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DEVELOPMENT AND APPLICATION OF THE COAL MINE ROOF RATING (CMRR) 

By Christopher Mark, Ph.D., P.E.,1

 and Gregory M. Molinda2 

1

Principal research mining engineer. 

2

Research geologist.

 Pittsburgh Research Laboratory, National Institute for Occupational Safety and Health, Pittsburgh, PA. 

ABSTRACT 

The Coal Mine Roof Rating (CMRR) was developed 

10 years ago to fill the gap between geologic characterization and engineering design. It combines many years of 

geologic studies in underground coal mines with worldwide experience with rock mass classification systems. 

Like other classification systems, the CMRR begins with 

the premise that the structural competence of mine roof 

rock is determined mainly by the discontinuities that 

weaken the rock fabric. However, the CMRR is specifically designed for bedded coal measure rock. Since its 

introduction, the CMRR has been incorporated into many 

aspects of mine planning, including longwall pillar design, 

roof support selection, feasibility studies, extended-cut 

evaluation, and others. It has also become truly international, with involvement in mine designs and funded 

research projects in South Africa, Canada, and Australia. 

This paper discusses the sources used in developing the 

CMRR, describes the CMRR data collection and calculation procedures, and briefly presents a number of practical 

mining applications in which the CMRR has played a 

prominent role. 

INTRODUCTION 

Roof falls continue to be one of the greatest hazards 

faced by underground coal miners. In 2006, there were 

7 fatalities from roof falls and nearly 500 rock fall injuries 

in the United States. In addition, more than 1,300 major 

roof collapses were reported to the Mine Safety and Health 

Administration. These roof falls can threaten miners, damage equipment, disrupt ventilation, and block critical emergency escape routes. 

One reason roof falls have proven so difficult to 

eradicate is that mines are not built of manmade materials 

like steel or concrete, but rather of rock, just as nature 

made it. The structural integrity of a coal mine roof is 

greatly affected by natural weaknesses, including bedding 

planes, fractures, and small faults. The engineering properties of rock cannot be specified in advance with adequate 

precision and can vary widely from mine to mine and even 

within individual mines. 

Engineers require quantitative data on the strength of 

rock masses for design. Traditional geologic reports 

contain valuable descriptive information, but few engineering properties. Laboratory tests, on the other hand, are 

inadequate because the strength of a small specimen is 

only indirectly related to the strength of the rock mass. 

ROCK MASS CLASSIFICATION 

Rock mass classification schemes were developed 

to address these concerns. The most widely known systems, including Deere’s Rock Quality Designation (RQD), 

Bieniawski’s Rock Mass Rating (RMR), and Barton’s 

Q-system, have been used extensively throughout the 

world [Deere and Miller 1966; Bieniawski 1973; Barton 

et al. 1974]. Rock mass classifications have been successful [Bieniawski 1988] because they— 

•	 Provide a methodology for characterizing rock mass 

strength using simple measurements; 

•	 Allow geologic information to be converted into 

quantitative engineering data; 

•	 Enable better communication between geologists and 

engineers; and 

•	 Make it possible to compare ground control experiences between sites, even when the geologic conditions are very different. 

This last point highlights an extremely powerful application of rock mass classification systems, which is their 

use in empirical design methods. Empirical designs are 

based on mine experience—on the real-world successes 

and failures of actual ground control designs. By collecting 

a large number of case histories into a single database and 

subjecting them to statistical analysis, reliable and robust 

guidelines for design can be developed. A key advantage 

of empirical techniques is that it is not necessary to obtain 

a complete understanding of the mechanics to arrive at a 

reasonable solution. Rock mass classifications play an 

essential role in empirical design because they allow the 

overwhelming variety of geologic variables to be reduced 

to a single, meaningful, and repeatable parameter. 

Unfortunately, the standard rock mass classification 

systems are not readily applicable to coal mining because— 

•	 They tend to focus on the properties of joints, 

whereas bedding is generally the most significant 

discontinuity affecting coal mine roof. 
 

 

 

 

 

 

 

 

 

 

 

•	 They rate just one rock unit at a time, whereas coal 

mine roof often consists of several layers bound 

together by roof bolts. 

In addition, the dimensions and stability requirements of 

tunnels are often very different from those of mines. 

COAL MINE GROUND CONTROL 

The Coal Mine Roof Rating (CMRR) was developed 

more than 10 years ago to meet the needs of mine planners 

for a simple, repeatable, and meaningful classification 

system [Molinda and Mark 1994]. It employs the familiar 

format of Bieniawski’s RMR, summing the individual 

ratings to obtain a final CMRR on a 0–100 scale. It is also 

designed so that the CMRR/unsupported span/standup 

time relationship is roughly comparable to the one determined for the RMR. 

In determining the specific rock mass attributes and 

weightings to use, the CMRR built upon the rich vein of 

experience with coal mine ground control during the past 

30 years. These sources can be divided into two groups. 

The first are papers describing specific geologic features, 

such as faults, clay veins, sandstone channels, kettlebottoms, and others. A summary of this work was reported 

by Molinda [2003]. The second group, which includes 

efforts to generalize results for specific mines, regions, or 

countries, was more directly relevant to the development 

of the CMRR. In effect, these papers describe rock mass 

classification systems, although most are qualitative rather 

than quantitative. Table 1 provides a list of the coal mine 

roof classification systems consulted in the development of 

the CMRR, along with the significant geologic factors that 

they identified as being important to ground control. 

