A Probabilistic Model to Determine Main Caving Span by Evaluating Cavability of Immediate Roof Strata in Longwall Mining

Autor: Sadjad Mohammadi, Mohammad Ataei, Ali Mirzaghorbanali, Reza Kakaie, Naj Aziz
Rok vydání: 2020
Předmět:
Zdroj: Geotechnical and Geological Engineering. 39:2221-2237
ISSN: 1573-1529
0960-3182
DOI: 10.1007/s10706-020-01620-y
Popis: Caving process is a complex dynamic phenomenon influences safety and productivity of coal longwall mining. It improves safety due to reduction of load on support, face convergence and abutment stresses. Proper caving with respect to the quality and time of occurrence ensures continuity of operation and subsequently, the productivity of coal extraction. Therefore, a reliable prediction of strata behaviour and its caving potential are imperative in design of longwall projects. This paper presents a hybrid probabilistically qualitative–quantitative model to evaluate cavability of immediate roof and to estimate main caving span in longwall mining by combining empirical model and numerical solution. For this purpose, numerical simulation was incorporated to Roof Strata Cavability index (RSCi) as summation of ratings for nine significant parameters. Distinct element code was used to simulate numerically main caving span corresponding to various RSCi classes probabilistically. The newly proposed model was verified against actual field data collected from different longwall panels around the world. The results of proposed model agreed well with those of collected data.
Databáze: OpenAIRE
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