Effects of Turbulence Models on Microbubble Distributions in Dissolved Air Flotation Process for Water Treatment


Dissolved air flotation(DAF) system is one of the water treatment processes that clarifies wastewaters by floating internal contaminants to the water surface by attaching microbubbles to them. Since the first use of DAF for drinking water treatment in Scandinavia during the 1920s, DAF has been very widely used in treating the industrial wastewater effluents such as oil refineries, petrochemical and chemical plants, natural gas processing plants and general water treatment. In the present study, 2-phase flow of micro air bubbles and water mixture is simulated by computational fluid dynamics to investigate changes of internal flow behaviors in DAF system depending on the turbulence models. For a given geometry of DAF system and boundary conditions, microbubble distribution is analyzed with several turbulence models, which are standard k-ε, realizable k-ε, RNG k-ε, standard k-ω and SST k-ω, respectively. From analysis, it is observed that standard k-ε model, which has been frequently used in the previous researches, predicts somewhat different behaviors from other turbulence models. Also, RNG k-ε and standard k-ω model yield relatively excessive rotational flow inside water. By comparing computation time and convergence success, it is found that k-ε models are much faster to complete computations than k-ω models, and also they showed good convergence success except for RNG k-ε model. From the present results, it is revealed that a selection of a turbulence model should be considered more carefully when an internal flow analysis is conducted on the DAF process.

Author Information
Min A Park, Sejong University, South Korea
Kyun Ho Lee, Sejong University, South Korea
Jae Dong Chung, Sejong University, South Korea

Paper Information
Conference: ACSEE2015
Stream: Environmental Sustainability and Environmental Management: Freshwater

This paper is part of the ACSEE2015 Conference Proceedings (View)
Full Paper
View / Download the full paper in a new tab/window

Comments & Feedback

Place a comment using your LinkedIn profile


Share on activity feed

Powered by WP LinkPress

Share this Research

Posted by James Alexander Gordon