TBM performance prediction based on rock properties

被引:11
|
作者
Yagiz, S. [1 ]
机构
[1] Pamukkale Univ, Fac Engn, Dept Geol Engn, Denizli, Turkey
关键词
D O I
10.1201/9781439833469.ch97
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
The knowledge of rock type and technology using for tunnel opening is essential for any mechanical excavation. In present, utilizing Tunnel Boring Machines (TBM) that is full-face tunnel machine is the most common way to excavate tunnels since this method offers numerous advantages over drill and blasting methods, for an example; TBM applies power to the rock in a relatively constant operation, automatically gathers up the cuttings and conveys them to a haulage unit. Having some prior knowledge of the potential performance of the selected TBM is very important in rock excavation projects for the scheduling and the cost estimation. Most of the TBM performance estimation analysis is based on TBM specifications, various intact or mass rock parameters. There have been numerous efforts in the last thirty years to develop methods to accurately predict TBM penetration rate in a given geology and rocks. These models/equations are mainly based on theoretical analysis combined with empirical data. Using the actual TBM field data, intact and mass rock properties, including rock strengths, brittleness and joint orientations, that was collected from a recently excavated hard rock TBM project in New York City, an empirical equation was developed for prediction of TBM performance.
引用
收藏
页码:663 / 670
页数:8
相关论文
共 50 条
  • [31] Performance Prediction of TBM Disc Cutting on Marble Rock under Different Load Cases
    Tan, Qing
    Yi, Liang
    Xia, Yi-Min
    [J]. KSCE JOURNAL OF CIVIL ENGINEERING, 2018, 22 (04) : 1466 - 1472
  • [32] TBM tunneling parameters prediction method based on clustering classification of rock mass
    基于岩体聚类分级的TBM掘进参数预测方法
    [J]. Zheng, Yinghao (yizheng0501@foxmail.com), 1600, Academia Sinica (39): : 3326 - 3337
  • [33] Prediction model of rock mass quality classification based on TBM boring parameters
    Ji, Feng
    Lu, Junfu
    Shi, Yuchuan
    Chen, Guoqing
    [J]. DISASTER ADVANCES, 2013, 6 : 265 - 274
  • [34] Prediction of the rock properties ahead of the tunnel face in TBM tunnels by geostatistical simulation technique
    Aoki, K
    Mito, Y
    Yamamoto, T
    Shirasagi, S
    [J]. ENVIRONMENTAL ROCK ENGINEERING, 2003, : 245 - 250
  • [35] Bayesian prediction of TBM penetration rate in rock mass
    Adoko, Amoussou Coffi
    Gokceoglu, Candan
    Yagiz, Saffet
    [J]. ENGINEERING GEOLOGY, 2017, 226 : 245 - 256
  • [36] Assessing TBM performance in heterogeneous rock masses
    Sarah Sissins
    Chrysothemis Paraskevopoulou
    [J]. Bulletin of Engineering Geology and the Environment, 2021, 80 : 6177 - 6203
  • [37] Prediction and classification of rock mass boreability in TBM tunnel
    Wu Xin-lin
    Zhang Xiao-ping
    Liu Quan-sheng
    Li Wei-wei
    Huang Ji-min
    [J]. ROCK AND SOIL MECHANICS, 2020, 41 (05) : 1721 - +
  • [38] Assessing TBM performance in heterogeneous rock masses
    Sissins, Sarah
    Paraskevopoulou, Chrysothemis
    [J]. BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT, 2021, 80 (08) : 6177 - 6203
  • [39] Empirical estimates of TBM performance in hard rock
    Stevenson, GW
    [J]. 1999 RAPID EXCAVATION AND TUNNELING CONFERENCE, PROCEEDINGS, 1999, : 993 - 1009
  • [40] Classification and Prediction of Rock Mass Boreability Based on Daily Advancement during TBM Tunneling
    Li, Zhiqiang
    Tao, Yufan
    Du, Yuchao
    Wang, Xinjie
    [J]. BUILDINGS, 2024, 14 (07)