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Updating of the hierarchical rock mass rating(HRMR) system and a new subsystem developed for weathered granite formations

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International Journal of Mining Science and Technology 2014年第6期24卷 769-775页

作者： Miranda Tiago e Sousa L.Ribeiro tinoco joaquim ISISE University of Minho Guimar?es 4800-058 Portugal State Key Laboratory of Geomechanics and Deep Underground Engineering China University of Mining & Technology University of Porto Porto 4200 Portugal

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 which 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.

关键词： Rock mass classification system Decision tree Weathered granite formations

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The Use of Data Mining Techniques in Rockburst Risk Assessment

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Engineering 2017年第4期3卷 552-558页

作者： Luis Ribeiro e Sousa Tiago Miranda Rita Leal e Sousa joaquim tinoco State Key Laboratory for GeoMechanics and Deep Underground Engineering China University of Mining and Technology (Beijing) Beijing 100083 China Institute for Sustainability and Innovation in Structural Engineering Department of Civil Engineering University of Minho Campus de Azurem Guimaraes 4800-058 Portugal Masdar Institute of Science and Technology Musdar City Abu Dhabi UAE

Rockburst is an important phenomenon that has affected many deep underground mines around the world. An understanding of this phenomenon is relevant to the management of such events, which can lead to saving both costs and lives. Laboratory experiments are one way to obtain a deeper and better understanding of the mechanisms of rockburst. In a previous study by these authors, a database of rockburst laboratory tests was created; in addition, with the use of data mining （DM） techniques, models to predict rockburst maximum stress and rockburst risk indexes were developed. In this paper, we focus on the analysis of a database of in situ cases of rockburst in order to build influence diagrams, list the factors that interact in the occurrence of rockburst, and understand the relationships between these factors. The in situ rockburst database was further analyzed using different DM techniques ranging from artificial neural networks （ANNs） to naive Bayesian classifiers. The aim was to predict the type of rockburst-that is, the rockburst level-based on geologic and construction characteristics of the mine or tunnel. Conclusions are drawn at the end of the paper.

关键词： Rockburst Data mining Bayesian networks In situ database

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