively on the system in question and,at present,cannot be determined a priori in advance of an experiment.In this paper,we take a step toward resolving this issue,using discrete element method simulations of a simple vibrofluidised granular bed to develop a series of scaling laws relating said minimum averaging time to a variety of key system variables.The scaling laws developed may be used by future experimentalists to predict the required averaging time for each given system during an experimental campaign,thus improving both the efficiency with which particle tracking techniques may be applied,and the reliability of the data produced thereby.