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A Genetic Algorithm Based Approach to Coalescence Parameters: Estimation in Liquid‐Liquid Extraction Columns
Authors:A Hasseine  A‐H Meniai  M Korichi  M Bencheikh Lehocine  H‐J Bart
Abstract:The population balance model is a useful tool for the design and prediction of a range of processes that involve dispersed phases and particulates. The inverse problem method for the droplet population balance model is applied to estimate coalescences parameters for two‐phase liquid‐liquid systems. This is undertaken for two systems, namely toluene/water and n‐butyl acetate/water in a rotating disc contactor (RDC), using a droplet population balance model. In the literature, the estimation procedure applied to this problem is often based on the deterministic optimization approach. These methods generate instabilities near a local minimum, inevitably requiring information about the derivatives at each iteration. To overcome these limitations, a method providing an estimate for the coalescences parameters is proposed. It is based on a simple and adapted structure of the genetic algorithm, for this particular problem. The agreement between the experimental observations and the simulations is encouraging and, in particular, the models used have proven to be suitable for the prediction of hold‐up and Sauter diameter profiles for these systems. Finally, these results demonstrate that the optimization procedure proposed is very convenient for estimating the coalescences parameters for extraction column systems.
Keywords:Coalescences  Extraction  Modeling  Two‐Phase systems
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