酸刺沟煤矿3.0Mta新井设计【含说明书、翻译、CAD图纸】
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英文原文A Method for The Design of Longwall Gateroad Roof Support W.LawrenceGeowork Engineering, Emerald, QLD, AustraliaAbstract:A longwall gateroad roof support design method for roadway development and panel extraction is demonstrated. It is a hybrid numerical and empirical method called gateroad roof support model(GRSM), where specification of roof support comes from charts or equations. GRSM defines suggested roof support densities by linking a rock-mass classification with an index of mining-induced stress, using a large empirical database of Bowen Basin mining experience. Inherent in the development of GRSM is a rock-mass classification scheme applicable to coal measure strata. Coal mine roof rating(CMRR) is an established and robust coal industry standard, while the geological strength index(GSI) may also be used to determine rock-mass geomechanical properties. An elastic three-dimensional numerical model was established to calculate an index of mining induced stress, for both roadway development and longwall retreat.Equations to calculate stress index derived from the numerical modeling have been developed. An industry standed method of quantifying roof support is adopted as a base template (GRSUP). The statistical analyses indicated that an improved quantification of installed support can be gained by simple modifications to the standard formulation of GRSUP. The position of the mathematically determined stable/failed boundary in the design charts can be changed depending on design criteria and specified risk.Key words:Coal mine;Roof control;Support;Design.1 IntroductionLongwall gateroad strata stability is essential to ensure uninterrupted production. In Central Queenslands Bowen Basin, immediate gateroad roof lithology varies from coal to weak interlaminated material, to strong almost massive sandstone, with localised areas of weak fault affected strata. It is usual for roof conditions within any one mine to vary signicantly. Typically, longwall mines in the Bowen Basin have specied gateroad roof support based on past practice. Modications to gateroad support are generally reactive, due to encountered difcult strata conditions, and less proactive. Current gateroad support design approaches have limitations, which have restricted their applicability and adoption as mine site design tools.A prototype for an improved gateroad support design methodology has been developed that is integrated and systematic, based on rock engineering principals, but requires engineering judgement and experience. There were several broad objec- tives for the design methodology. A consistent and unambiguous denition of strata conditions and behaviour was required. Gateroad roof support needed to be assessed and specied. The method had to provide design calculations and justication for compliance and statutory purposes, and could serve as a framework for a mine strata management system. Mine site support designers must be able to readily use the method to manage uncertainty and risk. The method must be able to be reviewed, modied and expanded.2 Current Roof Support Design Methods for Longwall GateroadsNumerous roof support design methods have been proposed over the years, but none have gained widespread acceptance by the coal mining industry. There are empirical databases, some proprietary, based on industry practice, which specify gateroad primary and secondary support densities, using a statistical approach. Analytical methods are not appropriate when rock-mass yield due to high mining induced stresses occurs, but may be applicable and adapted to low stress environments. The application of complex post-yield numerical modelling in the design process for excavation support is valid although contentious, and requires a more comprehensive justication and better industry understanding of its strength and limitations. The complete mathematical representation of rock-mass properties and behaviour is a complex issue, which is still outside the capability of current numerical modelling code.Engineers and mathematicians do not have the current capability to fully dene rock-mass geomechanical properties and their mathematical representation. Elasticplastic numerical modelling is a useful tool if used appropriately. It is not exclusively correct or unique, or always superior to other available and accepted design techniques. These aspects have been recognised during recent collaborative Australian Coal Association Research Program research on longwall microseismics, where it was considered that current 3D numerical models lack sufcient validated constitutive relationships, and are forced to make compromises when dealing with complex rock-mass behaviour.Simplied elastic numerical methods have merit and are certainly applicable for more massive sedimentary