El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / The application of conventional techniques, such as kriging, to model rock mass is limited because rock mass spatial variability and heterogeneity are not considered in such techniques. In this context, as an alternative solution, the application of the Gaussian simulation technique to simulate rock mass spatial heterogeneity based on the rock mass rating (RMR) classification is proposed. This research proposes a methodology that includes a variographic analysis of the RMR in different directions to determine its anisotropic behavior. In the case study of an underground deposit in Peru, the geomechanical record data compiled in the field were used. A total of 10 simulations were conducted, with approximately 6 million values for each simulation. These were calculated, verified, and an absolute mean error of only 3.82% was estimated. It is acceptable when compared with the value of 22.15% obtained with kriging.
| Identifer | oai:union.ndltd.org:PERUUPC/oai:repositorioacademico.upc.edu.pe:10757/656171 |
| Date | 01 January 2020 |
| Creators | Rodriguez-Vilca, Juliet, Paucar-Vilcañaupa, Jose, Pehovaz-Alvarez, Humberto, Raymundo, Carlos, Mamani-Macedo, Nestor, Moguerza, Javier M. |
| Publisher | Springer |
| Source Sets | Universidad Peruana de Ciencias Aplicadas (UPC) |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/article |
| Format | application/html |
| Source | Universidad Peruana de Ciencias Aplicadas (UPC), Repositorio Académico - UPC, Advances in Intelligent Systems and Computing, 1209 AISC, 342, 349 |
| Rights | info:eu-repo/semantics/embargoedAccess |
| Relation | https://link.springer.com/chapter/10.1007/978-3-030-50791-6_44 |
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