ROCK MASS CHARACTERIZATION FIRST STEP TO DESIGN …

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FINAL TECHNICAL REPORT

May 1, 2013, though April 30, 2014

Project Title: ROCK MASS CHARACTERIZATION – FIRST STEP TO DESIGN

SAFETY MEASURES AND CONTROL ROOF FALLS

ICCI Project Number: 13/ER-8

Principal Investigator: Dr. A. Osouli, Southern Illinois University Edwardsville

Project Manager: Dr. Joseph Hirschi, ICCI

ABSTRACT

Rock mass characterization is the key initial step in designing safe and economic roof

control systems for underground coal mines. Coal Mine Roof Rating (CMRR) is the most

widely used index for characterizing immediate rock units. This index was developed

through investigations into the performance of roof rock units for several case studies;

mostly located in the Appalachian coal fields, which have typically strong roof units. The

CMRR index ranges from 0 to 100 representing weak to strong rocks. Applying the

CMRR approach to case studies outside the previous database may misrepresent

associated rock masses and a mischaracterized designing method may lead to erroneous

roof control plans and consequently additional maintenance costs. Therefore, application

of the CMRR procedure in the Illinois Basin, with its weak and moisture-sensitive roof

rock units, first requires an inventory of local geologic conditions as well as mine-

specific conditions, such as roof fall analysis, mining method, supplemental roof control

measures, and geotechnical properties of roof rock units, to validate the suitability of the

approach for the region.

To accomplish this objective, three major tasks were completed with cooperation and

assistance from an underground coal mine in Illinois. Firstly, geological information,

roof bolt intensity and type, mine opening widths, utilized mining methods, and roof rock

samples along with roof performance information were collected from the mine.

Secondly, geotechnical engineering properties were determined for rock samples

collected from the mine by conducting standard laboratory tests. Finally, roof rock mass

characterization was determined and a reliability analysis was conducted to determine the

applicability of the CMRR method for the Illinois Basin. In this research, geotechnical

properties of various rock types from the Illinois Basin have been compiled and

conversion factors were developed for correlating point load test results to results from

conventional tests such as Unconfined Compressive Strength and Indirect Tensile

Strength. Also, the reliability of the Analysis of Roof Bolt Systems program for

designing a mine in the Illinois Basin was investigated. A comprehensive sensitivity

analysis was performed on effective factors involved in determining the CMRR index in

order to distinguish specific parameters that are most influential to the Illinois Basin.

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EXECUTIVE SUMMARY

Although several mining agencies have been focused on finding practical, safe mine

design approaches to reduce roof fall accidents and consequently worker injuries, roof

falls continue to be one of the most critical issues faced by mine operators from year to

year (Mark and Molinda, 2007). Among all US coal fields mined primarily by

underground methods, Illinois has the highest incident rate of roof falls due to its weak

and severely moisture-sensitive roof rock units. It has also been discovered that strong

biaxial horizontal stress plays a significant role in contributing to Illinois’ weak roof rock

structure. Due to its importance in terms of miner safety, but also for economic reasons,

the roof control plan has always been the most critical element in estimating the mining

feasibility of a coal reserve.

The main purpose of this exploratory research was to evaluate the applicability of the

Coal Mine Roof Rating (CMRR) approach in Illinois coal fields with their specific roof

conditions. Any enhancement in this approach that increases its utility for the Illinois

Basin could result in more economic roof control plans and a reduction in the number of

roof falls and worker injuries. To that end, it was necessary to probe earlier mine design

approaches, geologic conditions, roof fall analyses, and geotechnical properties of typical

Illinois Basin rock units. The performance of roof rock units given various design

condition had to be compared with expected roof design behavior based on guidelines

developed by the National Institute for Occupational Safety and Health (NIOSH). The

most popular of those guidelines is the Analysis of Roof Bolt Systems (ARBS) program.

To meet the objectives of this exploratory research project, the research team at Southern

Illinois University Edwardsville (SIUE) investigated roof conditions and the performance

of the roof control plan at a room-and-pillar coal mine in Illinois. The mine produces coal

from the Illinois No. 6 coal seam. Three major tasks were defined for this study:

Task 1 – Collecting roof performance and geological information from Illinois mines.

Task 2 – Determining engineering properties for collected rock samples.

Task 3 – Evaluating roof conditions and the reliability of the current design method.

Available mine plans, boring logs, laboratory testing data, mine geometries, roof control

plans, and implemented roof support systems were carefully reviewed and analyzed. At

each borehole location, careful judgment was exercised to classify roof rock units within

the bolted interval based on boring logs and rock mechanics test data conducted by the

mining company. This activity resulted in development of required input parameters (i.e.,

layer type, thickness, strength, discontinuity characteristics, and moisture sensitivity) to

determine a CMRR for each borehole location and helped to identify what information

was missing and what layers needed further rock mechanics laboratory testing. In order

to fill gaps in geomechanical properties data, more than 500 feet of borehole rock cores

of shale, black shale, sandy shale, clay stone, limestone, and shale-limestone were

collected for further testing in the SIUE rock mechanics laboratory. Rock mechanics

laboratory tests such as moisture content, axial and diametral point load, slake durability,

and indirect tensile strength were conducted on these cores following American Society

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for Testing and Materials (ASTM) standards. Tests results were added to data provided

by the mining company and used to determine CMRR values for borehole cores. An

analysis of these results concluded that there are correlations between the Axial Point

Load (PLA) test and the Unconfined Compressive Strength (UCS) test as well as

between the Diametral Point Load (PLD) test and the Indirect Tensile Strength (ITS) test

with the former correlation being linear and the latter nonlinear. A sensitivity analysis on

PLD and UCS data showed that for the Illinois Basin, the CMRR is more affected by

PLD values. It was also observed that strength properties of roof layers are more volatile

in the horizontal plane than in the axial direction requiring enhancement of the CMRR

determination by incorporating the effect of bedding strengths in the horizontal direction.

In addition to determining the CMRR for borehole cores, roof rock samples were

collected in the mine near borehole locations and in places where there had been roof

falls. Then the CMRR was determined for these samples. Underground and borehole

core CMRR values showed reasonable agreement for a majority of the selected locations.

Comparing the CMRR at roof fall locations with the CMRR from nearby where roof was

still intact helped to identify lower boundaries of stable roof. The ARBS program

showed that the NIOSH-recommended CMRR versus depth of cover, which is a

representative measure of stress levels at the mine depth, required CMRR of more than

45 in order to limit roof falls. However, analysis of mine samples showed locations that

had CMRR between 35 and 45 and did not experience roof falls. It was not possible to

effectively measure to what extent supplemental support and skin protection employed

by the mine contributed to this better than expected roof performance.

