Comparison of Fatality Incident Rates

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Figure 1. Fatality rates in mining and other U.S. industrialsectors.

Overview of Ground Control Research for Underground Coal Mines in TheUnited States

C. MarkNational Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, Pittsburgh, PA, USA

ABSTRACT: Underground coal mining continues to evolve in the U.S., and more reserves are being mined underdeeper cover, with worse roof, or with interactions from previous workings. At the same time, the miningcommunity is responding to higher safety standards and intense competitive pressures. The need for effectiveground control design has never been greater. Ground control safety issues that have been addressed by recent theNational Institute for Occupational Safety and Health (NIOSH) research include: Improving roof supportperformance; Maintaining safe tailgate escapeways from longwalls; Optimizing pillar design for retreat mining;Controlling multiple seam interactions; Predicting roof conditions during extended cuts, and; Preventing massivepillar collapses. As funding from both government and the private sector has diminished, the emphasis in researchhas focused on providing the mining community with practical techniques for improved ground control design.Many projects have successfully employed empirical methods that emphasize the statistical analysis of casehistories from underground mines. Other projects have employed numerical models and large-scale laboratorytesting of roof support elements. Using these data, NIOSH has developed an entire toolbox of computer programsthat have been effectively transferred to the mining community.

1 INTRODUCTION

Roof falls have been the single greatest hazard thatunderground coal miners face in the U.S. Throughoutthe 20th century, roof falls accounted for approximatelyhalf of all deaths underground. While overall safety inU.S. coal mines has improved dramatically in the last50 years, fatality rates continue to exceed other majorindustrial sectors (fig. 1). Fatalities due to ground fallsstill make up a significant portion of this rate.

Currently, underground coal production in the U.S.is split almost 50-50 between large longwall mines andsmaller, room-and-pillar mines. Most longwallsoperate at depths of cover in excess of 300 m. Room-and-pillar operations are still primarily at shallowdepth, often working small, irregular deposits that wereabandoned by earlier miners. Approximately 20% ofthe room-and-pillar coal is won on retreat faces (Market al, 1997a).

Today's underground coal industry faces intensecompetitive pressures from the $4/ton Powder RiverBasin strip mine coal and from the pace-settingmillion-ton-per-month longwalls. Ground failures canhardly be afforded in this climate, yet they continue tooccur. Some examples:

Roof falls: In 1998, more than 1,800 unplanned rooffalls occurred where the roof had already been

supported. While few of these resulted in injuries,each one represented direct threat to life and limb, andan indirect threat to ventilation, escape, and equipment.In each of these roof falls, the majority of whichoccurred in intersections, the roof bolt system failed toperform successfully.

Massive Collapses: In 1992, miners were splittingpillars at a southern West Virginia mine when thefenders in a 2.3 ha area suddenly collapsed. The minerswere knocked to the floor by the resulting air blast, and103 ventilation stoppings were destroyed. At least 12similar events have occurred in recent years,

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N = 90

Figure 2. The Coal Mine Roof Rating observed in variousU.S. coalfields

miraculously without a fatality (Mark et al., 1997b).Pillar Squeezes: At a Kentucky coal mine, pillars

were being extracted in the main entries under 270 mof cover. The pillars began to crush in response to thevertical load, resulting in a roof fall that killed twominers. This incident is an extreme example ofhazardous conditions that can be associated with slowpillar failure. Research has identified at least 45 recentinstances of pillar squeezes in room-and-pillar mines(Mark and Chase, 1997).

Longwall Tailgate Blockages: In 1984, 26 miners atthe Wilberg Mine in Utah could not escape a deadlyfire because of a tailgate roof fall. Similar blockageswere common in the 1980's, and 50 cases have beendocumented (Mark, 1992).

Multiple Seam Interactions: Studies indicate that themajority of remaining room-and-pillar reserves, and33% of longwalls, will be subject to multiple seaminteractions. At one West Virginia mine where fourseams had previously been extracted, a fatalityoccurred when the roof collapsed without warningbeneath a barrier pillar.

