Predicting the Behavior of Concrete Dams Using Artificial Neural Networks (Case study of Dez Dam)
Large dams store a significant amount of water behind them. Therefore, their safety and stability control have a special place. Changes in temperature and hydrostatic pressure are the most important factors that affect the dam structure; And will cause shifts in the crown of the dam upstream and dow...
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| Autor*in: |
Hosein Naderpour [verfasserIn] Seyed Rohollah Hoseini Vaez [verfasserIn] Naser Malekshahi [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Persisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: پژوهشهای زیرساختهای عمرانی - University of Qom, 2024, 6(2021), 2, Seite 123-132 |
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| Übergeordnetes Werk: |
volume:6 ; year:2021 ; number:2 ; pages:123-132 |
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| DOI / URN: |
10.22091/cer.2021.6898.1242 |
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DOAJ095834737 |
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| 520 | |a Large dams store a significant amount of water behind them. Therefore, their safety and stability control have a special place. Changes in temperature and hydrostatic pressure are the most important factors that affect the dam structure; And will cause shifts in the crown of the dam upstream and downstream. Therefore, the data obtained from the monitoring center should be evaluated regularly in order to analyze the behavior of the dam. Due to this issue, in this study, using artificial neural networks, a model is presented to predict the horizontal displacement of the Dez dam crown due to changes in pressure and temperature. According to the results, it is observed that the neural network has a good performance in predicting real values. The average error of the modeled network is about 4%. This indicates that the network is well trained. Using the generated network, the radial displacement changes against the reservoir water level for different temperatures are obtained, and plotted. Using diagrams, it is possible to predict the behavior of Dez dam for different temperatures and changes in reservoir water level, which can be very useful in monitoring and maintaining this dam. | ||
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10.22091/cer.2021.6898.1242 doi (DE-627)DOAJ095834737 (DE-599)DOAJ95f2bb8062414a248d8ff5ea62b688c1 DE-627 ger DE-627 rakwb per TA630-695 Hosein Naderpour verfasserin aut Predicting the Behavior of Concrete Dams Using Artificial Neural Networks (Case study of Dez Dam) 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Large dams store a significant amount of water behind them. Therefore, their safety and stability control have a special place. Changes in temperature and hydrostatic pressure are the most important factors that affect the dam structure; And will cause shifts in the crown of the dam upstream and downstream. Therefore, the data obtained from the monitoring center should be evaluated regularly in order to analyze the behavior of the dam. Due to this issue, in this study, using artificial neural networks, a model is presented to predict the horizontal displacement of the Dez dam crown due to changes in pressure and temperature. According to the results, it is observed that the neural network has a good performance in predicting real values. The average error of the modeled network is about 4%. This indicates that the network is well trained. Using the generated network, the radial displacement changes against the reservoir water level for different temperatures are obtained, and plotted. Using diagrams, it is possible to predict the behavior of Dez dam for different temperatures and changes in reservoir water level, which can be very useful in monitoring and maintaining this dam. concrete dam artificial neural network dez dam hydrostatic pressure temperature variation Structural engineering (General) Seyed Rohollah Hoseini Vaez verfasserin aut Naser Malekshahi verfasserin aut In پژوهشهای زیرساختهای عمرانی University of Qom, 2024 6(2021), 2, Seite 123-132 (DE-627)DOAJ09066969X 2783140X nnns volume:6 year:2021 number:2 pages:123-132 https://doi.org/10.22091/cer.2021.6898.1242 kostenfrei https://doaj.org/article/95f2bb8062414a248d8ff5ea62b688c1 kostenfrei https://cer.qom.ac.ir/article_1878_4a6eb3052f059b3ba1d1d3564e5c74c3.pdf kostenfrei https://doaj.org/toc/2783-140X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 6 2021 2 123-132 |
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10.22091/cer.2021.6898.1242 doi (DE-627)DOAJ095834737 (DE-599)DOAJ95f2bb8062414a248d8ff5ea62b688c1 DE-627 ger DE-627 rakwb per TA630-695 Hosein Naderpour verfasserin aut Predicting the Behavior of Concrete Dams Using Artificial Neural Networks (Case study of Dez Dam) 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Large dams store a significant amount of water behind them. Therefore, their safety and stability control have a special place. Changes in temperature and hydrostatic pressure are the most important factors that affect the dam structure; And will cause shifts in the crown of the dam upstream and downstream. Therefore, the data obtained from the monitoring center should be evaluated regularly in order to analyze the behavior of the