Employing NIOSH guidelines for mine design should allow for large intersection spans

(i.e., more than 30 feet) at some locations based on roof quality measured by the CMRR

approach; however, the mine limited intersection spans to less than 26 feet. Therefore, it

was not possible to effectively verify the NIOSH recommendation although it was

observed that the NIOSH-recommended intersection span was not conservative at roof

fall locations. Furthermore, given the mine’s use of 6-ft fully grouted bolts on 4-5-ft

spacing, the ARBS number used to evaluate roof bolting intensity was determined to be

7.2 to 7.5. Using a minimum allowable ARBS of 3, the required roof bolt length for this

mine could be less (i.e., 2 to 3 feet). Because the mine utilizes screening for skin control

in all panels and mains and installs up to 10 cable bolts in intersections in addition to the

normal bolting pattern previously described, the roof control plan at this mine is

considered over designed and it was not possible to effectively evaluate the applicability

of NIOSH guidelines (i.e., ARBS numbers). Despite this over design, it was observed

that roof falls occurred in places where the wet CMRR was less than 35.

Overall, it is concluded that roof rock characterization using the CMRR can be a

challenge in the Illinois Basin, but with some modification it can be reliable and

effective. In particular, incorporating rock strength in the horizontal plane for weak roof

units is critical in order to more accurately represent the rock mass index. This

enhancement in CMRR methodology for the Illinois Basin requires examination and

studying of several mines and expanded database.

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OBJECTIVES

The overall objective of this exploratory research was to determine if CMRR is a

reasonable and representative rock mass strength index for the Illinois Basin in its

developed form or if modifications are needed. This study concentrated on analyzing

geotechnical properties of Illinois rock units, particularly those associated with roof fall

incidents, and evaluating the performance of roof support systems including type and

intensity to characterize roof conditions. To accomplish this, three tasks were undertaken.

Task 1 – Collecting Roof Performance and Geological Information from Illinois Mines

A database of roof fall features and roof performance characteristics for the Illinois Basin

was developed from the most recent Mine Safety and Health Administration (MSHA)

District 8 and 10 roof fall reports; roof control plans, laboratory test results, and other

general geological information provided by mining companies; and mine inspection

reports from the Illinois State Geological Survey. This information was used to

investigate correlations between mine panel width, intersection span width, groundwater

conditions, mining method, roof control plan, and supplemental support specifications on

the type, volume, dimension, location, and timing of roof failures after mining.

Task 2 – Determining Engineering Properties for Collected Rock Samples

After analyzing all available information collected in Task 1, mines were visited to

collect available cores of roof rock and roof samples for laboratory testing to fill gaps in

the database. Collected samples were logged and tested in the laboratory for moisture

content, axial and diametral point load index, indirect tensile strength, and moisture

sensitivity. Also, during mine visits, tests such as the Ball Peen Hammer test and the

Chisel Splitting test were performed on roof rock. Fracture spacing, discontinuity, and

rock quality designation (RQD) values were determined where applicable. Previous

studies showed that unconfined compressive strength correlates well with axial point load

test results for various rocks (Rusnak and Mark, 2000); therefore, PLA tests were used in

lieu of UCS tests. However, data is lacking to identify a similar correlation between

diametral point load test results and other common rock tensile strength tests. In this task,

the potential correlation between tensile strength and PLD test results was investigated.

Task 3 – Evaluating Roof Conditions and the Reliability of the Current Design Method

After compiling all data from Tasks 1 and 2, roof bolt intensity, cause and type of roof

difficulties, geologic conditions, room width, intersection span, and type of support

system were examined to understand the geomechanics of the mine opening. The CMRR

at roof fall locations as well as in areas that did not have any roof problems was

determined using all pertinent information. Existing intersection span and roof bolt

intensity were compared to recommended NIOSH guidelines and specifications.

Additionally, through a set of sensitivity analyses, the effect of strength and discontinuity

parameters on determining the rock mass strength index was explored.

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INTRODUCTION AND BACKGROUND

According to MSHA statistics, of the 1500 roof falls that occur each year in US coal

mines, the highest number occur in the Illinois Basin (MSHA, 2006). Roof falls are the

result of weak roof units or inadequate support. CMRR is used to evaluate the

competency of roof rock and can also be incorporated in designing roof support systems

using ARBS (Molinda and Mark, 2001). Therefore, it is important to verify if the current

procedure of determining CMRR works for Illinois coal fields.

The CMRR incorporates many factors, such as thickness and number of different roof

units, moisture sensitivity of roof beds, shear and compressive strength of rock units, and

existence of groundwater, into one single index (Hill, 2007). Among these parameters,

moisture sensitivity is one of the most critical factors in evaluating mine roof stability. It

can cause several defects in the roof control system by decreasing rock strength. In short-

term applications it may not necessarily affect rock strength; however, in long-term

applications, it might cause hazardous mine incidents (Mark and Molinda, 2007). The

procedure for determining CMRR reflects conditions with and without a moisture

sensitivity effect, which are defined as wet and dry CMRR, respectively.

Geomechanical engineering parameters can be obtained using either rock laboratory tests

or underground field information. In either case, shear strength of rock layers (e.g. UCS),

moisture sensitivity, spacing and frequency of bedding planes, joint sets, slickensides,

and other discontinuities are considered. Uniaxial Compressive Strength (which is the

same as UCS) and ITS tests provide two most important geotechnical properties of rocks

that have wide application in the determination of CMRR. These tests are time

consuming and costly. On the other hand, the point load test is simple, cheap, and quick,

and can be used to estimate UCS and ITS. A number of studies have been conducted to

provide the relationship between point load test results and conventional strength (Singh

et al., 2011; Rusnak and Mark, 2000; Kahraman, 2001; Cargill and Shakoor, 1990).

Conversion factors of 21 to 25 were suggested for converting PLA to UCS in these

studies. However, there is a lack of data for determining a reasonable correlation between

the Diametral Point Load index and the ITS index for different types of rocks.

EXPERIMENTAL PROCEDURES

The research team had the support of three different coal mining companies in the Illinois

Basin, identified as Mines A, B, and C; however, since the support of Mine A was more

than the other mining companies, it was selected as the cooperating mine for the study.

Exploratory Borehole Information

Mine A is located in the Illinois Basin coal field. Boreholes drilled by and for the

company were categorized in four groups: A, B, C, and D consisting of 13, 11, 4, and 23

boreholes, respectively. Cores from Group A boreholes had the most rock testing of all

four groups, cores from Group B boreholes had some rock testing completed, and cores

from Group C boreholes had no rock testing results. Furthermore, Group A borehole

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locations were spaced to cover the entire mine reserve area while Group B and C

boreholes were drilled three to five years earlier than Group A and only covered a limited

area of the mine reserve. Group D boreholes were drilled the same year as Group A

boreholes; however, very limited rock mechanics testing was done on these cores.

