Abstract

In this paper, combining a theoretical method of predicting subsidence over time and using a geographical information system (GIS), a GIS-based dynamic model is proposed to rapid simulate the phenomenon of progressive movement distribution from large sequential mining. The theoretical method uses stochastic medium concept involving Knothe time function for basic governing equations to calculate progressive movement because this solutions have been widely developed and used in Chinese mining practice to solve the coal extraction problem under building, railways, and rivers. In order to assess the impact of progressive movement to the surface structures, a fuzzy model is suggested to identify damage classifications with contributions of subsidence calculations and building mesh data. For implementation of the GIS-based prediction and assessment model, a new GIS coupling model is established by implementing tight coupling strategy using the component object model (COM) program to overcome the problems of complex model integration for dynamic prediction and assessment. Furthermore, this paper demonstrates the effectiveness of this GIS-based model for prediction and evaluation of subsidence-induced damage from coal mining beneath surface structures in China.

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