rock-masses. An assessment of their applicability to weaker, laminated clastic rock-masses is required. Hybrid numerical and empirical methods have been developed for the geotechnical design of undercut and production level drifts of block caving mines.3 Geotechnical Roof Classication of Longwall GateroadsTwo classication schemes were considered appropriate. Firstly, the coal mine roof rating(CMRR), which is an established coal industry standard. Secondly, the Geological Strength Index, GSI with strength parameters included. A recent publication has contended that GSI estimates of rock-mass strength should not be used for coal mine roof problems, where the geometrical scale of the problem is similar to discontinuity spacing. A distinction needs to be made between the GSI classication and the related HoekBrown failure criterion. This scale effect and situations where the failure criterion should not be used have been discussed. However, this does not mean that a classication of the rock-mass cannot be made. Indeed, this scale issue is a problem inherent in any rock-mass classication scheme, not just GSI, and for any failure criterion. For example, some mines appropriately use unconned compressive strength (UCS) as an index or failure criterion, but UCS is also scale dependent and has the same limitations.Within the support design methodology, the rock-mass classification schemes will link mining-induced stresses (or stress index) and required installed roof support. Therefore, the classifications should be independent of environmental and geometrical factors, such as mining induced stresses and excavation orientation and size. A rock-mass classification scheme must also provide rock-mass geomechanical properties to enable the calculation of mining induced stresses. It is anticipated that CMRR will be the principal classification scheme used. However, the single rock-mass classification scheme that is best suited is the GSI derived global rock-mass strength. For numerical or analytical models, HoekBrown failure criterion parameters, modulus of deformation and rock-mass strength can be estimated from GSI. Direct utilisation of either CMRR or GSI is included within the design methodology.4 An index of mining induced stressAn index of mining induced stress in the gateroad roof at a location of interest is required. The three-dimensional (3D) stress distribution about a longwall panel including goaf reconsolidation, and the continuous stress redistribution that occurs during panel retreat, is a complex and difficult phenomena to quantify. One approach would be to construct a full elasticplastic, 3D numerical model. This approach would have limitations to a verified, unique and readily achieved calculation of stress, for several reasons. Generalised model roadway and goaf geometry may not always match the actual geometry. Generalised model roof lithology may not always match the actual lithology and variations. The roof/seam/floor interaction is a complex system and is difficult to model accurately. Rock-mass geomechanical properties, in particular post-yield cannot be fully defined. The geomechanical properties of the goaf, extent and behaviour of strata fracturing and caving, and goaf stress reconsolidation are largely unknown. The model may take many days to complete just a single scenario. While calculated mining induced stress from a detailed elasticplastic, 3D numerical model may be an appropriate parameter, there is little justification to improved accuracy compared to other methods. An alternative approach is to calculate mining induced stress from elastic 3D numerical models. Calculated mining induced stress in the immediate gateroad roof just outbye of the face-line may not be accurate if rock-mass yield occurs, but as an index of stress, it may be appropriate. An important criterion of its suitability would be how reasonable its relative variation is with changes in input parameters. A significant advantage is that it could be readily calculated for variable scenarios and would be within the range of capability of more geotechnical engineers. Maximum elastic tangential stress in the roof of a modelled gateroad could be considered a better indicator of rock-mass failure than the residual post-yield stress. Undoubtedly, significant rock-mass failure and subsequent stress redistribution do occur, which are not reflected in an elastic model. In the immediate roof of the gateroad, these failures are initiated at a critical mining induced stress. The stress index is a reasonable and appropriate measure of this critical stress, even if it may not agree in absolute magnitude after stress redistribution occurs. For mining induced stresses from an elastic 3D numerical model to be a reasonable representation, several issues influencing the stress distribution must be considered, which include strata fracturing