Mechanical characteristics of ultra-shallow buried high-speed railway tunnel in broken surrounding rock during construction

被引:3
|
作者
Hao, Shaoju [1 ]
Fei, Ruizhen [2 ]
Yu, Jia [3 ]
机构
[1] Henan Radio & Televis Univ, Zhengzhou 450046, Peoples R China
[2] Cent South Univ, Changsha 410075, Peoples R China
[3] Zhenhua Port Machinery Co LTD, Shanghai 200125, Peoples R China
关键词
broken surrounding rock; ultra-shallow buried; high-speed railway tunnel; numerical sim-ulation; deformation characteristics; EXCAVATION; PARAMETERS; SUPPORT;
D O I
10.24425/ace.2022.141908
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The mechanical state of broken surrounding rock during the construction of ultra-shallow buried high-speed railway tunnel is very complicated, seriously affecting the construction safety. Tak-ing Huying Xishan tunnel on Beijing-Shenyang Line as engineering background, MADIS/GTS NX numerical simulation and field test methods are used to analyze the characteristics of stress field, over-all displacement, horizontal convergence of tunnel sidewalls and vault settlement during construction. The main mechanical characteristics of ultra-shallow buried high-speed railway tunnel with broken sur-rounding rock include: (1) After the stress redistribution, the stress concentration occurs at the boundary of the tunnel sidewall and surrounding rock, and the vertical displacement of tunnel vault and bottom appears obviously. (2) The horizontal displacement on both sides of the initial lining is obvious, while the horizontal displacement on the upper and lower support is small. The maximum lateral displace-ment of the initial lining is 1.71 cm, while the maximum vault settlement of the lower invert is 9.3 cm. (3) Both the horizontal convergence and the vault settlement increase with time. The growth rate is large in the early stage and tends to be stable in the later stage. (4) Compared with exponential and hyperbolic functions, the logarithmic function is most suitable for regression analysis of horizontal convergence and measured vault settlement data, and its fitting accuracy is higher than 90%.
引用
收藏
页码:645 / 659
页数:15
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