Following is a discussion of some of these factors and the 

issues involved with incorporating them into the CMRR.

 Bedding: Bedding was the factor that was most 

consistently cited as causing roof problems in coal mines. 

The two most common examples were weak laminations 

in shale and thinly interbedded sandstone and shale 

(stackrock). In both examples, it is not just that the bedding planes are closely spaced, but also that the bedding 

surfaces are very weak. Indeed, several authors included 

“massive shale” as one of the more stable rock types 

[Moebs and Ferm 1982]. 

The issue of bedding (or grain alignment) is further 

complicated because some shales may appear massive, 

particularly to untrained eyes, but are actually highly 

laminated. The CMRR therefore emphasizes testing of the 

rock material to determine bedding plane strength even 

when the bedding is not visible. The approach is similar to 

that proposed by Buddery and Oldroyd [1992] and used 

successfully in South African coal mines. 

Strong Bed: A problem unique to horizontally layered sedimentary rocks is that the roof structure often 

consists of several layers with different engineering 

characteristics. In developing the CMRR, two key questions had to be answered: 

1.	 How far up into the roof should the evaluation 

extend? 

2.	 How should the different layers be combined into a 

single rating? Should they be averaged together, or 

should the weakest or strongest layers be given 

precedence? 

Few answers were available in the literature. Buddery 

and Oldroyd [1992] evaluated the first 2 m of roof, but 

weighted the layers nearest the roof line more heavily. 

Several authors seemed to imply that a weak layer can be 

very important by their emphasis on rider coal seams 

[Karmis and Kane 1984; Stingelin et al. 1979; Miller 1984]. 

The CMRR started with the insight that the roof bolt 

length largely determines the thickness of the mine roof 

structure. All coal mine roof in the United States must be 

bolted, and the bolts bind the different layers together. 

Generally, the layers above the bolts have much less influence than the units that are penetrated by the roof bolts. 

Moreover, experience in many U.S. coalfields has 

clearly established that roof stability is greatly enhanced 

when the roof bolts anchor in a strong layer. This effect is 

most evident in the Illinois Basin, where roof falls are 

almost unknown when the bolts anchor in a limestone that 

is at least 0.6 m thick [Kester and Chugh 1980; Schaffer 

1985; Damberger et al. 1980]. The strong bed effect has 

also been recognized in Alabama [Martin et al. 1988] and 

central Appalachia [Hylbert 1978]. Indeed, even the Code 

of Federal Regulations implies a strong bed effect when it 

states at 30 CFR 75.204(f)(1) that “roof bolts that provide 

support by suspending the roof from overlying stronger 

strata shall be long enough to anchor at least 12 inches into 

the stronger strata.” 

Moisture Sensitivity: Moisture sensitivity is another 

factor that has been ignored by traditional rock mass 

classification systems, but is extremely important to coal 

mine ground control. Two roof shales may initially have 

very similar properties, but one may be essentially impervious to moisture while the other completely disintegrates 

when exposed to groundwater or even humid mine air 

(Figure 1). 

The presence of moisture-sensitive mudrocks may be 

just a nuisance, or it can severely damage the roof by 

reducing rock strength, generating swelling pressures, or 

compromising support effectiveness by causing sloughing 

around roof bolt plates. While the Slake Durability Test 

(SDT) has been widely used to evaluate moisture sensitivity [Hoek 1977], the CMRR employs a modified version 

of the simpler immersion test described by Sickler [1986]. 
Rock Strong Moisture Sandstone Minor No. of Ground- Lineaments/ Rider Author Location Bedding Slickensides Joints strength bed sensitivity channels structures beds water faults coals 

Buddery and Oldroyd [1992]; South Africa x x Lattila et al. [2002] ........................ 

Damberger et al. [1980]................... Illinois Basin x x x

Ealy et al. [1979].............................. S. West Virginia x x 

Hylbert [1978] .................................. E. Kentucky x x x x Karmis and Kane [1984] .................. Virginia x x x x x x 

Kester and Chugh [1980] ................ Illinois Basin x x x x x

Martin et al. [1988]........................... Alabama x x x x 

Milici et al. [1982]............................. Virginia x x x 

Central Miller [1984] ..................................... x x x x x x Appalachia 

Moebs and Ferm [1982]; Virginia, x x x x Ferm et al. [1978] ......................... S. West Virginia 

Moebs and Stateham [1985] .......... United States x x x x x x 

Newman and Bieniawski [1986] ...... United States x x x x x x 

Schaffer [1985] ................................ Illinois Basin x x Sinha and Venkateswarlu [1986]; India x x x x x x x x Venkateswarlu et al. [1989] .......... Stingelin et al. [1979] ...................... N. Appalachia x x x Zhou et al. [1988]............................. United States x x x x x Coal Mine Roof Rating (CMRR) ...... United States x x x x x x x x x 

Table 1.—Rock mass classification systems for coal mines 
Figure 1.—Effect of water on a moisture-sensitive shale. 