and caving and goaf reconsolidation. For bulking-controlled caving, empirical relationships are used to predict the height of caving (goaf) and fracturing : (m) (1) (m) (2)Where Hc is the caving(goaf) height above top of extracted horizon, Hf is the thickness of the fractured zone above top of caving zone, h is extraction thickness, and c1, c2, c3, c4, c5 and c6 are coefficients depending on lithology(Table1).Table1Coefficients for average height of caving zone17.LithologyCompressive strength(MPa)Coefficientsc1c2 (m)c3 (m)c4c5 (m)c6 (m)Strong and hard402.1162.51.228.9Medium strong20-404.7192.21.63.65.6Soft and weak206.2321.53.154Weathered-7631.2583Goaf stressstrain behaviour can be been defined (Eq. (3), based on earlier work, as follows: (MPa) (3)where, and are the vertical goaf strain and stress, respectively, E0 is the initial tangent modulus, and m is the maximum possible strain of the bulked goaf material. The initial bulking factor, BF, defines m as follows: (4)The initial tangent modulus, E0, can be defined as a function of the compressive strength of rock pieces, c, and the bulking factor, BF: (MPa) (5)The FLAC3D double-yield constitutive model is used to simulate a strain-stiffening material with irreversible compaction, i.e. volumetric yield, in addition to shear and tensile failure. Upper-bound tangential bulk and shear moduli are specified, with the incremental tangent and shear moduli evolving as plastic volumetric strain takes place. In addition to the shear and tensile strength criteria, a volumetric yield surface or cap has to be defined. The cap surface, defined by the cap pressure, pc, is related to the plastic volume strain, pv. The cap pressure, pc, is not the goaf vertical stress, v. The relationship between cap pressure and plastic volume strain is derived from an iterative FLAC2D compression test model, using a one element, 1m1m, grid. Loading was simulated by applying a velocity to the top of the element, which has confined sides and base. The constitutive equation was derived from the iterative results by a Microsoft Excel Solver regression analysis, assuming a linear function. Goaf deformation and material strength parameters are defined as follows(Table2).Table2FLAC3D goaf reconsolidation parameters.Upper bound tangent modulus230MPaPoissons ratio0.3Density1.7gm/ccCohesion0.001MPaFriction angle25Dilation2Tensile strength0MPapvTable3FLAC3D numerical model geometrical, geomechanical and geotechnical para- meters.ParameterRangeRoadway hight2-3.4mRoadway width4.8-6.5mLongwall panel width200-300mPillar width15-45mDepth60-330mImmediate roof UCS8-62MPaRatio of in situ horizontal to vertical stressRock-mass stiffness dependent. Ranges from 1.2(coal) to 2.0(competent rock) for the major principal stressRock-mass stiffnessRock-mass Poissons ratio0.25 for stone,0.30 for coalThere are many theories on goaf reconsolidation, based on sound principles. Results from the various formulations do vary significantly. Which, if any, are correct is unknown, as goaf stresses have not been measured. For no other reasons than it is well described, and includes more of the parameters perceived to be important, the goaf stressstrain behaviour as defined Fig. 1. Typical 3D model geometryhorizontal section taken from the top of seam.Fig. 2. Example of FLAC3D model output.is utilised in the calculation of a stress index. The elastic FLAC3D numerical model simulates a single two-heading longwall. Roof and floor strata are composite, uniform continuum. Strong contact is assumed between the coal seam and roof and floor. No discontinuities were modelled. Pillars will always be stable, which means that the actual pillar design must be appropriate and pillars adequately sized for the strata conditions. Some rock-mass geomechanical properties may be derived from the geological strength index.5 Characterisation of installed roof supportA standard measure of the intensity of installed support, widely used within the Industry is GRSUP (ground support rating), given by 4 (6)Where Lb is the thickness of the bolted horizon defined by roof bolts (m), Nb is the average number of roof-bolts in each bolt row, Cb is the ultimate tensile strength of roof-bolts(kN), Sb is the spacing between roof-bolt rows(m), Nt is the average number of cables in each cable row, Ct is the ultimate tensile strength of cables (kN), St is the spacing between cable rows(m), w is the roadway width(m), and 14.6 is a constant that is needed to convert from the original NIOSH equation, which was in Imperial units, to SI units.Roof-bolt variables included in the installed support parameter are length, spacing within and between rows, installed density, and effective density, i.e. Cable variables included in the installed support parameter are ultimate tensile strength, capacity of end anchorage, e.g. barrel and wedge arrangement, row spacing, installed