This article deals with numerical modeling of dolomite behavior and fracture under dynamic compressive loading. The dolomite was modelled using the Karagozian and Case Concrete (KCC) constitutive model, for which a calibration procedure was also briefly described. The constants for the KCC model were determined based on the literature data and experimental tests performed within a wide range of pressures and strain rates. The Dynamic Increase Factor (DIF) which is a scaling factor for KCC strength surfaces, was also determined and implemented. Numerical simulation of a dynamic uniaxial test using Split Hopkinson Pressure Bar (SHPB) was performed with a good quantitative and qualitative correlation. Moreover, an 30 % increase in the maximum strength, compared to quasi-static test results, was observed.

1. Introduction

Rocks are the main component of the Earth's crust. Depending on the forming method and the occurrence region (the influence of atmosphere conditions), their appearance and properties may significantly varies. Over the past decades, the rapid development of numerical and computational methods has caused an increased interest in field of rock modelling. The main reason for this fact is a constant pursuit of safety improvement in civil engineering (transportation infrastructure) and cost reduction in mining industries (related to the large amount of explosives used for the crushing of rock masses). The most commonly used numerical algorithm is Finite Element Method that allows e.g. for calculation of stress distribution near boundaries of tunnels or caves, verification of the stability of mountain slopes, etc. This method is often applied for optimization of borehole distribution that can maximize the amount of excavated rocks with the reduced use of explosive materials (Wang et al., 2018; Baranowski et al. 2019).

Numerical modeling of rocks is a demanding task due to their complex nature: they contains pores, voids, micro and macro cracks, anisotropy of strength properties for different loading directions, relatively high sensitivity for strain rates and occurrence of dilatation effects, etc. (Hudson et al., 2000). It is challenging task to consider all of those phenomena in modelling, therefore, some simplifications are necessary. The most popular approach to rock modeling includes a usage of constitutive models that can reproduce the above phenomena (Holmquist, 1993; Malvar et al. 1997; Berg et al., 2004), adaptation of discrete methods (Lisjak, 2014), implementation of meshless methods (Nguyen et al., 2016), etc. However, reliable modeling of rocks requires a complex characterization of their mechanical properties assessed during experimental testing according to ISRM standards (Hudson et al., 2007).

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