Rock cuts and rockfalls for this project were modeled using RocFall 6.0 from RocScience. The program allows a slope to be modeled using 2D (X, Y) coordinates, where X corresponds to the lateral direction and Y corresponds to the slope elevation. Each section of the slope between these vertices is given material properties comprising coefficients of restitution and coefficients of friction. The exact parameters used in each model differ with the selection of lumped mass or rigid
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body mechanics. These coefficients are also typically given a standard deviation and normal distribution bounded by ±3 times the standard deviation. This variability in the coefficients of restitution, coupled with potential variance in the specified rock, is used to produce realistic, variable trajectories. Without variation in the slope or rock material, and the rock initial orientation when using a rigid body model, the mathematically-defined trajectory is identical for all simulations. As rock and soil are not homogeneous, it is realistic to expect variation in the material properties.
Rocks can be designed in RocFall by specifying the density and mass of the rock. These can also be given a statistical distribution if desired. If the rigid body analysis method is used, the shape of the rock is also defined. Default shapes included in the program include polygons with sharp or rounded corners, such as spheres, squares, rectangles, triangles, and ellipses of varying proportions. The actual size of the rock is calculated based on the unit shape and the assigned mass and density. A “seeder,” or starting rock location, is placed on the slope, and one or more rock models are chosen to be dropped from that seeder. A total number of rockfall simulations is assigned to each seeder.
The output used from the RocFall software in this research includes “rock path end points.” This term refers to the ending locations of the rock trajectories, which may include rocks that bounce backward from their impact point. While this is distinct from maximum rock runout, the farthest distance that a rock moves from the base of the rock slope, end points are used as a proxy for runout in this research. The RocFall outputs are histograms giving the number of rocks that end their trajectory within specified intervals on the slope, which are labeled by the interval midpoint. The size of the intervals is defined by the length of the modeled slope data divided by the number of bins chosen by the user. For this research, bins were typically chosen to group rock
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path end locations into approximately 1 m intervals. Because of the histogram format, all end path locations presented are estimated.
Other parameters that may be included in rockfall simulations using the RocFall software are variations in slope roughness, damping due to forested slopes or vegetation, and scarring of the slope as a rock falls, which changes the friction coefficients. Though a rock cannot be simulated to break up upon impact in the rockfall software, the coefficients of restitution account for some possible energy loss in this scenario, and the scarring tool could as well. An available option is also a “line seeder” that starts multiple rocks from a distribution of locations, which may be used to simulate the trajectories of a broken rock. This was not used in this research, in order to better compare modeled results to the single rocks used for Smart Rock experiments. Vegetation damping and scarring were excluded from the models in this research under the assumption that the rock cuts modeled are predominantly bare rock faces, and neither are applicable. Slope roughness variation is an important aspect of predictive modeling, however, particularly in 2D, to account for differences in a rockfall path that are not captured in a single 2D profile (Crosta et al., 2015). This was included in two models using DEM profiles to compare to results from the original and higher-resolution slope models.
The slope roughness parameter in RocFall varies the slope profile randomly between data vertices with spacing and amplitude limits defined by the user. In a rigid body model, this tool creates a slightly different slope for each simulated rock. Figure 3.4 shows an example of this variation in a DEM cross-section of a rock cut in Londonderry, NH. The randomized changes add variation below the resolution of the actual data. In this research, the profiles of interest are well characterized by images and high-resolution data and comparisons are made assuming this location is the single rockfall path. Varying slope roughness in a low resolution data set might simulate
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some of the irregularity of a higher resolution data set. A second method of introducing slope variation in the RocFall software is to include a standard deviation with the slope coordinates, which was not used in this research.
Figure 3.4: An example of a slope profile with slope roughness varied from the original slope.
The DEM profile from Londonderry, NH Station 912+00 is shown by a thin line. The varied profile is a thicker line offset from the original smooth slope.