基于贝叶斯更新的盾构掘进经验模型可靠性分析

Reliability analysis of shield tunneling empirical model based on Bayesian updating

利用一种能够考虑经验模型不确定性的贝叶斯更新方法,将模型偏差系数视为随机变量,并根据现场观测数据对其进行不断更新,所得更新结果可用于后续阶段盾构掘进最大地表沉降和失效概率的预测。以福州地铁某区间隧道掘进为例,将本文所提方法应用于Peck模型、O′Reilly-New模型和刘建航修正的Peck模型等3种经验模型。研究结果表明:3种模型一般都会高估最大地表沉降,其中Peck模型偏差最大,刘建航修正的Peck模型次之,O′Reilly-New模型最小,而刘建航修正的Peck模型偏差比O′Reilly-New模型的变异性更小,通过所提方法可以有效考虑模型不确定性的影响;盾构掘进过程中,与另外2个模型比较,利用刘建航修正的Peck模型进行计算得到的结果更加准确;在本文所研究的算例中,盾构掘进过程中,检测数据不断增加,降低了模型偏差系数和土体参数的波动概率,从而使隧道失效概率的预测值降低。

A Bayesian updating method considering the uncertainty of the empirical model is used.The model deviation coefficient was regarded as a random variable,and it was updated continuously by using the field observation data.The updating results can be used to predict the maximum surface settlement and failure probability of foundation pit excavation in the subsequent stage.Taking a section of Fuzhou Metro Line 6 as an example,the proposed method was applied to Peck model,O'Reilly-New model,and Peck model modified by Liu Jianhang.The results show that the three models generally overestimate the maximum surface subsidence,among which Peck model has the largest deviation,followed by Liu Jianhang’s revised Peck model,and O'Reilly-New model has the smallest deviation,while the variability of Liu Jianhang’s revised Peck model is smaller than that of O′Reilly-New model,and the influence of model uncertainty can be effectively considered by the proposed method.The results of the modified Peck model are more accurate than those of the other two models.In the case study,the monitoring data increase with the excavation,which reduces the uncertainty of the model deviation coefficient and soil parameters,and ultimately leads to the decrease of the failure probability of shield tunnels.