Method for the Interpretation of RMR Variability Using Gaussian Simulation to Reduce the Uncertainty in Estimations of Geomechanical Models of Underground Mines
| Autor: | Carlos Raymundo, Humberto Pehovaz-Alvarez, Javier M. Moguerza, Juliet Rodriguez-Vilca, Nestor Mamani-Macedo, Jose Paucar-Vilcañaupa |
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| Rok vydání: | 2020 |
| Předmět: |
Mean squared error
Gaussian 0211 other engineering and technologies Soil science Context (language use) 02 engineering and technology 010502 geochemistry & geophysics 01 natural sciences symbols.namesake Kriging Rock mass rating symbols Spatial variability Rock mass classification Uncertainty analysis Geology 021101 geological & geomatics engineering 0105 earth and related environmental sciences |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030507909 AHFE (9) |
| DOI: | 10.1007/978-3-030-50791-6_44 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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