A New Method for Pore Pressure Prediction on Malfunctioning Cells Using Artificial Neural Networks

Embankment rockfill dams are the most common dam construction types used in the world today. One third of all embankment dam failures are caused by dam slope instability. The dam is stable when the slopes are stable. Slope safety of the dam is assessed through pore and total pressure data analysis registered on pressure measurement cells installed in the dam. During the service life of a dam, one or more cells may malfunction after years of operation. Cell replacement implies economically unjustified high costs and is usually technically impossible and high risk. In this paper, the problem of a malfunctioning cell with a small available dataset is analysed. A new method for pore pressure prediction on malfunctioning cells has been developed using several successive artificial neural networks (ANNs) to obtain high accuracy of the predicted values. The results show that these predicted values are more precise than values we could have obtained using only one artificial neural network for prediction.

Automated summary

Embankment rockfill dams are the most common type of dams used in the world today, with one third of failures caused by dam slope instability. The stability of the dam is assessed through analysis of pore and total pressure data from pressure measurement cells. A new method using artificial neural networks has been developed to predict pore pressure on malfunctioning cells, resulting in more precise predicted values compared to using only one network.