Investigations of coagulation–flocculation process by performance optimization, model prediction and fractal structure of flocs Original Research Article

In this paper, results of an experimental study of polymeric phosphate-aluminum chloride (PPAC) as a modified coagulation reagent used to treat wastewater and fractal characteristics of flocs in a sewage treatment process were presented. Operating variables such as P/Al molar ratio, wastewater initial pH, coagulant dosage and agitation speed, which could influence the coagulation behavior of PPAC were experimentally tested. The evaluation of treatment efficiency was determined by measuring both the reduction of chemical oxygen demand (COD) and residual turbidity. It showed that the optimum removal efficiency was achieved when the P/Al molar ratio, wastewater initial pH, coagulant dosage and agitation speed were 1.2, 9.0, 0.36 g/L and 100 rpm respectively. Under optimum conditions, the removal efficiency was 73.5% and 99.5% for COD and turbidity. In addition, radial basis function (RBF) neural network established in this paper was used to predict the flocculation efficiency. The results revealed a promising operational forecasting capability. Furthermore, an inverted optical microscope was used to investigate the fractal structure of flocs formed during coagulation–flocculation. The results showed that under optimum conditions, with the increase of fractal dimension of the flocs, the COD removal efficiency increased while the flocs became denser with large cutter size.