dam. Due to this issue, in this study, using artificial neural networks, a model is presented to predict the horizontal displacement of the Dez dam crown due to changes in pressure and temperature. According to the results, it is observed that the neural network has a good performance in predicting real values. The average error of the modeled network is about 4%. This indicates that the network is well trained. Using the generated network, the radial displacement changes against the reservoir water level for different temperatures are obtained, and plotted. Using diagrams, it is possible to predict the behavior of Dez dam for different temperatures and changes in reservoir water level, which can be very useful in monitoring and maintaining this dam. concrete dam artificial neural network dez dam hydrostatic pressure temperature variation Structural engineering (General) Seyed Rohollah Hoseini Vaez verfasserin aut Naser Malekshahi verfasserin aut In پژوهشهای زیرساختهای عمرانی University of Qom, 2024 6(2021), 2, Seite 123-132 (DE-627)DOAJ09066969X 2783140X nnns volume:6 year:2021 number:2 pages:123-132 https://doi.org/10.22091/cer.2021.6898.1242 kostenfrei https://doaj.org/article/95f2bb8062414a248d8ff5ea62b688c1 kostenfrei https://cer.qom.ac.ir/article_1878_4a6eb3052f059b3ba1d1d3564e5c74c3.pdf kostenfrei https://doaj.org/toc/2783-140X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 6 2021 2 123-132 |
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10.22091/cer.2021.6898.1242 doi (DE-627)DOAJ095834737 (DE-599)DOAJ95f2bb8062414a248d8ff5ea62b688c1 DE-627 ger DE-627 rakwb per TA630-695 Hosein Naderpour verfasserin aut Predicting the Behavior of Concrete Dams Using Artificial Neural Networks (Case study of Dez Dam) 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Large dams store a significant amount of water behind them. Therefore, their safety and stability control have a special place. Changes in temperature and hydrostatic pressure are the most important factors that affect the dam structure; And will cause shifts in the crown of the dam upstream and downstream. Therefore, the data obtained from the monitoring center should be evaluated regularly in order to analyze the behavior of the dam. Due to this issue, in this study, using artificial neural networks, a model is presented to predict the horizontal displacement of the Dez dam crown due to changes in pressure and temperature. According to the results, it is observed that the neural network has a good performance in predicting real values. The average error of the modeled network is about 4%. This indicates that the network is well trained. Using the generated network, the radial displacement changes against the reservoir water level for different temperatures are obtained, and plotted. Using diagrams, it is possible to predict the behavior of Dez dam for different temperatures and changes in reservoir water level, which can be very useful in monitoring and maintaining this dam. concrete dam artificial neural network dez dam hydrostatic pressure temperature variation Structural engineering (General) Seyed Rohollah Hoseini Vaez verfasserin aut Naser Malekshahi verfasserin aut In پژوهشهای زیرساختهای عمرانی University of Qom, 2024 6(2021), 2, Seite 123-132 (DE-627)DOAJ09066969X 2783140X nnns volume:6 year:2021 number:2 pages:123-132 https://doi.org/10.22091/cer.2021.6898.1242 kostenfrei https://doaj.org/article/95f2bb8062414a248d8ff5ea62b688c1 kostenfrei https://cer.qom.ac.ir/article_1878_4a6eb3052f059b3ba1d1d3564e5c74c3.pdf kostenfrei https://doaj.org/toc/2783-140X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 6 2021 2 123-132 |
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10.22091/cer.2021.6898.1242 doi (DE-627)DOAJ095834737 (DE-599)DOAJ95f2bb8062414a248d8ff5ea62b688c1 DE-627 ger DE-627 rakwb per TA630-695 Hosein Naderpour verfasserin aut Predicting the Behavior of Concrete Dams Using Artificial Neural Networks (Case study of Dez Dam) 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Large dams store a significant amount of water behind them. Therefore, their safety and stability control have a special place. Changes in temperature and hydrostatic pressure are the most important factors that affect the dam structure; And will cause shifts in the crown of the dam upstream and downstream. Therefore, the data obtained from the monitoring center should be evaluated regularly in order to analyze the behavior of the dam. Due to this issue, in this study, using artificial neural networks, a model is presented to predict the horizontal displacement of the Dez dam crown due to changes in pressure and temperature. According to the results, it is observed that the neural network has a good performance in predicting real values. The average error of the modeled network is about 4%. This indicates that the network is well trained. Using the generated network, the radial displacement changes against the reservoir water level for different temperatures are obtained, and plotted. Using diagrams, it is possible to predict the behavior of Dez dam for different temperatures and changes in reservoir water level, which can be very useful in monitoring and maintaining this dam. concrete dam artificial neural network dez dam hydrostatic pressure temperature variation Structural engineering (General) Seyed Rohollah Hoseini Vaez verfasserin aut Naser Malekshahi verfasserin aut In پژوهشهای زیرساختهای عمرانی University of Qom, 2024 6(2021), 2, Seite 123-132 (DE-627)DOAJ09066969X 2783140X nnns volume:6 year:2021 number:2 pages:123-132 https://doi.org/10.22091/cer.2021.6898.1242 kostenfrei https://doaj.org/article/95f2bb8062414a248d8ff5ea62b688c1 kostenfrei https://cer.qom.ac.ir/article_1878_4a6eb3052f059b3ba1d1d3564e5c74c3.pdf kostenfrei https://doaj.org/toc/2783-140X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 6 2021 2 123-132 |
