| 双向八车道连拱隧道围岩力学参数反演分析 |
| 投稿时间：2011-01-24 修订日期：1900-01-01 点此下载全文 |
| 引用本文：崔志盛,金磊,赵凯.双向八车道连拱隧道围岩力学参数反演分析[J].钻探工程,2011,38(5):65-69.CUI Zhi-sheng,JIN Lei,ZHAO Kai. Back Analysis on Mechanical Parameters of Surrounding Rock in a Bi-arch Tunnel with Eight Lanes[J]. Drilling Engineering, 2011,38(5):65-69. |
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| 基金项目:国家自然科学基金项目(40972178) |
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| 中文摘要:在采用双侧壁导坑法施工的双向八车道特大断面连拱隧道中，施工步繁多，临时支护设置的时间长，隧道全断面的变形量测只能在临时支护拆除后进行。由于全断面变形数据获取得较晚，故较难将其用于围岩力学参数的反演。将有限元计算和BP神经网络技术相结合，并在有限元计算过程中考虑实际的施工步，建立起所有临时支护拆除之前这一施工状态下导坑的变形量与围岩力学参数之间的非线性映射关系，并通过对应状态下实测的导坑变形值反演了围岩的力学参数。将反演的结果用于正分析验算，验证了该方法是可行的。 |
| 中文关键词:隧道工程 双连拱隧道 位移反分析 有限元 BP神经网络 |
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| Back Analysis on Mechanical Parameters of Surrounding Rock in a Bi-arch Tunnel with Eight Lanes |
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| Abstract:In a bi-arch tunnel with eight lanes using double-side-drift method, it is the deformation of the drifts rather than the whole tunnel section that is measured due to the restriction from the temporary linings. Only by the time when all the temporary linings are removed can the back analysis be implemented if we choose to use the whole section’s deformation data to get the mechanical parameters of surrounding rock, which is time-consuming. This paper discusses a method which involves both FEM and BP neural network to establish a nonlinear mapping relationship between surrounding rock’s mechanical parameters and drifts’ final deformation rather than the whole section’s deformation with construction sequences taking into consideration, followed by a back analysis on the mechanical parameters using the drifts’ in-situ monitoring deformation data on the basis of the above relationship. There’s a good agreement between the in-situ deformation data and the numerical deformation data achieved from a normal analysis using the back analyzed parameters. |
| keywords:tunneling engineering bi-arch tunnel displacement back analysis FEM BP neural network |
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