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Superposition model for analyzing the dynamic ground subsidence in mining area of thick loose layer

Authors :
Li Dehai
Zhang Yanbin
Xu Guosheng
Hou Defeng
Source :
International Journal of Mining Science and Technology, Vol 28, Iss 4, Pp 663-668 (2018)
Publication Year :
2018
Publisher :
Elsevier BV, 2018.

Abstract

The dynamic ground subsidence due to underground mining is a complicated time-dependent and rate-dependent process. Based on the theory of rock rheology and probability integral method, this study developed the superposition model for the prediction and analysis of the ground dynamic subsidence in mining area of thick loose layer. The model consists of two parts (the prediction of overlying bedrock and the prediction of thick loose layer). The overlying bedrock is regarded as visco-elastic beam, of which the dynamic subsidence is predicted by the Kelvin visco-elastic rheological model. The thick loose layer is regarded as random medium and the ground dynamic subsidence is predicted by the probability integral model. At last, the two prediction models are vertically stacked in the same coordinate system, and the bedrock dynamic subsidence is regarded as a variable mining thickness input into the prediction model of ground dynamic subsidence. The prediction results obtained were compared with actual movement and deformation data from Zhao I and Zhao II mine, central China. The agreement of the prediction results with the field measurements show that the superposition model (SM) is more satisfactory and the formulae obtained are more effective than the classical single probability integral model (SPIM), and thus can be effectively used for predicting the ground dynamic subsidence in mining area of thick loose layer. Keywords: Thick loose layer, Dynamic groundsubsidence, Kelvin visco-elastic rheological model, Random medium, Single probability integral model, Superposition model

Details

ISSN :
20952686
Volume :
28
Database :
OpenAIRE
Journal :
International Journal of Mining Science and Technology
Accession number :
edsair.doi.dedup.....eba576d476159665212002b0b09bf049