Prediction of Crest Settlement of Center Cored Rockfill Dam using an Artificial Neural Network Model
2012
Kim, Y.S., Kangwon National University, Chuncheon, Republic of Korea | Kim, B.J., Dongguk University, Seoul, Republic of Korea | Oh, S.E., Kangwon National University, Chuncheon, Republic of Korea
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.
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