Influence of data characterization process on the kinematic stability analysis of engineered rock slopes using discrete fracture network models and its implications for rock mass classification system
department or school: Applied Science, Faculty of
department or school: Mining Engineering, Keevil Institute of
data provider: DSpace
degree campus: UBCV
creator: Miyoshi, Takako
issued: 2018-09-11T16:01:50Z
issued: 2018
related degree: Master of Applied Science - MASc
degree grantor: University of British Columbia
description: The thesis investigates the influence of data characterization process on kinematic slope stability analysis using a Discrete Fracture Network (DFN) approach. The first aspect of the data characterization process considered in this thesis is the influence of separate statistical procedure to define fracture set (aggregate vs disaggregate approach). The DFN models generated using aggregate and disaggregate approaches are compared in terms of simulated fracture properties and the kinematic slope stability analysis. The results showed the aggregate approach either overestimates or underestimates the important fracture properties such as fracture intensity and length. Accordingly, the number and volume of blocks formed on the slope would not be truly representative of field condition. The second aspect of data characterization process is the influence of conditioning (incorporation of mapped fractures) to DFN models. The unconditioned and conditioned DFN model are compared in terms of kinematic slope stability analysis, with emphasis on the locations of potential block formations. The results showed that the conditioned DFN model would allow for a better consideration of spatial locations of potentially unstable blocks. Lastly, the thesis presents the application of DFN approach to study the variability of Geological Strength Index (GSI). The Particle Size Distribution (PSD) plots obtained from DFN models are combined with the quantification method of GSI to estimate the GSI rating. Additionally, the implication of two-dimensional (2D) versus three-dimensional (3D) data to characterize rock mass blockiness is examined. The results showed that the range of GSI rating for a rock mass could be as large as ±10. This suggests the limitation on using a unique value of GSI rating, when the GSI rating is variable due to the inherent uncertainty of the rock mass in reality. The comparison between 2D and 3D blockiness showed that the blockiness observed on a 2D plane does not nec…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/67145
note: INFLUENCE OF DATA CHARACTERIZATION PROCESS ON THE KINEMATIC STABILITY ANALYSIS OF ENGINEERED ROCK SLOPES USING DISCRETE FRACTURE NETWORK MODELS AND ITS IMPLICATIONS FOR ROCK MASS CLASSIFICATION SYSTEM by Takako Miyoshi B.A.Sc., The University of British Columbia, 2017 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Mining Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) September 2018 © Takako Miyoshi, 2018 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis/dissertation entitled: Influence of data characterization process on the kinematic stability analysis of engineered rock slopes using discrete fracture network models and its implications for rock mass classification system submitted by Takako Miyoshi in partial fulfillment of the requirements for the degree of Master of Applied Science in Mining Engineering Examining Committee: Davide Elmo, Mining Engineering Supervisor Ilija Miskovic, Mining Engineering Supervisory Committee Member Supervisory Committee Member Additional Examiner iii Abstract The thesis investigates the influence of data characterization process on kinematic slope stability analysis using a Discrete Fracture Network (DFN) approach. The first aspect of the data characterization process considered in this thesis is the influence of separate statistical procedure to define fracture set (aggregate vs disaggregate approach). The DFN models generated using aggregate and disaggregate approaches are compared in terms of simulated fracture properties and the kinematic slope stability analysis. The results showed the aggregate approach either overestimates or underestimates the important fracture properties such as fracture intensity and length. Accordingly, the number and volume of blocks formed on the slope would not be truly representa…
has type: Thesis/Dissertation
date issued: 2018-11
is shown at: 10.14288/1.0372017
language: eng
degree discipline: Mining Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/67145