摘要
为研究土岩起伏地层中基坑开挖对下卧地铁隧道变形的影响,基于Boussinesq解与Mindlin解,考虑土与结构的共同作用,提出土岩起伏地层中基坑开挖引起下卧地铁隧道变形的半解析预测方法。通过系统参数研究,提出考虑土岩分界面埋深影响的隧道最大隆起变形经验预测公式,并预测厦门地铁1号线区间隧道的变形。为确保施工过程中隧道的安全,采用人工与自动化监测相结合的方案,开展基坑施工全过程中隧道竖向变形现场测试。通过对比分析理论预测值和实测数据,验证所提出的经验预测公式的准确性,并结合实测数据进一步探讨岩面起伏对开挖引起的隧道变形的影响规律。研究表明:1)所提出的经验预测公式可以较为准确地预测不同土岩分界面埋深条件下隧道的最大隆起变形;2)位于残积土及全风化岩中的右线隧道最大隆起变形比位于强、中风化岩中的左线隧道最大隆起变形大约40%;3)风化岩地区隧道隆起变形为软土地区隧道隆起变形的1/5~1/4。
Based on the Boussinesq solution and Mindlin solution and considering the combined effect of soil and structure, a semi-analytical prediction method for the deformation of subjacent metro tunnel caused by foundation pit excavation in undulant soil and rock strata is proposed. A prediction formula considering the burial depth of the bedrock surface is proposed by comprehensive parameter analysis. In order to ensure the safety of the tunnel during the construction, the tunnel deformation is monitored throughout the construction process by using combination scheme of artificial measurement and automatic measurement. By analyzing the predicted theoretical values and measured data, the accuracy of the proposed formula is verified and the influence of foundation pit excavation on tunnel deformation is further investigated. The results show that:(1) The proposed empirical prediction formula can accurately predict the maximum uplift of the tunnel under different buried depths of bedrock surface.(2) Compared with the maximum uplift deformation of the left line tunnel in strongly-weathered rock and moderately-weathered rock, the maximum uplift deformation of the right line tunnel in fully weathered rock and residual soil increases by about 40%.(3) Tunnel uplift deformation in weathered rock area is 1/5-1/4 of that in soft soil area.
作者
张建斌
ZHANG Jianbin(Xiamen Road & Bridge Construction Investment Development Co., Ltd., Xiamen 361026, Fujian, China)
出处
《隧道建设(中英文)》
北大核心
2019年第8期1247-1254,共8页
Tunnel Construction
关键词
土岩起伏地层
地铁隧道
隆起变形
开挖卸荷
半解析预测方法
undulant soil and rock strata
metro tunnel
uplift deformation
excavation unloading
semi-analytic prediction method