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By P A. Grossman, J H. Rubinstein, M Brazil

The installation of truck turntables at above-ground crushers has the potential to yield gains in efficiency and productivity by eliminating the need for the trucks to turn around and reverse up to the crusher to dump their loads. The benefits include savings in time, fuel consumption and tyre wear. In addition, having a smaller area near the crushers dedicated to manoeuvring the trucks can be a significant benefit at some sites. Safety is also enhanced using turntables.This paper describes a project with the Australian Turntable Company to develop software that generates near-optimal layouts for the paths taken by the trucks in the vicinity of the crushers when turntables are present or absent. The geometry of the paths is constrained by the turning radius of the trucks and by the boundary of the manoeuvring area. The software quantifies the benefit of installing turntables by generating a design for paths with turntables and comparing it with the layout in current or planned use by the mining company. Through the use of this software tool, a mining company can readily assess the benefits of using turntables at their site.CITATION:Brazil, M, Grossman, P A, Rubinstein, J H and Thomas, D A, 2014. Demonstrating efficiency gains from installing truck turntables at crushers, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 259–266 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By D Kentwell

A resource model serves two main purposes depending on the stage of a project. The first is to provide an early indication of likely tonnages and grades at certain cut-offs so that decisions can be made on whether continued spending on the project is justified. The second is to provide a basis for mine planning, feasibility studies and reserves. Resource models are not designed for selection of actual blocks in the ground for processing. This is the purpose of a grade control model, which is created at a stage beyond both resources and reserves.Inferred, Indicated and Measured Resources contain different levels of uncertainty with respect to the accuracy of the resulting grade and tonnage curves. These uncertainties arise from three broad areas: quality of information, geological assumptions and estimation technique. This paper focuses on known problems with the ordinary kriging (OK) estimation technique. Resource estimates often produce smoothed block grade distributions with much lower block grade variability than true selective mining unit (SMU) block grade distributions. There are two main factors that are involved in this smoothing. Firstly, where the block size used for estimation is larger than the SMU block size, this will smooth the block grade distribution and move the grade and tonnage curves away from the true SMU block grade and tonnage curves. Secondly, and less well recognised, is that smoothing is inherent in the OK estimator. This also moves the grade and tonnage curves away from the true SMU grade and tonnage curves, even when the estimate is done at the SMU block size. There are a number of techniques, such as simulation, uniform conditioning and degraded search neighbourhoods that can provide a better approximation of the true SMU block grade and tonnage curves at the expense of individual block accuracy.This paper aims to explore the extent to which OK resource estimates designed to maximise individual block accuracy can differ from (an estimate of) the true resource at SMU block size in terms of grade and tonnage curves. The differences at economic cut-offs and above are examined. In some cases these differences are significant. Both the OK estimation technique and block size play a part in the differences observed. To do this we will examine a number of commodities and deposit types using real project data.The conclusion is that the current industry standard default practice of targeting maximum individual block accuracy (conditional unbiasedness) using OK at resource stage, without consideration or evaluation of the extent of associated smoothing at SMU scale, can lead to significant errors in fundamental mine planning decisions. This then has implications for resource classification if the classifications are based heavily on the OK quality without consideration of the true SMU distribution.CITATION:Kentwell, D, 2014. Aligning resource estimates with mine planning, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 185–192 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By J Deraisme, P Epinoux, O Bertoli