Slickensides and Other Discontinuities: While bedding is generally the most significant weakness in the 

fabric of coal measure rocks, often some other type of discontinuity is present. Slickensides, which are small-scale 

(<2-m) fault surfaces of highly aligned clay minerals 

distinguished by glassy, grooved surfaces, are frequently 

cited as greatly reducing the competence of coal measure 

mudrocks (for example, see Moebs and Stateham [1985]). 

Jointing is encountered in Virginia [Karmis and Kane 

1984] and occasionally elsewhere. In sandstones, coal 

spars and crossbeds can be significant. The original RMR 

rates only the most significant discontinuity set and largely 

ignores the others. The CMRR contains a “multiple discontinuity adjustment” so that the weakening effects of 

slickensides and other discontinuities can be explicitly 

included. 

 Large-scale Features: Large-scale features include 

sandstone channel margins, lineaments, faults, and some 

medium-scale features such as seam rolls and clay veins. 

These types of features are not included directly in the 

CMRR, although in some cases one CMRR value can be 

determined for “typical conditions” and another for 

“fracture zones” or “sandstone channel margin areas,” and 

these can then be plotted on hazard maps. However, the 

CMRR is not designed to rate conditions impacted by a 

major throughgoing discontinuity such as a fault. Such 

features normally require specially designed support 

systems. 

DATA COLLECTION AND CALCULATION 

OF THE CMRR 

The data required for the CMRR can be determined 

either from underground exposures, such as roof falls and 

overcasts, or from exploratory drill core. In either case, the 

main parameters measured are the— 

•	 Uniaxial compressive strength (UCS) of the intact 

rock; 

•	 Intensity (spacing and persistence) of bedding and 

other discontinuities; 

•	 Shear strength (cohesion and roughness) of bedding 

and other discontinuities; 

•	 Moisture sensitivity of the rock; and 

•	 Presence of a strong bed in the bolted interval. 

Other secondary factors include the number of layers, the 

presence of groundwater, and surcharge from overlying 

weak beds. 

The CMRR is calculated in a two-step process. First, 

the mine roof is divided into structural units, and Unit 

Ratings are determined for each. A structural unit generally contains one lithologic layer, but several rock layers 

may be lumped together if their engineering properties are 

similar. In the second step, the CMRR is determined by 

averaging all the Unit Ratings within the bolted interval 

(with the contribution of each unit weighted by its thickness) and applying appropriate adjustment factors. This 

second step is the same regardless of whether the Unit 

Ratings were from data collected underground or from 

core. Figure 2 illustrates the process. 

Figure 2.—Flowchart for the CMRR. 

The procedures for gathering data and calculating the 

CMRR from underground exposures have remained essentially unchanged since they were first proposed in 1993. 

The underground data sheet is shown in Figure 3. Procedures to determine Unit Ratings from drill core have now 

been streamlined and updated based on new research 

[Mark et al. 2002]. Calculating the CMRR has been greatly 

simplified by the development of a CMRR computer program that can be obtained free of charge. 

The sections below discuss each of the input parameters used in the CMRR. 
A.

B.

12

3

4

Groundwater (inflow/10 m of entry length) L/min 

(Circle one) 

 Dry 0 1 Heavy Drip 2.7 - 12.2 4  Damp 0 - 1.3 2 Flowing >13.2 5  Light Drip 1.3 - 2.7 3 

Describe condition in vicinity of fall (circle one)  1. Good 3. Heavy  2. Scaly 4. Failed 

CMRR 

DATE MINE LOCATION PAGE OF CMRR TYPE OF EXPOSURE NAME 

UNIT UNIT DISCONTINUITIES 

Unit

No. 

Unit

Thickness 

Strip

Log Description Strength Moisture Sensitivity Disco. I.D. Description Cohesion Roughness Spacing Persistence Lateral/Vert 

A.

B. 3 

C. 

CONTACT 

A.

B. 2 

C. 

CONTACT 

1 

C. 

Rebounds Not Sensitive 1 Strong (>7)** Jagged >1.8 m 0 - 0.9 m 

Pits Slightly Sensitive 2 Moderate (4-7) Wavy 0.6 - 1.8 m 0.9 - 3 m 

Dents Moderately Sensitive 3 Weak (1-3) Planar 20 - 60 cm 3 - 9 m 

Craters Severely Sensitive 4 Slickensided (0) 6 - 20 cm >9 m 

5 Molds 5 <6 cm 

**Chisel blows necessary to split bedding. 

 COMMENTS: 

Figure 3.—Underground data sheet for the CMRR. 
 

 

Uniaxial Compressive Strength (UCS) 

The UCS of the rock material influences roof strength 

in several ways. First, it determines the ease with which 

new fracturing (as opposed to movement along preexisting 

discontinuities) will take place. Second, the compressive 

strength of the rock is a factor in the shear strength of 

discontinuities. Approximately one-third of the CMRR is 

determined by the compressive strength rating, which is 

approximately twice the weight given to the UCS in the 

original RMR. 

Laboratory testing is generally considered the standard 

method of determining the UCS. Unfortunately, laboratory 

tests are expensive because the samples must be carefully 

prepared. The variability in the results is also high, with 

the standard deviation typically about one-third of the 

mean for coal measure rocks [Rusnak and Mark 2000]. 

As an alternative, the CMRR recommends the point 

load test (PLT) for drill core. The PLT has been accepted 

in geotechnical practice for nearly 30 years [Hoek 1977]. 

