长江科学院院报 ›› 2022, Vol. 39 ›› Issue (12): 56-61.DOI: 10.11988/ckyyb.20221069

• 软弱围岩稳定分析 • 上一篇    下一篇

香炉山隧洞5#支洞应急抢险段围岩参数反演及稳定性分析

韩钢, 黄书岭, 丁秀丽, 马旭强, 张雨霆, 何军   

  1. 长江科学院 水利部岩土力学与工程重点实验室,武汉 430010
  • 收稿日期:2022-08-22 修回日期:2022-10-13 出版日期:2022-12-01 发布日期:2022-12-01
  • 作者简介:韩 钢(1991-),男,山东青岛人,工程师,博士,主要从事地下洞室稳定性分析与数值方法研究。E-mail: 2450904009@qq.com
  • 基金资助:
    云南省重大科技专项计划项目(202102AF080001-2)

Inversion Analysis of Rock Mass Mechanical Parameters and Stability Analysis of Emergency Rescue Section in Adit 5# of Xianglushan Tunnel

HAN Gang, HUANG Shu-ling, DING Xiu-li, MA Xu-qiang, ZHANG Yu-ting, HE Jun   

  1. Key Laboratory of Geotechnical Mechanics and Engineering of Ministry of Water Resources, Yangtze River Scientific Research Institute, Wuhan 430010, China
  • Received:2022-08-22 Revised:2022-10-13 Published:2022-12-01 Online:2022-12-01

摘要: 在建的滇中引水工程香炉山隧洞5#支洞穿越活动断裂带,地质条件极为复杂,施工过程中发生过严重的涌水突泥灾害,围岩稳定问题极为突出,严重制约施工进度和工程安全。为深入系统地研究5#支洞应急抢险洞段合理的围岩力学参数及隧洞稳定性情况,充分利用现场监测及物探资料,采用基于神经网络和遗传算法的位移反演方法确定了应急抢险洞段围岩的力学参数;并在此基础上,模拟施工开挖支护全过程,进行了围岩稳定性分析。结果表明:在当前开挖支护条件下,5#支洞应急抢险洞段整体处于稳定状态,除桩号K0+501—513洞段右边墙围岩变形量较大外,其余部位围岩变形量整体<15 cm;塑性区深度在2~5 m范围内;支护结构受力整体处于正常水平。相关研究结果对于5#支洞后续洞段或相近条件隧洞安全快速施工具有指导意义。

关键词: 围岩参数反演, 神经网络, 遗传算法, 稳定性分析, 香炉山隧洞

Abstract: The 5# adit of Xianglushan tunnel under construction of Central Yunnan Water Diversion Project features complex geological conditions as it crosses active fault zones. Severe water-mud bursting disasters and prominent stability problems of surrounding rock hinder the construction progress and project safety. According to field monitoring and geophysical exploration data, we determined the mechanical parameters of surrounding rock at emergency rescue section by using inversion analysis based on neural network and genetic algorithm; on this basis, we simulated the whole process of construction, excavation, and support, and analysed the surrounding rock stability. Results manifested that the surrounding rock mass of emergency rescue tunnel section of adit 5# was in an overall stable state. Except that the deformation of surrounding rock on the right side of the tunnel section K0+501-513 was relatively large, the deformation of other parts was less than 15 cm in general; the depth of plastic zones was within the range of 2-5 m; and the stress of support structures was at a normal level. The research findings would guide the safe and rapid construction of subsequent tunnel sections of 5# adit or tunnels with similar geological conditions.

Key words: inversion of rock mass parameters, neural network, genetic algorithm, stability analysis, Xianglushan Tunnel

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