Statistical Assessment of the Effects of Grain-Structure Representation and Micro-Properties on the Behavior of Bonded Block Models for Brittle Rock Damage Prediction

Carlos Efrain Contreras Inga, Gabriel Walton and Elizabeth Holley
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Carlos Efrain Contreras Inga: Department of Geology and Geological Engineering, Colorado School of Mines, 1516 Illinois St., Golden, CO 80401, USA
Gabriel Walton: Department of Geology and Geological Engineering, Colorado School of Mines, 1516 Illinois St., Golden, CO 80401, USA
Elizabeth Holley: Department of Mining Engineering, Colorado School of Mines, 1600 Illinois St., Golden, CO 80401, USA

Sustainability, 2021, vol. 13, issue 14, 1-27

Abstract: The ability to predict the mechanical behavior of brittle rocks using bonded block models (BBM) depends on the accuracy of the geometrical representation of the grain-structure and the applied micro-properties. This paper evaluates the capabilities of BBMs for predictive purposes using an approach that employs published micro-properties in combination with a Voronoi BBM that properly approximates the real rock grain-structure. The Wausau granite, with Unconfined Compressive Strength (UCS) of 226 MPa and average grain diameter of 2 mm, is used to evaluate the effectiveness of the predictive approach. Four published sets of micro-properties calibrated for granites with similar mineralogy to the Wausau granite are used for the assessment. The effect of grain-structure representation in Voronoi BBMs is analyzed, considering grain shape, grain size and mineral arrangement. A unique contribution of this work is the explicit consideration of the effect of stochastic grain-structure generation on the obtained results. The study results show that the macro-properties of a rock can be closely replicated using the proposed approach. When using this approach, the micro-properties have a greater impact on the realism of the predictions than the specific grain-structure representation. The grain shape and grain size representations have a minor effect on the predictions for cases that do not deviate substantially from the real average grain geometry. However, the stochastic effect introduced by the use of randomly-generated Voronoi grain-structures can be significant, and this effect should be considered in future studies.

Keywords: strength prediction; brittle rock; grain-structure representation; micro-properties; bonded block models; Voronoi tessellation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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