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Application of Artificial Neural Networks in Assessing Mining Subsidence Risk
Open AccessArticle

Simulation of Mining-Induced Ground Damage Using Orthogonal Experiments to Determine Key Parameters of Super-Large Coalface: A Case Study in Shendong Coalfield in China

1
College of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, China
2
School of Public Administration, Shanxi University of Finance and Economics, Taiyuan 030024, China
3
School of Public Affairs, Zhejiang University, Hangzhou 310058, China
4
Institute of land reclamation and ecological restoration, China University of Mining & Technology (Beijing), Beijing 100083, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2020, 10(7), 2258; https://doi.org/10.3390/app10072258
Received: 29 February 2020 / Revised: 16 March 2020 / Accepted: 23 March 2020 / Published: 26 March 2020
(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)
High-strength mining of super-large coalfaces in the Shendong coalfield causes significant damage to the ground surface. To study the key parameters of undermined coalfaces that affect ground damage, 25 numerical simulation models were designed using an orthogonal experimental method based on the geological and mining conditions of the Bulianta Mine. In the orthogonal design, four factors (the lengths in both the dip and strike directions, the thickness and the mining speed of the coalface) were considered, with five levels designed for each factor. The subsidence displacements and deformations caused by the excavation were then simulated and verified using field surveying data. A damage extent index (DEI) was introduced and used to assess the extent of global ground damage caused by each simulative excavation. Analysis of variance (ANOVA) method was then employed to determine the key parameters of the coalface that significantly influence the ground damage. It was found that the coalface dip length and thickness and the coalface thickness can be regarded as the key parameters for ground objects of building and timberland, respectively. This research provides theoretical and technical support for the coordinated exploitation of resources and environments in Shendong and other similar, ecologically fragile coalfields. View Full-Text
Keywords: key parameters of a super-large coalface; mining subsidence; global ground damage extent index (DEI); orthogonal experiment; variance analysis key parameters of a super-large coalface; mining subsidence; global ground damage extent index (DEI); orthogonal experiment; variance analysis
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Cai, Y.; Li, X.; Xiao, W.; Zhang, W. Simulation of Mining-Induced Ground Damage Using Orthogonal Experiments to Determine Key Parameters of Super-Large Coalface: A Case Study in Shendong Coalfield in China. Appl. Sci. 2020, 10, 2258.

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