A new model for predicting the advance rate of a Tunnel Boring Machine (TBM) in hard rock conditions

被引:13
作者
Arbabsiar, Mohammad Hossein [1 ]
Farsangi, Mohammad Ali Ebrahimi [1 ]
Mansouri, Hamid [1 ]
机构
[1] Shahid Bahonar Univ Kerman, Min Engn Dept, Kerman, Iran
来源
RUDARSKO-GEOLOSKO-NAFTNI ZBORNIK | 2020年 / 35卷 / 02期
关键词
Advance rate; Regression models; TBM geotechnical risk; Rock engineering systems; Hard rock TBM; Zagros long tunnel; PERFORMANCE PREDICTION; PENETRATION RATE; CASE-HISTORY; PRESSURE; PROJECT;
D O I
10.17794/rgn.2020.2.6
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The prediction of the advance rate of a Tunnel Boring Machine (TBM) in hard rock conditions is one of the most important concerns for estimating the time and costs of a tunnel project. In this paper, in the first step, a model based on Rock Engineering Systems (RES) is proposed to predict geotechnical risks (representing media characteristics) in rock TBM tunnelling. Fifteen main parameters that influence the geotechnical hazards were used in the modelling. In establishing an interaction matrix and also a parameter rating, the views of five experts were taken into account. The Vulnerability Index (VI) (geotechnical risk levels) for 2058 datasets out of 2168 sets of data from 53 geological zones in 11 km of the Zagros long tunnel was obtained. In the second step, based on the machine operating parameters such as torque, cutter head rotation per minute, cutter normal force and media characteristics (represented by VIs), which were used as input parameters and advance rate was used as an output parameter, while using 2058 datasets, linear and non-linear multiple regression analyses were carried out. no datasets (out of 2168 datasets), which were not used in the modelling, were applied to evaluate the performance of regression models and other models in literature and the results were compared. The obtained results showed that the new linear model proposed with R-2=0.83 and RMSE=0.12 has a better performance than the other models.
引用
收藏
页码:57 / 74
页数:18
相关论文
共 90 条
[1]  
ABROCK Research Project, 2013, ANAL PREDICTION PENE
[2]   A fuzzy logic model to predict specific energy requirement for TBM performance prediction [J].
Acaroglu, O. ;
Ozdemir, L. ;
Asbury, B. .
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, 2008, 23 (05) :600-608
[3]   Prediction of face advance rate and determination of the operation efficiency in retreat longwall mining panel using rock engineering system [J].
Aghababaei, Sajjad ;
Jalalifar, Hossein ;
Saeedi, Gholamreza .
INTERNATIONAL JOURNAL OF COAL SCIENCE & TECHNOLOGY, 2019, 6 (03) :419-429
[4]   Face stability conditions with earth-pressure-balanced shields [J].
Anagnostou, G ;
Kovari, K .
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, 1996, 11 (02) :165-173
[5]  
[Anonymous], 1982, TUNNELING
[6]  
[Anonymous], 2000, TUNN UNDERGR SPACE T
[7]  
[Anonymous], 1984, PROC ISRM S PERFORM
[8]  
[Anonymous], 1993, P 1993 RAPID EXCAVAT
[9]  
[Anonymous], 1993, INT J ROCK MECH MIN, DOI DOI 10.1016/0148-9062(93)92171-L
[10]  
[Anonymous], 2002, THESIS