A probabilistic fragmentation-based rockfall model for open-pit and natural slopes

Accurate prediction of rockfall propagation is critical for designing safe slopes in open-pit mines as well as in other engineered or natural environments. Fragmentation during impact significantly alters runout distances, energy dissipation, and the hazard footprint, yet most trajectory models neglect this phenomenon or treat it empirically. This study applies RockFRAG, a novel probabilistic 2D lumped-mass model, developed by the author and implemented in a code, that explicitly incorporates fragmentation processes informed by laboratory experiments accounting for impact energy, block shape and rock-mass structure through probabilistic fragment trajectories. Applied to synthetic open‑pit bench profiles, fragmentation‑aware and intact‑block simulations are compared across different bench configurations, showing that neglecting fragmentation is not inherently conservative: depending on face angle and bench geometry, breakage can either extend runout and increase pit‑floor arrival probability, or promote earlier arrest through fracture‑energy dissipation. These geometry dependent, non monotonic effects cannot be captured by non fragmenting assumptions and lead to significant differences in runout envelopes and impact conditions. These findings underscore the need to account for fragmentation in runout based design checks and bench performance evaluation. A probabilistic treatment is essential to cover uncertainty in fragment behaviour and slope interaction, enabling risk informed design beyond deterministic assumptions, with implications extending to mountainous environments where impact induced breakage commonly influences runout variability and the performance of protective measures.