摘要
为提高对盾构施工引起的地表沉降预测的准确性,采用基于子集模拟思想的贝叶斯更新方法进行关键土体参数的概率反分析,充分融合现场监测数据,动态预测由盾构掘进引起的地表沉降,并探讨了子集模拟每层的样本数量和融合监测数据阶段数对参数后验分布的影响。将该方法应用于杭州某隧道工程中,研究结果表明:子集模拟每层样本数量的增加虽然可以提高反演分析的稳定性,但过大的样本会增加计算负担;结合监测数据的阶段数越多,土体参数的不确定性估计越低,预测的变形也会越接近监测值,笔者所提方法应用于隧道地表沉降预测具有可行性和实用性。
To improve the accuracy of predictions of ground settlements caused by shield tunneling,a ground settlement prediction method is developed based on the Bayesian updating with structural reliability.The key soil parameters are updated using the available field monitoring data,which in turns update the settlement predictions at the subsequent stages.The method is applied to a tunnel project in Hangzhou.The results show that the increase in the number of samples within the subset simulation can improve the stability of the inverse analysis,but a huge number of samples will increase the computational burden.As more stages of monitoring data are incorporated,the estimated uncertainty of soil parameters becomes lower and the settlement predictions are more accurate.
作者
徐建华
虞梦菲
XU Jianhua;YU Mengfei(Zhejiang Huadong Engineering Consulting Co.,Ltd.,Hangzhou 311122,China;College of Civil Engineering,Zhejiang University of Technology,Hangzhou 310023,China)
出处
《浙江工业大学学报》
北大核心
2025年第4期384-391,共8页
Journal of Zhejiang University of Technology
关键词
土木工程
盾构隧道
数据融合
贝叶斯方法
地表沉降
civil engineering
tunnel shield
data assimilation
Bayesian method
ground settlement
作者简介
徐建华(1969-),男,河南上蔡人,高级工程师,研究方向为工民建与市政,E-mail:xu_jhhdec.com。
