George Poropat
Commonwealth Scientific and Industrial Research Organisation
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Publication
Featured researches published by George Poropat.
Rock Mechanics and Rock Engineering | 2012
Marc Elmouttie; George Poropat
This paper presents a new technique for estimating the in situ block size distribution in a jointed rock mass. The technique is based on Monte Carlo simulations using more realistic fracture geometry as its input compared to other block size estimation methods described in the literature. This geometry represents fractures as either polygons or triangulated surfaces and therefore models persistence and truncation of fractures accurately. Persistence has been shown to be critically important for the accurate prediction of block size and shape. We show that for rock masses with relatively small discontinuities, the results of our predictions differ markedly from previous methods which over-predict fragmentation.
Rock Mechanics and Rock Engineering | 2014
Marc Elmouttie; Greg Krahenbuhl; George Poropat; Ian Kelso
Discrete fracture network representations of discontinuities in rock masses have been shown to be useful in capturing heterogeneity in rock mass properties. Providing computational efficiency in the resulting simulations and analyses is attained, these fracture representations can be combined with structural modelling and sampling algorithms. Multiple fracture network realisations can be generated and the resulting rock mass properties interrogated. Statistical analyses based on fracture connectivity, block size distribution and slope stability can be performed and provide results defined in terms of confidence intervals. For sedimentary geology consisting of dense bedding, equivalent medium continuum methods have traditionally been used in preference to discrete fracture representations due to the large numbers of structures involved and resulting computational complexity. In this paper, it is shown that stochastic representation of these layers can be employed. An analytical solution to accommodate bedding given an assumed block size distribution has been derived. Using this formulation, polyhedral modelling has been used to investigate the influence of bedding on block formation and block size distributions using field data. It is shown that the analysis is both computationally efficient and can capture truncation of size distribution by such layers without numerical methods.
PeerJ | 2017
Anthony Romilio; Jorg M. Hacker; Robert Zlot; George Poropat; Michael Bosse; Steven W. Salisbury
The abundant dinosaurian tracksites of the Lower Cretaceous (Valanginian–Barremian) Broome Sandstone of the Dampier Peninsula, Western Australia, form an important part of the West Kimberley National Heritage Place. Previous attempts to document these tracksites using traditional mapping techniques (e.g., surface overlays, transects and gridlines combined with conventional photography) have been hindered by the non-trivial challenges associated with working in this area, including, but not limited to: (1) the remoteness of many of the tracksites; (2) the occurrence of the majority of the tracksites in the intertidal zone; (3) the size and complexity of many of the tracksites, with some extending over several square kilometres. Using the historically significant and well-known dinosaurian tracksites at Minyirr (Gantheaume Point), we show how these issues can be overcome through the use of an integrated array of remote sensing tools. A combination of high-resolution aerial photography with both manned and unmanned aircraft, airborne and handheld high-resolution lidar imaging and handheld photography enabled the collection of large amounts of digital data from which 3D models of the tracksites at varying resolutions were constructed. The acquired data encompasses a very broad scale, from the sub-millimetre level that details individual tracks, to the multiple-kilometre level, which encompasses discontinuous tracksite exposures and large swathes of coastline. The former are useful for detailed ichnological work, while the latter are being employed to better understand the stratigraphic and temporal relationship between tracksites in a broader geological and palaeoecological context. These approaches and the data they can generate now provide a means through which digital conservation and temporal monitoring of the Dampier Peninsula’s dinosaurian tracksites can occur. As plans for the on-going management of the tracks in this area progress, analysis of the 3D data and 3D visualization will also likely provide an important means through which the broader public can experience these spectacular National Heritage listed landscapes.
Rock Mechanics and Rock Engineering | 2014
Marc Elmouttie; George Poropat
In one approach to predicting the behaviour of rock masses, effort is being devoted to the use of probabilistic methods to model structures interior to a rock mass (sometimes referred to as ‘inferred’ or ‘stochastic’ structures). The physical properties of these structures (e.g. position, orientation, size) are modelled as random parameters, the statistical properties of which are derived from the measurements of a sample of the population (sometimes referred to as ‘deterministic’ structures). Relatively little attention has been devoted to the uncertainty associated with the deterministic structures. Typical geotechnical analyses rely on either an entirely stochastic analysis, or deterministic analyses representing the structures with a fixed shape (i.e. disc), position, size, and orientation. The simplifications assumed for this model introduce both epistemic and stochastic uncertainties. In this paper, it is shown that these uncertainties should be quantified and propagated to the predictions of behaviour derived from subsequent analyses. We demonstrate a methodology which we have termed quasi-stochastic analysis to perform this propagation. It is shown that relatively small levels of uncertainty can have large influence on the uncertainties associated with geotechnical analyses, such as predictions of block size and block stability, and therefore this methodology can provide the practitioner with a method for better interpretation of these results.
Archive | 2002
David L. B. Jupp; David A Parkin; George Poropat; Jennifer L Lovell
International Journal of Rock Mechanics and Mining Sciences | 2010
Marc Elmouttie; George Poropat; Grégoire Krähenbühl
Computers and Geotechnics | 2010
Marc Elmouttie; George Poropat; Grégoire Krähenbühl
Computers and Geotechnics | 2013
Marc Elmouttie; Grégoire Krähenbühl; George Poropat
Archive | 2012
George Poropat
International Journal of Rock Mechanics and Mining Sciences | 2015
Dong Hyun Kim; George Poropat; Ivan Gratchev; Arumugam Balasubramaniam
Collaboration
Dive into the George Poropat's collaboration.
Commonwealth Scientific and Industrial Research Organisation
View shared research outputsCommonwealth Scientific and Industrial Research Organisation
View shared research outputsCommonwealth Scientific and Industrial Research Organisation
View shared research outputsCommonwealth Scientific and Industrial Research Organisation
View shared research outputsCommonwealth Scientific and Industrial Research Organisation
View shared research outputsCommonwealth Scientific and Industrial Research Organisation
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