Flow Discharge Prediction Study Using a CFD-Based Numerical Model and Gene Expression Programming

Water

Mehdi Neshat¹  Sevda Mozaffari²  Erfan Amini³  Hossein Mehdipour³ 

[1] Center for Artificial Intelligence Research and Optimization, Torrens University Australia, Brisbane 4006, Australia;Department of Water Engineering, Urmia University, Urmia 57561, Iran;School of Civil Engineering, College of Engineering, University of Tehran, Tehran 13145, Iran;

关键词: ogee spillway;    flow prediction;    numerical modeling;    Flow-3D;    CFD method;    gene expression programming artificial intelligence model;   

DOI  :  10.3390/w14040650

来源: DOAJ

【 摘 要 】

The significance of spillways is to allow the flood to be safely discharged from downstream. There is a strong correlation between the poor design of spillways and the failures of dams. In order to address this concern, the present study investigates the flow over the Nazloo-ogee spillway using the CFD 3D numerical model and an artificial intelligence method called Gene Expression Programming (GEP). In a physical model, discharge and flow depths were calculated for 21 different total heads. Among different turbulence models, the $RNG$ turbulence model achieved the maximum compatibility in computational fluid dynamic simulation. In addition, GEP was used to estimate Q, in which 70% of collected data was dedicated to training and 30% to testing. $R^2$, $RMSE$, and $MAE$ were obtained as performance criteria, and the new mathematical equation for the prediction of discharge was obtained using this model. Finally, the numerical model and GEP outputs were compared with the experimental data. According to the results, the numerical model and GEP exhibited a high level of correspondence in simulating flow over an ogee-crested spillway.

【 授权许可】

Unknown