Modeling Oxygen transfer of Multiple PlungingJets Aerators using Artificial Neural Networks
Journal Title: JOURNAL OF ADVANCED RESEARCH IN CONSTRUCTION AND URBAN ARCHITECTURE - Year 2017, Vol 2, Issue 3
Abstract
Aeration is mainly used to remove the undesirable gases dissolved in wastewater. In this article, the experimental data of aeration of the multiple plunging jets having varying jet velocity, jet parameters and no. of openings (1, 2, 4 and 8) has been collected from the studies. On the basis of experiment data, the values of oxygen- transfer coefficient (KL a) were calculated by using artificial neural network (ANN), multi linear regression (MLR), and two empirical equations Tojo and Miyanami and Shukla and Goel. Three standard statistical potential parameters such as correlation coefficient (R), determination coefficient (R2 )and root mean square error (RMSE) are utilized to compare the performance of modeling techniques and two empirical equations Tojo and Miyanami and Shukla and Goel. The values of coefficient of correlation, coefficient of determination and root mean square error values are 0.9897, 0.9795 and 0.00107 for ANN, 0.9585, 0.9404 and 0.00150 for MLR, 0.8424, 0.9178 and 0.0055 for equations of Tojo and Miyanami and 0.9273, 0.9629 and 0.0109 for equations of Shukla and Goel. On the basis of comparison of the performance of ANN and MLR modeling approaches with two empirical equations Tojo and Miyanami and Shukla and Goel, it is concluded that the ANN gives the best results in comparison for calculating the values of oxygen- transfer coefficient (KLa) for plunging jets.
Authors and Affiliations
Pritam Reddu
Keywords
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