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Predicting the Behavior of Concrete Dams Using Artificial Neural Networks (Case study of Dez Dam) |
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Large dams store a significant amount of water behind them. Therefore, their safety and stability control have a special place. Changes in temperature and hydrostatic pressure are the most important factors that affect the dam structure; And will cause shifts in the crown of the dam upstream and downstream. Therefore, the data obtained from the monitoring center should be evaluated regularly in order to analyze the behavior of the dam. Due to this issue, in this study, using artificial neural networks, a model is presented to predict the horizontal displacement of the Dez dam crown due to changes in pressure and temperature. According to the results, it is observed that the neural network has a good performance in predicting real values. The average error of the modeled network is about 4%. This indicates that the network is well trained. Using the generated network, the radial displacement changes against the reservoir water level for different temperatures are obtained, and plotted. Using diagrams, it is possible to predict the behavior of Dez dam for different temperatures and changes in reservoir water level, which can be very useful in monitoring and maintaining this dam. |
| abstractGer |
Large dams store a significant amount of water behind them. Therefore, their safety and stability control have a special place. Changes in temperature and hydrostatic pressure are the most important factors that affect the dam structure; And will cause shifts in the crown of the dam upstream and downstream. Therefore, the data obtained from the monitoring center should be evaluated regularly in order to analyze the behavior of the dam. Due to this issue, in this study, using artificial neural networks, a model is presented to predict the horizontal displacement of the Dez dam crown due to changes in pressure and temperature. According to the results, it is observed that the neural network has a good performance in predicting real values. The average error of the modeled network is about 4%. This indicates that the network is well trained. Using the generated network, the radial displacement changes against the reservoir water level for different temperatures are obtained, and plotted. Using diagrams, it is possible to predict the behavior of Dez dam for different temperatures and changes in reservoir water level, which can be very useful in monitoring and maintaining this dam. |
| abstract_unstemmed |
Large dams store a significant amount of water behind them. Therefore, their safety and stability control have a special place. Changes in temperature and hydrostatic pressure are the most important factors that affect the dam structure; And will cause shifts in the crown of the dam upstream and downstream. Therefore, the data obtained from the monitoring center should be evaluated regularly in order to analyze the behavior of the dam. Due to this issue, in this study, using artificial neural networks, a model is presented to predict the horizontal displacement of the Dez dam crown due to changes in pressure and temperature. According to the results, it is observed that the neural network has a good performance in predicting real values. The average error of the modeled network is about 4%. This indicates that the network is well trained. Using the generated network, the radial displacement changes against the reservoir water level for different temperatures are obtained, and plotted. Using diagrams, it is possible to predict the behavior of Dez dam for different temperatures and changes in reservoir water level, which can be very useful in monitoring and maintaining this dam. |
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| title_short |
Predicting the Behavior of Concrete Dams Using Artificial Neural Networks (Case study of Dez Dam) |
| url |
https://doi.org/10.22091/cer.2021.6898.1242 https://doaj.org/article/95f2bb8062414a248d8ff5ea62b688c1 https://cer.qom.ac.ir/article_1878_4a6eb3052f059b3ba1d1d3564e5c74c3.pdf https://doaj.org/toc/2783-140X |
| remote_bool |
true |
| author2 |
Seyed Rohollah Hoseini Vaez Naser Malekshahi |
| author2Str |
Seyed Rohollah Hoseini Vaez Naser Malekshahi |
| ppnlink |
DOAJ09066969X |
| callnumber-subject |
TA - General and Civil Engineering |
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c |
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false |
| doi_str |
10.22091/cer.2021.6898.1242 |
| callnumber-a |
TA630-695 |
| up_date |
2024-07-03T16:52:24.517Z |
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1803577505373749248 |
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7.4013834 |