Radar-Informed automated back-analysis of rock fall hazards

罗克瀑布对自然山区的基础设施和生计以及沿着路边和露天矿的工程边坡构成重大危险。在边坡稳定性设计中，工程师了解这些落石事件的可能性和后果至关重要。当前最先进的落石模拟软件在考虑局部地形和刚体动力学方面非常复杂，然而工程师缺乏工具来确定用于其分析的适当参数。雷达跟踪器，已成功地部署到记录岩石的运动与高的时间和空间分辨率的事件，提供了一个很好的机会来描述岩石边坡的原位行为。可以校准数值模型参数，使得建模的岩石坠落轨迹与测量的轨迹匹配，然后可以将校准的参数应用于具有类似地质的附近区域。目前的建议概述了一种方法来进行自动和鲁棒的校准，从而使工程师能够更准确地在其sites.The方法建模落石灾害制定为一个优化的损失函数之间的总和距离建模和测量反弹点。采用高斯过程来估计目标函数的真实形式，这使得我们能够最小化落石模拟器的函数调用次数。这还允许我们考虑拟合优度的误差，为从业者提供最终解决方案的误差范围。

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.