The National Institute for Occupational Safety andHealth (NIOSH) has the primary responsibility forconducting research to reduce mining hazards in theU.S. NIOSH continues the tradition of the U.S. Bureauof Mines, which was closed in 1995. Mining researchis conducted at two Research Laboratories, one inSpokane and the other in Pittsburgh.

The past 20 years has seen a steady decline in theresources devoted to ground control research. Thelabor- and instrumentation-intensive field studies ofpast years are rarely feasible today. As a result, NIOSHscientists have had to develop new approaches toconducting ground control research.

2 THE COAL MINE ROOF RATING (CMRR)

One approach that has proven exceptionally successfulfor solving complex problems is the empirical, orstatistical, approach. It relies on the scientificinterpretation of actual mining experience representedas case histories. For example, hundreds of longwalland room-and-pillar panels are mined each year, andeach one is a full-scale test of a pillar design. Oncedata has been collected on enough of these casehistories, statistical techniques can be used todetermine those combinations of factors most likely toresult in pillar failure. A key advantage is that criticalvariables may be included even if they are difficult tomeasure directly, through the use of rating scales. Asignificant breakthrough was the development of arock mass classification system specifically applicableto coal mine roof.

Coal Mine Roof Rating (CMRR) was proposedbecause neither traditional geologic reports norlaboratory strength tests on small rock samplesadequately described the structural competence of mine

roof. The CMRR combined 20 years of research ongeologic hazards in mining with worldwide experiencewith rock mass classification systems (Molinda andMark, 1994). Field data was collected from nearly 100mines in every major U.S. coalfield (figure 2).

The CMRR weighs the geotechnical factors thatdetermine roof competence, and combines them into asingle rating on a scale from 0 to 100. The underlyingphilosophy of the CMRR is that it is not the strength ofthe intact rock that determines the stability of a mineroof, but rather the defects or discontinuities whichweaken or destroy the roof beam.

The CMRR makes four significant contributions:• Focuses on the characteristics of bedding planes,

slickensides, and other discontinuities thatweaken the fabric of coal measure rock;

• Applies to all U.S. coalfields, and allowsmeaningful comparison even where lithologiesare quite different;

• Concentrates on the ability of the immediate roofto form a stable structure, focusing on thecharacteristics of the strongest bed within thebolted interval, and;

• Provides a methodology for geotechnical datacollection.

Originally, the data for the CMRR was collected atunderground exposures like roof falls and overcasts. Tomake it more generally useful, procedures weredeveloped for determining the CMRR from drill core(Mark and Molinda, 1996). The drill core proceduresemploy the Point Load Test to estimate the uniaxialcompressive rock strength and the rock strengthparallel to bedding. A new conversion factor frompoint load index of strength (Is(50)) to uniaxialcompressive strength (UCS) has been determined from

Figure 3. Plan view of a typical U.S. longwall mine.

Figure 4. ALPS case history data base and design guidelines.

a large data base provided by a large U.S. coalcompany (Rusnak and Mark, 2000).

The CMRR has found many applications in groundcontrol research and mining practice, as described inmany of the examples below. It has also beensuccessfully applied in Australia and South Africa(Colwell et al., 1999; Mark, 1998; Mark, 1999). Acomputer software package has recently beendeveloped that makes the CMRR easier to use and tointegrate into exploratory drilling programs.

3 DESIGN OF LONGWALL GATE ENTRYSYSTEMS

In the fifteen years after 1972 the number of U.S.longwall faces grew from 32 to 118 (Barczak, 1992).The new technology created a host of operational andsafety problems, including the maintenance of stabletravelways on the tailgate side (figure 3). Researchersinitially viewed gate entry ground control primarily asa pillar design issue. The clear correlation betweenlarger pillars and improved conditions that had beenestablished by trial-and-error at many mines supportedthis approach.

