Citas bibligráficas
Paucar, J., Rodriguez, J. (2022). Caracterización de la incertidumbre del modelo geomecánico del túnel de acceso principal en el tramo crítico con presencia de aguas hidrotermales de un proyecto minero al sur del Perú utilizando Simulación Gaussiana [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/659198
Paucar, J., Rodriguez, J. Caracterización de la incertidumbre del modelo geomecánico del túnel de acceso principal en el tramo crítico con presencia de aguas hidrotermales de un proyecto minero al sur del Perú utilizando Simulación Gaussiana [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2022. http://hdl.handle.net/10757/659198
@misc{renati/398696,
title = "Caracterización de la incertidumbre del modelo geomecánico del túnel de acceso principal en el tramo crítico con presencia de aguas hidrotermales de un proyecto minero al sur del Perú utilizando Simulación Gaussiana",
author = "Rodriguez Vilca, Juliet Haydee",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2022"
}
Accurate characterization and modeling of the rock mass geomechanical heterogeneity leads to efficient mine planning and design. The use of conventional techniques such as Kriging for modeling the rock mass is limited, since it does not consider the spatial variability and heterogeneity of the rock mass, resulting in estimates that do not represent the real behavior of the rock mass. In this context, it is proposed as an alternative solution to use the Gaussian Simulation to estimate the spatial heterogeneity of the rock mass based on the analysis of the values of UCS, RQD, Water condition and joint condition for the RMR modeling, this technique consists in simulating different values from known data, in addition to allowing to analyze the uncertainty of the obtained simulations. The methodology proposed in this research considers the variographic analysis of the regionalized geomechanical variables in directions, in order to determine their anisotropic behavior; Likewise, the uncertainty analysis is developed using the cross-validation technique that consists of dividing the original data into two subsets at random. 85% of the database was used to estimate the RMR values, while 15% was used as a test subset. The case study is the critical section with the presence of hydrothermal waters of the main access tunnel of a mining project in southern Peru, the geomechanical record data taken in the field was used, with them a total of 5 simulations were produced for each variable, producing approximately 3 million values for each variable. The mean absolute error of the model generated with Gaussian Simulation is only 6.58%, which is considered admissible compared to the 38.01% obtained with Kriging.
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