A New Stochastic Rockfall Fragmentation Approach for Lumped Mass Simulations

Abstract This paper presents a novel fragmentation model for rockfall applications, integrating experimental, theoretical, and numerical observations with stochastic predictions. Extensive experiments with artificial spherical rock-like specimens revealed crucial aspects of block fragmentation upon impact, including fragmentation patterns and the relationship between the number, mass, and velocities of fragments relative to the impact velocity. A stochastic fragmentation prediction model, based on the statistical distribution of material properties of both the falling block and the impacted material, was proposed by the authors. Numerical studies using marble spheres led to a model that stochastically accounts for cumulative damage in the energy required to break the falling block. These insights were incorporated into a fragmentation module within the NURock lump mass trajectory simulator. Validation through targeted simulation, sensitivity analysis, and comparison with in-situ tests confirmed the model's accuracy. The proposed approach significantly advances rockfall simulation, impacting the design of rockfall protection structures by considering block fragmentation and cumulative damage from repeated impacts. This enables more accurate predictions of the masses and energy levels of blocks reaching designated areas, which is crucial for designing effective rockfall protection measures.