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研究与探索

基于围岩力学参数的TBM净掘进速率多元回归预测模型

  • 闫长斌 ,
  • 杜旭阳 ,
  • 戴晓亚 ,
  • 闫珊 ,
  • 李高留 ,
  • 陈思远
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  • (郑州大学土木工程学院, 河南 郑州 450001)
闫长斌(1979—),男,河南濮阳人,2006年毕业于中南大学,岩土工程专业,博士,副教授,主要从事岩土与地下工程方面的研究工作。Email: yanchangbin_2001@163.com。

收稿日期: 2018-04-17

  修回日期: 2018-10-30

  网络出版日期: 2019-02-01

基金资助

国家自然科学基金资助项目(U1504523); 河南省重点研发与推广专项(182102210014); 郑州大学校级大学生创新创业训练计划项目(2017cxcy246)

Multiple Regression Prediction Model for TBM Net Boring Rate Based on  Mechanical Parameters of Surrounding Rock

  • YAN Changbin ,
  • DU Xuyang ,
  • DAI Xiaoya ,
  • YAN Shan ,
  • LI Gaoliu ,
  • CHEN Siyuan
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  • (School of Civil Engineering, Zhengzhou University, Zhengzhou 450001, Henan, China)

Received date: 2018-04-17

  Revised date: 2018-10-30

  Online published: 2019-02-01

摘要

TBM净掘进速率与围岩地质条件密切相关,特别是岩体力学参数。为研究TBM净掘进速率与围岩力学参数之间的内在联系,以兰州水源地建设工程输水隧洞双护盾TBM施工为背景,选取岩石单轴抗压强度、单轴抗拉强度、泊松比、变形模量等围岩力学参数,进行TBM净掘进速率与围岩力学参数相关性分析,得到相应的拟合关系式。在单因素分析的基础上,经过线性处理,建立TBM净掘进速率的多元线性回归预测模型。研究结果表明: TBM净掘进速率与围岩力学参数之间具有明显的线性相关性,TBM净掘进速率随单轴抗压强度、单轴抗拉强度和变形模量的增大而减小,随泊松比的增大而增大; TBM净掘进速率多元线性回归预测模型总体上精度较高,其预测误差在15%以内,且对不同围岩类型具有较强的适用性。研究成果能够为TBM施工性能评估提供新的参考。

本文引用格式

闫长斌 , 杜旭阳 , 戴晓亚 , 闫珊 , 李高留 , 陈思远 . 基于围岩力学参数的TBM净掘进速率多元回归预测模型[J]. 隧道建设, 2019 , 39(1) : 48 -53 . DOI: 10.3973/j.issn.2096-4498.2019.01.005

Abstract

The tunneling performances of TBM are closely related to the geological conditions of surrounding rock, especially the mechanical parameters of rock mass. Hence, the study of the relationship between the net boring rate of TBM and mechanical parameters of surrounding rock is of great importance. The doubleshield TBM tunneling in water conveyance tunnel of Lanzhou Water Source Construction Project is taken as an example to analyze the relationship between the net boring rate of TBM and mechanical parameters of surrounding rock; the mechanical parameters of surrounding rock, such as uniaxial compressive strength, uniaxial tensile strength, Poisson′s ratio and deformation modulus, are chosen as key parameters; and the corresponding fitting formula is obtained. And then the single factor fitting analysis is linearly processed to establish a multiple regression prediction model of TBM boring rate. The research results show that: (1) There is a clear linear correlation between the net boring rate of TBM and the mechanical parameters of surrounding rock; the TBM net boring rate decreases with the increase of uniaxial compressive strength, uniaxial tensile strength and deformation, while increases with the increase of Poisson′s ratio. (2) The model has a higher accuracy in general, and its prediction error is less than 15%, which shows good feasibility to different surrounding rocks. The research results can provide reference for TBM tunneling performance evaluation.

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