Provider: CSIRO & The University of Queensland (JKMRC)


The JointStats software was initially produced by the Julius Kruttschnitt Mineral Research Centre (JKMRC), University of Queensland, as part of the International Caving Study research and technology transfer program.  The original software accepted standard structural data from a face mapping or borehole scanline and organised the data hierarchically according to its orientation, length, spacing, and persistence (trace length) attributes.  A (DFN) model of the fracture network could be exported to a 2D or 3D numerical modelling code using an XML text file. For the LOP project the software was enhanced jointly by the JKMRC and CSIRO to deliver a structural and a rock mass material properties database that enables data uncertainty to be assessed and confidence limits determined for specified data and/or attributes from within a single geotechnical domain. This includes:

  • expanding the existing JointStats data base to include;
    • quantitative measures of rock mass parameters, and
    • data exported from Sirovision in a form suited to statistical analysis,
  • providing a means of analysis of rock mass parameter data that leads to a measure of the reliability of that data from within a single geotechnical domain;
  • providing a means of statistical joint analysis of;
    • joint orientation that is equipped with measures of the reliability of the calculated mean set direction and Fisher dispersion constant, and
    • joint persistence data that is equipped with measures of the reliability of the calculated joint size distribution and joint spatial density of scanline data, with joints modelled as full disks,
  • providing a means of determining the goodness of fit of the disk model of joints to a set of data that can also be used to test for a significant difference between orientation or persistence data sets; and
  • providing a means of combining the measure of uncertainties arising from orientation, persistence and rock mass parameter analysis to arrive at overall measures of uncertainty.