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Virginia Tech

Enhancing Mine Subsidence Prediction and Control Methodologies for Long-Term Landscape Stability

Abstract

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. 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.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Mining and Minerals Engineering
Department dc:contributor.department
Mining and Minerals Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2008

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Andrews, Kevin
Chair dc:contributor.committeechair
  • Karmis, Michael E.
Committee members dc:contributor.committeemember
  • Agioutantis, Zacharias
  • Westman, Erik C.
  • Karfakis, Mario G.

Subjects

dc:subject × 8

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-06272008-153059
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/33782

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Andrews, Kevin. Enhancing Mine Subsidence Prediction and Control Methodologies for Long-Term Landscape Stability. masters thesis, Virginia Tech, 2008. http://hdl.handle.net/10919/33782