An advantage of the PLT is that numerous tests can be 

performed because the procedures are simple and inexpensive. The apparatus is also inexpensive and portable. The 

International Society for Rock Mechanics has developed 

standard procedures for testing and data reduction [ISRM 

1985]. 

Another advantage of the PLT is that both diametral 

and axial tests can be performed on core. In a diametral 

test, the load is applied parallel to bedding (Figure 4). The 

diametral test is therefore an indirect measure of the lateral 

strength, or bedding plane shear strength, and is further 

discussed later. 

Figure 4.—Diametral and axial point load tests. 

When the axial PLT is used to estimate the UCS, the 

Point Load Index (Is50) is converted using the following 

equation:

 UCS = K (Is50) (1) 

where K is the conversion factor. A comprehensive study 

involving more than 10,000 tests of coal measure rocks 

from six states [Rusnak and Mark 2000] found that K=21 

fit the data well for the entire range of rock types and 

geographic regions (Figure 5). The study also found that 

the variability of the PLT measurements, as measured by 

the standard deviation, was no greater than for UCS tests. 

The UCS rating scale used in the CMRR program is shown 

in Figure 6. 

 Figure 5.—Relationship between axial PLT and UCS 

test for shale (Rusnak and Mark [2000]). 

Figure 6.—CMRR rating scale for UCS tests. 

Underground, the CMRR employs an indention test 

proposed by Williamson [1984] to estimate UCS. The 

exposed rock face is struck with the round end of a ball 

peen hammer, and the resulting characteristic impact 

reaction is compared to the drawings shown on the left 

side of Figure 3. It is the nature of the reaction (indentation), not its magnitude, that is important. 

A study was conducted to compare the UCS ratings 

derived from the Ball Peen Test with the PLT. In 17 of the 

23 sites studied (or 74% of the cases), the difference 

between the two measurements was 4 points or less (Figure 7). The analysis resulted in slight changes to the 

Williamson rock strength classes, as shown in Table 2. 
 

 

 

 

 

Ball Peen Rating 30 

25 

20 

15 

10 

5 

5 10 15 20 25

UCS Rating 

3

Figure 7.—Comparison between UCS and Ball Peen Tests. 

0 

Table 2.—Approximate UCS ranges from 

Ball Peen Hammer Tests 

Ball peen 

hammer class 

Williamson UCS 

range (MPa) 

CMRR UCS 

range (MPa) CMRR rating 

Molds ............... <7 <14 5 

Craters ............. 7–21 14–35 10 

Dents ............... 21–56 35–70 15 

Pits................... 56–105 70–120 22 

Rebounds ........ >105 >120 30 

Discontinuity Intensity 

Intensity is determined by the spacing between 

bedding planes or other discontinuities and the persistence, 

or extent, of each individual discontinuity. The more 

closely spaced a set of discontinuities, the greater the 

weakening effect on the rock mass. Persistence is more 

important for discontinuities that are widely spaced. Like 

UCS, intensity accounts for about one-third of the total 

CMRR. 

Underground, both spacing and persistence can be 

measured directly using the standard methods for rock 

mass characterization [ISRM 1982]. Table 3 shows the 

Bedding/Discontinuity Rating Scale for underground data. 

The matrix shows what point value is added for each 

combination of spacing and persistence of discontinuities. 

Table 3.—Bedding/discontinuity intensity rating table 

for underground data 

Persistence 

Spacing 

>1.8 m 0.6–1.8 

m 

0.2–0.6 

m 

60–200 

mm 

<60 

mm 

 0–1 m ........... 

1–3 m .......... 

 >1 m ............ 

35 

32 

30 

30 

27 

25 

24 

21 

20 

17 

15 

13 

9 

9 

9 

Most standard geotechnical core logging procedures 

include some measure of the natural breaks in the core. 

The two most commonly employed are the fracture 

spacing and the RQD. Fracture spacing is easily determined by counting the core breaks in a particular unit and 

then dividing by the thickness of the unit. The RQD is 

obtained by dividing combined length of core pieces that 

are greater than 4 in long by the full length of the core run. 

Both measures have their advocates in the geotechnical community. Priest and Hudson [1976] suggested 

that the two can be related by the following formula: 

RQD = 100 e–0.1L (0.1L+1) (2) 

where L = number of discontinuities per meter. 

As input, the CMRR uses either the RQD or the fracture spacing. When the fracture spacing is greater than 

about 1 ft, the RQD is not very sensitive, so the fracture 

spacing is used directly. At the other extreme, when the 

core is highly broken or lost, the RQD seems to be the 

better measure. Either measure may be used in the intermediate range. 

The program uses the equations shown in Figure 8 to 

calculate the Discontinuity Spacing Rating (DSR) of core 

from RQD or the fracture spacing. The equations were 

derived from the original CMRR rating tables. The minimum value of the DSR is 20; the maximum is 48 (see 

Figure 8). 

Figure 8.—CMRR rating scale for fracture spacing or RQD. 

Shear Strength of Discontinuities 

Bedding plane shear strength is a critical parameter for 

coal mine ground control because the most severe loading 

applied to coal mine roof is normally lateral, caused by 

horizontal stress [Mark and Barczak 2000]. Molinda and 

Mark [1996] found that the lateral strength of some shales 

are just one-sixth of their axial strength. 

