| EPSRC Reference: |
GR/R94602/01 |
| Title: |
Stochastic modelling of fractures in rock masses |
| Principal Investigator: |
Fowell, Dr RJ |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Mining and Mineral Engineering |
| Organisation: |
University of Leeds |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
17 June 2002 |
Ends: |
16 September 2005 |
Value (£): |
262,498
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| EPSRC Research Topic Classifications: |
| Statistics & Appl. Probability |
Waste Management |
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| EPSRC Industrial Sector Classifications: |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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07 Mar 2001
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MARCH 2001 Mathematics Responsive Mode
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Deferred
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Summary on Grant Application Form |
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The context of this proposal is the characterisation of rock masses for environmental risk assessment. The areas covered include risk assessment for the safe storage of hazardous wastes in underground repositories; prediction of pollutant trajectories in the subsurface of the earth and their likely consequences; investigations into the causes and effects of contamination of the natural environment; and promotion of the public understanding of risks associated with earth engineering projects. Risk analysis in the design and assessment of underground waste repositories and landfill sites involves the assessment of the likelihood, often over very long periods of time, of contaminants being transported out of the repository. In crystalline rocks this likelihood rests on flow-paths provided by connected fractures. Risk analysis requires an assessment of the uncertainties caused by the limited amount, and nature, of the data and this is only possible via a stochastic (probabilistic) approach. Repeated stochastic simulation of fracture networks will provide sets of possible fracture patterns covering the range of possible connectivities and thereby allow an assessment of the risk of encountering contaminant pathways. The simulated fracture patterns can be validated against laboratory-scale rock masses to provide a realistic basis on which to assess uncertainties, such as fluid flow, as a function of the connectivity, lengths and densities of fractures. We will extend our own work in spatial statistics, and that of others, to provide validated methods for the simulation of fracture networks with stochastic discontinuity geometries.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.leeds.ac.uk |