In comparing longwall pillars to traditional coalpillars, the most obvious difference is the loading.Longwall pillars are subjected to complex and severeabutment loads arising from the retreat mining process.The loads are also changing throughout the pillar'sservice lives. The major contribution of the originalAnalysis of Longwall Pillar Stability (ALPS) was aformula for estimating the longwall pillar load, basedon numerous underground measurements (Mark,1990).

It became clear, however, that tailgate stabilityrequired more than good pillar design. Other factors,

such as roof quality and artificial support, must beimportant. Data were collected from approximately55% of all U.S. longwall mines, selected to representa geographic and geologic cross-section of the U.S.longwall experience. A total of 64 case histories wereclassified as "satisfactory" or "unsatisfactory."Unsatisfactory conditions almost always caused themine to adjust their design in future panels.Satisfactory designs were used for at least threesuccessive panels without significant ground controldelays.

Each case history was described by severaldescriptive variables, including the ALPS stabilityfactor (SF), the CMRR, entry width, and primarysupport rating. Multi-variate statistical analysis showedthat when the roof is strong, smaller pillars can safelybe used (Mark et al., 1994). For example, when theCMRR is 75, the an ALPS stability factor (SF) of 0.7is adequate. When the CMRR drops to 35, the ALPSSF must be increased to 1.3 (figure 4). Significantcorrelations were also found between the CMRR andboth entry width and the level of primary support.

Since 1987, ALPS has become the most widely-usedpillar design method in the U.S. The ALPS-CMRRmethod directly addresses gate entry performance, andmakes U.S. longwall experience available to mineplanners in a practical form. Tailgate blockages are farless common today than they were 10 years ago, andALPS can surely claim some of the credit.

4 PILLAR DESIGN FOR RETREAT MINING

The classical empirical pillar strength formulas wereall developed for room and pillar mining. However,none ever attempted to consider the abutment loadsthat occur during pillar recovery operations. Theabutment load formulas used in ALPS provided ameans to rectify that shortcoming.

The Analysis of Retreat Mining Pillar Stability(ARMPS) employs the same basic constructs as ALPS,

Figure 5. Model of a room-and-pillar mining section used bythe ARMPS program

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Figure 6. The ARMPS case history data base.

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Figure 7. Pillar collapse case histories in the U.S

adapted to more complex and varied mininggeometries (Mark and Chase, 1997). The abutmentload formulas have been adapted to three dimensions,to account for the presence of barrier pillars andpreviously-extracted panels. Features such as variedentry spacings, angled crosscuts, and slab cuts in thebarrier can all be modeled (figure 5).

To evaluate the validity of ARMPS, more than 200retreat mining case histories were obtained from fieldvisits throughout the U.S. When the entire data set wasevaluated, it was found that 77% of the outcomes couldbe correctly predicted simply by setting the ARMPSSF to 1.46 (figure 6). When the data set was limited tocases where the depth of cover (H) was less than200 m, the accuracy improved to 83%. The conclusionseems to be that ARMPS works quite well at shallowdepth and moderate width-to-height (w/h) ratios (Mark,1999). Research is currently underway to determinewhat other factors need to be included when designingsquat pillars at great depth.

The study also answered some ancient questionsregarding the value of laboratory tests to determine theUCS of coal specimens. The analyses clearly showedthat UCS was of no value whatever in predicting thestrength of coal pillars, thus confirming the results ofan earlier study (Mark and Barton, 1996). It also foundthat the best results are achieved with ARMPS whenthe in situ coal strength is assumed to be 6.2 Mpa. Thestudy concluded that while the in situ strength of U.S.coal seams is probably not uniform, laboratory tests donot measure the geologic features (like bedding planesand rock partings) which are most likely responsiblefor variations in seam strength.