Underground, the cohesion of bedding surfaces is 

evaluated by using a 9-cm mason chisel and a hammer to 

split hand samples of rock. Weaker, less cohesive surfaces 

require fewer chisel blows to split (see Figure 3). Cohesion 

can also be estimated by observing the nature of the 

fractured wall of a roof fall. If the wall “stairsteps,” with 

most of the roof failure occurring along bedding, then the 

cohesion is probably low. On the other hand, if most of the 
 

ided

Jagged ............... 

Wavy.................. 

35 

35 

29 

27 

24 

20 

10

10

Planar................. 35 25 16 10 1

If unit has no bedding/discontinuities, then apply test to the 

intact rock. 

 

 

 

 

 

failure surfaces cut across bedding, then the strength of the 

bedding is most likely equal to or greater than that of the 

intact rock. Slickensided surfaces are already planes of 

failure and receive the minimum rating. 

The roughness along a discontinuity surface is the 

other component of the surface’s shear strength. In the 

CMRR, roughness of a surface is estimated visually and 

classified as jagged, wavy, or planar, using the system 

proposed by Barton et al. [1974]. This measure is to be 

applied on a scale that ranges from hand sample size to 

several feet across a fall exposure. The CMRR assumes 

that roughness significantly affects shear strength only 

when cohesion is in the middle range (see Table 4). 

Figure 9.—CMRR rating scale for diametral point load tests. 

Table 4.—Bedding/discontinuity shear strength rating table 

for underground data1 

 

COHESION Roughness Strong Moderate Weak Slickens

When drill core is available, strength testing can be 

conducted. The diametral PLT is a convenient index test 

that provides a substitute for bedding plane shear testing. 

Because the precise relationship between bedding plane 

shear strength and the PLT is not known, and since it 

seems unlikely that the same K-factor used to convert the 

axial test to the UCS would apply, the CMRR uses the 

Point Load Index (IS50) directly. The diametral PLT rating 

values were derived from the original CMRR tables and 

the data presented by Molinda and Mark [1996] and are 

shown in Figure 9. 

If the diametral test results show that the rock fabric or 

laminations are low-strength, it would be illogical to give 

the rock high marks for discontinuity spacing. In fact, both 

the fracture spacing and the RQD also actually measure the 

strength of discontinuities as well as their spacing, because 

strong discontinuities might withstand the rigors of the 

 

 

 

 

 

 

 

 

IMMERSION TEST 

Mine: Date: 

Unit No.: Tester: 

Sample Description (Lithology, bedding, etc.): 

Immersion Breakability

Observation

Appearance of Water 

 Rating Observation Rating

Clear = 0 

Misty = -1 

Cloudy = -3 

No Change 0 

Small Change-2 

Large Change -6

 Talus Formation 

None = 0 

Minor = -1 

Major = -3 

Breakability Index 

Cracking of Sample 

None = 0 

Minor/Random = -1 

Major/Preferred Orientation =-3 

Specimen Breakdown = -9

 Total Immersion Index 

Procedure for Immersion Test 

1. Select sample(s) - ~ hand sized 

2. Test for hand breakability. 

3. Rinse specimen (to remove surface dirt, dust, etc.) 

4. Immerse in water for 1 hour 

5. Observe and rate water appearance, talus formation, and cracking of sample 

6. Sum Rating for Immersion Index. 

7. Retest for hand breakability. 

8. Determine Breakability Index 

9. The final Immersion Test Index is the greater of the Breakability Index or the Immersion Index. 

Figure 10.—Data sheet for the Immersion Test. 

drilling process while weak ones break apart. Therefore, 

the discontinuity rating is the lower of the Diametral PLT 

Rating or the Discontinuity Spacing Rating. 

Moisture Sensitivity Deduction 

In the CMRR, the maximum deduction for moisture 

sensitivity is 15 points. The data sheet for the Immersion 

Test is shown in Figure 10. If Immersion Test results are 

not available, moisture sensitivity can sometimes be estimated visually in underground exposures. 

Usually, some time is required for contact with humid 

mine air to affect rock strength. In short-term applications, 

therefore, it may not be appropriate to apply the moisture 

sensitivity deduction. The CMRR program reports both the 

Unit Rating and the CMRR with and without the moisture 

sensitivity deduction. 

Research was conducted to explore the relationship 

between the Slake Durability Test (SDT) and the Immersion Test. In the SDT, 10 lumps of rock, each weighing 

about 0.1 lb, are oven-dried, weighed, and then rotated 

through a water bath for 10 min. The repeated wetting and 

drying, together with the mild abrasion that takes place 

during the test, causes moisture-sensitive rocks to break 

down. The Slake Durability Index is the final dry weight of 

the sample expressed as a percentage of the original dry 

weight [Hoek 1977]. 
 

 

To compare the two tests, rock samples were collected 

underground from a variety of mine settings, carefully 

wrapped to maintain in situ moisture content, and tested in 

the laboratory. A total of 96 tests were run on 16 distinct 

rock types from 9 mines. The results are shown in Figure 11. 

From the testing conducted to date, there is a good 

correlation between the two tests for the “not sensitive” 

and “slightly sensitive” classes. The correlation is less 

reliable for distinguishing “moderately sensitive” rocks 

from “severely sensitive” rocks. Table 5 indicates how the 

results from either test can be used for input to the CMRR. 