Rock testing included PLA, PLD, UCS, moisture content, slake durability, and ITS tests.

After reviewing all available test results on similar rock layers, appropriate rock

properties were assigned to layers that did not have laboratory tests results. Boring logs,

rock mechanics test data, and rock units within 10-15 feet of roof rock units were studied

and summarized to develop roof rock geotechnical properties for each layer (i.e., shale,

limestone, shale and limestone inter-beds, etc.). A total of nine layers were identified in

the immediate roof of the mine through careful utilization of engineering judgment to

classify representative layers for rock mass characterization.

Conducting Laboratory Tests

For Task 2, 50 boxes of borehole cores (equivalent to 500 feet of rock core) from the

immediate (10 feet) roof layers of the mine were collected for additional testing in the

SIUE rock mechanics laboratory. The majority of these cores were wrapped in plastic at

the time of coring to protect them from being damaged. Numerous tests were conducted

on these rock core specimens with results summarized in Table 1. Point load, moisture

content, UCS, and ITS tests were performed based on D5731-08, D1558-10, D7012-10,

and D3967-08 ASTM standards, respectively (ASTM, 2014).

Determining CMRR

CMRR can be determined using a computer program available from NIOSH (Mark and

Molinda, 2003). Using data obtained either from borehole cores or underground

information, the CMRR program evaluates the rock mass index of each unit in the bolted

interval and generates a rating for that unit. Then, a thickness-weighted average of unit

indexes are calculated and reflected as the final CMRR value. It is worth mentioning that

the program also takes into account the effects of water surcharge, ground water

dripping, and rock unit contacts in determining the final CMRR value.

Using Borehole Cores: Equation 1 shows the general function for determining the

CMRR rating for a unit of rock based on borehole core information.

Unit Rating = f (UCS Rating, Discontinuity Rating, Moisture Sensitivity Deduction) (1)

In developing CMRR, Molinda and Mark (2001) have suggested that the PLA test is an

acceptable alternative to the UCS test in determining the UCS rating. The discontinuity

rating is determined by considering both spacing between discontinuities, and the

persistence or endurance of each single discontinuity, which takes both PLD test results

and RQD into account. The CMRR program uses the minimum of RQD or PLD for the

discontinuity rating. Any moisture sensitivity effect has a maximum deduction of 15

points from the dry CMRR.

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Using Samples Collected from Underground Exposures: The program can also use

underground exposure data to calculate the CMRR. For this case, the strength and

cohesion of internal discontinuities are used to determine the CMRR index for the

observed location. For this method, the number, roughness, spacing, and persistence of

discontinuities are required. These data are collected during mine visits. Also, the

moisture sensitivity of mine samples needs to be evaluated with Slake Durability tests.

Exploratory Borehole Core CMRR vs. Underground Sample CMRR

In order to compare CMRR values for borehole core information and underground

samples, two site visits were made and underground information were collected for

sixteen locations within the min. It is worth mentioning that in the majority of these

locations, accessible roof rock layers were less than three feet in thickness. Therefore,

underground CMRR values were determined using the following two assumptions:

1. 6-ft bolts are used and the top layer of accessible roof rock is extended to 6 feet.

These values are labeled as CMRR-UG-I.

2. 3-ft bolts are used and the top layer of accessible roof rock is extended to 3feet.

These values are labeled as CMRR-UG-II.

Roof Support Design

Three important variables – stress level, intersection span, and bolt properties – affect the

stability of a mine roof. In the eastern US, it was observed that increasing depth of cover

directly correlates with greater levels of maximum horizontal stresses (Mark and Mucho,

1994). According to this correlation and the fact that estimating horizontal stress may be

too complicated, depth of cover is used as the best representative of stress level. The

procedure recommended by Molinda and Mark (2001) is used to identify the suggested

intersection span and bolt properties.

Analysis of Roof Bolt System (ARBS) Procedure

Per Molinda and Mark (2001), the step-by-step procedure for using ARBS is as follows:

1. Assessing the Geology and Stress Level: The depth of cover and CMRR indices

related to different areas of the studied mine should be determined.

2. Determining the Design Support Reinforcement Mechanism: Equation 2 is

used to determine the roof bolt reinforcement mechanism. Different roof support

mechanisms are categorized as skin control, suspension, beam building, and

supplemental support. Skin control and suspension mechanisms refer to self-

supporting mechanism of roof units, while the beam building mechanism

represents the case that self-supporting layers do not exist in the roof composition

and bolt-supported roof units function as a “beam” to prevent failures. If the

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CMRR is larger than the one obtained from Equation 2, then skin control and/or

suspension mechanism will probably be adequate. Otherwise, beam building is

the probable roof support mechanism.

(2)

where H (in feet) is the overburden depth.

3. Determining the Recommended Bolt Length: Using Equation 3, the suggested

intersection span (ISG) is obtained based on the CMRR index. Then, the

appropriate bolt length (LB) for the recommended intersection span is determined

using Equation 4.

(3)

(

) (4)

where H (in feet) refers to overburden thickness.

4. Determining Required Roof Bolt Intensity: The suggested roof bolt intensity

(ARBSG) is calculated using Equation 5. It should be greater than 3.0.

( )[ ] (5)

where is the difference (in feet) between actual and suggested

intersection spans and H (in feet) refers to overburden thickness. A value of 1.2 is

recommended for SF, which is a Stability Factor.

5. Deciding on the Roof Bolt Pattern: ARBS was developed to representative a

roof support intensity index. It is used in Equation 6 to determine the remaining

design variables including bolt capacity, length, and pattern.

(6)

where Lb is bolt length (in feet), Nb is the number of bolts per row, C is bolt

capacity (in kips), Sb is spacing between rows of bolts (in feet), and Wc is the

entry width (in feet).

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RESULTS AND DISCUSSION

Point Load Tests vs. Conventional Tests

Statistical geomechanical properties data comparing UCS vs. PLA and ITS vs. PLD were

compiled according to rock type (shale, black shale, sandy shale, clay stone, limestone,

and shale-limestone) and are presented in Tables 2 and 3. Average UCS varies from 1627

to 3939 psi for shale and clay stone rock types and from 12983 to 16115 psi for limestone

and shale-limestone rock types. Therefore, according to classifications established by the

International Society for Rock Mechanics (ISRM), shale and clay stone rocks are

categorized as low strength rocks; while, limestone and shale-limestone rock types are

higher strength rocks (Bieniawski and Bernede, 1979).

UCS vs. PLA and ITS vs. PLD data are plotted in Figures 1 and 2. Regression lines

showing the correlation between testing data sets are shown in Figures 3 and 4.

Differences in correlation for various rock types could be due to their anisotropic nature,

joint settings or bedding characteristics, and the mineralogy of each rock type. As seen in

Figure 3, the relationship between UCS and PLA is linear with limestone and shale-

limestone having larger values. Regression analysis results are shown in Table 4.

