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2006-05-16_REPORT - M1974004
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2006-05-16_REPORT - M1974004
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Last modified
8/23/2019 8:40:42 AM
Creation date
11/27/2007 8:25:08 AM
Metadata
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Template:
DRMS Permit Index
Permit No
M1974004
IBM Index Class Name
Report
Doc Date
5/16/2006
Doc Name
Annual Fee/Report/Map
From
Lafarge West, Inc.
To
DMG
Permit Index Doc Type
Annual Fee / Report
Media Type
D
Archive
No
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6.0 Analysis of Structural Discontinuities <br />The stability of the rock mass that forms the highwalls of the quarry is mainly <br />controlled by the discontinuities that exist within the rock mass. Discontinuities <br />create the surfaces that sliding can occur upon and the intersections of multiple <br />discontinuities define the boundaries of wedges or blocks that have the potential <br />to slide. As observed throughout the quarry, the discontinuity sets all have a <br />range of dip and dip direction, and therefore it is possible that discontinuity <br />orientations in a specific location of the quarry deviate from the general <br />discontinuity orientations assumed for the analyses presented in this report. <br />6.1 Evaluation of Discontinuity Measurements <br />As the database for discontinuity measurements has increased, various methods <br />have been utilized to efficiently analyze the new geologic data relative to the <br />existing data. The analysis of the discontinuity data was conducted using Dips <br />5.0 (Rocscience, 2002), which is an interactive program for the analysis of <br />discontinuity orientations based on geological data inputs. For this study, the <br />data were evaluated with stereographic plots using a combination of contour <br />analyses and cluster analyses to determine representative dip directions and dip <br />angles for the predominant discontinuity set. The contour analysis of the entire <br />dataset (i.e., 2,960 points) resulted in a plot of density contours, which facilitated <br />our determination of the general discontinuity orientations (Figure 4). The cluster <br />analysis has helped to further refine the data by utilizing an iterative approach to <br />group the data measurements into representative clusters. The nucleus of each <br />cluster represents the concentration center for the data set (Figure 6). The <br />differences between each of the individual year's analyses can best be seen on a <br />stereographic presentation showing each of the concentration poles for the <br />clusters for multiple years analyses (Figure 7). A combination of the clusters <br />from Figure 6 and the results of the contour and cluster analysis of the entire <br />dataset (Figure 7) were used to define the discontinuities and their orientations <br />-15- <br />
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