Journal of The Korean Society of Agricultural Engineers (한국농공학회논문집)

The Korean Society of Agricultural Engineers (한국농공학회)
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Prediction of Crest Settlement of Center Cored Rockfill Dam using an Artificial Neural Network Model

인공신경망기법을 이용한 중심차수벽형 석괴댐의 정부침하량 예측

  • 김용성 (강원대학교 농업생명과학대학 지역건설공학과) ;
  • 김범주 (동국대학교 공과대학 건설환경공학과) ;
  • 오상은 (강원대학교 농업생명과학대학 바이오자원환경학과)
  • Received : 2012.05.14
  • Accepted : 2012.06.13
  • Published : 2012.07.31
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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.

Keywords

References

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Cited by

  1. Long-term Settlement Prediction of Center-cored Rockfill Dam using Measured Data vol.15, pp.11, 2014, https://doi.org/10.14481/jkges.2014.15.11.21
  2. A Study on Settlement Prediction of Concrete-faced Rockfill Dam Using Measured Data During Construction and After Impounding vol.16, pp.2, 2015, https://doi.org/10.14481/jkges.2015.16.2.5