Grant: Alliance Grants

Rock falls pose a significant hazard to infrastructure and livelihood in natural mountainous terrain as well as engineered slopes along roadsides and in open-pit mines. It is of utmost importance for engineers to understand the potential for, and consequences of, these rock fall events in slope stability design. Current state-of-the art rock fall simulation software are highly sophisticated in their consideration of local topography and rigid body dynamics, however engineers lack tools to determine the appropriate parameters to select for their analyses. Radar trackers, which have been successfully deployed to record the motion of rock fall events with high temporal and spatial resolution, present a great opportunity to characterize the in-situ behaviour of rock slopes. The numerical model parameters can be calibrated so that the modelled rock fall trajectory matches the measured trajectory, and the calibrated parameters can then be applied to nearby regions with similar geology. The present proposal outlines a methodology to conduct this calibration automatically and robustly, thereby allowing engineers to model rock fall hazards more accurately at their sites.The methodology is formulated as an optimization where the loss function is the summed distance between the modelled and measured bounce points. A Gaussian Process is employed to estimate the true form of the objective function, which allows us to minimize the number of function calls of the rock fall simulator. This additionally allows us to consider the error of the goodness-of-fit to provide practitioners with error bounds on the final solution.