Modification of Peck Formula to Predict Ground Surface Settlement of Twin Tunnels in Low Permeability Soil

Accurate prediction of surface settlement induced by tunnel excavation is significant for preventing damage to existing structures under complex geological conditions. The Peck formula is currently considered as an efficient solution for surface settlement prediction. This paper proposes a modified Peck formula considering geological conditions to improve the accuracy of surface settlement prediction of twin tunnels. The asynchronization of the sinking rate and stability of the vault settlement and surface settlement within the river-affected area may attribute to the groundwater drawdown caused by cofferdam construction on the river. A modified Peck formula is put forward with soil permeability and width-controlling parameters involved. There is a small settlement at the center of the twin tunnels, making the settlement trough upward buckling, which is like a “W” shape. This situation can be accurately predicted by the modified formula with a significantly increased adjusted R-square. The modified formula can accurately predict the surface settlement of tunnels excavated in low permeability soil layers with a permeability coefficient between 10−4 cm/s and 10−7 cm/s, especially in the groundwater drawdown environment. The reliability of the modified Peck formula is verified by other cases in Nanjing and Singapore.

Ground Movements Prediction in Shield-Driven Tunnels using Gene Expression Programming

Introduction: The increase in population and traffic in metropolitan areas has led to the development of underground transportation spaces. Therefore, the estimation of the surface settlement caused by the construction of underground structures should be accurately considered. Several methods have been developed to predict tunneling-induced surface settlement. Among these methods, artificial intelligence-based methods have received much attention in recent years. This paper is aimed to develop a model based on Gene Expression Programming (GEP) algorithm to predict surface settlement induced by mechanized tunneling. Methods: For this purpose, Tehran Metro Line 6 was simulated numerically to investigate the effects of different parameters on the surface settlement, and 85 datasets were prepared from numerical simulations. Subsequently, several GEP models were implemented using the obtained datasets from numerical simulations and finally, a model with 30 chromosomes and 3 genes was selected as the optimum model. Results: A comparison was made between obtained maximum surface settlements by the proposed GEP model and numerical simulation. The results demonstrated that the proposed model could predict surface settlement induced by mechanized tunneling with a high degree of accuracy. Conclusion: Finally, a mathematical equation was derived from the proposed GEP model, which can be easily used for surface settlement prediction.