The influence of rock mass properties on TBM performance was studied and a new empirical equation for predicting TBM performance in Alborz Service Tunnel developed by using multiple linear regression analysis in this study. Fabric indices of four rock mass classification systems along with uniaxial compressive strength of rock material normalized by cutter load and the angle between tunnel axis and joints were included in the model. Comparison of measured ROPs with those predicted by the multi-linear regression model showed good agreement with correlation coefficient of 0.89.
Since the first hard rock TBM was successfully used in1950s, the performance analysis of machine and the development of accurate prediction models have been the ultimate goals of many researchers. Even though intact rock parameters, mainly uniaxial compressive and tensile strength, and/or predictive indices such as fracture toughness, Schmidt hammer, Shore hardness, Punch penetration and DRI tests have been widely used as input parameters for predicting TBM performance (Graham 1976, Farmer & Glossop 1980, Blinheim 1979, Bamfrod 1984, Dollinger et al. 1998), a variety of theoretical models (Roxborough&Phillips 1975, Ozdemir et al. 1978, Snowdon et al. 1982, Sanio 1985, Rostami & Ozdemir 1993) and empirical models (Bruland 1998, Nelson et al. 1999, Gong & Zhao 2008, Yagiz 2008, Hassanpour et al. 2009) has been also used for performance prediction. Besides, many researchers have made attempts to correlate TBM performance to rock mass classifications due to their simplicity and easy measurement (Cassinelli et al. 1982, Innaurato et al. 1991, Palmström 1995, Barton 2000, Sapigni et al. 2002, Ribacchi & Lembo-Fazio 2005, Bieniawski et al. 2006, Khademi Hamidi et al. 2010). In this study, a new empirical model of TBM performance is developed based on fabric index of four common rock mass classifications.