 Figure 11.—Comparison of the Slake Durability and 

Immersion Tests. 

Table 5.—Moisture sensitivity classes and ratings from both 

Immersion and Slake Durability Tests1 

Moisture sensitivity Rating Immersion Slake Durability 

class adjustment Index Index 

Not sensitive............ 0 0–1 100–98 

Slightly sensitive....... –3 2–4 98–92 

Moderately sensitive.. –7 5–9 92–80 

Severely sensitive..... –15 >9 <80 

 1

Apply rating adjustment to Unit Rating only when unit forms the 

immediate roof or if water is leaking through the bolted interval. 

Calculation of the Unit Rating 

When using underground data, the equation for calculating the Unit Rating is— 

Unit Rating = UCS Rating + Discontinuity Intensity

 Rating + Discontinuity Shear Strength Rating

 + Multiple Discontinuity Adjustment 

+ Moisture Sensitivity Deduction 

For drill core data, the equation is even simpler: 

Unit Rating = UCS Rating + Discontinuity Rating 

+ Moisture Sensitivity Deduction 

Thickness-weighted Average Roof Rating 

The next step in calculating the CMRR is to determine 

the thickness-weighted average of the Unit Ratings of all 

the units within the bolted interval. For example, assume 

that the roof consists of three units (from top down): 

•	 2-m sandstone, Unit Rating = 60 

•	 0.8-m siltstone, Unit Rating = 50 

•	 0.4-m shale, Unit Rating = 40 

If the length of the roof bolts is 1.8 m, then the thicknessweighted average (RRW) is: 

[(0.4 ∗ 40) + (0.8∗50) + (0.6∗ 60)] RRW =	 = 51.1 (3) 1.8 

Note that even though the uppermost layer was 2 m thick, 

only the lowest 0.4 m (the distance to the top of the bolts) 

was used in the calculation. 

The CMRR is now determined by applying several 

adjustment factors to the RRW. 

Strong Bed Adjustment (SBADJ) 

One of the most important concepts in the CMRR is 

that the strongest bed within the bolted interval often 

determines the performance of mine roof. The strong bed’s 

effect on the CMRR depends first upon how much stronger 

it is than the other units. Second, the strong bed must be at 

least 0.3 m thick before it can provide any additional 

support, and the amount of the adjustment is maximum 

when the bed is at least 1.2 m thick. Third, the roof bolts 

must obtain at least 0.3 m of anchorage in the strong bed 

for the adjustment to be considered. Finally, the higher into 

the roof that the strong bed is located, the less its positive 

effect will be. 

In the original CMRR, the SBADJ was determined 

using a table. For improved accuracy and to facilitate 

implementation of the table in the computer program, 

Equation 4 was derived using multiple regression:

SBADJ = [(0.72 SBD * TH – 2.5] SB)

 (4) * [1 – (0.33 (THWR – 0.5))]

where: 

•	 SBD is the strong bed difference—the difference 

between the strong bed’s Unit Rating and the 

thickness-weighted average of all the Unit Ratings 

within the bolted interval; 

•	 THSB is the thickness of the strong bed (m); and 
 

 

 

 

•	 THWR is the thickness of the weak rock suspended 

from the strong bed (m). 

Note that if the strong bed is at the top of the bolted 

interval, its full thickness is used in the calculation of the 

SBADJ (up to a maximum of 1.2 m). 

Other Adjustments 

Number of Units: Many workers have indicated that 

mine roof that contains numerous lithologic contacts is less 

competent than roof that consists of a single rock type 

[Karmis and Kane 1984; Kester and Chugh 1980]. When 

depositional processes change and deposit distinctly different material, there is generally, but not always, a sharp 

contact between units. Since gradational contacts do not 

weaken the roof, the characteristics of major bedding contact surfaces (cohesion and roughness) should be noted. 

The maximum deduction from the CMRR is 5 points when 

more than four weak contacts are present. 

Groundwater Adjustment: Groundwater is most 

prevalent in shallow mines, particularly beneath stream 

valleys, but it can also be introduced by leakage from 

pooled water in abandoned mines or fracturing of overlying aquifers during high-extraction mining. The CMRR 

maintains the RMR system’s rating scale, with a maximum 

deduction for flowing groundwater of 10 points. 

Surcharge: The strength of rocks overlying the bolted 

interval is considered only when they are significantly 

weaker than the rocks within it. An example is a western 

mine where 1.2 m of relatively strong top coal was 

overlain by 6 m of weak, rooted claystone. Because the 

roof beam needed to carry some of the surcharge (extra 

weight) of the incompetent claystone, stability was 

reduced. The CMRR accounts for the surcharge with a 

3-point deduction. 

THE CMRR COMPUTER PROGRAM 

The CMRR program is designed to facilitate the entry, 

storage, and processing of field data. Either core or 

underground data can be entered, and calculations are 

updated instantly when a change is made. This allows the 

user to vary parameters, such as the bolt length, to see their 

effect on the final CMRR. 

The underground data entry screen contains dropdown menus that are used to enter the data for each of the 

parameters. In the core data screen, the user has the option 

of entering PLT test data and having the program automatically determine the mean UCS and diametral Is(50). 

