Experimental and numerical studies of the impact breakage of granite with high ejection velocities

Abstract

The impact-induced fragmentation of rock is widely and frequently encountered when natural hazards occur in mountainous areas. This type of fragmentation is an important and complex natural process that should be described. In this study, laboratory impact tests under different impact velocities were first conducted using a novel gas-driven rock impact apparatus. The three-dimensional digital image correlation (3D DIC) technique was used to monitor the dynamic fragmentation process upon impact. Then, coupled 3D finite-discrete element method (FDEM) numerical simulations were performed to numerically investigate the energy and damage evolutions and fragmentation characteristics of the sample under different impact velocities. The laboratory test results show that as the impact velocity increases, the failure pattern of the rock sample gradually changes from shear failure to splitting failure, and the fragmentation intensity increases obviously. The strain localization area gradually increases as the impact velocity increases and as the location gradually deviates away from the impacting face. In the numerical simulation, the proposed model is validated by quasi-static uniaxial compression tests and impact tests. The numerical simulations clearly show the progressive fracture process of the samples, which agrees well with the experimental observations. The evolutions of energy and damage variables were also derived based on the simulation results, which are markedly affected by the impact velocity. The fragment size distributions based on mass and number can be well fitted using a generalized extreme value law. Finally, the distribution of the fragment flying velocity and angle are analyzed.

Global Mapping of Fragmented Rocks on the Moon with a Neural Network: Implications for the Failure Mode of Rocks on Airless Surfaces

“…Many of the morphologies detected in the visual survey (Section 3.2) have been described in previous work on rock failure (e.g., Basu et al 2013;Zhang et al 2022) or shattering (e.g., Fujiwara et al 1989;Nakamura et al 2008;Durda et al 2015); although, it is the first time that these morphologies are observed for very large target sizes (10-50 m) and for the velocity regime of ∼5-40 km s −1 (e.g., Ivanov 2001;McNamara et al 2004). The similarity of morphological types for impact-induced fragmentation occurs over a wide range of target sizes: centimeters (in laboratory experiments) to tens of meters (reported here).…”

“…Fracturing, fragmentation and fragment size frequency distribution (SFD) resulting from impact-induced failure of solids are aspects relevant for a wide range of studies (e.g., Kun & Herrmann 1999). In the case of failure of rocks, these aspects provide information about rock strength and are studied for engineering applications and geological research (e.g., Hogan et al 2012;Zhang et al 2022). The process of collision and fragmentation is key for the evolution of planetesimals, asteroids, and solid surfaces (e.g., Capaccioni et al 1986;Housen & Holsapple 1990;Giblin et al 1998;Ryan & Melosh 1998;Tanga et al 1999;Durda et al 2007).…”

Review of Linear Electric Motor Hammers—An Energy-Saving and Eco-Friendly Solution in Industry

“…The results of experimental and numerical studies of the impact breakage of granite with high ejection velocities are represented by Zhang et al [108]. The dependencies of the high-speed collision parameters granite damage ratio (α d ) and energy dissipation (E nd ) on impact velocity are shown in Figure 15.…”

Inversion study on elastic–plastic material parameters of red sandstone in uniaxial compression test

“…Techniques for characterizing the non-uniformity of rock materials involve the Digital Image Correlation (DIC) and the assignment of specific probability distribution parameters. Notably, the Digital Image Correlation is frequently combined with software such as ABAQUS, FLAC, PFC, and UDEC to conduct numerical simulations and analyze rock damage characteristics and damage evolution 9 , 10 . The method of assigning specific probability distribution parameters often relies on the Realistic Failure Process Analysis (RFPA) model or the Elasto-Plastic Cellular Automaton (EPCA) model, assuming that material parameters follow Weibull distribution, normal distribution, lognormal distribution, and so on, and establishing a damage and failure model for non-uniform material parameters 11 , 12 .…”