Please use this identifier to cite or link to this item:

TitleRockburst laboratory tests database - Application of data mining techniques
Author(s)He Manchao
Sousa, Luís Ribeiro e
Miranda, Tiago F. S.
Zhu Gualong
Experimental tests
Data mining
Rockburst index
Issue date2015
JournalEngineering Geology
CitationHe, M., e Sousa, L. R., Miranda, T., & Zhu, G. (2015). Rockburst laboratory tests database - Application of data mining techniques. Engineering Geology, 185, 116-130. doi: 10.1016/j.enggeo.2014.12.008
Abstract(s)Rockburst is characterized by a violent explosion of a 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 avoided and/or managed saving costs and possibly lives. The failure mechanism of rockburst needs to be better understood. Laboratory experiments are undergoing at the Laboratory for Geomechanics and Deep Underground Engineering (SKLGDUE) of Beijing and the system is described. A large number of rockburst tests were performed and their information collected, stored in a database and analyzed. Data Mining (DM) techniques were applied to the database in order to develop predictive models for the rockburst maximum stress (σRB) and rockburst risk index (IRB) that need the results of such tests to be determined. With the developed models it is possible to predict these parameters with high accuracy levels using data from the rock mass and specific project.
AccessRestricted access (UMinho)
Appears in Collections:ISISE - Artigos em Revistas Internacionais

Files in This Item:
File Description SizeFormat 
  Restricted access
3,21 MBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID