Predicting Re-aeration Rates Using Artificial Neural Networks in Surface Aerators

The paper illustrates the application of a neural-network model to the modeling of mass transfer in unbaffled surface aeration tank fitted with six flat bladed rotors under geometrically similar conditions. Back-propagation with Levenberg-Marquadt algorithm is used for the modeling of neural-network. This paper discusses the ability of neural-network to model the mass transfer rate in unbaffled surface aeration tank. A thorough sensitive analysis has also been made to ascertain which variables are having maximum influence on reaeration rates.