基于BP神经网络反演分析的隧道塌方机理研究

陈航, 张贝贝, 旷华江, 肖丽娜. 基于BP神经网络反演分析的隧道塌方机理研究[J]. 水文地质工程地质, 2023, 50(3): 149-158. doi: 10.16030/j.cnki.issn.1000-3665.202208066
引用本文: 陈航, 张贝贝, 旷华江, 肖丽娜. 基于BP神经网络反演分析的隧道塌方机理研究[J]. 水文地质工程地质, 2023, 50(3): 149-158. doi: 10.16030/j.cnki.issn.1000-3665.202208066
CHEN Hang, ZHANG Beibei, KUANG Huajiang, XIAO Lina. A study of the tunnel collapse mechanism based on the BP neural network inversion analysis[J]. Hydrogeology & Engineering Geology, 2023, 50(3): 149-158. doi: 10.16030/j.cnki.issn.1000-3665.202208066
Citation: CHEN Hang, ZHANG Beibei, KUANG Huajiang, XIAO Lina. A study of the tunnel collapse mechanism based on the BP neural network inversion analysis[J]. Hydrogeology & Engineering Geology, 2023, 50(3): 149-158. doi: 10.16030/j.cnki.issn.1000-3665.202208066

基于BP神经网络反演分析的隧道塌方机理研究

  • 基金项目: 国家自然科学基金项目( 51608141);贵州省教育厅青年科技人才成长项目(黔教合KY字[2022]008);贵阳市科技局贵阳学院专项资助项目(GYU-KY-[2021]);贵州省教育厅青年科技人才成长项目(黔教合KY字[2020]079)
详细信息
    作者简介: 陈航(1990-),男,硕士,主要从事岩土工程、地下工程等领域的教学与科研工作。E-mail:330596225@qq.com
    通讯作者: 张贝贝(1986-),男,博士,副教授,主要从事岩土、隧道等相关领域的工作。E-mail:369226241@qq.com
  • 中图分类号: U455

A study of the tunnel collapse mechanism based on the BP neural network inversion analysis

More Information
  • 岩溶区隧道在施工过程中易发生崩塌,针对力学方面的隧道塌方机理分析较多,而针对岩溶软弱破碎带等地层方面的隧道塌方机理研究分析较少。为保证隧道施工的安全性、经济性和可行性,掌握隧道施工中的塌方机理非常有必要。依托贵州某岩溶破碎地层隧道在开挖过程中发生的坍塌现象,结合隧道的监测数据,运用BP神经网络的构建原理,对隧道的地层参数进行反演。将反演土体力学参数输入到FLAC3D有限元软件构建的不同施工方法模型中,对典型断面的崩塌破坏机制和风险进行判断和分析。结果表明:施工方法对隧道开挖的稳定性影响较大,针对围岩等级为Ⅴ级的隧道,采用三台阶七步法和单侧壁导坑法施工较安全,隧道塌方与隧道双向同时开挖没有关系;反演所得的隧道拱顶位移预测值为2.3 cm,地表位移预测值为1.2 cm,与监测数据偏差13%左右,反演结果具有一定的可信度。研究结果对岩溶区软弱破碎地层断面隧道公路建设具有重要指导意义。

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  • 图 1  ZK98+738坍塌现场

    Figure 1. 

    图 2  模型计算网格

    Figure 2. 

    图 3  隧道边界条件示意图

    Figure 3. 

    图 4  监测点位置

    Figure 4. 

    图 5  大断面隧道施工模型

    Figure 5. 

    图 6  两台阶施工法

    Figure 6. 

    图 7  两台阶施工法和位移监测点

    Figure 7. 

    图 8  隧道断面位移图

    Figure 8. 

    图 9  隧道断面塑性区图

    Figure 9. 

    图 10  不同施工法和位移监测点

    Figure 10. 

    图 11  模拟不同施工法沉降位移图

    Figure 11. 

    图 12  两台阶单双线开挖沉降位移图

    Figure 12. 

    表 1  隧道不同级别围岩长度及占比

    Table 1.  Surrounding rock grade and length ratio of the tunnel

    隧 道名称围岩级别长度/m占比/%
    青岗山隧道 395 61.7
    19029.7
    558.6
    下载: 导出CSV

    表 2  正交设计试验表

    Table 2.  Orthogonal test tables

    编号粉质黏土围岩位移
    弹性模量/MPa黏聚力/kPa摩擦角/(°)弹性模量/GPa黏聚力/kPa摩擦角/(°)拱顶位移/mm地表位移/mm
    1 5 8.5 20 10 5 10 21 0.42
    216.2511.875201532.518.7440.88
    327.515.2520206027.5621.24
    438.7518.62202587.536.278.51.57
    55022203011545961.92
    638.752226.251032.527.554.51.09
    7508.526.25156036.260.51.21
    8511.87526.252087.54532.50.65
    916.2515.2526.25251151057.51.15
    1027.518.6226.2530518.7380.76
    1116.2518.6232.510604549.50.99
    1227.52232.51587.51064.51.29
    1338.758.532.52011518.7691.38
    145011.87532.525527.548.50.97
    15515.2532.53032.536.238.50.77
    165015.2538.751087.518.7621.24
    17518.6238.751511527.5480.96
    1816.252238.7520536.2591.18
    1927.58.538.752532.54555.51.11
    2038.7511.87538.75306010691.38
    2127.511.875451011536.2561.12
    2238.7515.254515545641.28
    235018.62452032.510531.06
    2452245256018.753.51.07
    2516.258.5453087.527.5420.84
    下载: 导出CSV

    表 3  地层参数反演数值

    Table 3.  Inversion of formation parameters

    地层弹性模量/MPa黏聚力/kPa摩擦角/(°)
    粉质黏土 5.17 13.52 13.24
    围岩142.51428.1225.54
    下载: 导出CSV
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出版历程
收稿日期:  2022-08-19
修回日期:  2022-10-02
录用日期:  2022-10-24
刊出日期:  2023-05-15

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