5 MASSIVE PILLAR COLLAPSES

Most of the pillar failures included in the ARMPS database are “squeezes” in which the section convergedover hours, days or even weeks. Another importantsubset are 15 massive pillar collapses (Mark et al.,1997b). These occurred when undersized pillars failedand rapidly shed their load to adjacent pillars, which inturn failed. The consequences of such chain reaction-like failures typically include a powerful, destructive,and hazardous airblast.

Data collected at 12 massive collapse sites revealedthat the ARMPS SF was less that 1.5 in every case, andwas less that 1.2 in 81% of the cases. What reallydistinguished the sudden collapses from the slowsqueezes, however, was the pillar’s w/h ratio (figure 7).Every massive pillar collapse involved slender pillarswhose w/h was less than 3. Laboratory tests haveshown that slender pillars typically have little residualstrength, which means that they shed almost their entireload when they fail. As the specimens become moresquat, their residual strength increases, reducing thepotential for a rapid domino failure. The mechanism ofmassive collapses has been replicated in a numericalmodel (Zipf, 1996).

Two alternative strategies were proposed to preventmassive pillar collapses. Prevention requires increasingeither the SF of the pillars, or their w/h ratio.

Figure 8. Stress analysis of multiple seam interaction usingLAMODEL.

A. Single-Seam Stress

B. Multiple-Seam Stress

C. Additional Stress from Upper Seam

Legend (MPa)-2-7 3 8 13 18

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Containment is used if barrier pillars are used toseparate compartments in which high extraction ispracticed. The small pillars may collapse within acompartment, but because the compartment size islimited, the consequences are not great. Design chartshave been developed for each approach, consideringthe width of the panel, the seam thickness, and thedepth of cover (Mark et al., 1997b).

6 LAMODEL: A NUMERICAL MODEL FORMULTIPLE SEAM DESIGN

Multiple seam situations and other complex mininggeometries do not lend themselves readily to simplisticempirical models like ALPS and ARMPS. Numericalmethods are the alternative approach, but to be usefulthey must realistically portray the behavior of largevolumes of rock. In addition, they must not requirerock material properties that cannot be easilydetermined.

To address these concerns, NIOSH has developedthe displacement-discontinuity model LAMODEL(Heasley and Salamon, 1996a). LAMODEL simulatesthe overburden as a stack of homogeneous isotropiclayers, with frictionless interfaces and with each layerhaving the identical elastic modulus, Poisson’s ratio,and thickness. This “homogeneous stratification”formulation does not require specific materialproperties for each individual layer, and yet it stillprovides a realistic suppleness to the overburden thatis not possible with the homogeneous overburden(Salamon, 1989; Heasley and Salamon, 1986b).

For practical pillar design using a DD model, theinput coal strength is generally derived from empiricalpillar strength formulas which are solidly based onobserved pillar behavior, as opposed to laboratory tests(Mark and Barton, 1996). Similarly, the gob andoverburden properties in the DD model are calibratedso that the resultant gob and abutment stresses closelymatch field measurements/observations such as theabutment load formulas in ALPS or ARMPS. Thistechnique of combining empirical pillar strength andabutment load formulas with the analytical mechanicsof a displacement-discontinuity model capitalizes onthe strengths of both the empirical and analyticalapproaches to pillar design. Using this technique, adisplacement-discontinuity model can be the mostpractical approach for stress analysis and pillar designin complex mining situations such as; multiple seams,random pillar layouts and/or variable topography(figure 8).

7 GUIDELINES FOR ROOF BOLT SELECTION

Despite more than half a century of experience withroof bolting, no design method has received wide

acceptance. To begin to improve this situation, NIOSHevaluated the performance of roof bolt systems at37 mines (Molinda et al., 2000). Success was measuredin terms of the number of roof falls that occurred per3,000 m of drivage with a particular roof bolt designwhen other geotechnical variables were held constant.A variety of statistical techniques were used to exploretrends in the data.

L 0.12(I ) log (3.25H)100 CMRR

100B s 10=−

Figure 9. Roof bolt performance case histories.

