盾构双线隧道随机有限差分法地表变形研究
Research on Surface Deformation of Twin Shield Tunneling by Random Finite Difference Method
吴波 1郑卫强 1夏倩 1朱若男 1曾佳佳 1王吾浩 1徐世祥1
作者信息
摘要
研究目的:准确预测盾构双线隧道开挖引起的地表问题对保障线路周边安全十分重要.基于随机场理论框架,将非侵入式随机分析、有限差分法和响应面法有机耦合,建立非侵入式盾构双线隧道地表变形分析有限差分模型,系统研究土体参数与双线隧道间距对地表变形的影响特性.研究结论:(1)土体参数变异系数与双隧间距对地表变形特征曲线变化影响明显;(2)地表变形曲线特征与土层参数随机分布密切相关,由于低刚度占优效应与模量呈现对数正态分布;(3)相较蒙特卡罗法,PCE法的计算精度相近,精度随阶数增加而提升,计算效率优势突出;(4)本研究成果可为设计参数选取提供一种快速可靠简便方法,也可为类似工程提供参考.
Abstract
Research purposes:Accurate prediction of surface problems caused by twin shield tunneling excavation is very important to ensure the safety of the surrounding area.We have organically coupled non-invasive stochastic analysis,the finite difference method,and the response surface method within the framework of random field theory to establish a finite difference model for analyzing surface deformation in non-invasive shield double-track tunnels.We systematically study the influence of soil parameters and the spacing of twin shield tunneling on surface deformation.Research conclusions:(1)The variation coefficient of soil parameters and the distance between double tunnels have obvious influence on the change of surface deformation characteristic curve.(2)The characteristics of surface deformation curve are closely related to the random distribution of soil parameters.Due to the dominant effect of low stiffness,the modulus shows a lognormal distribution.(3)Compared with the Monte Carlo method,the calculation accuracy is similar,and the accuracy increases with the increase of the order,and the calculation efficiency advantage is prominent.(4)The research results can provide a quick,reliable and simple method for the selection of design parameters,and can also provide reference for similar projects.
关键词
双线隧道/随机有限差分法/地表变形/可靠度/土体参数变异性Key words
twin shield tunneling/random finite difference method/surface deformation/reliability theory/variability of soil parameters引用本文复制引用
基金项目
国家自然科学基金(52168055)
江西省"双千计划"创新领军人才项目(jxsq2020101001)
江西省自然科学基金(20212ACB204001)
出版年
2024
NETL
NSTL
万方数据