Quantitative characterization of discontinuities is fundamental to define the mechanical behavior of discontinuous rock masses. Several techniques for the semi-automatic and automatic extraction of discontinuities and their properties from raw or processed point clouds have been introduced in the literature to overcome the limits of conventional field surveys and improve data accuracy. However, most of these techniques do not allow characterizing flat or subvertical outcrops because planar surfaces are difficult to detect within point clouds in these circumstances, with the drawback of undersampling the data and providing inappropriate results. In this case, 2D analysis on the fracture traces are more appropriate. Nevertheless, to our knowledge, few methods to perform quantitative analyses on discontinuities from orthorectified photos are publicly available and do not provide a complete characterization. We implemented scanline and window sampling methods in a digital environment to characterize rock masses affected by discontinuities perpendicular to the bedding from trace maps, thus exploiting the potentiality of remote sensing techniques for subvertical and low-relief outcrops. The routine, named QDC-2D (Quantitative Discontinuity Characterization, 2D) was compiled in MATLAB by testing a synthetic dataset and a real case study, from which a high-resolution orthophoto was obtained by means of Structure from Motion technique. Starting from a trace map, the routine semi-automatically classifies the discontinuity sets and calculates their mean spacing, frequency, trace length, and persistence. The fracture network is characterized by means of trace length, intensity, and density estimators. The block volume and shape are also estimated by adding information on the third dimension. The results of the 2D analysis agree with the input used to produce the synthetic dataset and with the data collected in the field by means of conventional geostructural and geomechanical techniques, ensuring the procedure’s reliability. The outcomes of the analysis were implemented in a Discrete Fracture Network model to evaluate their applicability for geomechanical modeling.
Based on a previous risk calculation study along a road corridor, risk is recalculated using stochastic simulation by introducing variability for most of the parameters in the risk equation. This leads to an exceedance curve comparable to that of catastrophe models. This approach introduces uncertainty into the risk calculation in a simple way, which can be used for poorly documented cases to fulfil lack of data. This approach seems to tend to minimize risk or to question risk calculations.
Based on a previous risk calculation study conducted along a road corridor, risk is recalculated using a stochastic simulation by introducing variability into most of the parameters in the risk equation. This leads to an exceedance curve comparable to those of catastrophe models. This approach introduces uncertainty into the risk calculation in a simple way, and it can be used for poorly documented cases to compensate for a lack of data. This approach tends to minimize risk or question risk calculations.
<p>Freezing-thaw weathering is recognized as one of the most significant factors in the fatigue of rock mass in areas where the temperature periodically fluctuates around the freezing point.&#160;<br>A one-year monthly SfM monitoring program from December 19, 2019, to January 7, 2021, was done to detect rockfall activity on a rockslide cliff composed of marl-sandstone at La Cornalle, Switzerland. More than one hundred rockfall events were detected during this period with the volumes varied from 0.005m<sup>3</sup> to 4.85m<sup>3</sup>.&#160;<br>We texture all the rockfalls on the 3D SfM model. It is shown that most of them are mainly located in three areas: &#160;the top of the cliff, the foot of the cliff, and the medium-left part of the cliff. The common feature of these three parts is that the layers are more or less overhanging with dense fractures around them. At the same time, the meteorological data collected by a weather station on site is correlated with the rockfall events to figure out the relationship between each other. Actually, about 30% of total rockfall volume fell during winter on this site. The triggering factor of rockfall during winter is related to freezing-thaw cycling. This kind of weathering can be understood as an interplay between rock properties and its dynamic environment.<br>In order to make clear the role of freezing-thaw played on the rockfall generation, an on-site 24h monitoring measurement program that consists of two crack meters, one rock thermal sensor, and thermal camera monitoring is installed in January 2021. Those datasets will help to understand how the crack grows with the changing temperature. In addition, freezing-thaw cycling laboratory experiments for the rock samples taken from different areas of the cliff will be done with an environmental test chamber. The topography of the rock samples before and after the experiments will be acquired by a 3D handheld scanner. This work will benefit to reveal the rock surface evolution during the freezing-thaw cycling in a dynamic environment with varied humidity and number of cycles.&#160;<br>In conclusion, the combination of on-site measurements and laboratory freezing-thaw experiments will provide a good basis for a better understanding of the rockfall triggering mechanism led by physical weathering.</p>
<p>The identification of discontinuity sets and their properties is among the key factors for the geomechanical characterization of rock masses, which is fundamental for performing stability analyses, and for planning prevention and mitigation measures as well.<br>In practice, discontinuity data are collected throughout difficult and time-consuming field surveys, especially when dealing with areas of wide extension, difficult accessibility, covered by dense vegetation, or with adverse weather conditions. Consequently, even experienced operators may introduce sampling errors or misinterpretations, leading to biased geomechanical models for the investigated rock mass.<br>In the last decades, new remote techniques such as photogrammetry,<em> Light Detection and Ranging</em> (LiDAR), <em>Unmanned Aerial Vehicle</em> (UAV) and <em>InfraRed Thermography </em>(IRT) have been introduced to overcome the limits of conventional surveys. We propose here a new tool for extracting information on the fracture pattern in rock masses, based on <em>remote sensing </em>methods, with particular reference to the analysis of high-resolution georeferenced photos. The first step consists in applying the <em>Structure from Motion</em> (SfM) technique on photos acquired by means of digital cameras and UAV techniques. Once aligned and georeferenced, the orthophotos are exported in a GIS software, to draw the fracture traces at an appropriate scale. We developed a MATLAB routine to extract information on the geostructural setting of rock masses by performing a quantitative 2D analysis of the fracture traces, based on formulas reported in the literature. The code was written by testing few experimental and simple traces and was successively validated on an orthophoto from a real case study.<br>Currently, the script plots the fracture traces as polylines and calculates their orientation (strike) and length. Subsequently, it detects the main discontinuity sets by fitting an experimental composite Gaussian curve on histograms showing the number of discontinuities according to their orientation, and splitting the curve in simpler Gaussian curves, with peaks corresponding to the main discontinuity sets.<br>Then, for each set, a linear scanline intersecting the highest number of traces is plotted, and the apparent and real spacing are calculated. In a second step, a grid of circular scanlines covering the whole area where the traces are located is plotted, and the mean trace intensity, trace density and trace length estimators are calculated.<br>It is expected to test the presented tools on other case studies, in order to optimize them and calculate additional metrics, such as persistence and block sizes, useful to the geomechanical characterization of rock masses.<br>As a future perspective, a similar approach could be investigated for 3D analyses from point clouds.</p>
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