Tunnel face reliability analysis using active learning Kriging model—Case of a two-layer soils

Abstract

This paper is devoted to the probabilistic stability analysis of a tunnel face excavated in a two-layer soil. The interface of the soil layers is assumed to be positioned above the tunnel roof. In the framework of limit analysis, a rotational failure mechanism is adopted to describe the face failure considering different shear strength parameters in the two layers. The surrogate Kriging model is introduced to replace the actual performance function to perform a Monte Carlo simulation. An active learning function is used to train the Kriging model which can ensure an efficient tunnel face failure probability prediction without loss of accuracy. The deterministic stability analysis is given to validate the proposed tunnel face failure model. Subsequently, the number of initial sampling points, the correlation coefficient, the distribution type and the coefficient of variability of random variables are discussed to show their influences on the failure probability. The proposed approach is an advisable alternative for the tunnel face stability assessment and can provide guidance for tunnel design.

摘要

本文旨在研究双层土壤中隧道开挖时掌子面的稳定性问题。首先, 假设双层土壤的分界面位于 隧道拱顶上方, 以极限分析方法为依据, 采用旋转破坏机制构建掌子面失稳模型, 同时, 考虑了开挖 介质的剪切强度参数随机性对掌子面稳定性的影响。采用克里金模型代替其原始的功能函数, 进而采 用蒙特卡洛法计算掌子面的破坏概率, 从而大大提高了计算效率和节约了计算成本。本文采用主动学 习函数对克里金模型进行训练, 因此, 可以确保其对掌子面破坏概率的预测高效而不失准确性。本文 首先建立了隧道掌子面破坏模型, 通过计算分析, 验证了所提出模型的正确性, 随后讨论了随机变量 的初始采样点数、相关系数、分布类型和变异系数等对隧道掌子面稳定性的影响。研究结果表明该方 法是一种高效精确的可靠度分析方法, 可以为隧道设计提供一定的理论指导和依据。