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  Combination of Artificial Neural Networks and FLAC3D for Predicting Tunnel Support

  Selection of diversion tunnel support system in dam projects is a very important factor affecting the safety and operation cost and can be estimated via several methods. In this study, one model whose data such as geomechanical parameters of rocks and tunnel geometry are obtained for diversion tunnel in Pirtaghi dam in Iran, is provided to estimate the axial force and bending moment of support system by using the artificial neural network techniques (ANN). Neural networks are trained with a set of data which are produced by numerical simulations. The results showed that the proposed method had an excellent capability for predicting the diversion tunnel support system and it could be used to determine the tunnel support system in similar condition.

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