APPLICATION OF EVOLUTIONARY POLYNOMIAL REGRESSION IN ULTRAFILTRATION SYSTEMS CONSIDERING THE EFFECT OF DIFFERENT PARAMETERS ON OILY WASTEWATER TREATMENT

• Main Authors: Amin Reyhani, Mahmood Hemmati, Fatemeh Rekabdar, Mehdi Ahmadi
• Format: Article
• Language: English
• Published: Reaserch Institute of Petroleum Industry 2013-04-01
• Series: Journal of Petroleum Science and Technology
• Subjects: ultrafiltration; wastewater; fouling; rejection; evolutionary polynomial regression
• Online Access: https://jpst.ripi.ir/article_2_6cd7803013f978af0cea7091d86657e7.pdf

In the present work, the effects of operating conditions including pH, transmembrane pressure, oil concentration, and temperature on fouling resistance and the rejection of turbidity for a polymeric membrane in an ultrafiltration system of wastewater treatment were studied. A new modeling technique called evolutionary polynomial regression (EPR) was investigated. EPR is a method based on regression algorithm, which combines the best properties of the conventional numerical regression technique. This paper employs the capability of EPR as a powerful tool to develop a formula with a variable number of polynomial coefficients. Herein, the evolutionary polynomial regression approach is adopted on two parametric studies, i.e. total fouling resistance and rejection rate. These parameters are all evaluated as a function of some mentioned independent variables. Maximum average error and minimum average error are obtained to be equal to 4.25% and 0.05%, respectively. Therefore, EPR is a practical and useful method to describe a membrane performance.