Szczegóły publikacji

Opis bibliograficzny

Roof fall hazard assessment with the use of artificial neural network / Piotr MAŁKOWSKI, Dariusz Juszyński // International Journal of Rock Mechanics & Mining Sciences ; ISSN 1365-1609. — 2021 — vol. 143 art. no. 104701, s. 1-12. — Bibliogr. s. 12, Abstr. — Publikacja dostępna online od: 2021-05-16

Autorzy (2)

Słowa kluczowe

artificial neural networksroof fall hazard indexpredisposition of the roof to collapsefactors influencing on roof fall hazardroof fall hazard assessment

Dane bibliometryczne

ID BaDAP134277
Data dodania do BaDAP2021-05-25
Tekst źródłowyURL
DOI10.1016/j.ijrmms.2021.104701
Rok publikacji2021
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Czasopismo/seriaInternational Journal of Rock Mechanics and Mining Sciences

Abstract

The paper presents the results of roof fall hazard analysis for the copper mines in Poland. At first, RMR and RFRI systems have been checked as a tool for roof fall hazard assessment. It was proved that rock mass deteriorates in time because of mining operation at the site, hence the roof fall phenomena analysis needs a new approach. In the next step of the analysis the key factors of roof deterioration were determined, and divided into four groups: geological, mining, technical and monitoring. It was demonstrated that only regular roof monitoring can ensure the proper rock fall hazard assessment. Subsequently, the artificial neural network was created and several dozen simulations were conducted. As a result, two dimensionless indices were developed. The first one shows predisposition of a part of the rock mass to destruction, dislocation and deformation - - Coefficient of Roof Fall – Predisposition and the second one represents predisposition and possibility of maintaining of the working - - Coefficient of Roof Fall - Maintenance. The research on roof fall details and the running workings’ roof observations allowed for categorization of the values of both indices, and providing that way the information about roof stability , and the information about necessary measures and solutions for the supervisory staff in regard of monitoring of the roof rocks . Both indices allow for a reliable roof fall hazard assessment by comprehensively combining information from monitoring, observations and investigations.

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