"Société le Nickel exploits the Dôme lateritic nickel orebody at its Tiébaghi operations in New Caledonia. The site geology has an obvious bearing on recovery and metallurgical performance, with controls that are extremely complex at all scales, including lithology, oxydo-reduction conditions, mineralogy and multivariate geochemistry. In this context, establishing an adapted recoverable resource estimation method that is efficient and transparent proves an interesting challenge. The method must address the key notions of: support effect – the exploration data set can only warrant the estimation of large panels of 20 × 20 × 3 m3 that are much larger than the selective mining units (SMUs) of 5 × 5 × 3 m3 information effect – the selection at the production stage uses estimates based on information that is much denser than that available for mine planning.The problem is rendered more complex in this type of deposit by the fact that the additive variables used for the estimation (metal accumulation and ore tonnage) are not the ones used to establish the selection at the mining stage (ie the nickel grade of SMUs, which is the ratio of accumulation on tonnage). Eventually, the selection criteria not only involve Ni grades, but also other elements such as Al2O3, Fe2O3, MgO and SiO2.The solution presented in this paper is to construct an SMU multivariate simulation in the saprolitic horizon and construct an efficient post-processing aimed at producing multivariate recoverable resource estimates. The efficiency constraints imposed by the number of blocks to be simulated (1.5 million) lead to resorting to direct block simulations. The underlying multivariate discrete Gaussian model, which had its validity tested beforehand, is put to good use to mimic the selection process that happens at the mining stage by offering the ability to simulate a composite value located at random within each block.The paper also presents the application of a scenario reduction algorithm to pick a representative subset of a few simulations to help appraise the risk attached to the downstream (reserve optimisation and mine sequencing) phases of the project. The original version of the paper (see Deraisme, Bertoli and Epinoux, 2014) used an early version of the scenario reduction plug-in (named S2RM) built in Isatis® software, where measuring the distance between the initial set of scenarios and the reduced set was based on Ni only. The implementation presented here is for the second generation of S2RM, where measuring the distance between the initial and the reduced set of realisations is based on all study variables. The benefits of the measure adapted to the true multivariate nature of the problem are highlighted in this updated version of the paper.CITATION:Bertoli, O, Deraisme, J and Epinoux, P, 2014. Multivariate block simulations of a lateritic-type nickel deposit and post-processing of a representative subset, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 99–108 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 24, 2014

By M Recabarren, A Echeverria, J Ronda, J I. Guzman, R Dodds, G Juarez, E Vila-Echague

A strategic mine plan is a fundamental part of any mining operation. It must provide a realistic and operative extraction and processing schedule, and yield the highest value for the business. For open pit mines, the problem can be modelled as a set of blocks representing the deposit, for each of which we need to decide if it is going to be mined, if so, when and where it will be sent (process, stock or dump).This problem can be proven to be of NP-Hard complexity. The traditional approach used by mining engineers to tackle this complexity is to separate the problem into more tractable components, solving each separately. The first step is to use the Lerchs-Grossman (LG) algorithm to obtain the final pit limit, as well as a set of optimised pit shells (nested pits), using different input prices. Then, using this input, operational phases are designed. Third, the set of phases can be used as an input for a phase-bench style optimisation, usually using a mathematical programming-based algorithm.There are, however, several problems with this approach. First, dividing the problem into simpler parts has the consequence that any compromises made at early stages limit the potential value left for the following steps. Second, LG is a static algorithm, with no concept of the time-value of money, capacity limits, opportunity costs, etc. Phase design is essentially a manual step, for which nested pits provide insufficient information in practice, and therefore the quality of the result in terms of potential net present value (NPV) depends strongly on the experience and expertise of the designer. This means that key input data such as commodity prices, different processes capacities and mine movement limits, are considered only at scheduling, when there is little room for optimisation. This sequential approach limits the potential value in each step, where a simplified problem is addressed, instead of addressing the real, and more complex problem, which is dynamic and should be solved as a whole.We present in this paper an algorithm, and its commercial software implementation, that addresses the dynamic problem as a whole, simultaneously and automatically creating a high-value strategic mine plan that adheres to basic operational constraints, determining dynamic cut-off grades and delivering a set of phases which can serve as a much stronger guide than nested pits for the final design. We discuss some of the key elements of the algorithm and propose a new methodology for strategic mine planning, where phase design dynamically responds to mining strategy definition. Results using different mining and operational parameters on a fictitious copper deposit are used as a demonstrative example.CITATION:Juarez, G, Dodds, R, Echeverria, A, Guzman, J I, Recabarren, M, Ronda, J and Vila-Echague, E, 2014. Open pit strategic mine planning with automatic phase generation, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 147–154 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By R Dimitrakopoulos, K Kawahata, L Montiel

