Optimization of site exploration program for improved prediction of tunneling-induced ground settlement in clays

Abstract

Excessive settlement caused by tunneling during construction often damages adjacent infrastructures and utilities. Such excessive settlement can also present a challenge in the maintenance of subways during their operation. Thus, it is important to be able to accurately predict tunneling-induced settlement. The uncertainties in geotechnical parameters, however, can lead to either an overestimation or an underestimation of the tunneling-induced settlement. Such uncertainties can arise from many sources such as spatial variability, measurement error, and model error; in this paper, the focus is on the geotechnical parameters characterization from site exploration. The goal here is to determine an optimal level of site exploration effort so that effective predictions of the tunneling-induced settlement in clays can be achieved. To this end, a Monte Carlo simulation-based numerical model of site exploration is first established to generate artificial test data. Then, a series of parametric analyses are performed to investigate the relationship between the level of site exploration effort and the accuracy of the tunneling-induced ground settlement prediction. Through the assumed different levels of site exploration effort, statistics of soil parameters are estimated using the maximum likelihood method and the tunneling-induced ground settlement is then analyzed using the probabilistic method, and finally the effect of site exploration effort is assessed. The knowledge generated from this series of analyses is then used to develop the proposed framework for selecting an optimal site exploration program for improved prediction of the tunneling-induced ground settlement in clays. Examples are presented to illustrate the proposed framework and demonstrate its effectiveness and significance.