Study of Dead-End Microfiltration Flux Variety Law, Part II: Choice of Favorable Model Parameter

Abstract

The applicability of model predictive accuracy and the selection of suitable model parameters for the membrane flux prediction and prediction of the filtration characteristics of dead-end filtration systems were assessed. In determining the model predictive accuracy using model parameters, the selection of suitable model parameters is of great significance. A series of experiments were conducted. The relative deviations, average deviations, and root mean square between the experimental and predicted values were calculated to evaluate predictive accuracy. The results showed that the model parameter has changed nonlinearly with operating conditions. Particularly, in the membrane flux prediction model, the time-dependent character of the model parameter can result in a considerable error. However, model prediction accuracy can be improved indisputably and the model will get higher predictive accuracy than that of other predictive models if the constant membrane fouling index in the flux prediction model is either replaced by the average membrane fouling index or it takes a composite parameter with free combination of the initial membrane fouling index, meantime, minimum and the maximum of the model parameter. These results give us a possibility to see the panorama of the variation of the model parameters in different situations and an idea to establish the foundation for building mathematical models.