The paper presents the use of advanced stochastic simulation techniques for estimating the strength behavior of rock materials. The Shore Rebound hardness was measured on fifty rock specimens coming from eleven different geological localities in Czech Republic. The dry unit weight of every tested rock material was determined also. Uniaxial compressive strength of rock was evaluated then by conducting the compression test on every specimen. Empirical distribution of Shore hardness and dry unit weight variables obtained from laboratory tests was approximated by the best fitted theoretical probability distribution. The stochastic simulation using Latin Hypercube Sampling was conducted based on those distributions. Two different equations used for estimating the compressive strength of rock on the basis of Shore hardness in practice was used as model functions. Comparison and statistical evaluation of uniaxial compressive strength of rock determined by compression test and those obtained as a result of stochastic simulation is discussed. The description of probability distribution of uniaxial strength is obtained as a result of introduced analysis, which can be used as input for fully probabilistic design models of rock materials.
Several studies using Shore hardness have been done to estimate strength parameters of intact rock. For example: ,  or . Extension of referenced knowledge and practical experience in using of Shore hardness parameter from region of Czech Republic is presented in this paper. The authors collected relatively wide range of rock types, hence the results of examination of currently used correlations are general valid. Shore hardness of rock specimens was measured firstly. Uniaxial compressive strength was tested on the same specimens so obtained results can be correlated and reliably compared. Two basic formulas for estimation of UCS from Shore hardness were chosen for detailed analysis. Results of measurements were then used as inputs for stochastic simulation method and sensitivity analysis to evaluate the possibility of estimation of rock material strength in this way.