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山东大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (6): 127-134.doi: 10.6040/j.issn.1672-3961.0.2016.144

• • 上一篇    

基于离散裂隙网络模型的隧道涌水量预测

包建业1,王静2*   

  1. 1. 内蒙古建筑职业技术学院建筑工程学院, 内蒙古 呼和浩特 010070;2. 内蒙古建筑职业技术学院市政与路桥工程学院, 内蒙古 呼和浩特 010070
  • 收稿日期:2016-04-29 出版日期:2016-12-20 发布日期:2016-04-29
  • 通讯作者: 王静(1984— ),女,内蒙古呼和浩特人,讲师,本科,主要研究方向为道路桥梁工程. E-mail:hailan567@163.com E-mail:2897577391@qq.com
  • 作者简介:包建业(1982— ),男,内蒙古兴和人,讲师,本科,主要研究方向为道路桥梁工程. E-mail:2897577391@qq.com

Prediction of flow rate during tunnel excavation based on discrete fracture network models

BAO Jianye1, WANG Jing2*   

  1. 1. College of Civil Engineering, Inner Mongola Technical College of Construction, Hohhot 010070, Inner Mongola, China;
    2. Faculty of Civil and Transportation Engineering, Inner Mongola Techmical College of Construction, Hohhot 010070, Inner Mongola, China
  • Received:2016-04-29 Online:2016-12-20 Published:2016-04-29

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摘要： 通过建立不同赋存水体深度、不同隧道直径和不同开挖距离等共96个复杂裂隙网络数值模型,计算通过隧道掌子面的涌水量,拟合预测隧道涌水量的多参数回归方程。结果表明,流体的主要流动路径由连接入口边界和出口边界的连通裂隙组成。组成主要流动路径的裂隙内的流速最大;离连接入口边界和出口边界的连通裂隙越远,裂隙内的流速越小;水体较浅时,涌水量与开挖距离具有幂函数关系;水体较深时,涌水量与开挖距离具有线性关系;对隧道涌水量影响程度由高到低的影响因素依次为隧道直径、水体深度、开挖距离。隧道涌水量的预测结果和数值计算结果能很好吻合,验证了该回归方程具有普适性,可对节理发育岩体内隧道涌水量进行动态预测。

关键词: 裂隙网络, 回归方程, 动态预测, 隧道, 涌水量

Abstract: 96 complex fracture networks was modelled that had different water depths, tunnel diameters, and excavation distances, a multi-variable regression was proposed function to predict the flow rate at tunnel face by calculating flow rate of each case. The results showed that the main flow paths were formed by connected fractures between the inlet and outlet boundaries. The fractures which formed fracture network had the maximum flow rate, and the flow rate was smaller for fractures far from the flow paths. With the increment of excavation distance, the flow rate at tunnel face increased following power law functions when water depth was small and linear functions when water depth was large. Tunnel diameter was the most sensitive parameter to influence the flow rate at tunnel face, followed by water depth and excavation distance. The predicted and calculated results were tallied well, which indicated that the proposed multi-variable regression function was suitable for predicting flow rate at tunnel face. The obtained conclusions are helpful for the engineers to predict the flow rate at tunnel face during construction.

Key words: flow rate, fracture network, regression function, prediction, tunnel

中图分类号: 

  • U452
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