Remote Characterisation of Surface Roughness of Rock Discontinuities

Poropat, George

doi:10.36487/acg_repo/808_123

Cited by 24 publications

(15 citation statements)

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“…The terrestrial photogrammetry method is an alternative to traditional survey methods and greatly reduces the time required at potentially hazardous rock slopes. Using a digital single lens reflex (DSLR) camera and commercially available software packages, the applicability of photogrammetry to measure the orientation of discontinuities in large natural rock slopes and open pits has been investigated by many researchers (Poropat, 2009;Haneberg, 2008;Sturzenegger and Stead, 2009;Firpo et al, 2011;Brideau et al, 2011;Brideau and Stead, 2012). Moreover, 3D photogrammetry surface models can assist engineers with obtaining the joint surface roughness characteristics, including the joint roughness coefficient (JRC) (Haneberg, 2007;Poropat, 2009;Guo et al, 2011;Kim et al, 2013a,b), which helps to constrain values of joint friction.…”

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confidence: 99%

Back analysis of a natural jointed rock slope based on the photogrammetry method

2014

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In 2013, a potentially unstable jointed rock slope above a road in the Gold Coast area, Australia, partially failed after a rainfall event. In this study, the rock failure was back analysed to evaluate the presence of key blocks through block analysis based on photogrammetry surveys. Friction angles of the joint sets at the point of failure were also investigated by means of a parametric study using a 3D distinct element method (DEM). The photogrammetry method was employed to obtain measurements of the orientation of the joint sets of the slope and the shape and size of rock blocks at the inaccessible slope. The joint roughness coefficient (JRC) obtained from the 3D photogrammetry model was utilised to estimate friction angles and the strength of the joint set. Safety factors of the rock mass were computed by both analytical and numerical approaches. Parametric analyses, using a DEM model, assessed the critical friction angle of the joint sets and also demonstrated the failure mechanism of the blocks. The result of this study indicates that the obtained safety factors are in agreement with the block analysis and the results from the numerical analysis performed by the distinct element code "3DEC".

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Section: Introductionmentioning

confidence: 99%

Back analysis of a natural jointed rock slope based on the photogrammetry method

2014

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“…In addition, the high resolution 3D images taken from 2 and 5 m distances produced very large values of JRC (greater than 20). This can be attributed to the overestimation of JRC using both the Maerz and Tse-Cruden formulae (Poropat, 2008).…”

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“…In addition, photogrammetry enables the determination of JRC using high resolution 3D models. Previous studies demonstrated that photogrammetric methods are able to characterise the geometry of joint roughness profiles (Haneberg, 2007;Poropat, 2008;Guo et al, 2011). However, the accuracy of JRC depends on the spatial density of digital images and the error related to the spatial data (Haneberg, 2007).…”

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“…However, the accuracy of JRC depends on the spatial density of digital images and the error related to the spatial data (Haneberg, 2007). Poropat (2009) noted that the process of data smoothing was essential for noise reduction so that reliable JRC values could be obtained.…”

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“…Recent studies on the roughness of rock surface using photogrammetry have shown a new way to determine the roughness characteristics of discontinuities. Haneberg (2007) and Poropat (2009) demonstrated that roughness profiles can be produced using photogrammetric point clouds following the approach developed by Maerz et al (1990) and Tse and Cruden (1979). Maerz et al (1990) proposed to estimate JRC using a regression equation that describes the relationship between the JRC and the roughness profile index, R p , which is defined as the ratio of the true length of a fracture surface trace to its projected length in the fracture plane (Equation 3).…”

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The determination of joint roughness coefficient using three-dimensional models for slope stability analysis

Kim¹,

Gratchev²,

Poropat³

2013

Proceedings of the 2013 International Symposium on Slope Stability in Open Pit Mining and Civil Engineering

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Joint roughness coefficient (JRC) is one of the important parameters to determine shear strength of joints. JRC values are generally measured using profile gauges and estimated by comparing the surface profiles with typical roughness profiles. Therefore, the values can be subjective and vary depending on personal experience of an engineer. Digital photogrammetry methods provide 3D models based on high resolution digital images, and thus JRC values can be more objectively estimated from photogrammetry analysis using linear profile data. This paper seeks to investigate the feasibility of using the photogrammetry method to obtain JRC values. Photogrammetry surveys were performed at several slope sites, and JRC values were estimated using 3D images. To investigate the effect of resolution of digital images, the JRC values were first obtained using different distances between the slope and camera, and then compared with the roughness profiles which were manually measured by means of a Barton's comb. A computer analysis using the distinct element code UDEC was also performed to better understand the effect of JRC on the stability of slopes. A standard way to determine JRC is the visual estimation using Barton's standard profiles (Barton and Choubey, 1977). JRC values, which vary from 0 to 20, are obtained through the comparison of the joint https://papers.acg.uwa.edu.au/p/1308_15_Kim/ The determination of joint roughness coefficient using three-dimensional models for D.H. Kim et al. slope stability analysis

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Terrestrial laser scanning of rock slope instabilities

Abellán

Oppikofer

Jaboyedoff

et al. 2013

Earth Surf Processes Landf

279

176

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This manuscript presents a review on the application of a remote sensing technique (terrestrial laser scanning, TLS) to a well-known topic (rock slope characterization and monitoring). Although the number of publications on the use of TLS in rock slope studies has rapidly increased in the last 5-10 years, little effort has been made to review the key developments, establish a code of best practice and unify future research approaches. The acquisition of dense 3D terrain information with high accuracy, high data acquisition speed and increasingly efficient post-processing workflows is helping to better quantify key parameters of rock slope instabilities across spatial and temporal scales ranging from cubic decimetres to millions of cubic metres and from hours to years, respectively. Key insights into the use of TLS in rock slope investigations include: (a) the capability of remotely obtaining the orientation of slope discontinuities, which constitutes a great step forward in rock mechanics; (b) the possibility to monitor rock slopes which allows not only the accurate quantification of rockfall rates across wide areas but also the spatio-temporal modelling of rock slope deformation with an unprecedented level of detail. Studying rock slopes using TLS presents a series of key challenges, from accounting for the fractal character of rock surface to detecting the precursory deformation that may help in the future prediction of rock failures. Further investigation on the development of new algorithms for point cloud filtering, segmentation, feature extraction, deformation tracking and change detection will significantly improve our understanding on how rock slopes behave and evolve. Perspectives include the use of new 3D sensing devices and the adaptation of techniques and methods recently developed in other disciplines as robotics and 3D computer-vision to rock slope instabilities research.

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Remote Characterisation of Surface Roughness of Rock Discontinuities

Cited by 24 publications

References 0 publications

Back analysis of a natural jointed rock slope based on the photogrammetry method

Back analysis of a natural jointed rock slope based on the photogrammetry method

The determination of joint roughness coefficient using three-dimensional models for slope stability analysis

Terrestrial laser scanning of rock slope instabilities

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