Application of Machine Learning Methods in Estimating the Oxygenation Performance of Various Configurations of Plunging Hollow Jet Aerators

Abstract

Plunging jet aerators are considered energetically attractive devices for oxygenation because of their good mixing characteristics and ease of construction and operation. In this mechanism of plunging jet aeration, the air-water interfacial area is increased by a free-falling jet impinging on the surface of a water pool. In this study, experimental data from various configurations of plunging hollow jet aerators are explored in formulating the correlations for predicting the values of volumetric oxygen transfer coefficient (KLa) with the jet variables (discharge, jet thickness, jet velocity, jet length, depth of water pool, pipe outlet diameter, number of jets). Nonlinear regression modeling equations derived from dimensional and nondimensional data sets are compared with the neuro-fuzzy (ANFIS), support vector regression (SVM), artificial neural network (ANN), M5 tree (M5), and random forests (RF) methods. SVM models calibrated with both types of data sets provided better results when tested on the unseen data sets. Regression equations are also useful and give acceptable results. The SVM models and regression equations are further checked for effectiveness on the data set of past study on plunging hollow jets. The nondimensional form of the regression equation derived in the current study fits reasonably well when tested on the oxygenation data from previous work as compared to the other regression models. The sensitivity of the jet variables is also tested, which showed jet velocity and jet thickness as major contributing factors in oxygenating the aeration pools. An aeration device adds oxygen to water and wastewater during treatment to ensure that microorganisms have enough oxygen to oxidize organic pollutants. Aeration requirements for aeration tanks vary greatly depending on the organic load, and one or more hollow jet aerators can be fitted to accommodate the fluctuating load. Hollow jet aerators are well suited to use in packaged wastewater treatment plants. The annular opening of these aerators can be adjusted accordingly based on the varying load. High-velocity thinner jets are better for quickly renewing air-water films and generating shear and turbulence in the receiving pool, but wastewater should be well screened before aeration to avoid clogging of the small annular opening. The results of this study on the capacity of plunging hollow jet aerators of different configurations/arrangements at varying operating conditions were reflected by the dimensional as well as nondimensional relationships between oxygen transfer rate and jet equipment parameters. Implementing these relationships on previous jet aeration data indicates that the equations are accurate enough to be used to situations similar to those in this investigation. Without any prior experimental effort, these equations can be used to estimate the oxygen transfer expected in practical applications.