density, installed over conveyor belt structure, grouted, chemically encapsulated or point-anchored, and pretension. The statistical analysis of the database was used to propose modifications to parameters such as N (average number), C (ultimate tensile strength) and S (spacing).6 Design methodology6.1 IntroductionThe design methodology is tailored for roadway development and longwall gateroads. Roof support for bord and pillar first workings can also be assessed. Evaluating roof support using GRSM incorporates several design steps. An initial roof characterisation or classification is required, followed by a calculation of a stress index. Suggested minimum GRSUP is then determined. Finally, primary and secondary roof support patterns are proposed, also considering the influence of factors not assessed by GRSM.6.2 Rock-mass characterizationA classification is required for the immediate 2m of roof, and if a longwall retreat assessment is required, the 4m section above that. Typically, it would be expected that most practitioners would calculate CMRR. Alternatively, the GSI global rock-mass strength may be calculated. Similarly, the intact rock strength should not be overestimated, particularly when using a geophysical correlation.6.3 Stress indexTo effectively use GRSM it is important to be able to quickly and accurately calculate a stress index, without having to resort to a FLAC 3D numerical model. Equations to calculate stress index have been developed for two situations; roadway development and longwall retreat. A series of Microsoft Excel Solver analyses were conducted to define equations that could replicate this elastic numerical modelling calculation of stress index. It is recognised that there may be situations where the calculated stress index could be varied. At this stage in the development of GRSM no guidance can be offered about any adjustments. Intersections, both for roadway development and longwall retreat, have different mining-induced stress compared to roadways. Longwall start-up, before regular caving occurs, and major weighting events along the longwall face may have higher abutment stress. As a longwall approaches intersections, there may be an increase in mining-induced stress.Table4Stress index equation for roadway developmentinput parameters and constants.ParametersConstantsCMRRGSIa-7.66-7.43x1Immediate 2 m roof (eCMRR40 or GSI global rock-mass strength )b10.0330.0088x2Roadway or excavation height (m)b20.2270.227x3Roadway or excavation width (m)b30.00130.0041x4Depth of cover (m)b40.006770.00681x5Solid or rib-to-rib pillar width (m)b5-0.0013-0.0013x6Ratio of in situ horizontal stress to vertical stress for immediate 2 m roofb60.7670.772x71+sin;where is the angle between the roadway orientation and the in situ major principal horizontal stress. Only use a positive number between 0and 180b70.2800.282Table5Stress index equation for longwall retreatinput parameters and constants.ParametersConstantsCMRRGSIc-22.40-28.10y1Immediate 2 m roof (eCMRR40 or GSI global rock-mass strength )d10.7970.168y2Upper 4 m roof (eCMRR40 or GSI global rock-mass strength )d2-1.064-0.150y3Roadway or excavation height (m)d30.8170.794y4Roadway or excavation width (m)d4-0.406-0.215y5Depth of cover (m)d50.01080.0101y6Solid or rib-to-rib pillar width (m)d6-0.0129-0.0098y7Longwall panel width,rib-to-rib (m)d70.000210.00057y8Ratio of in situ horizontal stress to vertical stress for imm. 2 m roofd80.6860.690y9Ratio of in situ horizontal stress to vertical stress for upper 4 m roofd91.5530.953y101+sin-;where is the angle between the gateroad orientation looking inbye and the in situ major principal horizontal stress. Clockwise is positive. The is taken as 20. For the angle -, only use a positive number between 0and 180d100.6740.637There are 197 roadway development data points and 78 longwall retreat datapoints. The proposed roadway development stress index calculation is given by Eq.(7), with the input parameters and constants defined in Table4. The proposed longwall retreat stress index calculation is given by Eq.(8), with the input parameters and constants defined in Table5. Both Eqs. (7) and (8) have a correlation coefficient (R2) of 0.99. MPa (7) MPa (8)where, SIDEV is the stress index for roadway development, SILR is the stress index for longwall retreat, x1, x2, y1, y2, are independent input parameters, and a, b1, b2, c, d1, d2, are constants. Note that both Eqs. (7) and (8) suggest that the some parameters have little influence on the magnitude of the stress indices and need not be considered, e.g. pillar and panel width. Roadway width had little influence for the roadway development equation, but this is not the case for longwall retreat. An interesting outcome of the equation optimisation is the parameter, 1+sin(-). Essentially it says that the minimum mining induced stress does not occur when the gateroad