M. R. Khadilkar

Comparison of trickle-bed and upflow reactor performance at high pressure: Model predictions and experimental observations

Comparison of laboratory trickle-bed and up-flow reactors over a range of operating conditions, which cover both gas and liquid reactant limitations, has been investigated using hydrogenation of alpha-methylstyrene to cumene in a hexane solvent over 2.5% Pd on alumina extrudate catalyst as a test reaction. The results show that when the reaction is gas limited at low pressure and high liquid feed concentration, trickle bed reactor outperforms the upflow reactor. At high pressure and low liquid feed concentration, the reaction becomes liquid limited and upflow reactor performs better. It is concluded that the advantage of upflow or downflow depends on the reaction system type (i.e. whether the reaction is liquid or gas limited). A single criterion for identifying the limiting reactant is proposed which can explain most of the data reported in the literature on these reactors. Comparison of the experimental observations and the predictions of the reactor scale and pellet scale models available in the literature is presented.

CFD modeling of multiphase flow distribution in catalytic packed bed reactors: scale down issues

Flow maldistribution in either a bench-scale or commercial scale packed bed is often responsible for the failure of the scale down unit to mimic the performance of the large reactor. The modeling of multiphase flow in a bench-scale unit is needed for proper interpretation of reaction rate data obtained in such units. Understanding the mechanism of flow maldistribution is the first step to avoiding it. In order to achieve this objective, computational fluid dynamic (CFD) simulations of multiphase flow under steady state and unsteady state conditions in bench-scale cylindrical and rectangular packed beds are presented for the first time. The porosity distribution in packed beds is implemented into CFD simulation by pseudo-randomly assigned cell porosity values within certain constraints. The flow simulation results provide valuable information on velocity, pressure, and phase holdup distribution.

Two-phase flow distribution in 2D trickle-bed reactors

An extended discrete cell model (DCM), based on minimization of energy dissipation rate, is applied to predict two-phase flow distribution in the two-dimensional trickle-bed reactors. The main advantages of DCM are that it can qualitatively capture the experimental observations, and readily distinguish between flow distribution in prewetted and non-prewetted beds, as well as reflect the effects of bed structure and inlet liquid distributor on two phase flow distribution. For comparison purpose, the results of liquid distribution obtained by DCM are compared with both computational fluid dynamics (CFD) simulations and experimental observations in a 2D bed. The achieved qualitative and quantitative agreement justifies the use of DCM in predicting two phase flow distribution in packed beds. A particle wetting factor (f) has been introduced into DCM to account for the influence of particle surface wetting on liquid flow distribution. Analysis of DCM simulations presented based on maldistribution factor (mf ) provides a convenient way of quantifying the effects of particle surface wetting, distributor design and bed depth on the two-phase flow field.

Evaluation of trickle bed reactor models for a liquid limited reaction

The isothermal decomposition of hydrogen peroxide on a CuCr catalyst in a laboratory scale trickle bed reactor was used to test model predictions of the dependence of liquid reactant conversion on space time for different operating conditions. It is assured that the decomposition of hydrogen peroxide is a first order liquid-limited reaction. Comparison of model predictions and experimental data indicates that both external mass transfer effects and incomplete external catalyst wetting need to be accounted for. Dudukovics (1977) approximate model for the catalyst effectiveness factor adequately simulates both effects.