Performance of a rotating-anode electrocoagulation reactor for turbidity and hardness removal from high-salinity lake water

Abstract

ABSTRACT An electrocoagulation (EC) emerging reactor with a rotating anode was constructed to study its effectiveness in removing turbidity and total hardness from samples of Lake water. The EC process was carried out under varying operational parameters, including rotation speed (SR), current density, inter-electrode distance, electrolysis duration (RT), and solution pH. The optimum operational parameters were set at 75 rpm, 6 mA cm−2, 20 min, pH 8, and 10 mm, respectively. The effect of the rotating anode was adopted as the central focus of analysis to examine the nature and extent of its impact on the obtained results. The results showed high removal efficiencies of 88.3% for turbidity and 65.8 for total hardness, as well as low energy consumption and reduced electrode usage, resulting in a total operating cost of 0.192 US$ m−3. Furthermore, the study showed that the artificial neural network (ANN) model can successfully predict removal efficiencies for turbidity and total hardness. The optimized ANN architecture achieved a low mean squared error (MSE, 0.000644) and a high correlation coefficient (R = 0.97992) during the network training stage. The results indicate that the ANN model successfully captured the nonlinear relationships between the operational parameters and treatment performance.