Otherwise, the user can enter the mean strength values 

directly. 

An important feature of the new program is a built-in 

interface with AutoCAD. Data from up to 200 locations 

can be entered and saved in a single file, along with their 

geographic location coordinates. The program can create a 

file for export that includes both the calculated CMRR 

values and the locations. A CMRR layer can then be 

created in AutoCAD for use in mine planning. 

APPLICATIONS OF THE CMRR 

During the past 10 years, the CMRR has been used 

extensively in the United States. Figure 12 shows the 

current database, containing 264 observations from more 

than 200 mines. The figure reveals some very important 

regional trends. Weak roof predominates in the northern 

Appalachian and Illinois Basin coalfields, which are also 

areas where roof falls tend to occur more frequently 

[Pappas and Mark 2003]. Central Appalachian mines have 

a wide range of CMRR values, but the typical roof is of 

moderate strength. Utah mines tend to have the most 

competent roof in the United States. 

A number of mine planning design tools based on the 

CMRR are discussed below. 

120 

100 

N = 264 

<=40 41 - 50 51 - 60 61 -70 >70 

Coal Mine Roof Rating (CMRR) 

No. of Observations 

80 

60 

40 

20 

0 

Northern Appalachia Southern Appalachia Midwest 

CO,WY,NM Alabama Utah 

Figure 12.—Current CMRR database. 

Analysis of Longwall Pillar Stability (ALPS) 

The first, and perhaps the best known, application of 

the CMRR is the ALPS pillar design method [Mark et al. 

1994]. A large database of longwall case histories was 

collected from throughout the United States and subjected 

to statistical analysis. The results showed that when the 

roof was strong (CMRR>65), longwall chain pillars with 

an ALPS stability factor (SF) as low as 0.7 could provide 

satisfactory tailgate conditions (Figure 13). On the other 

hand, when the roof was weak (CMRR<45), the ALPS SF 

might need to be as high as 1.3. ALPS has been the 

standard technique employed to size pillars for most 

U.S. longwalls for many years. 
 

 

 

 

 

 

 

40 

50 

60 

70 

80 

90 

Satisfactory Cases 

Unsatisfactory Cases 

ALPS Design Equation

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 

ALPS STABILITY FACTOR 

CMRR 30 

20 

 Figure 13.—Relationship between the CMRR and the 

ALPS SF. 

Longwall Tailgate Design (Australia) 

ALPS was the starting point for a project under the 

Australian Coal Association Research Program (ACARP) 

to develop an Australian chain pillar design methodology 

[Colwell et al. 1999]. The project aimed to calibrate ALPS 

for the different geotechnical and mine layouts used in 

Australia. Ultimately, case history data were collected 

from 60% of Australian longwall mines. 

The study found strong relationships between the 

CMRR, the tailgate SF, and the installed level of primary 

support. Design equations were developed that reflected 

these trends. The final product, called the Analysis of 

Longwall Tailgate Serviceability (ALTS), was implemented in a computer program and has become widely 

used in Australia. Most recently, an expanded study 

resulted in an updated version called ALTS II [Colwell 

et al. 2003]. 

Stability of Extended Cuts 

Place change mining, in which mining equipment 

moves from entry to entry as the section is advanced, is the 

standard development method in the United States. The 

traditional 6-m cut length was determined by the distance 

from the cutting head to the operator’s compartment. With 

the advent of remote-control continuous miners, extended 

cuts up to 12 m long have become common. However, 

many mines with extended-cut permits only take them 

when conditions allow. Where the roof is competent, 

extended cuts are routine. At the other extreme, when the 

roof is very poor, miners may not be able to complete a 

traditional 6-m cut before the roof collapses. 

To help predict when conditions might be suitable for 

extended cuts, a study was conducted at 36 mines throughout the United States. The study found that when the 

CMRR was greater than 55, extended cuts were nearly 

always routine, but when the CMRR was less than 37, they 

were almost never taken [Mark 1999a]. The data also 

showed that extended cuts were less likely to be feasible as 

the roof span or the depth of cover increased (Figure 14). 

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

100 

CMRR

Always Stable 

Sometimes Stable 

Never Stable 

Extended Cut Equation 

0 100 200 300 400 500 

Depth of Cover (m) 

600 

 Figure 14.—Relationship between the CMRR and the 

feasibility of extended cuts. 

Roof Bolt Selection 

To help develop scientific guidelines for selecting roof 

bolt systems, the National Institute for Occupational Safety 

and Health conducted a study of roof fall rates at 37 U.S. 

mines [Mark et al. 2001; Molinda et al. 2000]. The study 

evaluated five different roof bolt variables, including 

length, tension, grout length, capacity, and pattern. Roof 

spans and the CMRR were also measured. Performance 

was measured in terms of the number of roof falls that 

occurred per 3 km of drivage. 

The study found that the depth of cover (which 

correlates with stress) and the roof quality (measured by 

the CMRR) were the most important parameters in determining roof bolting requirements. Intersection span was 

also critical. The study’s findings led to guidelines that can 

be used to select the proper span, bolt lengths, and bolt 

capacity based on the CMRR. The results have been 

implemented into a computer program called Analysis of 

Roof Bolt Systems (ARBS). 

