Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/41692

TitleUpdating of the hierarchical rock mass rating (HRMR) system and a new subsystem developed for weathered granite formations
Author(s)Miranda, Tiago F. S.
Sousa, Luís Ribeiro e
Tinoco, Joaquim Agostinho Barbosa
KeywordsRock mass classification system
Decision tree
Weathered granite formations
Issue date2014
PublisherElsevier
JournalInternational Journal of Mining Sciences and Technology
Abstract(s)The RMR system is still very much applied in rock mechanics engineering context. It is based on the evaluation of six weights to obtain a final rating. To obtain the final rating a considerable amount of information is needed concerning the rock mass which can be difficult to obtain in some projects or project stages at least with accuracy. In 2007 an alternative classification scheme based on the RMR, the Hierarchical Rock Mass Rating (HRMR) was presented. The main feature of this system was the adaptation to the level of knowledge existent about the rock mass to obtain the classification of the rock mass since it followed a decision tree approach. However, the HRMR was only valid for hard rock granites with low fracturing degrees. In this work, the database was enlarged with approximately 40% more cases considering other types of granite rock masses including weathered granites and based on this increased database the system was updated. Granite formations existent in the north of Portugal including Porto city are predominantly granites. Some years ago a light rail infrastructure was built in the city of Porto and surrounding municipalities whi h involved considerable challenges due to the high heterogeneity levels of the granite formations and the difficulties involved in their geomechanical characterization. In this work it is intended to provide also a contribution to improve the characterization of these formations with special emphasis to the weathered horizons. A specific subsystem applicable to the weathered formations was developed. The results of the validation of these systems are presented and show acceptable performances in identifying the correct class using less information than with the RMR system.
Typearticle
URIhttp://hdl.handle.net/1822/41692
DOI10.1016/j.ijmst.2014.10.006
ISSN2095-2686
Publisher versionhttp://www.sciencedirect.com/science/article/pii/S2095268614001402
Peer-Reviewedyes
AccessrestrictedAccess
Appears in Collections:ISISE - Artigos em Revistas Internacionais

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