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STRUCTURAL MAPPING AND ANALYSIS

Once fracture traces and planes have been digitized, they are separated in fracture sets on the stereonet and they are assigned different colors to refer to different fracture sets.

It is thus possible to identify and measure a sufficient number of fractures (e.g., in accordance with the ISRM (1978). "Suggested methods for the quantitative description of discontinuities in rock masses". Int. Journal Rock Mechanics, Mining Sciences & Geomechanical Abstr. 15: 319–368) even in cases in which the slope is inaccessible, too dangerous to access, or when moving about the slope may cause unintentional small rock falls that may be dangerous to people, motorists or equipment located below.

Digital Structural Analysis

Here is an example of a rock face located 1.8 to 2.5 km (1.1 to 1.5 mi) from the camera stations. The objective was to determine not only the fracture sets, but also the size of the rock blocks on the rock face; indeed, this study was necessary to then generate rock blocks for a rockfall simulation. In these cases, not only is it necessary to identify a sufficient number of fractures: it is necessary to digitize ALL fractures because otherwise the determination of the block size will be incorrect. This rules out the use of LiDAR because fracture traces cannot be correctly identified in LiDAR data.

When the fractures have been digitized as interpolating disks of different colors based on their fracture set as seen above, Tonon USA gains a fair amount of insight into the rock mass by rotating, zooming, panning, and examining the 3-D model textured with high resolution pictures. Likewise, fracture spacing measurements are carried out directly on the 3D model.

Although the engineering-geology field work remains necessary, this technology may complement the field work as follows:

  • Even when the slope is accessible, the time needed by a geologist to move about an entire slope with ropes and harness is much longer than that required to digitize the same number of fractures on a computer. Bad weather or scorching sun may further delay the work and/or make it very unpleasant. By working on a photogrammetric model, many more fractures are typically identified and measured with clear benefits to the rock mass characterization.
  • When fractures are long, it may be difficult for a person working close to the rock face to recognize that the same feature appears at different locations on (or all across) the mapped slope. Such features may be misidentified, measured several times (therefore creating bias in the collected data), or missed altogether (because too large for the hand-sample scale used at the face).
  • Identification and quantification of fracture clusters. Here is a typical example of a fracture cluster: the scale is about 1 m. The trace-digitized fractures are in red, the plane-digitized fractures are in cyan. Typically, water flow concentrates at fracture clusters. By documenting these clusters one knows exactly where these clusters were encountered during construction (e.g., if in the future an anomalous water ingress is observed), and their characterization (including geostatistics and Dershowitz’s PIJ system) allows one to refine the fracture modeling (e.g., by using stochastic, geostatistical, and fractal models) prepared at the design stage. Such an improved model can then be used for groundwater inflow, fluid flow, or contaminant migration predictions. Indeed, any type of scan line may be traced on the rock walls, including circular scanlines that provide unbiased data (e.g., M. Mauldon, J. G. Mauldon Fracture sampling on a cylinder: From scanlines to boreholes and tunnels. Rock Mechanics and Rock Engineering, 30, 129-144, 1997); just imagine tracing several circular scanlines on a vertical face when tied up with ropes and harness!
  • Identification of fracture coalescence. Here is a typical case where two fractures coalesced to form a stepped fracture, which may explain in part the orientation variability within a fracture set, and limits the reliability of rock block-size prediction based on natural fracture lengths. Indeed these detailed three-dimensional models revealed that oftentimes fallen blocks were formed by fractures (in the same set) that coalesced because of the blasting and of the stress redistribution induced by the excavation.
  • Accuracy of fracture traces. Here is a typical case in which two fractures in the same fracture set were digitized either by using a plane or a trace. The resulting generated planes have the same orientation. This is a consequence of the fact that Tonon USA (as opposed to LiDAR mapping) exactly attributes pixels to the three-dimensional surface. As a result, the lengths of the fracture traces may be accurately determined; Tonon USA has developed techniques to obtain the fracture size distribution from the fracture trace probability distribution (F. Tonon, and Chen, S. Closed-form and numerical solutions for the probability distribution function of fracture diameters. Int. J. of Rock Mech. and Mining Sci. 44 (3), 2007, 332-350. DOI: 10.1016/j.ijrmms.2006.07.013).

 

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Digital Structural Analysis
Digital Structural Analysis
Digital Structural Analysis
Digital Structural Analysis

 

E-mail: info@tononeng.com

Digital Structural Analysis