Modelling of batch ultrafiltration
ABSTRACT A model has been developed which predicts the performance of a batch ultrafiltration. By using the relationship for flux decline proposed by Merin and Cheryan in 1990, an analytical solution is presented. The proposed model includes the initial volume, feed solution concentrations, processing time, retention, membrane area and flux across the membrane. The model predictions are compared with experimental data, and satisfactory agreement is obtained.
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ABSTRACT: In our investigations the membrane filtration of quality wines (Tokaji Harslevelu and Egri Bikaver) - based on diafiltration principles, applying nanofiltration membranes has been studied. For the diafiltration experiments a relatively dense nanofiltration membrane NF 45 has been used, while for simple wine concentrations a membrane developed for organic components rejection NF200 has been investigated. The mixture of the retarded wine compounds was considered the main product of the process. The permeate that crossed the membrane was handled as the by product. Separated wine samples and the original wines have been subjected to gas chromatographic analysis: according to the results the partition of the main components and aroma compounds of the samples was approximately equal between the main and by-product. Membrane separation has been applied in accordance with a "prelaborated" experimental plan, when completing it the effect of operational parameters on the effectiveness of the process has been evaluated and analysed. By mathematical modelling of the phenomenon empirical and quasi-empirical relations were set up, and solutions for the practical realization of the procedure were searched for. Our new model describes the filtration efficiency with our new index in the function of the operational parameters' influence. The significance of the relation is, that the knowledge of the wine-constants might promote the expedient choice of the membrane, which is a primary aspect in planning and creating the process optimal.Acta Alimentaria 12/2010; 1(4):1-1. DOI:10.1556/AAlim.2010.0001 · 0.43 Impact Factor