期刊
WATER RESEARCH
卷 131, 期 -, 页码 346-355出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.watres.2017.10.062
关键词
Oxygen transfer; Overall volumetric oxygen transfer; coefficient; Hydrodynamics; Liquid viscosity; Wastewater treatment
Aeration is the largest energy consumer in most water and resource recovery facilities, which is why oxygen transfer optimization is fundamental to improve energy efficiency. Although oxygen transfer is strongly influenced by the bubble size distribution dynamics, most aeration efficiency models currently do not include this influence explicitly. In few cases, they assume a single average bubble size. The motivation of this work is to investigate this knowledge gap, i.e. a more accurate calculation of the impact of bubble size distribution dynamics on oxygen transfer. Experiments were performed to study bubble size distribution dynamics along the height of a bubble column at different air flow rates for both tap water and solutions that mimic the viscosity of activated sludge at different sludge concentrations. Results show that bubble size is highly dynamic in space and time since it is affected by hydrodrynamics and the viscosity of the liquid. Consequently, oxygen transfer also has a dynamic character. The concept of a constant overall volumetric oxygen transfer coefficient, K(L)a, can thus be improved. A new modeling approach to determine the K(L)a locally based on bubble size distribution dynamics is introduced as an alternative. This way, the K(L)a for the entire column is calculated and compared to the one measured by a traditional method. Results are in good agreement for tap water. The modeled K(L)a based on the new approach slightly overestimates the experimental K(L)a for solutions that mimic the viscosity of activated sludge. The difference appears to be lower when the air flow rate increases. This work can be considered as a first step towards more accurate and rigorous mechanistic aeration efficiency models which are based on in-depth mechanism knowledge. This is key for oxygen transfer optimization and consequently energy savings. (C) 2017 Elsevier Ltd. All rights reserved.
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