The application of error function for normalized flux prediction in dead-end microfiltration (MF) process

ABSTRACT

In this paper, error function was proposed for the first time to predict the normalized flux in dead-end microfiltration process at different operating conditions (transmembrane pressure, concentration, and temperature) using various feed suspensions and membranes. The results showed that the predictions of proposed model had good agreements with experimental data. In addition, model parameter k is analyzed quantificational by using multivariate nonlinear regression method. Moreover, the proposed model also showed high predictive accuracy (2.88%) than cake models (4.48%), and two empirical models (A (6.19%) and B (35.7%)).

KEYWORDS:

• Dead-end
• Flux prediction model
• Error function
• Operating conditions

Acknowledgements

The authors wish to thank the National Natural Science Foundation of China (Project No. 21476006) for the financial support of this study.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [Project No. 21476006].