Effects of Bed Materials to Flow Characteristics on Open Channel and Gradually Varied Flow Simulation Using Genetic Algorithm (GA)
DOI:
https://doi.org/10.14738/aivp.104.12709Keywords:
Estimation of open channel roughness, parameter estimation, optimization method, GVF profiles.Abstract
Determination of accurate roughness coefficient was realized necessary for hydraulic parameters estimation in open channel flow. For the purpose this study was planned to carry out on experimental basis in hydraulic laboratory hall of campus itself. In this study, a combination between experimental and numerical models study were carried out to investigate the influence of bed roughness on flow characteristics. Experiments were conducted on six bed materials (Sand, Gravel, Cement plaster, Grass, Formica and cast iron (original bed of channel)) in three conditions. Firstly the discharge was varied at same tail water level. Secondly the depths were varied for same discharge and thirdly the depths were measured for different discharges for each bed material Results were analyzed and were graphically presented .The Manning roughness coefficient was estimated for each bed material using the experimental and discharge optimization technique. The percentages of errors between the observed and predicted were reported. Since the channel represents compound case having glass wall and different bed material, the roughness coefficient of each bed materials were predicted by optimization on genetic algorithm to the lotter’s modified equation in which the exponent alpha value varies from 1.28 to 1.76 The shear stress distribution was examined by first and second approximation theory on smooth rectangular channel on Knight et al (1984) model. It was compared with the experimental average shear stress and was found the first approximation theory over estimated to the experimental value whereas second approximation result was within the average relative error of 1.61% for bed. Side wall/bed stress ration was found of 0.61. Similarly gradually varied flow was simulated in python using optimal value of roughness coefficient.
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Copyright (c) 2022 Dak Bahadur Khadka, Prajwal Bhandari
This work is licensed under a Creative Commons Attribution 4.0 International License.