Empirical methods of calculating the mechanical parameters of the rock mass

Abstract

The knowledge of the main mechanical constants of a rock mass (such as strength, deformability and the Poisson's ratio) is one of the most important for rock engineering design on or in rock mass. Until now, several empirical relationships were determined for calculating these material constants based on both the quality of the studied rock mass (ie. RMR or GSI values) IntroductionLarge scale rock mass characterization introduces material parameters related to mechanical properties. The most important properties are the deformation modulus; the unconfined strength and the Poisson's ratio value of the rock mass in interest. These material parameters are frequently related to laboratory data characteristics of intact rock samples and to the classical rock mass classification systems (e.g. RQD, Q, RMR or GSI). These rock mass quality measures quantify the relation between the rock mass and the intact rock.The established empirical relations between the mechanical parameters of rock masses (unconfined compressive strength, deformation modulus) and the rock mass classification systems (RMR or GSI values) show exponential increasing deformation modulus and compressive strength with the increasing quality of the rock mass.The paper summarizes the observed correlations published between the mechanical properties of rock masses and one of the rock mass classification systems. It was found, that the deformation modulus and the strength of a rock mass data may reflect a simple exponential relationship of the observed quantities. According to analysis of different proposed equations a new formula is suggested and the modification ratio (i.e. ratio of the deformation modulus and the strength of rock mass) is also determined.However, it is important to note, that there are huge differences between the published date and the empirical formulas. The reason for this variance is the difference in situ testing methods, that may give different values of mechanical parameters even for the same rock mass. According to Bieniawski [1], even a single testing method, such as flat jack test, can lead to a widely scattering results even where the rock mass is very uniform. The other reason for the discrepancy in the different calculation methods is the directional effect. Most rock masses are anisotropic and do not have single deformation modulus [2].There is no mechanical (physical) interpretation of the above empirical equations but these were analysed by e.g. [3]. Recently, Ván and Vásárhelyi [4] suggested a damage mechanical approach to analyse them. In this paper their method will be also presented.

Estimation of the Poisson’s Rate of the Intact Rock in the Function of the Rigidity

“…According to the publication of [8], in the rock engineering practice, the knowledge of the Poisson's rate value of the rock mass is highly important. The Poisson's rate value highly depend on the quality of the rock mass, thus in the increasing if the Geological Strength Index (GSI) increasing [8,21]:…”

Review of Rock-Mass Rating and Tunneling Quality Index Systems for Tunnel Design: Development, Refinement, Application and Limitation

“…A direct method of determining ν m from the RMR value was proposed [93,112] and is expressed in Equation (43).…”

“…This equation was modified and according to this modification, the ratio of ν m and ν i is a function of the corresponding RMR value [93], as shown in Equation (44). based.…”

“…This equation is suitable for dry conditions. c in Equation (20) is a general constant for Q > 1.0 that ranges from 10 to 40 with a mean value of 25 [68,93]. The applications of Equation (12) and (13) …”

New Method for Determination of Residual Strength Parameters and Critical Damage Value

“…Though repeat testing increases the accuracy of test results, there is still a challenge in the analysis of conventional rock mechanics test results. In rock engineering design, proper rock mass mechanical strength parameters need to be determined [2]. To overcome this problem, many researcher investigated sample preparation precision, sample screening, and test result correction [3][4], which provides a good foundation for improving the accuracy of test results.…”