Statistical regional calibration of subsidence prediction models
- Univ. of Nottingham (United Kingdom). Dept. of Mineral Resources Engineering
Like other influence function methods, the SWIFT subsidence prediction program, developed within the Mineral Resources Engineering Department at the University of Nottingham, requires calibration to regional data in order to produce accurate predictions of ground movements. Previously, this software had been solely calibrated to give results consistent with the Subsidence Engineer`s Handbook (NCB, 1975). This approach was satisfactory for the majority of cases based in the United Kingdom, upon which the calibration was based. However, in certain circumstances within the UK and, almost always, in overseas case studies, the predictions die no correspond to observed patterns of ground movement. Therefore, in order that SWIFT, and other subsidence prediction packages, can be considered more universal, an improved and adaptable method of regional calibration must be incorporated. This paper describes the analysis of a large database of case histories from the UK industry and international publications. Observed maximum subsidence, mining geometry and Geological Index for several hundred cases have been statistically analyzed in terms of developing prediction models. The models developed can more accurately predict maximum subsidence than previously used systems but also, are capable of indicating the likely range of prediction error to a certain degree of probability. Finally, the paper illustrates how this statistical approach can be incorporated as a calibration system for the influence function program, SWIFT.
- OSTI ID:
- 124690
- Report Number(s):
- CONF-950811-; ISBN 0-930284-56-9; TRN: IM9548%%280
- Resource Relation:
- Conference: 14. conference on ground control in mining, Morgantown, WV (United States), 1-3 Aug 1995; Other Information: PBD: 1995; Related Information: Is Part Of 14. International conference on ground control in mining: Proceedings; Peng, S.S. [ed.] [Univ. of West Virginia, Morgantown, WV (United States). Dept. of Mining Engineering]; PB: 330 p.
- Country of Publication:
- United States
- Language:
- English
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