Quantitative Evaluation and Case Study of Risk Degree for Underground Goafs with Multiple Indexes considering Uncertain Factors in Mines

The accidents caused by underground goafs are frequent and destructive due to irregular geometric shapes and complex spatial distributions, which caused severe damage to the environment and public health. Based on the theories of uncertainty measurement evaluation (WME) and analytic hierarchy proces...

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Bibliographic Details
Published in:Geofluids 2017-01, Vol.2017 (2017), p.1-15
Main Authors: Gong, Fengqiang, Zhou, Zilong, Li, Xibing, Shu, Weiwei, Dong, Longjun, Liu, XiLing
Format: Article
Language:English
Subjects:
Accidents
Analytic hierarchy process
Case studies
Casualties
Coal mining
Disasters
Earthquakes
Ecological risk assessment
Engineering
Entropy
Evaluation
Fatalities
Geology
Groundwater
Hydrogeology
Lead
Mathematical analysis
Mathematical problems
Measurement
Methods
Mineral industry
Mines
Mining
Mining accidents & safety
Mining industry
Numerical analysis
Public health
Quantitative analysis
Rankings
Risk assessment
Risk levels
Spatial distribution
Uncertainty
Underground mines
Vectors
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Summary:The accidents caused by underground goafs are frequent and destructive due to irregular geometric shapes and complex spatial distributions, which caused severe damage to the environment and public health. Based on the theories of uncertainty measurement evaluation (WME) and analytic hierarchy process (AHP), the comprehensive risk evaluation of underground goafs was carried out using multiple indexes. Considering the hydrogeological conditions, mining status, and engineering parameters of underground goafs, the evaluation index system was established to evaluate the risk degrees considering quantified uncertain factors. The single index measurement values were solved by the semiridge measurement function. The weights for evaluation vectors were calculated through the entropy theory and AHP. Finally, the risk level was evaluated according to the credible degree recognition criterion (CDRC) and the maximum membership principle. The risk levels of 37 underground goafs in Dabaoshan mine were evaluated using 4 coupled methods. The order for underground goafs risk degrees was ranked and classified on account of the uncertainty important degree. According to the ranked order, the reasonability of 4 coupled methods was evaluated quantitatively. Results show that the UME-CDRC can be applied in the practical engineering, which provides an efficient guidance to both reduce the accident risk and improve the mining environment.
ISSN:1468-8115
1468-8123
DOI:10.1155/2017/3271246