Analysis of Rockfall Risk Using Image Analysis and Data-Driven Models

ABSTRACT: The challenge of rockfall and its associated risks has been haunting the mining industry for quite some time. It has been a significant cause of fatalities, serious injuries, and financial losses. Taking advantage of recent technological developments, novel methods of studying rockfalls are introduced. Such renovations are mainly focused on automating geological mapping of the rock surface and data-driven trajectory estimation. UAV photogrammetry and LiDAR were used to gather point cloud data to build a 3D model of the rock slope and extract its geological features. Furthermore, a trajectory estimation model of rockfalls, also developed at UNR's Mining Automation lab, uses the mass and origin of rockfalls to calculate the impact characteristics and simulate a rockfall's energy changes during its fall. Both these developments rely on a combination of physics-based and data-driven models, necessitating continuous data flow. A lab-scale study will further examine the impact of projectile shape and volume on the coefficients of restitution. Building upon the existing correlation's initial results, a data-driven model for trajectory estimation of rockfalls will be developed. 1. INTRODUCTION Rockfall is the continuous movement of a rock down a steep slope instigated by adverse discontinuity orientation, freeze-thaw cycles, inefficient blasting, water presence, weathering, and vegetation on the slope. The rockfall movement is categorized into free-falling, bouncing, rolling, or sliding (Kliche, 2018). The rockfall hazard rating system (RHRS), introduced by the US Department of Transportation, is a uniform method to acquire the geographic locations of rockfall sites and categorize them using a two-phase process including three preliminary groups and a detailed classification to identify the most hazardous sites (Kliche, 2018). However, the general problem with these empirical procedures is their resource-exhaustive approach that requires a very experienced expert to yield the appropriate results. Hence, there is a need for a faster, state-of-the-art, and economical method to deliver reproducible results regardless of the raters' experience. The geotechnical digital twin (DT) will be a hub for a high-fidelity 3D model, an automated geological mapping algorithm of the rock discontinuities based on point cloud data, and a realistic 3D trajectory simulator for rockfalls, all combined to present the most holistic overview of the rockfall study and analyses.