Document Type
Conference Paper
Publication Date
2020
Abstract
Proper strata caving in longwall mining guarantees the success of the operation while delayed or poor caving will lead to severe consequences. Therefore, the reliable prediction of strata and its caving potential is essential during the planning stage of a longwall project. This paper reports a novel classification system to evaluate the cavability level of the immediate roof strata in coal mines. A Fuzzy integrated multi-criteria decision-making method was used to incorporate nine inherent parameters that control the caving behaviour. After the determination of parameters’ weights and assigning corresponding ratings, the Cavability Index (CI) was defined as the summation of ratings for all the parameters to indicate the potential of caving qualitatively. The proposed classification system was applied to evaluate twelve panels throughout the world. In addition, the applicability of the classification system was investigated through the estimation of the main caving intervals. For this purpose, statistical relationships were developed in which the Cavability Index (CI) and hydraulic radius was independent variables. Model validation indicated that the linear model possesses an acceptable accuracy in the estimation of the main caving intervals for actual cases. These results showed reliable performance of the novel developed classification system from a practical point of view.
Publication Details
Sadjad Mohammadi, Mohammad Ataei, Reza Kakaie, Ali Mirzaghorbanali, Zahra Faraji Rad and Naj Aziz, A roof cavability classification system and its use for estimation of main caving interval in longwall mining, Proceedings of the 2020 Coal Operators' Conference, University of Wollongong - Mining Engineering, 12-14 February 2020, University of Wollongong, 104-115.