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dc.contributor.authorAndrews, Kevinen_US
dc.date.accessioned2014-03-14T20:40:42Z
dc.date.available2014-03-14T20:40:42Z
dc.date.issued2008-06-23en_US
dc.identifier.otheretd-06272008-153059en_US
dc.identifier.urihttp://hdl.handle.net/10919/33782
dc.description.abstractPrediction and control methodologies for ground deformation due to underground mining (commonly referred to as mine subsidence) provide engineers with the means to minimize negative effects on the surface. Due to the complexity of subsidence-related movements, numerous techniques exist for predicting mine subsidence behavior. This thesis focuses on the development, implementation, and validation of numerous enhanced subsidence prediction methodologies. To facilitate implementation and validation, the improved methodologies have been incorporated into the Surface Deformation Prediction System (SDPS), a computer program based primarily on the influence function method for subsidence prediction. The methodologies include dynamic subsidence prediction, alternative model calibration capability, and enhanced risk-based damage assessment. Also, the influence function method is further validated using measured case study data. In addition to discussion of previous research for each of the enhanced methodologies, a significant amount of background information on subsidence and subsidence-related topics is provided. The results of the research presented in this thesis are expected to benefit the mining industry, as well as initiate ideas for future research.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartMicrosoftWord-ThesisFinalSubmitJuly2008.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectsubsidence predictionen_US
dc.subjectrisk-based damage analysisen_US
dc.subjectlong-term stabilityen_US
dc.subjectdynamic subsidenceen_US
dc.subjectground strainen_US
dc.subjectground deformationen_US
dc.subjectsubsidenceen_US
dc.subjectmine subsidenceen_US
dc.titleEnhancing Mine Subsidence Prediction and Control Methodologies for Long-Term Landscape Stabilityen_US
dc.typeThesisen_US
dc.contributor.departmentMining and Minerals Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineMining and Minerals Engineeringen_US
dc.contributor.committeechairKarmis, Michael E.en_US
dc.contributor.committeememberAgioutantis, Zachariasen_US
dc.contributor.committeememberWestman, Erik Christianen_US
dc.contributor.committeememberKarfakis, Mario G.en_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-06272008-153059/en_US
dc.date.sdate2008-06-27en_US
dc.date.rdate2008-08-01
dc.date.adate2008-08-01en_US


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