PREDICTING THE FILTRATION OF NONCOAGULATING PARTICLES IN-DEPTH FILTERS

A predictive model is developed for the filtration of noncoagulating p articles in packed-bed depth filters. The model uses the trajectory an alysis results of Rajagopalan and Tien (1976, A.I.Ch.E. J. 22, 523-533 ) to calculate initial collection efficiencies of the granular media. Stochastic simulations of particle deposition are used to predict the decrease in collection efficiency that results from deposited particle s not only occupying sites on the collector but also shadowing large d eposition areas. A comparison of model predictions with data obtained from batch latex filtration experiments showed qualitative but not qua ntitative agreement. The observed decrease in collection efficiency co uld be described by a simple empirical expression, characterized by a single shadowing exponent, that was first suggested by Terranova and B urns (1991, Biotechnol. Bioengng 37, 110-120). By developing a correla tion for the shadowing exponent from the stochastic simulations and ad justing the expression for the initial collection efficiency, reasonab ly accurate model predictions could be made once the model parameters from a single experiment were determined. A study of the effect of dim ensionless model parameters on predicted breakthrough curves showed th at the optimal operating conditions to filter a given liquid suspensio n occur when the ratio of the particle-to-collector diameter is maximi zed. An approximate analytical solution is also developed to predict b reakthrough behavior in lieu of a numerical solution. Copyright (C) 19 96 Elsevier Science Ltd