Development of Q for an underground project, probabilistic approach

In this paper a method of presenting key geotechnical parameters involving large amount of collected data is suggested. Method of geologic uncertainty presentation in subsurface conditions characterization is developed. The description of the system includes the probabilistic methodology for evaluation of the existing geologic information leading to Q index that can be used for design. An integral part of any design effort in underground construction is the estimation of rock mass properties. Behaviour of jointed rock mass requires determination of its intact as well as discontinuity surface properties. This data is traditionally collected during the geotechnical exploration program. For the large projects where a lot of data is collected, how the data is processed determines how quickly the data can be used in design. Large quantity of data can be easily evaluated using probabilistic methods. The statistics measure how good the distribution fits the input data and how confident are results produced by the distribution function. Software used to analyze statistical aspect of this work is called @RISK. The software ranks fitted distributions using chi-square, Anderson-Darling or Kolmogorov-Smirnov statistic. After completion of the simulation, this data is used to determine sensitivity. The results are displayed as a 'tornado' chart, with longer bars at the top representing the most significant input variables. Probabilistic approach has been successfully applied to analyze input information. Distribution of Q values are given for entire rock mass. Sensitivity analysis carried out identified influence of the parameters on the index, therefore identifying areas for further consideration. Probabilistic approach appears to be an excellent tool, which could be used as input for parametric study of rock mass using numerical methods. (A) "Reprinted with permission from Elsevier". For the covering abstract see ITRD E124500.

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  • English

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  • Accession Number: 01011602
  • Record Type: Publication
  • Source Agency: Transport Research Laboratory
  • Files: ITRD
  • Created Date: Dec 19 2005 3:20PM