Comparing conversion factors presented in the Table 4 for converting PLA indexes to

UCS, it can be observed that black shale and sandy shale show smaller PLA to UCS

conversion factors comparing to shale. Conversion factors between UCS and PLA in this

study are 21.1 for shale and 20.2 for limestone. These values are in agreement with those

suggested by Rusnak and Mark (2000) and those published by the ISRM (20-25).

The same process was followed for ITS-PLD data sets (see Figure 4). Since there are

only five sets of data related to shale-limestone (see Table 3), the regression analysis was

not conducted for this rock type. In contrast to the linear correlation between UCS and

PLA, a power law regression described by Equation 7 appears to be a more reasonable

depiction of the relationship between ITS and PLD.

ITS = a (PLD)b (7)

PLD and ITS values are in psi. Conversion equation constants a and b are shown in

Table 4. Regression lines are plotted in Figure 4. The ITS-PLD correlation presented

here is being reported for the first time. While the suggested correlations are reasonably

reliable for rock samples used in this study, they should be used cautiously for rocks in

other coal fields. It is also worth mentioning that failure in the PLD test is determined by

a point load acting on rock bedding planes, whereas in the ITS test, a linear load will act

on several rock bedding planes. Since mechanisms of failure are somewhat different

between these two sets, the observed variability in this correlation is expected.

There were some difficulties with sample preparation, testing, and failure planes of

samples in point load and ITS tests. During PLA tests, it was observed that some samples

failed layer by layer such that as the conical point loads would converge, the sample’s

layers would break one after the other without a sudden splitting of the bulk sample. In

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these cases, the failure surface did not pass through the loading points; therefore, the test

was rejected. ITS and PLA values obtained from these tests were either rejected or used

with careful judgment.

Exploratory Borehole Core vs. Underground Information

Table 5 provides a comparison of underground and borehole core CMRR values. Green

cells indicate that underground CMRR-UG-I and CMRR-UG-II are the same for the test

location. Slight changes in CMRR, however, occur in underground locations U-1, U-2,

U-3, UR-9, and UR-10. For these locations, conservative CMRR values were considered.

Figures 5 and 6 show both the wet and dry CMRR within the mine area derived from

borehole core information assuming 6-ft and 3-ft bolt lengths, respectively.

Figure 7 and 8 show the comparison of wet and dry CMRR using exploratory borehole

core and underground information. Figure 7 shows twelve predetermined testing

locations (i.e., U-1 to U-12) which are in the vicinity of selected boreholes belonging to

Groups A, B, C, and D. Based on this figure, there is a reasonable agreement between

underground and borehole core wet CMRR values. Locations labeled as UR-1 to UR-4,

had previous massive roof falls. Roof falls were 25 to 30 feet in length and 18 feet in

width. Observed roof fall height was estimated at 10 to 12 feet. During the mine visit to

these roof fall locations, it was noticed that at UR-1, UR-2, and UR-4 locations, a very

thin, yellowish, dark gray shale with very weak and severely moisture sensitive

characteristics was in the immediate three feet of the roof. Wet underground CMRR for

these locations were less than 35, a low value. Mining in areas of low CMRR requires

more caution and supplemental support. Although all of these locations had screen

protection and were supported with 10-12-ft long cable bolts at intersections, roof falls

still occurred. Since UR-1, UR-2, and UR-4 locations are about 2150 feet from the

closest borehole and the geology variability was significant, it is not unreasonable to

observe differences between CMRR contours and CMRR indices obtained from

underground information.

Figure 8 shows that for all sixteen testing locations (i.e., U-1 to U-12 and UR-1 to UR-4),

there is also an acceptable compatibility between the dry CMRR estimated from

underground samples and borehole core information. It seems that the presence of the

“yellowish dark gray shale” unit in the immediate roof affects stability mostly in long-

term applications, when wet CMRR is the driving factor for determining roof stability.

Overall, based on this comparison, the underground CMRR determination appears to be a

reasonable and inexpensive method to characterize roof rock mass conditions.

Roof Support Design

In this phase, borehole Groups A, B, and C and underground locations including U-1 to

U-12 and UR-1 to UR-4 are considered. Figure 9 shows the plot of wet CMRR versus

depth of cover for the case that 6-ft bolt length is used. Two trend lines are shown in this

plot. The dashed line applies the Molinda and Mark (2001) (i.e., Equation 2) correlation

to this study. The CMRR for roof fall locations during the mine visit is also shown in this

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figure with the circle symbols. The solid line in this figure shows the representative line

for success and failure cases that were analyzed in this study.

The trend line in the Molinda and Mark (2001) study discriminates between success and

failure cases, whereas the trend line in this study shows merely an estimation of the

discriminant line because of limited roof fall data points from the cooperating mine. The

difference between the two trend lines shows the diversity between the Illinois Basin and

other coal fields represented by Molinda and Mark. Figure 9 also shows that 90% of the

mine area has a wet CMRR index of more than 35. Three additional data points related to

borehole core cases (showing with diamond symbols) have CMRR less than the trend

line in this study; therefore, they are prone to failure. These diamond symbol data points

are plotted using borehole core information from areas that have not been mined yet.

Figure 10 shows the actual intersection spans of the studied mine versus wet CMRR.

This figure shows that the cases in this study have relatively small intersection spans;

therefore, no roof fall is expected. However, due to moisture-sensitive units and weak

roofs and despite intensive roof support utilization, roof falls have already been observed.

Figure 11 shows correlations between wet CMRR and ARBS (see Equation 6) indices.

Five typical 6-ft tensioned rebar, SRD Grade 75 bolts per row with 4-ft spacing were

utilized in the mains of the mine. Also, five typical 6-ft headed rebar, fully grouted,

Grade 60 bolts per row were utilized in panels. Entry width at the mine was designed to

be 18-19 feet. Molinda and Mark (2001) suggested that areas which have ARBS values

of more than suggested ARBSH (see Equation 8) have less frequency of roof falls.

(8)

where H (in feet) is overburden thickness. Equation 8 was used to define the suggested

discriminant dashed line for the Illinois Basin case study.

Figure 11 shows all boreholes including A-8, A-12, and B-3 (see diamond symbols),

which are below the trend line. There are also four observed roof fall spots (UR-1, UR-2,

UR-3, and UR-4) below the suggested line which show the compatibility of the

suggested trend line and observed roof fall locations. It is anticipated that A-8, A-12, and

B-3 locations, which are not mined yet, are prone to roof falls and will need supplemental

supports. It is worth mentioning that these areas generally have a wet CMRR index of

less than 35.

Applying Analysis of Roof Bolt Stability (ARBS)

In this study, the reliability of ARBS was investigated for the studied mine based on

information from borehole Groups A, B, and C as follows:

1. Assessing the Geology and Stress Level: The distribution of depth of cover

throughout the mine area was determined.

