Open AccessStudying the Effect of Head Difference on Exit Gradients and Uplift Pressures Beneath Hydraulic Structures by Gene Expression Programming
Author(s) -
Duaa Hadi Khashan,
Waqed H. Hassan
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1094/1/012099
Subject(s) - cutoff , hydraulic head , pressure gradient , isotropy , head (geology) , pressure head , mathematics , mechanics , finite difference , geology , geometry , physics , geotechnical engineering , mathematical analysis , geomorphology , optics , thermodynamics , quantum mechanics
The seeping flow under the hydraulic structure produces uplifting pressure on its floor, which affects the performance of these structures. This problem was numerically analyzed using the finite difference method in Matlab after verification with GeoStudio software. This study’s main objective is to investigate the effects of head difference variation, the cutoffs’ locations, and depths on the exit gradient and uplift pressure. An empirical equation has been developed to predict the exit gradient by employing gene expression programming (GEP). More than 975 runs were executed using finite difference code with differential (H=5,10,15m), were studied over isotropic soil foundation. The results indicate that the differential head ratio (H/B) had a considerable effect on increasing the exit gradient and uplift pressure, mainly when the value of the differential head ratio (H/B =3/3) and minimum exit gradient was observed when the cutoff location ratio at the downstream is of (x1/b=1) with a maximum relative depth of (d1/b=0.6), while the minimum uplift pressure was observed when the cutoff location ratio at the upstream is of (x1/B=0) with a minimum relative depth of (d1/B=0.1). The results also indicate that the maximum exit gradient is observed when the ratio of the length of upstream cutoff to the length of downstream cutoff is (d1/d2 = 1). Based on the simulation results, the equation obtained using the Genetic expression programming (GEP) model performed better predicting to exit gradient for one cutoff with a coefficient of determination R2 equals 0.954 for training and 0.957 for testing and two cutoffs with R2 equals 0.93 for training and 0.94 for testing.