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Prediction of cavern configurations from subsidence data
Authors:K Fuenkajorn  S Archeeploha
Institution:1. College of Transportation Science & Engineering, Nanjing Tech University, Nanjing 210009, China;2. School of Engineering, University of British Columbia, Kelowna, British Columbia V1V 1V7, Canada;3. Tongji University, College of Civil Engineering, Shanghai 200009, China;1. School of Geography, Nanjing Normal University, Nanjing, China;2. Department of Geography, University of Wisconsin-Madison, Madison, WI, USA;3. State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China;4. Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China;5. Department of Geography, University of Minnesota-Duluth, Duluth, MN, USA
Abstract:An analytical method has been developed to predict the location, depth and size of caverns created at the interface between salt and overlying formations. A governing hyperbolic equation is used in a statistical analysis of the ground survey data to determine the cavern location, maximum subsidence, maximum surface slope and surface curvature under the sub-critical and critical conditions. The regression produces a set of subsidence components and a representative profile of the surface subsidence under sub-critical and critical conditions. Finite difference analyses using FLAC code correlate the subsidence components with the cavern size and depth under a variety of strengths and deformation moduli of the overburden. Empirical equations correlate the subsidence components with the cavern configurations and overburden properties. For the super-critical condition, a discrete element method (using UDEC code) is used to demonstrate the uncertainties of the ground movement and sinkhole development resulting from the complexity of the post-failure deformation and joint movements in the overburden.
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