Estimating The Aeration Performance Of Venturi-Conduit By Artificial Bee Colony Programming

Abstract

Oxygen concentration dissolved in water is an important parameter used to measure the quality of water. Increasing the concentration of oxygen by transferring oxygen from the atmosphere is named as aeration. Aeration can be performed with many hydraulic structures. Two of the structures that have become widespread in the field of hydraulics are gated conduit and venturi. Venturi has throat part and air hole located into throat part. A difference of pressure, which provides aeration occurs between the venturi inlet and the throat part. A pressure difference occurs between up and down flows of the door in a partially opened gated conduit. Air entrains into flow from an air vent that were drilled downstream of the gate. A venturi was placed on air hole of a circular conduit that as called venturi-conduit, a new aeration system. The basic steps of the Artificial Bee Colony Programming (ABCP) developed for the solution of the symbolic regression problem come from the Artificial Bee Colony (ABC). In this study, ABCP is proposed to obtain functions that can model the ventilation performance of conduits with venture-conduit. The results of the method trained with experimentally measured data on 2 ventures with different contraction ratios were compared with artificial neural networks and genetic programming. ABCP outperformed genetic programming and neural networks on test data with an R2 value of 0.99 in both datasets. The RMSE values of 1.64 and 2.66, respectively, in the 2 data sets indicate that ABCP is capable of generating the appropriate function for the problem.