Flow Maldistribution in Dense- and Sock-Loaded Trilobe Catalyst Trickle-Bed Reactors: Experimental Data and Modeling Using Neural Network

In order to experimentally study the catalyst loading method (dense and sock) influence on liquid distribution, a trickle-bed reactor (TBR) packed with extrudate trilobe catalysts was used. Furthermore, an artificial neural network (ANN) algorithm has been applied; the results show acceptable agreement between the ANN model prediction and experimental data. Due to the isotropic distribution of porosity in sock-loaded bed with trilobe catalysts, the results illustrate that with the same operating conditions the sock-packed beds spread liquid better than dense ones. The effects of bed height and variations of gas/liquid flow rate on liquid distribution in sock- and dense-loaded TBRs have been investigated.