Multiple-seam Mining 

Interactions with previous mining in underlying or 

overlying seams are a major cause of ground instability in 

the United States. A statistical analysis of a database of 

more than 360 case histories found that the CMRR was 

highly significant in predicting the outcome of a multiseam 

interaction. Other significant variables include the pillar 

SF, the total pillar stress, whether the previous seam was 

above or below, and what type of pillar structure is present 

in the previous seam. 

 The statistical analysis became the foundation for the 

Analysis of Multiple-seam Stability (AMSS) software 

package. The output from AMSS is the critical interburden 

thickness that is necessary to avoid interactions. AMSS 
 

 

 

 

indicates that, all else being equal, a CMRR=45 roof 

requires approximately 15 m more interburden than a 

CMRR=65 roof. 

Longwall Mining Through Open Entries 

and Recovery Rooms 

Unusual circumstances may require that a longwall 

retreat into or through a previously driven room. The 

operation is usually completed successfully, but there have 

been a number of spectacular failures. To help determine 

which factors contribute to such failures, an international 

database of 131 case histories was compiled [Oyler et al. 

1998]. The study found that the CMRR and the density of 

standing support were the two most important parameters 

in predicting severe weighting-type failures. These failures 

occurred only when the CMRR was less than 55 and when 

the support density was less than 0.5 MPa. When the 

CMRR was 40 or less, all of the successful cases employed 

a standing support density of at least 1.0 MPa. 

Roof Fall Evaluations (South Africa) 

The CMRR featured prominently in an important 

research project sponsored by the Safety in Mines 

Research Advisory Committee (SIMRAC) and other leading industry, labor, and government organizations in South 

Africa. The goal of the project was to investigate the 

causes of fatal roof failures in South African coal mines. 

A team of recognized experts visited a broad spectrum of 

mines and collected data at 182 roof fall sites. The study 

found that roof falls were more likely where the roof was 

less competent in terms of the CMRR. Another finding 

was that the CMRR correlated well with roadway widths. 

Based on data presented by Mark [1999b] (see Figure 15), 

the study also concluded that “in South African coal 

mines, less support is used for comparable roof conditions 

than either the USA or Australia. This supports previous 

conclusions that in South African coal mines, the density 

of supports needs to be increased.” [van der Merwe 2001]. 

20 

30 

40 

50 

60 

70 

80 

90 

100 

0 0.1 0.2 0.3 0.4 0.5 0.6 

Primary Support Rating (PSUP) 

Coal Mine Roof Rating (CMRR)

USA Case Histories 

S. Afr. Case Histories 

South African 

Mines 

Australian 

Mines 

 Figure 15.—Relationship between the CMRR and roof bolt 

density in the United States, Australia, and South Africa. 

Another SIMRAC study found the CMRR easy to use 

and robust enough to adequately describe the roof 

conditions at most South African collieries [Butcher 2001]. 

It took less than 4 hr for a trained geologist to become 

competent with the method. The results seemed more 

reasonable than those obtained from the RMR, which 

tended to overrate ground conditions by at least one class 

(20 points) due to its lack of sensitivity to the characteristics of bedded strata. Some improvements were suggested for the CMRR, including adjustments for joint 

orientation, blasting, and horizontal stress. 

Baseline Comparison of Ground Conditions 

(Canada) 

The Canadian underground coal industry is small and 

geographically dispersed. To assist the mines in maintaining world-class safety standards, the Canada Centre for 

Mineral and Energy Technology (CANMET) established 

the Underground Coal Mine Safety Research Consortium. 

One of the consortium’s first projects was aimed at 

establishing a “best practice” baseline for conducting geological and geomechanical assessments and applying the 

findings to geotechnical design. 

The CMRR was found to be particularly valuable in 

the assessment [Forgeron et al. 2001]. It allowed the 

Canadian underground mines to be compared with each 

other and with international benchmarks. Based on the 

CMRR, many ground control safety technologies developed in the United States were found to have direct 

application to Canadian mines. 

Other Applications 

•	 Highwall mining can become uneconomic if the roof 

is so weak that it collapses before the miner has been 

withdrawn from the hole. The CMRR has been used 

to evaluate potential highwall mining reserves and to 

identify potentially unsuitable areas [Hoelle 2003]. 

•	 Tailgate support guidelines incorporating the CMRR 

have been included in the Support Technology Optimization Program (STOP) [Barczak 2000]. 

•	 Input for numerical models have been derived from 

the CMRR [Karabin and Evanto 1999].
 

 

 

CONCLUSIONS 

Roof geology is central to almost every aspect of 

ground control. The CMRR makes it possible to quantify 

roof geology so that it can be included in mine planning 

decisions. Worldwide experience has shown that the 

CMRR is a reliable, meaningful, and repeatable measure 

of roof quality. 

A wide variety of design tools based on the CMRR 

have now been developed. They address a broad range of 

ground control issues and rely upon large databases of 

actual mining case histories. Without the CMRR, it would 

not have been possible to capture this invaluable 

experience base. 

The new core procedures and computer program 

further expand the potential of the CMRR. It is now possible to routinely collect CMRR data during geologic 

exploration or from underground mapping, complete the 

calculations, and integrate the results into mine mapping 

software. Foreknowledge of conditions means better mine 

planning and fewer unexpected hazards underground. 

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