Determination of Flow through Homogeneous Earth Dams with Triangular Toe Filter

Abbas, Jawdat K.

doi:10.25130/tjes.24.1.08

Cited by 3 publications

(1 citation statement)

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“…(Salmasi and Jafari, 2016) studied the seepage from a homogenous earth dam on an impervious base and determined the location of the phreatic line by numerical simulation using (SEEP/W). (Abbas, 2017) used (SEEP/W) program to analyze the effect of boundary variables of the dam with triangular toe filter on the seepage discharge through it. Also, this study suggested an empirical equation to measure this discharge.…”

Section: Introductionmentioning

confidence: 99%

Easy Equation for Estimating Seepage Discharge through Earth Dams Based on Impermeable Foundation

Saud

Irzooki

Al-Obaidi

2022

IOP Conf. Ser.: Earth Environ. Sci.

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The goal of this work was to develop an easy and reliable equation for calculating seepage discharge through homogeneous earthen dams that operate with toe drains. For this purpose, many data were generated using (SEEP/W) program depending on the geometrical variables that affect this seepage, such as dam height (h), upstream water depth (H), dam top width (b), upstream and downstream slopes, and base length of toe drain. The seepage discharge quantity for 728 cases was determined using three different values for each of the aforementioned geometric variables. A straightforward and precise equation was created for computing the discharge via a homogeneous earth dam with chimney drain system using the dimensional analysis method and SPSS software, with an (R2) coefficient of 0.986. Then the dimensional analysis was applied to this information. A simple and accurate equation was obtained to calculate the discharge through a homogenous earth dam with a toe drain system with a coefficient (R2) of 0.986. The results indicated that the seepage discharge increases with an increase in the upstream water depth, the toe drain’s base length, and the angle of the upstream and downstream slopes, while it decreases with an increase in the dam top width. Additionally, utilizing the produced data, the artificial neural network model (ANN) was implemented. The results of this model revealed varying percentages of importance for the independent geometrical variables on the seepage quantity, where the upstream water depth (H) has the most important and amounted to 66.9%, while the upstream slope was the least important, where the importance percentage for this factor was 0.7%. The (ANN) model and predicted empirical equation results show excellent agreement when compared.

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Section: Introductionmentioning

confidence: 99%