Probabilistic analysis of a coal mine roadway including correlation control between model input parameters

Probabilistic analysis and numerical modelling techniques have been combined to analyse a deep coal mine roadway. Using the Monte Carlo method, a correlation control algorithm and a FLAC 2D finite difference model, a probability distribution of roof displacements has been calculated and compared to...

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Main Authors: Booth, Andrew J., Marshall, Alec M., Stace, Rod
Format: Article
Published: Elsevier 2016
Subjects:
Online Access:https://eprints.nottingham.ac.uk/34943/
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author Booth, Andrew J.
Marshall, Alec M.
Stace, Rod
author_facet Booth, Andrew J.
Marshall, Alec M.
Stace, Rod
author_sort Booth, Andrew J.
building Nottingham Research Data Repository
collection Online Access
description Probabilistic analysis and numerical modelling techniques have been combined to analyse a deep coal mine roadway. Using the Monte Carlo method, a correlation control algorithm and a FLAC 2D finite difference model, a probability distribution of roof displacements has been calculated and compared to a set of measurements from an actual mine roadway. The importance of correlation between input parameters is also considered. The results show that the analysis performs relatively well, but does tend to over predict the magnitude of displacements. Correlation between parameters is shown to be very important, particularly between the three model stresses.
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spelling nottingham-349432020-05-04T20:03:04Z https://eprints.nottingham.ac.uk/34943/ Probabilistic analysis of a coal mine roadway including correlation control between model input parameters Booth, Andrew J. Marshall, Alec M. Stace, Rod Probabilistic analysis and numerical modelling techniques have been combined to analyse a deep coal mine roadway. Using the Monte Carlo method, a correlation control algorithm and a FLAC 2D finite difference model, a probability distribution of roof displacements has been calculated and compared to a set of measurements from an actual mine roadway. The importance of correlation between input parameters is also considered. The results show that the analysis performs relatively well, but does tend to over predict the magnitude of displacements. Correlation between parameters is shown to be very important, particularly between the three model stresses. Elsevier 2016-04 Article PeerReviewed Booth, Andrew J., Marshall, Alec M. and Stace, Rod (2016) Probabilistic analysis of a coal mine roadway including correlation control between model input parameters. Computers and Geotechnics, 74 . pp. 151-162. ISSN 0266-352X Coal mine correlation control Latin hypercube Monte Carlo Probabilistic Uncertainty analysis http://www.sciencedirect.com/science/article/pii/S0266352X16000173 doi:10.1016/j.compgeo.2016.01.008 doi:10.1016/j.compgeo.2016.01.008
spellingShingle Coal mine
correlation control
Latin hypercube
Monte Carlo
Probabilistic
Uncertainty analysis
Booth, Andrew J.
Marshall, Alec M.
Stace, Rod
Probabilistic analysis of a coal mine roadway including correlation control between model input parameters
title Probabilistic analysis of a coal mine roadway including correlation control between model input parameters
title_full Probabilistic analysis of a coal mine roadway including correlation control between model input parameters
title_fullStr Probabilistic analysis of a coal mine roadway including correlation control between model input parameters
title_full_unstemmed Probabilistic analysis of a coal mine roadway including correlation control between model input parameters
title_short Probabilistic analysis of a coal mine roadway including correlation control between model input parameters
title_sort probabilistic analysis of a coal mine roadway including correlation control between model input parameters
topic Coal mine
correlation control
Latin hypercube
Monte Carlo
Probabilistic
Uncertainty analysis
url https://eprints.nottingham.ac.uk/34943/
https://eprints.nottingham.ac.uk/34943/
https://eprints.nottingham.ac.uk/34943/