Robust Estimates of Rock Strength Parameters via Improved Analysis of Rock Strength Data

This paper investigates the effect that small sample sizes have on uncertainties associated with intact rock strength parameter estimations, using various combinations of strength data (namely, uniaxial and triaxial compressive, uniaxial compressive and indirect tensile, and uniaxial and triaxial compressive together with indirect tensile). The analysis applies recently developed Bayesian nonlinear regression models to small sample sizes (n = 9, 12 and 15) drawn from an extensive published data set to obtain Hoek-Brown strength parameters. The results show how the uncertainty in parameter estimations, particularly the correlation between estimated m and s_c are affected by the data combination. The paper further discusses how using a combination of three data types could result in significant reduction of uncertainties associated with strength parameter estimations, and concludes with suggestions for allocation of resources to different types of laboratory testing.