中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
A case study of TBM performance prediction using a Chinese rock mass classification system - Hydropower Classification (HC) method

文献类型:期刊论文

作者Kong, Xiaoxuan3; Liu, Quansheng2,3; Liu, Jianping2,4; Pan, Yucong2,4; Hong, Kairong1
刊名TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
出版日期2017
卷号65页码:140-154
关键词Hydropower Classification method Tunnel boring machine (TBM) Performance prediction Field penetration index (FPI)
ISSN号0886-7798
DOI10.1016/j.tust.2017.03.002
英文摘要Basic Quality (BQ) method is a basic national standard of rock mass classification suitable for different industries in geomechanics and geotechnical engineering in China. Referring to the relevant provisions of BQ method, Hydropower Classification (HC) method, a specialized engineering geological classification system widely used in China, was compiled for evaluation on overall stability of surrounding rock and guide of excavation and support design of underground engineering in water conservancy and hydropower industry. As the input parameters of BQ or HC method are quite different with those used in RMR or Q system, which indirectly limits the applicability of the foreign developed TBM performance prediction models for the China's TBM tunnelling projects. In order to develop an empirical model for hard rock TBM performance prediction with more suitable applicability in China, 49 valid datasets were collected from a water conveyance tunnel mostly excavated in medium to hard igneous rocks, and the empirical relationships between TBM performance and each parameter in the database were studied. The results showed that the prediction accuracies of TBM performance based on HC or BQ are very limited as the effects of the input parameters of HC method on field penetration index (FPI) are different and their weights assigned are improper. TBM penetration rate (PR) reaches its maximum value in the HC range 40-60 and BQ range 350-450, respectively. Boreability of the rock mass in class III is higher than that in class II. Ridge regression, principal component regression and partial least-squares regression methods were employed to solve the multicollinearity between uniaxial compressive strength of intact saturated rock, intactness index of rock mass, angle between discontinuity plane and tunnel axis, and average overburden of tunnel section in the database. Comparisons between the measured FPI and predicted FPI showed good agreement. This highlights the powerful potential of multiple regression analysis model based on HC method in TBM performance prediction. However, it deserves to emphasize that the developed empirical relationships should be considered valid only for new projects with geological conditions similar to the studied tunnel in this study, and more field data from different projects need to be collected to develop a universal model in the future. (C) 2017 Elsevier Ltd. All rights reserved.
WOS研究方向Construction & Building Technology ; Engineering
语种英语
WOS记录号WOS:000401208800012
出版者PERGAMON-ELSEVIER SCIENCE LTD
源URL[http://119.78.100.198/handle/2S6PX9GI/4056]  
专题岩土力学所知识全产出_期刊论文
国家重点实验室知识产出_期刊论文
作者单位1.State Key Lab Shield Machine & Boring Technol
2.Chinese Acad Sci, State Key Lab Geomech & Geotech Engn, Inst Rock & Soil Mech ;
3.Wuhan Univ, Sch Civil Engn, Key Lab Safety Geotech & Struct Engn Hubei Prov ;
4.Univ Chinese Acad Sci ;
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Kong, Xiaoxuan,Liu, Quansheng,Liu, Jianping,et al. A case study of TBM performance prediction using a Chinese rock mass classification system - Hydropower Classification (HC) method[J]. TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY,2017,65:140-154.
APA Kong, Xiaoxuan,Liu, Quansheng,Liu, Jianping,Pan, Yucong,&Hong, Kairong.(2017).A case study of TBM performance prediction using a Chinese rock mass classification system - Hydropower Classification (HC) method.TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY,65,140-154.
MLA Kong, Xiaoxuan,et al."A case study of TBM performance prediction using a Chinese rock mass classification system - Hydropower Classification (HC) method".TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY 65(2017):140-154.

入库方式: OAI收割

来源:武汉岩土力学研究所

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