(2020) Environmental Pollution_Micro-bubble flow simulation of dissolved air flotation process for water treatment using computational fluid dynamics technique

Lee K.H., Kim H., KuK J.W., Chung J.D., Park S., Kwon E.E.

(Elsevier Ltd) Environmental Pollution ISSN: 2697491 Vol.256 Issue. Article No.112050 DOI: 10.1016/j.envpol.2019.01.011

A dissolved air flotation (DAF) system is one of the water treatment processes that purifies contaminants through a buoyancy effect by attaching the moiety of micro-bubbles on their free surface. Since the DAF system was first used in the drinking water treatment in the 1960s, it has been recognized as an effective treatment for the water purification process. Most previous works laid great emphasis on the internal flow behaviors of fluid to improve the purification efficiency of the DAF system. Nevertheless, the practical implementation with a pilot plant indeed revealed some technical incompleteness for the DAF system. To circumvent for the technical incompleteness, numerical simulation based on computational fluid dynamics (CFD) has been carried out to understand the in-depth knowledge on internal flow phenomena in the DAF system. However, the standard k-ε turbulence model has been conventionally used in the most studies without any proper consideration process. Accordingly, the objectives of this study were to investigate the major effects on the internal flow behaviors for an efficient numerical simulation of DAF when a different turbulence model and micro-bubble parameters are used. As a result, the present study found that the standard k-ε model would be not proper for the internal flow simulation of the DAF process and a careful consideration would be required for a more accurate prediction. In addition, the present study examined a desirable internal flow pattern with various operating conditions of the micro-bubble. Consequently, the main findings of this study are expected to provide realistic information to related researchers for designing the DAF system with the optimal operating parameters. © 2019 Elsevier Ltd

A part of this work was supported by the New & Renewable Energy Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20163010092290) and by the Small and Medium Business Administration (SMBA) (No. S2083708). A part of this work was supported by the New & Renewable Energy Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20163010092290 ) and by the Small and Medium Business Administration (SMBA) (No. S2083708 ).