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2. Determining the Design Support Reinforcement Mechanism: Analyses

showed that most of the mining area needs some form of substantial support

mechanism (i.e., beam building).

3. Determining the Recommended Bolt Length: Figure 12 shows suggested bolt

lengths in the vicinity of boreholes. This figure suggests that using 3-ft bolts

should meet the requirement of suggested bolt length throughout most of the

mine.

4. Determining Required Roof Bolt Intensity: Figure 13 shows suggested ARBS

values for the mine site, which indicates the suggested ARBS varies from 3.0 to

10.7. It is interesting to note that the suggested ARBS of 10.7 belongs to borehole

A-4, which is in the vicinity of UR-1 and UR-2 roof fall locations (see Figure 7).

5. Deciding on the Roof Bolt Pattern: Based on the mining company’s previous

practice, two roof bolt patterns of four and five bolts per row and tensioned rebar,

SRD grade 75 bolts were considered. Figure 14 shows the required row spacing

for these two patterns of bolt spacing. Bolt spacing which has been used in the

mined areas varies from 3.6 to 4.6 feet.

It seems that exercising the suggested ARBS method would result in various roof falls in

the mine due to following reasons, which could not be verified in this study:

1. The current utilized roof support is more intensive than the suggested plan based

on the ARBS method. The suggested roof support system requires shorter bolts.

The mining company is using screen protection for all areas of the mine to avoid

moisture exposure to upper roof layers. Furthermore, they have utilized cable

bolts at almost all intersections.

2. Considering the current practice for roof control plans and designs, the roof in

mines with 3- to 4-ft bolts is rarely stable in the Illinois Basin.

Sensitivity Analysis on CMRR Parameters

A sensitivity analysis on the CMRR calculation procedure was conducted to discover the

most influential parameters in this process with respect to the cooperating mine. To

generate CMRR indices for different boreholes, UCS, PLD, and RQD test results are

used (see Equation 1) and variation in each test parameter could influence the final

CMRR value. Moisture sensitivity effect is taken into account for long-term applications

by identifying wet CMRR. Since, the collected boring log information did not include

RQD values, RQD of 80 was used for shale, sandy shale, and black shale; and RQD of

90 was used for limestone. Therefore, in order to complete a meaningful investigation,

the effect of UCS and PLD are specifically explored.

The bolted interval of borehole Groups A, B, and C were divided into four general rock

layers. Table 6 shows statistical values for each rock type used in this sensitivity analysis.

13

The sensitivity analysis was conducted by following a three-step procedure. In the first

step, UCS, PLD, and RQD test values were varied as described in Table 7 and changes in

UCS, PLD, and RQD ratings were observed. In the second step, changes in unit rating

were calculated using Equation 1. Finally, the change in CMRR was extracted.

UCS and PLD test results for each rock unit were changed within their standard

deviations for that layer (see Table 7). To find out the most influential parameter in

CMRR determination procedure, two cases were considered. First, only the UCS test

value is changed while PLD and RQD are constant. Second, only PLD and RQD are

changed while UCS is constant. Unit ratings and then the dry CMRR index was

determined for each borehole. Figures 15 and 16 show CMRR changes for both cases.

Groups B and C boreholes show significantly less volatility in CMRR than Group A

boreholes when UCS is constant and PLD and RQD are changing (see Figure 15). This

result is justified by the three following remarks:

1. Figure 17 shows the roof layer plot for Groups A, B, and C boreholes. It was

observed that Groups B and C bolted intervals are mostly composed of shale and

limestone layers while the Group A bolted interval includes a variety of rock

layers other than shale and limestone, which typically have higher PLD values

than sandy shale or black shale layers.

2. A majority of the layers in Groups B and C boreholes did not have any rock

mechanics testing data for PLD; therefore, average rock mechanic properties were

assigned to these holes based on their lithological description. Table 6 shows that

the average of PLD values for shale and limestone are 102.1 and 456.2 psi (Is(50)),

respectively. PLD values for layers in Group A are significantly less than 100 psi

as the majority are black shale layers. It can be concluded that for weak bedding

layers such as black shale, the CMRR volatility is more pronounced.

3. In order to completely ignore the effect of RQD effects on discontinuity rating

and to compare the effect of UCS and PLD values on CMRR, large RQD ratings

were assumed so the discontinuity rating is governed only by PLD. Figure 18

shows the CMRR changing when UCS is constant and PLD is changing.

Comparing this to Figure 15, PLD exhibits a significantly larger effect than UCS

on CMRR determination for a majority of the boreholes evaluated in this study.

The other important observation was related to dispersion of PLD and UCS test results.

Figure 19 shows normalized distribution diagrams of test results for each rock unit. It is

demonstrated that for each rock type, the standard deviation of PLD values is more than

the standard deviation for UCS values. It is concluded that PLD test results are generally

more dispersed than UCS results for the studied data.

14

CONCLUSIONS AND RECOMMENDATIONS

This investigation was conducted on a room-and-pillar underground coal mine in Illinois.

The roof competency evaluation and rock mass characterization was conducted by using

Coal Mine Roof Rating. The analysis of lab test results show that there is correlation

between conventional tests, such as UCS and ITS, and simpler point load tests, such as

PLA and PLD, for each rock type. Enriching the data sets by including rock mechanics

lab test results from different coal mines will enhance the proposed correlations. Further

research on the mechanism of failure of rock units in point load tests for layered rocks

with weak bedding interfaces, such as black shale, is recommended.

It was observed in this research that CMRR can be a simple and reliable method for

designing roof control plans; however, some adjustments are needed for weak roof units

as they were not fully represented in the original development of the CMRR index. The

borehole core and underground CMRR indices match reasonably well in this study.

Given the simplicity of this approach, it can be a very useful method to evaluate roof

conditions in mined out areas and predict the rate of deterioration with time. This is

critically important for mining companies who deal with weak and moisture-sensitive

roof rocks and have to plan in advance for roof falls that might occur in the long term. It

was concluded that CMRR is very sensitive to PLD values of less than 100 psi, which is

very common in Illinois coal fields. These low PLD values will make the CMRR highly

volatile and predicting the roof performance becomes challenging. It is recommended to

find a more reliable test or modify the existing PLD method for discontinuity rating in

order to reduce dispersion.

This study demonstrated that in terms of designing intersection spans and roof bolt

intensity, the ARBS method will overestimate the capacity of the roof. Collection of case

study data from various mines in the Illinois Basin would help in appropriately

modifying this approach for weak roof conditions.

15

TABLES

Table 1: Geomechanical properties of roof rock units.

