Predicting Seepage of Earth Dams using Artificial Intelligence Techniques

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

NOURI M.; SALMASI F.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Irrigation Sciences and Engineering Year:2019 | Volume:42 | Issue:1 Page(s): 83-97

Download Full-Text

Persian Verion

View:

661

Download:

365

Cites:

Information Journal Paper

Title

Predicting Seepage of Earth Dams using Artificial Intelligence Techniques

Author(s)

NOURI M. | SALMASI F. | Issue Writer Certificate

Keywords

Firefly AlgorithmQ1

Hybrid ModelsQ1

Seepage PredictionQ1

Earth DamQ1

Abstract

Preventing water penetration and seepage control is of prime importance in hydraulic structures projects. Recent studies show that 30% of dam failures are due to the seepage from dam’ s body or foundation. Seepage control inherently is controlling potential energy of water molecules causing seepage and related losses. Constructing a core with low rate of permeability can considerably control seepage from dam body. So foundation seepages are significantly more than body seepages. Foundation seepage control is done to prevent uplift and piping, two phenomena which led to dam failure. One of the methods for controlling seepage from bottom of Earth Dams which are mounted on alluvial foundation with high rate of permeability, is utilizing a covering layer with low permeability on bed of river, bottom of reservoir (in upstream) and connecting it to central core of dam. In fact, the role of such methods and mentioned covering layer is lengthening flow path for increasing potential losses and decreasing water energy which is terminated to decrease penetrated water and related losses. This covering layer is called clay blanket. One of the longest upstream impermeable blankets is executed in Tarbela dam in Pakistan with 140 m height. This blanket has 1400 m length and its thickness is 1. 52 m at the dam (WCD, 2000). Khalili and Amiri (2015) investigated cutoff effect in reducing leakage, exit gradient and uplift, both experimentally and numerically analyze by software GEOSTUDIO and referring that the results of the software are in acceptable agreement with the experimental results. Tayfu et al. (2005) used Finite Element Method (FEM) and Artificial Neural Network (ANN) models for flow through Jeziorsko Earth fill Dam in Poland. This case study offers insight into the adequacy of ANN as well as its competitiveness against FEM for Seepage Prediction through an earth fill dam body. Ahmed and Sattar (2014) used Gene expression models (GEP) for prediction of dam failure and results showed the superiority of the developed GEP models over existing regression-based models...

Cites

No record.

References

No record.

Cite

APA: Copy

NOURI, M., & SALMASI, F.. (2019). Predicting Seepage of Earth Dams using Artificial Intelligence Techniques. IRRIGATION SCIENCES AND ENGINEERING (JISE) (SCIENTIFIC JOURNAL OF AGRICULTURE), 42(1 ), 83-97. SID. https://sid.ir/paper/217119/en

Vancouver: Copy

NOURI M., SALMASI F.. Predicting Seepage of Earth Dams using Artificial Intelligence Techniques. IRRIGATION SCIENCES AND ENGINEERING (JISE) (SCIENTIFIC JOURNAL OF AGRICULTURE)[Internet]. 2019;42(1 ):83-97. Available from: https://sid.ir/paper/217119/en

IEEE: Copy

M. NOURI, and F. SALMASI, “Predicting Seepage of Earth Dams using Artificial Intelligence Techniques,” IRRIGATION SCIENCES AND ENGINEERING (JISE) (SCIENTIFIC JOURNAL OF AGRICULTURE), vol. 42, no. 1 , pp. 83–97, 2019, [Online]. Available: https://sid.ir/paper/217119/en

Related Journal Papers