인공신경망기법을 이용한 중심차수벽형 석괴댐의 정부침하량 예측
Prediction of Crest Settlement of Center Cored Rockfill Dam using an Artificial Neural Network Model
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초록
In this study, the settlement data of 32 center cored rockfill dams (total 39 monitored data) were collected and analyzed to develop the method to predict the crest settlement of a CCRD after impounding by using the internal settlement data occurred during construction. An artificial neural network (ANN) modeling was used in developing the method, which was considered to be a more reliable approach since in the ANN model dam height, core width, and core type were all considered as input variables in deriving the crest settlement, whereas in conventional methods, such as Clements's method, only dam height is used as a variable. The ANN analysis results showed a good agreement with the measured data, compared to those by the conventional methods using regression analysis. In addition, a simple procedure to use the ANN model for engineers in practice was provided by proposing the equations used for given input values.
Abstract
In this study, the settlement data of 32 center cored rockfill dams (total 39 monitored data) were collected and analyzed to develop the method to predict the crest settlement of a CCRD after impounding by using the internal settlement data occurred during construction. An artificial neural network (ANN) modeling was used in developing the method, which was considered to be a more reliable approach since in the ANN model dam height, core width, and core type were all considered as input variables in deriving the crest settlement, whereas in conventional methods, such as Clements's method, only dam height is used as a variable. The ANN analysis results showed a good agreement with the measured data, compared to those by the conventional methods using regression analysis. In addition, a simple procedure to use the ANN model for engineers in practice was provided by proposing the equations used for given input values.
참고문헌 (10)
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- Dascal, O., "Postconstruction Deformations of Rockfill Dams", Journal of Geotechnical Engineering, 113(1), pp.46~59 (1987)
- Habibagahi, G., "Post-construction Settlement of Rockfill Dams Analyzed via Adaptive Network-based Fuzzy Inference Systems", Computers and Geotechnics, 29, pp.211~233 (2002)
- Hunter, G., "The Pre- and Post-failure Deformation Behavior of Soils Slopes", 박사, pp.2003
- Kim, Y. S, "Prediction of Relative Crest Settlement of Concrete-faced Rockfill Dams Analyzed using an Artificial Neural Network Model", Computers and Geotechnics, 35, pp.313~322 (2008)
- Dam Intergration Information System. Technical report, "K-water", Korea Water Resources Corporation, ~ (2005)
- Lawton, F. L., "Settlement of Rockfill Dams. Proceedings", Eighth International Congress on Large Dam. Q.32 R.2. Edinburgh, Scotland, 3, pp.599~613 (1964)
- Shin, H., "Neural Network Based Constitutive Models For Finite Element Analysis", 박사, pp.2001
- Soydemir, C., "Deformation of Membraine-faced Rockfill Dams", Seventh European Conference on Soil Mechanics and Foundation Engineering, 3, pp.281~284 (1979)
- Sowers, G. F., "Compressibility of Broken and the Settlementof Rockfills", Proceedings, Sixth International Conferenceon Soil Mechanics and Foundation Engineering. Toronto,Canada, 2, pp.561~565 (1965)