Test Type Number of Tests

Min Max Ave StDev

Shale (SH)

Moisture content (%) 368 0.4 17.6 5.7 3.4

UCS (psi) 352 35 25617 4229.7 4178.3

ITS (psi) 424 4 2366 403.1 343.4

PLA (psi) 301 4 1452 225.3 230.5

PLD (psi) 82 2 564 107 149.3

Slake Durability (%) 181 0 99.6 58.3 32.9

Sandy Shale (SSH)

Moisture content (%) 38 0.4 8.3 3.1 2

UCS (psi) 37 194 24309 3628.3 4825.9

ITS (psi) 40 102 1851 513.6 426.9

PLA (psi) 56 21 971.4 318.7 230.1

PLD (psi) 44 3 549.2 113.2 137.2

Slake Durability (%) 45 3 99.6 68.8 31.9

Shale-Limestone (SH-LS)


UCS (psi) 25 654 22725 8642.3 6796.1

ITS (psi) 24 86 1518 479.6 394.7

PLA (psi) 24 53 1452 412.8 333

PLD (psi) 10 82.4 855.7 375.5 248

Slake Durability (%) 11 10.8 96.6 60.8 27.9

Black Shale (BSH)


UCS (psi) 8 766 3019 1577.3 864

ITS (psi) 28 64 783.3 364.5 195

PLA (psi) 38 14.4 884.5 221.1 173.8

PLD (psi) 25 3.3 146.1 30.8 30.9


Limestone (LS)

Moisture content (%) 255 0.04 15.9 3 2.8

UCS (psi) 334 62 54255 15438.7 9667.5

ITS (psi) 299 9 2896 1015.9 632.1

PLA (psi) 193 0 2432 725.4 417.4

PLD (psi) 31 2 1511 462 362.8


16

Table 2: UCS and PLA test results on roof rock cores.

Data Pairs

(#)

Min. UCS

Max. UCS

Mean UCS

StDev UCS

Min. PLA

Max. PLA

Mean PLA

StDev PLA

(psi) (psi) (psi) (psi) (psi) (psi) (psi) (psi)

Shale 28 198 25,617 3,508 5,203 25 561 184 158

Black Shale 7 766 3,019 1,627 921 38 204 113 58

Sandy Shale

31 194 24,309 3,939 5,163 21 676 240 191

Shale-Limestone

6 8,434 22,665 16,115 5,998 395 815 639 155

Limestone 38 71 38,453 12,983 8,197 14 1,340 587 247

Clay Stone 19 339 9,384 2,861 2,838 17 740 218 241

Table 3: ITS and PLD test results on roof rock cores.

Data Pairs

(#)

Min. ITS

Max. ITS

Mean ITS

StDev ITS

Min. PLD

Max. PLD

Mean PLD

StDev PLD

(psi) (psi) (psi) (psi) (psi) (psi) (psi) (psi)

Shale 28 55 1,331 485 378 2 520 60 107

Black Shale

22 64 724 353 183 3 71 27 20

Sandy Shale

37 102 1,851 521 439 3 549 112 146

Shale-Limestone

5 300 1,518 1,023 456 253 856 525 219

Limestone 29 9 2,792 1,324 636 2 1,511 468 371

Clay Stone 9 27 1,773 493 598 5 432 99 156

Table 4: Conversion factors between UCS vs. PLA and ITS vs. PLD.

PLA to UCS PLD to ITS

Rock Type Data Pairs

(#)

Conversion Factor

Data Pairs

(#) a b

Shale 28 21.1 28 134.26 0.30

Black Shale 7 14 22 111.38 0.33

Sandy Shale 31 14.2 37 86.63 0.40

Clay Stone 19 11.3 9 64.07 0.38

Limestone 38 20.2 29 44.78 0.56

Shale-Limestone

6 25 - - -

All Shales 72 21.4 92 109.85 0.34

17

Table 5: Underground CMRR at sixteen locations in mined areas.

Testing

Location CMRR

Number of

Exposed Layers

Total Thickness of Layers

(ft)

Underground Borehole Core

CMRR -UG-I

CMRR-UG-II

Calculated CMRR

based on Figure 3

Calculated CMRR

based on Figure 4

U-1 Dry

3 5.37 57 47 49 < < 53 51 < < 56

Wet 56 45 49 < < 54 47 < < 52

U-2 Dry

1 3.3 47 47 45 < < 49 46 < < 51

Wet 32 32 29 < < 34 << 37

U-3 Dry

1 2.3 59 59 45 < < 49 41 < < 46

Wet 44 44 44 < < 49 42 < < 47

U-4 Dry

1 3 45 45 45 < < 49 41 < < 46

Wet 30 30 39 < < 44 37 < < 42

U-5 Dry

1 0.5 46 46 45 < < 49 46 < < 51

Wet 43 43 44 < < 49 42 < < 47

U-6 Dry

1 1.9 57 57 45 < < 49 41 < < 46

Wet 50 50 34 < < 39 << 37

U-7 Dry

1 1.4 46 46 41 < < 45 41 < < 46

Wet 39 39 34 < < 39 37 < < 42

U-8 Dry

1 1.5 46 46 45 < < 49 41 < < 46

Wet 31 31 39 < < 44 37 < < 42

U-9 Dry

3 1.25 +

Massive Gray Shale

53 49 41 < < 45 41 < < 46

Wet 51 46 39 < < 44 37 < < 42

U-10 Dry

2 2.5 +

Massive Gray Shale

56 51 45 < < 49 41 < < 46

Wet 49 44 39 < < 44 37 < < 42

U-11 Dry

1 1.75 36 36 41 < < 45 41 < < 46

Wet 29 29 39 < < 44 37 < < 42

U-12 Dry

1 2 48 48 45 < < 49 36 < < 41

Wet 45 45 44 < < 49 27 < <32

UR-1 Dry

1 3 41 41 41 < < 45 41 < < 46

Wet 26 26 39 < < 44 37 < < 42

UR-2 Dry

2 1.75 39 40 41 < < 45 41 < < 46

Wet 36 35 39 < < 44 37 < < 42

UR-3 Dry

3 2.85 36 34 45 < < 49 41 < < 46

Wet 35 33 39 < < 44 37 < < 42

UR-4 Dry

2 1 + Massive Gray Shale

39 39 45 < < 49 41 < < 46

Wet 29 29 39 < < 44 37 < < 42

18

Table 6: UCS, PLD, and RQD statistics for four rock layers used in sensitivity analysis.

Layer Description Parameter Max. Min. Ave. StDev

SH

UCS (psi) 25617 35 4230 4178

PLD (psi) 564 2 102 150

RQD (%) 80 80 80 0

SSH

UCS (psi) 24309 194 3628 4825

PLD (psi) 447 3 97 122

RQD (%) 80 80 80 0

BSH

UCS (psi) 3019 766 1577 864

PLD (psi) 68 5 22.6 22

RQD (%) 80 80 80 0

LS

UCS (psi) 54255 62 15439 9668

PLD (psi) 1511 2 456 375

RQD (%) 90 90 90 0

Table 7: PLD, UCS, and RQD variations considered in the sensitivity analysis.