orientation is parallel with the in situ major principal horizontal stress. The result is in general agreement with published data derived from both numerical modelling and stress measurements .6.4 Design chartsThe stablefailure boundary is determined mathematically using logistic regression, which is a statistical regression model for binary dependent variables. Logistic regression model parameters are determined using a maximum likelihood function called logitfit contained within the mathematical software package MATLAB. Orientation of the stablefailure boundary is determined by the logistic regression analysis. Fixing the position of the boundary is done by using cumulative distribution functions to minimize the number of misclassifications. The logistic regression analyses considered three independent variables; roof classification, stress index, and GRSUP. The initial stablefailure boundary was determined by cumulative distribution functions where there was the same proportion of mismatched data points either side of the boundary. However, the position of the stable/failed boundary can be changed depending on design criteria and specified risk. As the desired probability of stable outcome is increased the number of incorrectly assigned failed data points decreases. Therefore, given a design within the parametric bounds of the database there appears to be no benefit using a probability of stable outcome greater than 0.9. A reasonable conservative design could be obtained using a probability of stable outcome of 0.85 or 0.8, for a CMRR or GSI global strength classification, respectively. This level corresponds to all roof fall data points correctly assigned. Estimates of GRSUP can be calculated as follows: (KNm) (9) (KNm) (10)Fig. 3. Design chart for CMRR classification. For roadways away from intersections.Fig. 4. Design chart for GSI classification. For roadways away from intersectionsAlternatively, the design charts of Figs. 4 and 5 may be used to evaluate required GRSUP. The logistic regression analyses indicate that an improved quantification of installed support can be gained by simple modifications to the standard formulation of GRSUP(Eq.(11). Use effective installed primary support, not as-installed, but there is some subjectivity to specifying this. Use averaged bolt spacing. This is calculated as the mean of the bolt row spacing, and the average distance between bolts within a row. (KNm) (11)Where NBe is the effective installed primary support, and SBav is the average bolt spacing, both within and between rows. Empirical charts may be unreliable outside the parameter ranges within the database. Investigation of the database composition has indicated that the size of the database appears to be sufficient. At low levels of stress index there are more data points, therefore the stablefailure boundaries can be expected to be more reliably positioned. However, there are fewer data points at higher values of stress index, which means that the upper portion of the boundaries may not be well positioned, and this is confirmed by the logistic regression analyses. There are several deficiencies in the database. More longwall retreat data points at higher stress index are required. While there are a number of data points for depth of cover greater than 250 m, more are required. The database is particularly deficient of data points for depth of cover greater than 300 m. There is limited experience of mining in the Bowen Basin at depths greater than 300 m. The database requires more longwall retreat data for relatively weak roof (CMRR402.1162.51.228.9中硬20-404.7192.21.63.65.6软弱206.2321.53.154风化-7631.2583采空区应力应变可以被界定，根据先前的生产经验，根据如下（式3）： (MPa) (3)式中， 和 分别是采空区垂直应力和应变，E0 是初始切向模量，m 是膨体采空区材料的最大可能应变，BF是初始膨胀系数，m 的定义式如下： (4)初始切向模量E0 ，岩石抗压强度c，膨胀系数BF： (MPa) (5)用FLAC3D来模拟硬化材料的不可逆压缩，即容积率，除了剪切和拉伸破坏。随着塑性体积变化，上限切向体积模量和剪切模量被确定，增量切线和剪切模量也不断变化。除了剪切和拉伸强度准则，体积屈服面或上限已被定义。上限表面确定的上限压力pc ，和塑性体积应变 pv 相关。上限压力 pc ，不是采空区垂直应力 v 。上限压力和塑性体积应变之间的关系是从一个迭代FLAC2D压缩试验模型，采用一元，1m1m的网格所得出的。通过应用速度元素，仅限于侧面和底面，来模拟。假设一个线性函数，本构方程来源于由Microsoft Excel规划求解的迭代回归分析结果。采空区变形和强度参数的定义如下（表2）：表2 FLAC3D在采空区的再固结参数切线模量上界230MPa泊松比0.3密度1.7gm/cc凝聚0.001MPa摩擦角25张角2拉伸强度0MPa塑性体积应变pv表3 FLAC3D数值模型、地质力学及岩土参数参数范围巷道高度2-3.4m巷道宽度4.8-6.5m工作面长度200-300m煤柱宽度15-45m埋深60-330m直接顶的UCS8-62MPa在原水平比垂直应力岩体硬度，从1.2（煤）变化到2.0（岩层）作为主要应力岩体刚度岩体泊松比岩层取0.25,煤层取0.30有很多基于完善原则针对采空区再固结的理论，通常结果会根据不同公式变化很大。其中如果有正确的话，因为采空区应力没有测量也不为人所知。包含很多重要的参数，对采空区应力应变的定义也用在压力指数的计算中。用弹性FLAC3D数值模型模拟了两个综采面。顶板和底板岩层是复合和均匀连续的。煤层和顶底板之间联系密切。对连续性进行了建模。支柱将始终是稳定的，这意味着实际煤柱留设必须适当和充分地层条件。一系列几何特性、地质和岩土参数须在指定范围内，表3列出了一些参数的数据分布。一些岩体地质力学性能可能源于地质强度指标。5.顶板的支护特征一个广泛用于业内的支护强度的标准措施简称GRSUP，如下： (6)Lb是顶板厚度，Nb是顶板上每排锚杆的平均数，Cb 是顶板锚杆的抗拉强度，Sb 是顶板锚杆之间的排距，Nt 是每排中锚索的平均数，Ct 是锚索的最终拉伸强度，St 是锚索之间的排距，w 是巷道宽度，14.6是常数，从原来的用英制单位的NIOSH方程转化到国际单位制得出的。锚杆变量支护参数有长度、行距、排距，支护密度和有效密度等。锚索变量有极限拉伸强度、端锚固能力，例如：桶和楔形安排，行距，安装密度，
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