• 全国中文核心期刊
  • 中国科技核心期刊
  • 美国工程索引(EI)收录期刊
  • Scopus数据库收录期刊
Analysis and prediction of Ground settlement induced by Subway Construction with Shield tunneling in Xi’an Loess strata[J]. Chinese Journal of Geotechnical Engineering, 2010, 32(7).
Citation: Analysis and prediction of Ground settlement induced by Subway Construction with Shield tunneling in Xi’an Loess strata[J]. Chinese Journal of Geotechnical Engineering, 2010, 32(7).

Analysis and prediction of Ground settlement induced by Subway Construction with Shield tunneling in Xi’an Loess strata

More Information
  • Received Date: May 04, 2009
  • Revised Date: December 13, 2009
  • Published Date: July 14, 2010
  • It is the first time to use EPB method in the subway construction in Xi’an loess strata. There is no better work experience for reference. The difference between the observed results and the Peck expressions is larger for the ground settlement trough. The real process of shield tunneling construction is simulated by FEM with Duncan-Chang model, which is programmed with APDL. The Duncan-Chang parameters, moisture content and depth of the tunnel axis are employed to perform quantitative analysis. The law of the ground settlement induced by subway construction with shield tunneling in Xi’an loess strata is studied, and an expressions is put forward to predict a certain measured ground settlement. It shows that the expression is suitable for the investigation of the ground settlement characteristics, and the conclusion is significant for similar projects with shield tunneling in Xi’an loess strata.
  • Related Articles

    [1]RUAN Yong-fen, YU Dong-xiao, WU Long, TAN Gui-ping, LI Fei-peng, CHEN Bo. DE-GWO algorithm to optimize SVM inversion mechanical parameters of soft soil[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(S1): 166-170. DOI: 10.11779/CJGE2021S1030
    [2]NI Sha-sha, CHI Shi-chun. Back analysis of permeability coefficient of high core rockfill dam based on particle swarm optimization and support vector machine[J]. Chinese Journal of Geotechnical Engineering, 2017, 39(4): 727-734. DOI: 10.11779/CJGE201704019
    [3]TAN Xiaolong. Support vector machine prediction model based on slope displacement monitoring data[J]. Chinese Journal of Geotechnical Engineering, 2009, 31(5): 750-755.
    [4]LI Bo, XU Baosong, WU Jinkun, HU Jiang, XU Guanglei. Back analysis of dam mechanical parameters based on least squares support vector machine[J]. Chinese Journal of Geotechnical Engineering, 2008, 30(11): 1722-1725.
    [5]ZHAO Hongbo. Reliability analysis of slope based on support vector machine[J]. Chinese Journal of Geotechnical Engineering, 2007, 29(6): 819-823.
    [6]XU Chuanhua, REN Qingwen, ZHENG Zhi, XIAO Dexu. Displacement back analysis of rock mechanic parameters of underground grotto of Suofengying Hydraulic Power Plant[J]. Chinese Journal of Geotechnical Engineering, 2006, 28(11): 1981-1985.
    [7]ZHAO Hongbo. Parameters recognition of slide surface using genetic-support vector machine[J]. Chinese Journal of Geotechnical Engineering, 2006, 28(4): 541-544.
    [8]LIU Kaiyun, QIAO Chunsheng, TENG Wenyan. Research on non-linear time sequence intelligent model construction and prediction of slope displacement by using support vector machine algorithm[J]. Chinese Journal of Geotechnical Engineering, 2004, 26(1): 57-61.
    [9]ZHAO Hongbo, FENG Xiating. Study and application of genetic-support vector machine for nonlinear displacement time series forecasting[J]. Chinese Journal of Geotechnical Engineering, 2003, 25(4): 468-471.
    [10]Xu Jun, Shao Jun, Zheng Yingren. Application of genetic algorithm to reliability analysis of geotechnical engineering[J]. Chinese Journal of Geotechnical Engineering, 2000, 22(5): 586-589.

Catalog

    Article views (936) PDF downloads (542) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return