PLD Categories

UCS Categories

RQD Categories

19

FIGURES

Figure 1: UCS and PLA values for roof rock cores.

Figure 2: ITS and PLD values for roof rock cores.

0

5000

10000

15000

20000

25000

30000

0 200 400 600 800 1000 1200 1400 1600

UC

S (

psi

)

Axial Point Load Test (psi)

Shale

Black Shale

Sandy Shale

Shale Limestone

Claystone

Limestone

0

500

1000

1500

2000

0 100 200 300 400 500 600 700 800 900

Ind

irec

t T

ensi

le (

psi

)

Diametral Point Load Test (psi)

Shale

Black Shale

Sandy Shale

Shale Limestone

Clay Stone

Limestone

20

Figure 3: Relationship between UCS and PLA for roof rock cores.

Figure 4: Relationship between ITS and PLD for roof rock cores.

0

5000

10000

15000

20000

25000

30000

0 100 200 300 400 500 600 700 800 900

UC

S (

psi

)

Axial Point Load Test (psi)

Shale

Black Shale

Sandy Shale

Shale Limestone

Claystone

Limestone

All Shales

0

500

1000

1500

2000

0 100 200 300 400 500 600 700 800 900

Ind

irec

t T

ensi

le (

psi

)

Diametral Point Load Test (psi)

Shale

Black Shale

Sandy Shale

Clay Stone

Limestone

All Shale

21

Wet CMRR Dry CMRR

Figure 5: CMRR contours for 6-ft bolt length and exploratory borehole core data.

Wet CMRR Dry CMRR

Figure 6: CMRR contours for 3-ft bolt length and exploratory borehole core data.

D-1

D-3

A-2

A-3

A-4

A-6

A-10

A-11

A-12

A-13

52

32

37

42

45

39

3853

B-1B-2

B-3

B-4

B-7

B-8

B-9

B-11

43

46

32

52C-1

C-254

C-357

45

52

50

Legend:

A-12

32BoreholeCMRR

53

14

49

4548

46

55

46

45

41

56

5034

46

40

4242

42

45

37

45

0 mile 1 mile 2 mile

D-1

D-3

53

30

51

4949

47

56

47

46

44

56

5145

46

43

4446

45

45

42

47


A-2

A-3

A-4

A-6

A-9

A-10

A-11

A-12

A-13

52

39

43

40

43

47

42

395357

B-1B-2

B-3

B-4B-8

B-9

B-11

47

47

52C-1

C-254

C-357

46

53

Legend:

A-12

32BoreholeCMRR

20

4038

24

54

44

44

18

55

4728

45

17

2029

23

29

25

29

A-10

A-11

A-12

A-13

27

32

41

37

39

46

37

241255

B-1B-2

B-3

B-4

B-7

B-8

B-9

B-11

42

32

52C-1

C-254

C-357

47

34


A-2

A-3

A-4

A-6

A-9

Legend:

A-12

32BoreholeCMRR

D-1

D-3

53

14D-1

D-3

53

29

32

4444

35

55

46

45

32

55

4943

46

32

3343

32

36

36

36


A-2

A-3

A-4

A-6

A-9

A-10

A-11

A-12

A-13

27

39

40

42

49

43

352756

B-1B-2

B-3

B-4

B-7

B-8

B-9

B-11

45

47

54C-1

C-255

C-357

49

46

43

Legend:

A-12

32BoreholeCMRR

22

Figure 7: Comparison of wet CMRR using borehole core and underground data.

Figure 8: Comparison of dry CMRR using borehole core and underground data.

A-2

37

42

45B-3

46

32

C-2

54

C-3

57

45

46

45

42

45

U-12

U-11

29

51

U-9

U-8

31

U-5

43

U-7

39

UR-3

35

U-10UR-4

49 29

U-6

50

49

44 49

39

Borehole

Wet CMRR Legend 42

UR-236

U-2

32

44

U-3

U-4

30

UR-126

U-1

56

0 mile 1 mile0.5 mile

UR: Roof fall underground

information

U: Underground information

A-2

A-4

40

43

47

B-3

47

47

C-2

54

C-3

57

49

47

46

44

46

48

36

53

46

46

46 36 56 39

57

Borehole

Dry CMRR Legend 43

U-12

U-11

U-9

U-8

U-5

U-7UR-3U-10UR-4

U-6

UR-2

U-2

U-3

U-4

UR-1

U-1

57

41

39

59

47

45

0 mile 1 mile0.5 mile

UR: Roof fall underground

information

U: Underground information

23

Figure 9: Wet CMRR vs. depth of cover when 6-ft bolt length is used.

Figure 10: Wet CMRR vs. intersection span when 6-ft bolt length is used.

20

30

40

50

60

70

80

100 150 200 250 300 350 400

CM

RR

Depth of cover, H, (ft.)

Mark et al. (2001) failure cases

Mark et al. (2001) success cases

Mark et al. (2001) intermediate cases

Illinois mine cases - drill core information

Illinois mine cases - underground information

Illinois mine roof fall cases - underground information

Mark et al. (2001) correlation

Illinois mine correlation

20

30

40

50

60

70

80

22 24 26 28 30 32 34 36 38 40

CM

RR

Intersection span, Is, (ft.)



Illinois mine cases - drill core and underground information



24

Figure 11: Wet CMRR vs. ARBS values when 6-ft bolt length is used.

Figure 12: Recommended bolt length contours using borehole core data.

25.0

35.0

45.0

55.0

65.0

75.0

2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0

CM

RR

ARBS



Illinois mine cases - drill core and underground information

Illinois mine probable roof fall cases - drill core information




4440

36

44

48

40

44

48

44

44

40

36

36

48

A-2

A-3

A-4

A-6

A-9

A-10

A-11

A-12

A-13

2

3

2

2.5

2.5

2.5

2.5

2.52

B-1B-2

B-3

B-4

B-7

B-8

B-9

B-11

2.5

2.5

3

2C-1

C-2

2

C-32

2.5

2

2

Legend:

A-12

3

Borehole

Suggested Bolt

Length (ft)

Wet CMRR contours

25

Figure 13: Suggested ARBS contours using borehole core data.

Figure 14: Suggested bolt pattern distribution throughout the mine area.

