Development of a predictive model of the limiting current density of an electrodialysis process using response surface methodology

Abstract

Electrodialysis (ED) is known to be a useful membrane process for desalination, concentration, separation, and purification in many fields. In this process, it is desirable to work at high current density in order to achieve fast desalination with the lowest possible effective membrane area. In practice, however, operating currents are restricted by the occurrence of concentration polarization phenomena. Many studies showed the occurrence of a limiting current density (LCD). The limiting current density in the electrodialysis process is an important parameter which determines the electrical resistance and the current utilization. Therefore, its reliable determination is required for designing an efficient electrodialysis plant. The purpose of this study is the development of a predictive model of the limiting current density in an electrodialysis process using response surface methodology (RSM). A two-factor central composite design (CCD) of RSM was used to analyze the effect of operation conditions (the initial salt concentration (C) and the linear flow velocity of solution to be treated (u)) on the limiting current density and to establish a regression model. All experiments were carried out on synthetic brackish water solutions using a laboratory scale electrodialysis cell. The limiting current density for each experiment was determined using the Cowan-Brown method. A suitable regression model for predicting LCD within the ranges of variables used was developed based on experimental results. The proposed mathematical quadratic model was simple. Its quality was evaluated by regression analysis and by the Analysis Of Variance, popularly known as the ANOVA.

Investigation of Histamine Removal by Electrodialysis from the Fermented Fish Sauce and Its Effects on the Flavor

“…To evaluate the safety and quality, the histamine residual amount, 38.00 mg/100 mL, meet the criterion of Commission Regulation (EC) No 2073/2005, and the ANN residual amount, 1.06 g/100 mL, was still higher than the best level of the Chinese industrial standard SB/T 10324-1999 for fish sauce. Applying RSM to optimize the ED operation process has been carried out in many studies [ 51 , 52 , 53 ]. RSM was effective in providing comprehensive and informative insight into the system, by reducing the amount of time and effort required for the investigation of multi-factor, multi-response systems, leading to faster process optimization [ 54 , 55 ].…”

Evaluation of anti‐wetting nano‐fumed silica/PVDF hollow‐fiber membrane by central composite design optimization towards efficient desalination performance via membrane distillation

“…RSM is a statistical analysis that aims to understand the interactions between process variables. Central composite design (CCD) using RSM offers superior predictions in a complex process that involves more than two factors, how the input variables affect the responses and the interaction between several variables, which leads to better fitting of a quadratic model 27 . A few studies have applied RSM to find the optimum membrane and the best performance in MD 26,28‐30 …”

“…Central composite design (CCD) using RSM offers superior predictions in a complex process that involves more than two factors, how the input variables affect the responses and the interaction between several variables, which leads to better fitting of a quadratic model. 27 A few studies have applied RSM to find the optimum membrane and the best performance in MD. 26,[28][29][30] Yet there has not been much work that aims to evaluate the simultaneous control of the effective HF membrane spinning conditions and the membrane modification to find the best optimum HF membrane for the MD process.…”