Clarification of the slope mass rating parameters assisted by SMRTool, an open-source software

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Título: Clarification of the slope mass rating parameters assisted by SMRTool, an open-source software
Autor/es: Pastor Navarro, José Luis | Riquelme, Adrián | Tomás, Roberto | Cano, Miguel
Grupo/s de investigación o GITE: Ingeniería del Terreno y sus Estructuras (InTerEs)
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Ingeniería Civil
Palabras clave: Geology | Rock mechanics | Matlab | Slope mass rating | Geomechanical classification
Área/s de conocimiento: Ingeniería del Terreno
Fecha de publicación: dic-2019
Editor: Springer Berlin Heidelberg
Cita bibliográfica: Bulletin of Engineering Geology and the Environment. 2019, 78(8): 6131-6142. doi:10.1007/s10064-019-01528-9
Resumen: Geomechanics classifications are used to perform a preliminary assessment of rock slope stability for different purposes in civil and mining engineering. Among all existing rock mass classifications, slope mass rating (SMR) is one of the most commonly used for slopes. Although SMR is a geomechanics classification applied worldwide, often some misapprehensions and inaccuracies are made when professionally and scientifically used. Nearly all these miscalculations involve the influence of slope geometry and the dip and direction of the discontinuities. These problems can be overcome by a systematic assessment of SMR, which allows users to understand and visualize the relative orientation between discontinuities and slope. To fulfil this purpose, a complete and detailed definition of the angular relationships between discontinuities and slope are included in this paper, clarifying the assessment of the SMR parameters. Additionally, a Matlab-based open-source software for SMR (SMRTool) calculation is presented, avoiding miscalculations by automating the calculations and showing the graphical representation of slope and discontinuities. Finally, a general explanation of the method for the use of SMR is reviewed, stressing the common source of errors when applying this classification. The performance, benefits and usefulness of SMRTool are also illustrated in this paper through a specific case study.
Patrocinador/es: This work has been supported by the University of Alicante under the projects GRE14-04 and GRE17-11, the Spanish Ministry of Economy and Competitiveness (MINECO), the State Agency of Research (AEI) and the European Funds for Regional Development (FEDER) under projects TEC2017-85244-C2-1-P and TIN2014-55413-C2-2-P, and the Spanish Ministry of Education, Culture and Sport under project PRX17/00439 and CAS17/00392.
URI: http://hdl.handle.net/10045/99191
ISSN: 1435-9529 (Print) | 1435-9537 (Online)
DOI: 10.1007/s10064-019-01528-9
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: © Springer-Verlag GmbH Germany, part of Springer Nature 2019
Revisión científica: si
Versión del editor: https://doi.org/10.1007/s10064-019-01528-9
Aparece en las colecciones:INV - INTERES - Artículos de Revistas

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