A hybrid predictive model of unstable rock blocks around a tunnel based on estimated volumetric fracture intensity and circular variance from borehole data sets

Hekmatnejad A. Crespin B. Vallejos J.A. Opazo A. Adoko A.C.
May 2021 Elsevier Ltd

Tunnelling and Underground Space Technology
2021 #111

Several failure modes may occur around underground excavations, one of the most common being block failure. The size distribution and occurrence probabilities of unstable blocks depend on discontinuity parameters such as size, shape, intensity, and orientation. The knowledge about the size and the number of blocks provides critical information to optimize site characterization and design procedures, or at least to accomplish this more efficiently. In this work we introduce a new attribute, Circular Variance, to measure the degree of dispersion of the fracture poles in angular domain based on borehole data. In our study the final objective is to present a predictive model of the mean rate of the formation of unstable rock blocks and their uncertainty. To fulfill this goal, we introduce a hybrid approach based on the combination of probabilistic discrete fracture network modeling, rock block failure instability analysis and supervised vector machine concepts. The present research studies the impact of P₃₂, circular variance, and mean radius of the fractures on the mean generation rate of unstable blocks in a tunnel at El Teniente mine, Chile. A two and three factors supervised Poisson regression models are compared against each other for the prediction of the mean generation rate of unstable blocks. The results showed a good agreement between the real number of unstable blocks and the estimated ones with supervised Poisson regression models.

Circular Variance , Discrete fracture network model , Hybrid approach , Supervised vector machine , Tunnel instability , Volumetric fracture intensity

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School of Mining Engineering, University of Talca, Camino Los Niches Km. 1, Curico, Chile
Center for Mathematical Modeling, UMI (2807) UCHILE-CNRS, University of Chile, Casilla 170-3, Correo 3, Santiago, Chile
Univ. Limoges, XLIM/ASALI, UMR CNRS 7252, Limoges, F-87000, France
Department of Mining Engineering, University of Chile, Avenida Tupper, Santiago, 2069, Chile
Advanced Mining Technology Center, University of Chile, Avenida Beauchef, Santiago, 850, Chile
Nazarbayev University, School of Mining and Geosciences, 53 Kabanbay Batyr Avenue, Nur-Sultan city (Astana), Kazakhstan

School of Mining Engineering
Center for Mathematical Modeling
Univ. Limoges
Department of Mining Engineering
Advanced Mining Technology Center
Nazarbayev University

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