Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/15083

TitlePrediction of rockburst based on an accident database
Author(s)Peixoto, Ana
Sousa, L. R.
Sousa, Rita Leal
Xia-Ting, Feng
Miranda, Tiago F. S.
Martins, Francisco F.
KeywordsRisks and hazards
Numerical modeling
Case studies
Issue date2012
PublisherCRC Press
Abstract(s)Rockburst is characterized by a violent explosion of a certain block causing a sudden rupture in the rock and is quite common in deep tunnels. It is critical to understand the phenomenon of rockburst, focusing on the patterns of occurrence so these events can be avoid and/or managed saving costs and possibly lives. In order to further understand the conditions that trigger rockburst, several cases of rockburst that occurred around the world were collected, stored in a database and analyzed. The analysis of the collected cases allowed one to build influence diagrams, listing the factors that interact and influence the occurrence of rockburst, as well as the relation between them. Data Mining (DM) techniques were also applied to the database cases in order to determine and conclude on relations between parameters that influence the occurrence of rockburst during underground construction.Arisk analysis methodologywas developed based on the use of Bayesian Networks (BN) and applied to the existing information of the database and some numerical applications were performed.
TypeConference paper
URIhttp://hdl.handle.net/1822/15083
ISBN9780415804448
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:C-TAC - Comunicações a Conferências Internacionais

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