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Received Aug 23, 2017; Accepted Feb 18, 2018
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1. Introduction
Modeling of rock mass is a very difficult job due to the presence of discontinuities, anisotropic, heterogeneous, and nonelastic nature of rock mass, using empirical and numerical methods [1, 2]. The complex nature and different formation make the rock masses a difficult material for empirical and numerical modeling.
During initial stages of excavation projects, the detailed data are not available about strength properties, deformation modulus, in situ stresses, and hydrological of rock masses [3]. To handle the nonavailability of the detailed project data, the empirical methods like rock mass classification systems are considered to be used for solving engineering problems [4]. The empirical methods used defined input parameters in designing of any underground structures, recommendation of support systems, and determination of input parameters for numerical modeling [5]. The empirical methods classified the rock mass quantitatively into different classes having similar characteristics for easiy understanding and construction of underground engineering structures [3]. Despite its wide applications, the empirical methods do not evaluate the performance of support systems, stress redistribution, and deformation around the tunnel [6]. Therefore, it is very important to consider these parameters in designing of optimum underground structure and support systems. This deficiency of empirical method is solved by numerical methods.
Numerical modeling is gaining more attention in the field of civil and rock engineering for prediction of rock mass response to various excavation activities [7]. The numerical methods are convenient, less costly, and less time-consuming for the analysis of redistribution stresses and their effects on the behavior of rock mass and designing of structures within the rock mass environment. Numerical methods give the exact mathematical solution for the problem based on the engineering judgment and input parameters like physical and strength parameters of rock masses [8–12].
In this study, the rock mass along the tunnel axis was assessed using rock mass rating (RMR) and tunneling quality index (Q-system). The support system was recommended by these two classification systems. The rock mass behavior with the interaction of two different support systems was analyzed based...