A Study of Particle Histories during Spray Drying Using Computational Fluid Dynamic Simulations

Abstract

A study of particle histories during spray drying using computational fluid dynamic simulations --------------------------------------------- AbstractComputational fluid dynamics (CFD) models for short-form and tall-form spray dryers have been developed, assuming constant rate drying and including particle tracking using the source-in-cell method. The predictions from these models have been validated against published experimental data and other simulations. This study differs from previous work in that particle time-histories for velocity, temperature and residence time and their impact positions on walls during spray drying have been extracted from the simulations. Due to wet-bulb protection effects, particle temperatures are often substantially different from gas temperatures, which is important, since the particle temperature-time history has the most direct impact on product quality. The CFD simulation of an existing tallform spray dryer indicated that more than 60% of the particles impacted on the cylindrical wall and this may adversely affect product quality, as solids may adhere to the wall for appreciable times, dry out and lose their wet-bulb protection. The model also predicts differences between the particle primary residence time distributions (RTD) and the gas phase RTD. This study indicates that a short form dryer with a bottom outlet is more suitable for drying of heat sensitive products, such as proteins, due to the low amounts of recirculated gas and hence shorter residence time of the particles.--

Unsteady RANS and detached eddy simulation of the multiphase flow in a co-current spray drying

“…The dried particle size depends on the type of the nozzle used, for instance a twin-fluid nozzle produced a small particle about 20 µm, whereas the pressure atomiser produced larger particles with the mean diameter about 80 µm. The CFD approach used in this work is similar to those described in our earlier work [3], except for the grid and turbulence model employed. The dried particles are collected at the bottom of the cone or through the exit pipe.…”

“…Most of the CFD studies on spray drying process [1,3,7,8,17] were performed by using steady solver. However, the unsteady solver represents the real measurement better and should be able to produce a more accurate result [18].…”

“…Turbulence is not resolved for the discrete phase, but rather modelled as stochastic effects of particle interactions with eddy [11]. Turbulent particle dispersion is considered in the discrete phase model (DPM) as a discrete eddy concept similar to the one used by Anandharamakrishnan et al [3]. The turbulent air flow pattern is assumed to be made up of a collection of randomly directed eddies, each with its own lifetime and size.…”

“…The particles-fluid interaction were modelled using a DPM, and two-way coupling was considered in order to enable the prediction of simultaneous heat and mass transfer during the drying process [3,13]. The combined Eulerian and Lagrangian model were used to obtain the particle trajectories by solving the force balance equation as follows:…”

Residence time distribution of glass ballotini in isothermal swirling flows in a counter-current spray drying tower

“…Anandharamakrishnan et al (2010) carried out CFD modelling of RTD of particles in tall-and short-form co-current spray drying towers undergoing drying. Unfortunately, no direct measurements of the particle flow behaviour and trajectories were available for comparison with the predictions.…”