4440

36

44

48

40

44

48

44

44

40

36

36

48

A-2

A-3

A-4

A-6

A-9

A-10

A-11

A-12

A-13

B-1B-2

B-3

B-4

B-7

B-8

B-9

B-11

C-1

C-2 C-3

Legend:

A-12 Borehole

7.2 ARBS

7.2

7.7

3.3

8.8

3.0 5.59.3

8.0

9.2

9.6

10.7

6.9

6.47.9 5.5

8.5

3.03.0

7.0

4.28.4

8.1

7.2

3.07.3

3.3

4.4

8.7

Wet CMRR contours


4440

36

44

48

40

44

48

44

44

40

36

Legend:

A-12

A-2

A-3

A-4

A-6

A-9

A-10

A-11

A-12

A-13

B-1B-2

B-3

B-4

B-7

B-8

B-9

B-11

C-1

C-2 C-3

2.1 Spacing

(with 5 bolts

per row)

in feet

1.5

1.2

1.6

1.4

1.5

3.72.3

2.1

2.2

1.81.6 1.5

1.8

21.6

1.3

1.51.8

1.4

3.4

1.5

3.4

3.1

3.4

3.4 1.9

3.1

1.7

Spacing

(with 4 bolts

per row)

in feet

1.7

1.7

1.3

2.5

1.2

2.7

1.2

1.42.5

2.7 2.7

1.5

1

1.51.3 1.2

1.2

1.2

2.9

1.8

1.6

1.8

2.7

1.1

1.1

1.3

1.4

1.3

1.1

Wet CMRR contours

Borehole


26

Figure 15: CMRR change when UCS value is constant while PLD and RQD change.

Figure 16: CMRR change when PLD and RQD values are constant and UCS is changed.

-40

-20

0

20

40

60

80

A-1

A-2

A-3

A-4

A-5

A-6

A-7

A-8

A-9

A-1

0

A-1

1

A-1

2

A-1

3

B-1

B-2

B-3

B-4

B-5

B-6

B-7

B-8

B-9

B-1

0

B-1

1

C-1

C-2

C-3

C-4

CM

RR

ch

an

ge

(%)

Borehole ID

UCS constant, PLD & RQD decreasing (See Table 7)

UCS constant, PLD & RQD increasing (See Table 7)

-40

-20

0

20

40

60

80

A-1

A-2

A-3

A-4

A-5

A-6

A-7

A-8

A-9

A-1

0

A-1

1

A-1

2

A-1

3

B-1

B-2

B-3

B-4

B-5

B-6

B-7

B-8

B-9

B-1

0

B-1

1

C-1

C-2

C-3

C-4

CM

RR

ch

an

ge

(%)

Borehole ID

PLD & RQD constant, UCS decreasing within STD (See Table 7)

PLD & RQD constant, UCS increasing within STD (See Table 7)

27

Figure 17: Roof layer plot for borehole Groups A, B, and C.

Figure 18: CMRR change when UCS and RQD values are constant and PLD is changed.

B-2 B-3 B-4 B-5 B-6 B-7 B-8 B-9 B-10 B-11

C-1 C-2 C-3 C-4

Legends

Black Shale

Limestone

Sandy Shale

Shale

Scale: 0 ft

6 ft

12 ft

"Group A" Boreholes:

"Group B" Boreholes:

"Group C" Boreholes:

A-1 A-2 A-3 A-4 A-5 A-6 A-7 A-8 A-9 A-10 A-11 A-12 A-13

B-1

-40

-20

0

20

40

60

80

A-1

A-2

A-3

A-4

A-5

A-6

A-7

A-8

A-9

A-1

0

A-1

1

A-1

2

A-1

3

B-1

B-2

B-3

B-4

B-5

B-6

B-7

B-8

B-9

B-1

0

B-1

1

C-1

C-2

C-3

C-4

CM

RR

ch

an

ge

(%)

Borehole ID

UCS constant, PLD decreasing within STD (See Table 7)

UCS constant, PLD increasing whithin STD (See Table 7)

28

STD: Normal Standard Deviation

Figure 19: Normal distribution of data for different groups of rock layers.

29

REFERENCES

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D1558-10: “Standard Test Method for Moisture Content Penetration Resistance

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Tensile Strength of Intact Rock Core Specimens;” D5731-08: “Standard Test Method

for Determination of the Point Load Strength Index of Rock and Application to Rock

Strength Classifications.”

ASTM (2014) Annual Book of ASTM Standards, Vol. 04.09, Accessed at: www.astm.org.

D7012-13: “Standard Test Method for Compressive Strength and Elastic Moduli of

Intact Rock Core Specimens under Varying States of Stress and Temperatures.”

Bieniawski, Z.T. and Bernede, M.J. (1979) “Suggested Methods for Determining the

Uniaxial Compressive Strength and Deformability of Rock Materials: Part 1.

Suggested Method for Determining Deformability of Rock Materials in Uniaxial

Compression.” International Journal of Rock Mechanics and Mining Science &

Geomechanics, 16: 138-140.

Cargill, J.S. and Shakoor, A. (1990) “Evaluation of Empirical Methods for Measuring the

Uniaxial Compressive Strength of Rock.” International Journal of Rock Mechanics

and Mining Sciences & Geomechanics, 27: 495-503.

Hill, D. (2007) “Practical Experiences with Application of the Coal Mine Roof Rating

(CMRR) in Australian Coal Mines.” Proceedings of the International Workshop on

Rock Mass Classification in Underground Mining, Ed. by C. Mark et al., pp. 65-72.

Kahraman, S. (2001) “Evaluation of Simple Methods for Assessing the Uniaxial

Compressive Strength of Rock.” International Journal of Rock Mechanics & Mining

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Mark, C. and Molinda, G.M. (2003) “The Coal Mine Roof Rating in Mining Engineering

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DISCLAIMER STATEMENT

This report was prepared by Dr. Abdolreza Osouli of Southern Illinois University

Edwardsville with support, in part, by grants made possible by the Illinois Department

of Commerce and Economic Opportunity through the Office of Coal Development and

the Illinois Clean Coal Institute. Neither Dr. Abdolreza Osouli, Southern Illinois

University Edwardsville, nor any of its subcontractors, nor the Illinois Department

of Commerce and Economic Opportunity, Office of Coal Development, the Illinois

Clean Coal Institute, nor any person acting on behalf of either:

(A) Makes any warranty of representation, express or implied, with respect to the

accuracy, completeness, or usefulness of the information contained in this report, or that

the use of any information, apparatus, method, or process disclosed in this report may

not infringe privately-owned rights; or

(B) Assumes any liabilities with respect to the use of, or for damages resulting

from the use of, any information, apparatus, method or process disclosed in this report.

Reference herein to any specific commercial product, process, or service by trade name,

trademark, manufacturer, or otherwise, does not necessarily constitute or imply its

endorsement, recommendation, or favoring; nor do the views and opinions of authors

expressed herein necessarily state or reflect those of the Illinois Department of

Commerce and Economic Opportunity, Office of Coal Development, or the Illinois Clean

Coal Institute.

Notice to Journalists and Publishers: If you borrow information from any part of this

report, you must include a statement about the state of Illinois’ support of the project.

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