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In-Process Hydraulic and Dissolved Oxygen Characteristics of an Oxidation Ditch with Horizontal Brush Surface Aerators

Author(s): L. K. Horup; S. Mulligan; P. Leonard; E. Clifford

Linked Author(s): Sean Mulligan

Keywords: Eration efficiency; Oxidation ditch; Gas transfer; Surface aeration; Multiphase flow; Activated sludge

Abstract: Looking at treatment of wastewater in a wider perspective, energy consumption is often high and mainly attributed to the aeration process which itself can account for up to 75% of the total energy consumption at a treatment plant. Oxidation ditches are hydraulic structures commonly used in industrial and municipal wastewater treatment. In surface aerated oxidation ditches, where neither the hydraulics nor the dissolved oxygen distributions are homogenous, determining the oxygen transfer and subsequently the aeration efficiency is difficult which poses a challenge when resolving potential for energy efficient improvements. Therefore, as a first step, the in-process hydraulic and dissolved oxygen characteristics in a horizontal brush surface aerated oxidation ditch were studied to develop the fundamentals for further aeration optimization studies. A combination of prototype physical measurements and three-dimensional numerical simulations were undertaken on a 90 m long, 3 m deep oxidation ditch. The study revealed complex distributions in velocity and dissolved oxygen across the hydraulic structure which were not considered in previous oxygen transfer models. In particular, the largest variations in velocity and dissolved oxygen were observed in the vicinity of the aerator where the high velocities and air entrainment was localized at the free-surface. This resulted in recirculation zones and dead spots containing low dissolved oxygen levels below the aerator prone to sedimentation. Steady state numerical simulations on the hydraulic structure provided adequate results using the k-model to further understand the hydrodynamics in the structure which can aid in development of new oxygen transfer models and future optimization studies.


Year: 2020

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