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...
The problem of estimating the settlement of shallow foundations on granular soils is very complex an...
Overconsolidated soils are widely encountered in practice where settlement calculations are crucial....
This paper presents two Artificial Neural Network (ANN) based models for the prediction of peak outf...
Dam safety and potential failure is one of the issues with the highest risk in water resources manag...
© 2002 American Society of Civil EngineersOver the years, many methods have been developed to predic...
Unpredictable settlement of earth dams has led researchers to develop new methods such as artificial...
Deformation predicting models are essential for evaluating the health status of concrete dams. Never...
The goal of this paper is to assess the effectiveness of using artificial neural networks in the pre...
In recent years artificial neural networks (ANNs) have been applied to many geotechnical engineering...
"January 2003"Bibliography: p. 191-208.xviii, 297 p. : ill. ; 30 cm.This thesis presents research wh...
In this study, employing a database of 19 concrete face rockfill dam (CFRD) cases, two prediction me...
Over the years, many methods have been developed to predict settlement of shallow foundations on coh...
Regular surveillance, data acquisition, and visual observation of high embankment dams are extremely...
Piled-raft in recent years has been accepted as an economical and efficient form of foundation which...
Ground surface settlement trough associated to tunneling is characterized by two important parameter...
The problem of estimating the settlement of shallow foundations on granular soils is very complex an...
Overconsolidated soils are widely encountered in practice where settlement calculations are crucial....
This paper presents two Artificial Neural Network (ANN) based models for the prediction of peak outf...
Dam safety and potential failure is one of the issues with the highest risk in water resources manag...
© 2002 American Society of Civil EngineersOver the years, many methods have been developed to predic...
Unpredictable settlement of earth dams has led researchers to develop new methods such as artificial...
Deformation predicting models are essential for evaluating the health status of concrete dams. Never...
The goal of this paper is to assess the effectiveness of using artificial neural networks in the pre...
In recent years artificial neural networks (ANNs) have been applied to many geotechnical engineering...
"January 2003"Bibliography: p. 191-208.xviii, 297 p. : ill. ; 30 cm.This thesis presents research wh...
In this study, employing a database of 19 concrete face rockfill dam (CFRD) cases, two prediction me...
Over the years, many methods have been developed to predict settlement of shallow foundations on coh...
Regular surveillance, data acquisition, and visual observation of high embankment dams are extremely...
Piled-raft in recent years has been accepted as an economical and efficient form of foundation which...
Ground surface settlement trough associated to tunneling is characterized by two important parameter...
The problem of estimating the settlement of shallow foundations on granular soils is very complex an...
Overconsolidated soils are widely encountered in practice where settlement calculations are crucial....
This paper presents two Artificial Neural Network (ANN) based models for the prediction of peak outf...