Improving the performance of industrial clarifiers using three-dimensional computational fluid dynamics

ABSTRACT

Sedimentation is one of the most popular wastewater treatment processes, and is used to separate solid particles from carrier fluid in settling tanks known as clarifiers. The clarifier, as the last major facility in wastewater treatment plants (WWTPs), can limit or define the performance of the overall WWTP. This paper presents a novel three-dimensional unsteady computational fluid dynamics (CFD) model to improve the efficiency of an industrial clarifier that had been experiencing underperformance and reduction in wastewater handling capacity. We propose a numerical technique to address the transient process of removing sludge from the floor of clarifiers by using rotating rakes. The CFD model was first applied to analyzing the ramifications of the current clarifier geometry on performance. The results show that the root causes for underperformance are related to the unconventional top side feed design of the clarifier, which leads to significant asymmetry in the flow distribution. The CFD model was next used to investigate various design modifications with the goal of improving the clarifier performance. A few geometry modification ideas such as an inward baffle, dissipating inlets, and a submerged skirt were found to create a more uniform flow distribution in the clarifier, significantly reducing the backflow into the feedwell and the velocity of the flow exiting the feedwell, which helps the solid particles to settle in the clarifier. These three designs were found to reduce the effluent total suspended solids (TSS) by more than 80% and thus significantly improve clarifier performance. It is believed that the CFD model developed in this study can become a computationally efficient tool for investigating the performance of industrial clarifiers with complex geometries and rotating rakes.

KEYWORDS:

• Clarifier
• wastewater treatment
• feedwell
• energy dissipating inlet
• total suspended solids

Acknowledgements

The authors would like to thank Christopher Jian, Wu Chen, Karl Jacob, Ray Collins, Leslie Pittser, Ashley Graves, Bobby Hart, and Max Lee for their support and insightful discussions for this study.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Chunliang Wu http://orcid.org/0000-0002-9697-5560