Predicting TBM performance in soft sedimentary rocks, case study of Zagros mountains water tunnel projects

Abstract

Soft rock formations are widespread throughout the mountainous regions of the world including the mountains of western and southern Iran. Therefore, it is very common to pass through soft rock formations while building long tunnels for various purposes in the mountainous regions. The soft sedimentary rocks are frequently found in Zagros Mountains located in the south and west of Iran, where most of Iran's water conveyance projects (long and deep tunnels) have been constructed or are under construction. The behavior of these rocks in tunneling projects has received much attention in the past decades, but some features comprising the boreability and performance of tunneling machines in such rocks have received little attention. Many of these sedimentary rocks, especially those composed mainly of clay minerals, exhibit “non-structurally controlled” behavior in deep tunnels and below the groundwater level, and are completely continuous. During loading by disc cutters, these rocks usually exhibit plastic behavior, and the formation of chips in these rock types are often different than brittle and discontinuous rocks. Obviously, this necessitates the development of special models to predict the TBM performance in these rocks. In this study, the machine performance in soft rock formations along some of the Zagros Mountains water tunnel projects has been investigated. Efforts have been made to develop a special empirical model for continuous (intact) soft rock formations to complement the models presented in previous studies. Evaluation of the relationships between different geological and machine performance and operating parameters in these projects indicated that there is a strong correlation between intact rock properties (uniaxial compressive strength) and two parameters including penetration and cutter load. New empirical models developed based on statistical analyses of machine performance in these projects are presented for predicting TBM performance in similar conditions.