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A Probabilistic Approach for Predicting Settlement Due to Tunneling in Spatially Varying Glacial Till
The prediction of ground surface settlement resulting from the excavation of shallow tunnels in soft ground is instrumental for determining the required tunnel boring machine support pressures to minimize the impact on nearby infrastructure. Conventional practice uses a deterministic approach to estimate these pressures. However, actual settlements resulting from tunneling operations may not match the deterministic prediction, particularly when soil properties exhibit a high degree of spatial variability. This highlights the need for a probabilistic approach in settlement prediction that incorporates spatial variability to quantify and account for uncertainties in the required support pressures. By evaluating site investigation data to assess spatial variability, this paper introduces an approach utilizing Monte Carlo simulations coupled with a finite difference model to produce a probability distribution of maximum settlements. The results provide a quantitative measure of both the probability of exceedance for maximum surface settlement and the corresponding uncertainty, which can be used to optimize design support pressures for tunneling.
A Probabilistic Approach for Predicting Settlement Due to Tunneling in Spatially Varying Glacial Till
The prediction of ground surface settlement resulting from the excavation of shallow tunnels in soft ground is instrumental for determining the required tunnel boring machine support pressures to minimize the impact on nearby infrastructure. Conventional practice uses a deterministic approach to estimate these pressures. However, actual settlements resulting from tunneling operations may not match the deterministic prediction, particularly when soil properties exhibit a high degree of spatial variability. This highlights the need for a probabilistic approach in settlement prediction that incorporates spatial variability to quantify and account for uncertainties in the required support pressures. By evaluating site investigation data to assess spatial variability, this paper introduces an approach utilizing Monte Carlo simulations coupled with a finite difference model to produce a probability distribution of maximum settlements. The results provide a quantitative measure of both the probability of exceedance for maximum surface settlement and the corresponding uncertainty, which can be used to optimize design support pressures for tunneling.
A Probabilistic Approach for Predicting Settlement Due to Tunneling in Spatially Varying Glacial Till
Grasmick, Jacob G. (author) / Mooney, Michael A. (author)
Geo-Risk 2017 ; 2017 ; Denver, Colorado
Geo-Risk 2017 ; 300-309
2017-06-01
Conference paper
Electronic Resource
English
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