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A new dynamic prediction method for surface subsidence based on numerical model parameter sensitivity

Author:
Li, Huaizhan, Zha, Jianfeng, Guo, Guangli
Source:
Journal of cleaner production 2019 v.233 pp. 1418-1424
ISSN:
0959-6526
Subject:
buildings, case studies, deformation, mathematical models, prediction, subsidence, sustainable development, underground mining, China
Abstract:
Surface subsidence is a widespread problem frequently caused by underground mining. Accurate surface subsidence prediction is particularly important for protecting buildings and structures above the goaf. Because mining is a dynamic process, surface dynamic movement and deformation can significantly affect buildings and structures. However, dynamic predictions are often highly inaccurate because of the complex nature of dynamic surface movement and deformation. To address this problem, we performed numerical simulations to assess the sensibility of geomechanical parameters to surface movement values. Our results show that: 1) Sensitive factors of surface movement extremum gradually shift from stiffness parameters to strength parameters with increased mining degree; and 2) the sensitivity of the evaluation indicators to the geomechanical parameters is related to the proportion of plastic zones in the mining-affected area. We propose a new dynamic prediction method of surface subsidence and verify the method with a case study from the Yanzhou mine in China. It is proofed that the new method can greatly improve the prediction accuracy of dynamic surface subsidence. The research results are significant for accurately predicting dynamic surface subsidence, protecting ground buildings and structures while promoting sustainable development of mine areas.
Agid:
6475628