Shallow Cover

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Figure 10. Design equations for roof bolts.

The study evaluated five different roof boltvariables, including length, tension, grout length,capacity, and pattern. Roof spans and the CMRR werealso measured. Stress levels could not be measureddirectly, but the depth of cover was used as a surrogate.

As expected, the competence of the roof rock,represented by the CMRR, was the single bestpredictor of the roof fall rate. More surprising was theimportance of depth. The higher horizontal stressesencountered in deeper mines apparently require greaterlevels of roof support (figure 9). Important findingswere also made regarding bolt length and intersectionspan. Unfortunately, the data was too sparse and tooscattered to allow conclusions to be made regardingtension and other roof bolt variables.

The study’s findings were used to developguidelines for designing roof bolt systems (Mark,2000). Building upon an equation initially proposed byUnal (1984), a formula for selecting bolt length wasproposed:

Where: LB = Bolt Length (m) IS = Intersection span (average of the sum-

of-the-diagonals, m) H = Depth of Cover (m)

Once the bolt length has been determined, the boltpattern and capacity is determined using the followingequation:

Where: NB=Number of bolts per rowC=Capacity (kN)

SB=Spacing between rows of bolts (m)We=Entry width (m)

The suggested value of PRSUP depends on theCMRR and the depth of cover, as expressed in thefollowing equations:

PRSUP = 15.5 - 0.23 CMRR (low cover)

PRSUP = 17.8 - 0.23 CMRR (high & moderate cover)

Figure 10 shows these equations together with thefield data from which they were derived. The designequations are slightly more conservative than thediscriminate equations that they are based on. Theguidelines are currently being implemented into acomputer program called Analysis of Roof BoltSystems (ARBS).

8 SUPPORT TECHNOLOGY OPTIMIZATIONPROGRAM

The 1990’s saw an unprecedented development ofinnovative supplemental roof support technologies forunderground coal mines. Compared with thetraditional wood posts and cribs, the new supportsprovide better roof control and material handlingadvantages. The new supports include both engineeredwood products and novel concrete designs.

As new support systems are developed, they shouldbe tested to determine their performancecharacteristics. NIOSH operates a world-class facilitycalled the Safety Structures Testing Laboratory(Barczak, 2000a). During the past seven years, over

Figure 11. Typical Windows screen from the STOP program.

1,000 tests have been conducted on various supportsystems. As a result of this effort, 18 new supportsystems have been introduced to the miningcommunity.

To facilitate the use of these new supports, NIOSHdeveloped the Support Technology OptimizationProgram (STOP). STOP includes a complete databaseof the support characteristics and loading profilesobtained from the testing (Barczak 2000b). Usingcriteria introduced by the user, STOP can determinethe support pattern that will carry the required load andprovide convergence control. Comparisons among thevarious support technologies are easily made. STOPcan also estimate material handling requirements andinstallation costs. Figure 11 shows a typical screenfrom the STOP program.

9 CONCLUSIONS

The NIOSH ground control program has focused onproviding the mining community with practical toolsfor improving the safety of U.S. underground coalminers. Using these techniques, mine planners canoptimize pillar design and support selection for avariety of mining techniques.

Transferring these tools to the industry is an integralpart of the program. Traditional techniques, such asconference presentations and NIOSH publications, areemployed extensively. But innovative methods are alsoemployed to bring the research results directly to theend users. Open Industry Briefings are regularly held innumerous coalfield locations, to allow researchersdirect access to their customers. Software packages aremade available free of charge, and hundreds aredistributed at meetings or in response to requests. Mostrecently, all the ground control software has beenposted on the NIOSH mining website for easy access.

The technology transfer efforts have paid off inmany ways. Large segments of the mining communityuses NIOSH software routinely for many aspects of

mine design. Mine operators and safety regulators bothconsider NIOSH as the central source for informationground control. While it is hard to measure directly,there is every reason to believe that our efforts havehelped make underground coal mines safer places towork.

