Abstract
A new method is proposed for efficiently predicting filter cake resistance as a function of crystal size distribution. The method is useful for the preliminary design of processes where an economic tradeoff is encountered between a crystallization step and a filtration step. In that case it is necessary to estimate the filter cake resistance repeatedly as a function of crystal size distribution for the process design and optimization. The method is faster than CFD-DEM and more precise than the random packing assumption. The proposed method is validated using published experimental data. To demonstrate the proposed method, an integrated crystallization-filtration process of ammonium alum is simulated and analyzed. The results show that by increasing the residence time of ammonium alum crystals in the crystallizer from 15 min to 60 min, the crystal cake resistance can be reduced by 42% and the filter area can be reduced by 23%.
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