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2009-02-17_REPORT - M1974004 (2)
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2009-02-17_REPORT - M1974004 (2)
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Last modified
8/24/2016 3:43:40 PM
Creation date
2/23/2009 8:38:11 AM
Metadata
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Template:
DRMS Permit Index
Permit No
M1974004
IBM Index Class Name
REPORT
Doc Date
2/17/2009
Doc Name
Structural Geology Evaluation 2009 Annual Report
From
Lafarge West, Inc.
To
DRMS
Permit Index Doc Type
Annual Reclamation Report
Media Type
D
Archive
No
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<br />5.0 Analysis of Structural Discontinuities <br />' The stability of the rock mass that forms the highwalls of the quarry is mainly controlled <br />by the discontinuities. Discontinuities create the surfaces that sliding can occur upon <br />and the intersections of multiple discontinuities define the boundaries of wedges or <br />blocks that have the potential to slide. As observed throughout the quarry, the <br />discontinuity sets all have a range of dip and dip direction, and therefore it is possible <br />that discontinuity orientations in a specific location of the quarry deviate from the <br />general discontinuity orientations assumed for the analyses presented in this report. <br />5.1 Evaluation of Discontinuity Measurements <br />As the database for discontinuity measurements has increased, various methods have <br />been utilized to efficiently analyze the new acquired geologic data. The analysis of the <br />discontinuity data was conducted using Dips 5.1 (Rocscience, 2006), which is an <br />interactive program for the analysis of discontinuity orientations based on geological <br />data inputs. For this study, the data were evaluated with stereographic plots using a <br />combination of contour analyses and cluster analyses to determine representative dip <br />directions and dip angles for the predominant discontinuity sets. <br />The contour analysis of the entire dataset (i.e., 3053 points) resulted in a plot of density <br />contours, which facilitated our determination of the general discontinuity orientations <br />across the entire facility (Figure 4). The cluster analysis has helped to further refine the <br />data by utilizing an iterative approach to group the data measurements into <br />representative clusters. The nucleus of each cluster represents the concentration <br />center for a given data set as is shown for the cumulative dataset (i.e. 3053 datapoints) <br />in Figure 6. The differences between each of the individual year's analyses can best be <br />seen on a stereographic presentation showing each of the concentration poles for the <br />clusters for each annual analysis (Figure 7). A combination of the clusters from Figure <br />6 and the results of the contour and cluster analysis of the entire dataset (Figure 7) <br />were used to define the discontinuities and their orientations for use in this year's <br />-11-
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