Ann model for prediction of rockfill dam slope stability

Abstract

Dam safety and potential failure is one of the issues with the highest risk in water resources management. The dam slope stability is adversely influenced by the natural seepage process in the dam. Thus, monitoring of the pore and total pressures in the dam core is essential in the seepage process analysis. It is possible during the dam operation period to have one or more cells malfunctioning, after years of operation. Sometimes it is technically not possible to replace the cell or the costs of the replacement are too high and not economically justified. At the Pridvorica Dam, several instruments-cells for pore and total pressure monitoring malfunctioned. The objective of this study is to develop a neural network model for the prediction of the pore and total pressure on the malfunctioning cells and to demonstrate its quick and effective practical application for identifying complex non-linear relationship between the input and output variables. The proposed approach can be a very helpful tool for modeling of the stochastic behavior of the dam in order to give adequate warning of soil pressures to prevent failures.