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Barczak, T. M. NIOSH Safety Performance Protocols forStanding Roof Supports and Longwall Shields. Proceedings:New Technology for Coal Mine Roof Support, NIOSH IC9453, 2000a, pp. 207-222.

Barczak, T. M. Optimizing Secondary Support with the NIOSHSupport Technology Optimization Program (STOP).Proceedings: New Technology for Coal Mine Roof Support,NIOSH IC 9453, 2000b, pp. 151-164.

Colwell, M., Frith, R. and Mark, C. Calibration of the Analysis ofLongwall Pillar Stability (ALPS) for Australian Conditions.Paper in the Proceedings of the 18th International Conferenceon Ground Control in Mining, Morgantown, WV, 1999, pp.282-290.

Heasley, Keith A., and Miklos D. G. Salamon, 1996a, A NewLaminated Displacement-Discontinuity Program, Proceedingsof the Second North American Rock Mechanics Symposium,Montreal, Quebec, Canada, June 19-21, p. 1879-1886.

Heasley, Keith A., and Miklos D. G. Salamon, 1996b, A NewLaminated Displacement-Discontinuity Program: FundamentalBehavior, Proceedings of the Fifteenth InternationalConference on Ground Control in Mining, August 13-15. p.111-125.

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Mark, C. Pillar Design Methods for Longwall Mining. USBM IC9247, 1990, 53 pp.

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Mark C, and T. M. Barton. The Uniaxial Compressive Strength ofCoal: Should it be Used to Design Pillars? Proceedings, 15thInternational Conference on Ground Control in Mining.Golden, CO, August 13-15, 1996.

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Mark, C., F. E. McCall, and D. M. Pappas. A Statistical Overviewof Retreat Mining of Coal Pillars in the United States. Paper in

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Mark, C., F. Chase, and R. K. Zipf, Jr. Preventing Massive PillarCollapses in Coal Mines. Paper in New Technology forGround Control in Retreat Mining, NIOSH IC 9446, 1997b,pp. 35-48.

Mark, C., F. E. Chase, and G. M. Molinda. Design of LongwallGate Entry Systems Using Roof Classification. Paper in NewTechnology for Longwall Ground Control: Proceedings of theUSBM Technology Transfer Seminar, USBM SP 94-01, 1994,pp. 5-18.

Mark, C. and G. M. Molinda. Rating Coal Mine Roof Strengthfrom Exploratory Drill Core. Proceedings, 15th InternationalConference on Ground Control in Mining. Golden, CO,August 13-15, 1996, pp. 415-428.

Molinda, G. M., C. Mark, and D. R. Dolinar. Assessing coal mineroof stability through roof fall analysis. Proceedings: NewTechnology for Coal Mine Roof Support, NIOSH IC 9453,2000, pp. 53-72.

Molinda, G. and C. Mark. The Coal Mine Roof Rating (CMRR)--A Practical Rock Mass Classification for Coal Mines. USBMIC 9387, 1994, 83 pp.

Rusnak J., and Mark, C. Using the Point Load Test to Determinethe Uniaxial Compressive Strength of Coal Measure Rock. InPeng SS, Mark C, eds. Proceedings of the 19th InternationalConference on Ground Control in Mining, Morgantown, WV,2000, pp. 362-371.

Salamon, M. D. G. 1989b. Some Applications of the FrictionlessLaminated Model. Paper in Proceedings of the 30th U.S.Symposium of Rock Mechanics. A. A. Balkema, Rotterdam.1989, pp. 891-898.

Unal, E. Empirical approach to calculate rock loads in coal mineroadways. Proc. 5th Intl. Conf. On Ground Control in Mining,Morgantown, WV, 1986, pp. 232-246.

Zipf, R. K. Jr. Simulation of cascading pillar failure in room-and-pillar mines using the boundary element method. Paper inProceedings of the 2nd North American Rock MechanicsSymposium, Balkema, 1996, pp. 1887-1892.