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Article type: Research Article
Authors: Liu, Shilianga | Li, Wenpingb; *
Affiliations: [a] School of Civil Engineering, Shandong University, Jinan, Shandong, China | [b] School of Resources and Geosciences, China University of Mining and Technology, Xuzhou, China
Correspondence: [*] Corresponding author. Wenping Li, School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China. Tel.: +86 516 8359 0289; Fax: +86 516 8359 0289; E-mail: lslcumt@cumt.edu.cn.
Abstract: The risk assessment of roof water inrush is of great significance for sustainable development of mine and ecological environment. Taking the Jurassic coalfield in northwest China as an engineering background, we firstly selected nine indexes influencing roof water inrush based on three essential conditions with the water source, the water inrush channel and the mining space, i.e., unit water inflow, flushing fluid consumption, aquifer thickness, effective aquiclude thickness, lithological association of the effective aquiclude, inclined length of coalface, buried depth of coal seam, mining thickness and advancing speed of coal mining, and then established the hierarchy structure model for mutation evaluation of roof water inrush. Secondly, the expert scoring method and trapezoidal fuzzy distribution were chosen to construct the initial fuzzy membership function based on the characteristics with fuzziness and mutability of roof water inrush. Thirdly, based on quantized recursion operation with the normalization formula and the (non) complementarity principle, total mutation membership function value was calculated, and the water inrush risk grade was determined. Eventually, the proposed method has successfully predicted the water inrush risk in the first mining face of Jinjitan coal mine. The research achievements provide an important reference for the sustainable development of the Jurassic coalfield.
Keywords: Jurassic coalfield, risk evaluation of roof water inrush, the mutation theory, fuzzy analysis, sustainabledevelopment
DOI: 10.3233/JIFS-171157
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2101-2111, 2019
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