Search

Copyright of Rudarsko-Geolosko-Naftni Zbornik is the property of Faculty of Mining, Geology & Petroleum Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Nowadays, Tunnel Boring Machines (TBM) are widely used around the world on account of their high rate of excavation, little impact on the surrounding rock, and their high safety standards. The rock mass boreability is considered as one of the main parameters in evaluating the TBMs' performance in jointed rock masses. Boreability is a parameter reflecting the interaction between the rock mass and cutting tools. This paper aims to render an account of the effect of Joints Geometrical Parameters on the boreability by use of a database prepared to utilize the data (TBM operation and geological parameters) collected from Kerman Water Conveyance Tunnel projects in Iran. For this purpose, the joint parameters (orientation, spacing, persistence) affecting the boreability have initially been investigated. Then, the total fracturing factors (Bruland) and Persistence classification were used to investigate the effects of all three parameters on the boreability. The results showed that the boreability is also increased by increasing the joint persistency. Besides, the effect of fracturing factor (Ks-total) on boreability increases by increasing the joint persistency. In this paper, a new parameter called "Rock Joint Index"(RJI) is also presented according to the analysis performed on the database. The boreability value estimated based on the RJI shows a good agreement with the actual penetration rates. [ABSTRACT FROM AUTHOR]

The risk of excavation operations due to high capital costs can be reduced by correct estimation of machine performance. Many models have been proposed to study this issue, but considering the nature of the problem, it is rather difficult to estimate tunnel boring machine performance by simple linear prediction models. The purpose of the present study is to construct linear and non-linear multivariate prediction models to estimate TBM performance as a function of rock mass properties in granitic and mica-gniess rocks. For this purpose, rock properties and machine data were obtained from a historical TBM tunneling project in Norway and then the database was established to develop performance prediction models utilizing the linear and the non-linear multiple regression methods. This study proposes more accurate and practical statistical models compared to the previous ones based on multivariate regression analyses to estimate the performance of hard rock TBMs. [ABSTRACT FROM AUTHOR]