Optimization of tunnel boring machine’s parameters under controlled surface settlement

Abstract

The construction of the tunnel usually leads to settlement which normally depends on the tunnel geometries, geological parameters and tunnel boring machine’s parameters. The tunneling construction rate is commonly reduced with more strict value of controlled surface settlement, resulting in an increase of time and budget of tunnel construction. This study is aimed to determine the optimal tunnel construction parameters using Genetic Algorithm (GA) with varying allowable surface settlements incorporated with the Artificial Neural Network (ANN) for predictions of surface settlement and tunneling construction rate. In this study, the MRTA Blue Line data are used to train the ANN and used as case study for determining optimal tunnel construction parameters. The results also indicated that the penetration rate and grouting pressure change significantly with the variation of allowable settlement.