{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/33782"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/33782","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Enhancing Mine Subsidence Prediction and Control Methodologies for Long-Term Landscape Stability","abstract":"Prediction 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.","abstract_html":"Prediction 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.","abstract_has_math":false,"creators":["Andrews, Kevin"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Mining and Minerals Engineering","degree_department":"Mining and Minerals Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Karmis, Michael E."],"committee_members":["Agioutantis, Zacharias","Westman, Erik C.","Karfakis, Mario G."],"year":2008,"date_issued":"2008-06-23","date_published":"2008-06-23","updated_at":"2026-07-22T22:20:21Z","subjects":["subsidence prediction","risk-based damage analysis","long-term stability","dynamic subsidence","ground strain","ground deformation","subsidence","mine subsidence"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-06272008-153059"],"render_values":[{"text":"etd-06272008-153059","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/33782","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Karmis, Michael E."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Agioutantis, Zacharias","Westman, Erik C.","Karfakis, Mario G."]},{"key":"dc:contributor.department","label":"Department","values":["Mining and Minerals Engineering"]},{"key":"dc:creator","label":"Author","values":["Andrews, Kevin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T20:40:42Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T20:40:42Z","2008-08-01"]},{"key":"dc:date.issued","label":"Date","values":["2008-06-23"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mining and Minerals Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["subsidence prediction","risk-based damage analysis","long-term stability","dynamic subsidence","ground strain","ground deformation","subsidence","mine subsidence"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-06272008-153059"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/33782"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Prediction 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. 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The results of the research presented in this thesis are expected to benefit the mining industry, as well as initiate ideas for future research."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:title","label":"Title","values":["Enhancing Mine Subsidence Prediction and Control Methodologies for Long-Term Landscape Stability"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Karmis, Michael E."],"dc:contributor.committeemember":["Agioutantis, Zacharias","Westman, Erik C.","Karfakis, Mario G."],"dc:contributor.department":["Mining and Minerals Engineering"],"dc:creator":["Andrews, Kevin"],"dc:date.accessioned":["2014-03-14T20:40:42Z"],"dc:date.available":["2014-03-14T20:40:42Z","2008-08-01"],"dc:date.issued":["2008-06-23"],"dc:description.abstract":["Prediction 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. 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