A Hydrodynamic and Surface Coverage Model Capable of Predicting Settled Effluent Turbidity Subsequent to Hydraulic Flocculation

Abstract

A widely applicable hydraulic flocculator design model would facilitate increased adoption of this sustainable technology. To this end, the authors previously proposed rate equations for the removal of nonsettleable aggregates in hydraulic flocculators (Pennock et al.). This work continues the prior effort by developing two models for coupled flocculation/sedimentation performance. The first model describes settled effluent turbidity for flocculators where the relative velocities between particles are dominated by viscous forces (e.g., laminar flows). Similarly, the second model applies where inertial forces dominate. Predictions of these models were compared with laboratory-scale flocculation/ sedimentation data obtained from both a laminar-and a turbulent-flow flocculator. The viscous equation fit data from the laminar flow flocculator well. For the turbulent flocculator, both models gave good fits of the data, but the inertial model performed slightly better. The similarity of the two models under the experimental constraints explains this result, and further study in different conditions is needed to delineate the applicability of the models in turbulent flocculation. Given the similarity between the models and that the product of the mean fluid velocity gradient applicable to laminar flow (G) and hydraulic residence time (h), Gh, has historically been used in flocculator design, it is recommended that the viscous flocculation model introduced in this article be used. The new flocculation models have a single adjustable parameter and, in addition to being able to predict settled effluent turbidity from coagulant dose, also provide reasonable estimates of flocculator design parameters from first principles and dimensional analysis.

Estimating effluent turbidity in the drinking water flocculation process with an improved random forest model

“…Pesic et al (2016) pointed out that an appropriate regression model can be used for short-term turbidity simulation. Pennock et al (2018) proposed a hydrodynamic and land cover model with adaptive variables, which can predict the turbidity of sediment according to the dosage of coagulant. Mather & Johnson (2015) used a combined cluster analysis and classification tree approach to predict the stream turbidity of three rivers in the Mid-Atlantic region of the United States.…”