Theoretical Analysis and Development of an Artificial Neural Network Model to Evaluate Earthen Dam Slope Stability
In the design of earth dams, it must be considered that the water leakage through the earth dam generates upward and pore pressure, in addition to leakage forces that cause internal erosion, which has a direct influence on the structural stability of this system. Also, the rising and dropping in th...
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| Format: | Article |
| Language: | English |
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Tikrit University
2022-12-01
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| Series: | Tikrit Journal of Engineering Sciences |
| Subjects: | |
| Online Access: | https://tj-es.com/ojs/index.php/tjes/article/view/800 |
| _version_ | 1797782365644259328 |
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| author | Ruqiya Abed Hussain Asmaa Al-samarrae |
| author_facet | Ruqiya Abed Hussain Asmaa Al-samarrae |
| author_sort | Ruqiya Abed Hussain |
| collection | DOAJ |
| description |
In the design of earth dams, it must be considered that the water leakage through the earth dam generates upward and pore pressure, in addition to leakage forces that cause internal erosion, which has a direct influence on the structural stability of this system. Also, the rising and dropping in the water level has a direct effect on the stability of the dam's face slope. One way to solve these issues is the installation of a core or a horizontal water drainage system. The present study relied on the GEO-Studio computer tool to evaluate cross-sectional models of earthen dams by determining the safety factor under different situations represented by a change in filter type, and the flow state as a result of raising and lowering the water level at the dam reservoir and the full fill condition of the dam reservoir. The research found that the existence of a core substantially contributed to improving the safety coefficient for the case of rising the water level (2m) and rapidly rising by assigning it the greatest safety coefficient values. The absence of a filter had an opposite influence on the safety coefficient by decreasing it. Also, the factor of safety for the downstream slope was affected by less than 5% for different flow conditions, compared with the higher effect generated by the upstream slope. Furthermore, an artificial neural network model with an accuracy ratio of more than 97% was developed for the predicted safety factor.
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| first_indexed | 2024-03-13T00:09:57Z |
| format | Article |
| id | doaj.art-b7f928d2d9ca4e0c9663cc1276fcf1dd |
| institution | Directory Open Access Journal |
| issn | 1813-162X 2312-7589 |
| language | English |
| last_indexed | 2024-03-13T00:09:57Z |
| publishDate | 2022-12-01 |
| publisher | Tikrit University |
| record_format | Article |
| series | Tikrit Journal of Engineering Sciences |
| spelling | doaj.art-b7f928d2d9ca4e0c9663cc1276fcf1dd2023-07-12T19:21:54ZengTikrit UniversityTikrit Journal of Engineering Sciences1813-162X2312-75892022-12-0129410.25130/tjes.29.4.1Theoretical Analysis and Development of an Artificial Neural Network Model to Evaluate Earthen Dam Slope StabilityRuqiya Abed Hussain0Asmaa Al-samarrae1Civil Engineering Department, College of Engineering, Tikrit University, Tikrit, Iraq.Civil Engineering Department, College of Engineering, Tikrit University, Tikrit, Iraq. In the design of earth dams, it must be considered that the water leakage through the earth dam generates upward and pore pressure, in addition to leakage forces that cause internal erosion, which has a direct influence on the structural stability of this system. Also, the rising and dropping in the water level has a direct effect on the stability of the dam's face slope. One way to solve these issues is the installation of a core or a horizontal water drainage system. The present study relied on the GEO-Studio computer tool to evaluate cross-sectional models of earthen dams by determining the safety factor under different situations represented by a change in filter type, and the flow state as a result of raising and lowering the water level at the dam reservoir and the full fill condition of the dam reservoir. The research found that the existence of a core substantially contributed to improving the safety coefficient for the case of rising the water level (2m) and rapidly rising by assigning it the greatest safety coefficient values. The absence of a filter had an opposite influence on the safety coefficient by decreasing it. Also, the factor of safety for the downstream slope was affected by less than 5% for different flow conditions, compared with the higher effect generated by the upstream slope. Furthermore, an artificial neural network model with an accuracy ratio of more than 97% was developed for the predicted safety factor. https://tj-es.com/ojs/index.php/tjes/article/view/800ANNCoreEarth DamHorizontal Filter Slope Stability |
| spellingShingle | Ruqiya Abed Hussain Asmaa Al-samarrae Theoretical Analysis and Development of an Artificial Neural Network Model to Evaluate Earthen Dam Slope Stability Tikrit Journal of Engineering Sciences ANN Core Earth Dam Horizontal Filter Slope Stability |
| title | Theoretical Analysis and Development of an Artificial Neural Network Model to Evaluate Earthen Dam Slope Stability |
| title_full | Theoretical Analysis and Development of an Artificial Neural Network Model to Evaluate Earthen Dam Slope Stability |
| title_fullStr | Theoretical Analysis and Development of an Artificial Neural Network Model to Evaluate Earthen Dam Slope Stability |
| title_full_unstemmed | Theoretical Analysis and Development of an Artificial Neural Network Model to Evaluate Earthen Dam Slope Stability |
| title_short | Theoretical Analysis and Development of an Artificial Neural Network Model to Evaluate Earthen Dam Slope Stability |
| title_sort | theoretical analysis and development of an artificial neural network model to evaluate earthen dam slope stability |
| topic | ANN Core Earth Dam Horizontal Filter Slope Stability |
| url | https://tj-es.com/ojs/index.php/tjes/article/view/800 |
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