A method that optimises mining complexes that are comprised of multiple processing destinations, open pits and underground operations is presented. Mining, blending, processing and transportation decision variables are simultaneously optimised while accounting for geological uncertainty. The method uses a simulated annealing algorithm at different decision levels to generate a stochastic-based extraction sequence and processing policies. A case study shows its ability to generate a higher net present value while facing a reduced amount of risk when compared to traditional optimisation methods.CITATION:Montiel, L, Dimitrakopoulos, R and Kawahata, K, 2014. Globally optimising open pit and underground mining operations under geological uncertainty, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 201–212 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By D J. Thobaven

Project financing challenges caused by declining commodity prices have heightened the need to improve project metrics such as minimising capital payback and maximising net present value (NPV). Khnaiguiyah Mining Company (KMC) recognised the need to improve early cash flows at their Khnaiguiyah zinc-copper project after initial studies showed the project could not provide the desired financial outcomes necessary to compete for investment dollars in the current market.A significant improvement to the project cash flow in early years was realised through simultaneous optimisation of cut-off grade, mining sequence and strategic stockpiling. This improvement was achieved by accelerating mining in the pits, stockpiling lower value material and feeding higher value material directly to the plant. The schedule required higher mining and stockpile capacities than the sequential mine plan although minimal change occurred in the definition of ore and waste as measured by tonnes and grade. The practicality of the strategic schedule was demonstrated by implementation in the production plan with excellent conformance.CITATION:Thobaven, D J, 2014. An application of simultaneous optimisation – improving the payback period of a zinc-copper open cut project, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 137–144 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By K G. van den Boogaart, U Mueller

"An accurate prediction of benefit for some types of ore may require not just the ore grade, but a whole compositional characterisation of the estimates; that is, its full mineral composition including waste composition and nuisance elements. An example is Nickel laterite ores, where Ni/Co content must be complemented by estimates of many other elements, as these might have a notable impact on ore processing.Estimates are often obtained with (co-)kriging or co-simulation; however, geostatistics applied to compositional data may yield spurious and inconsistent results because of the constant sum constraint. The log-ratio approach avoids such problems. It proposes a three-step procedure: data are mapped to a set of log ratios of components; for example, the additive log-ratio transformation (alr) transformed scores are modelled with an appropriate fully multivariate geostatistical toolbox; for example, direct/cross-semivariograms and co-kriging or co-simulation results are back-transformed to the original units.Some practical aspects may make the application of this technique difficult: the assumption of Gaussianity and the high dimensionality of the compositions combined with the need for using multivariate methods. This contribution compares several ways of treating compositional data (combining normal score transformation, log-ratio transformations, and minimum/maximum autocorrelation factor (MAF) decomposition) with respect to their ability to generate sensible simulations. The various approaches considered are illustrated with a Nickel laterite data set for which ten variables are available. Both theoretical considerations and illustration results suggest that the best combination is (log)ratio-normal score transform-MAF, in this order. The factors so obtained are closer to Gaussian, approximately spatially decorrelated and can be simulated independently. Simulations can later be recombined to alr-simulations, which in turn may be converted back to point compositions. The resulting simulated compositions are compared with a full Gaussian co-simulation of the raw data. The log-ratio methods show reasonable to good reproduction of mean values, and distribution of the data set and by construction satisfy the total sum constraint, in contrast to the simulations based on raw data for which the total sums fluctuate strongly.CITATION:Mueller, U, Tolosana-Delgado, R and van den Boogaart, K G, 2014. Approaches to the simulation of compositional data – a nickel-laterite comparative case study, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 61–72 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 24, 2014

By L Blackwell

Strategic mine scheduling is an industry best practice for increasing the long-term value of mining operations and supply chains. The application of optimisation technology such as mixed integer linear programming (MILP) is able to achieve a mathematically optimal result for a given scheduling model. Such a model will typically define the available source material, processing options and desired constraints for accessing and processing the material. Most strategic scheduling models, however, do not include a sufficiently detailed model of capital expenditure options related to capacity expansion.Typical strategic schedule models do not include important capital expenditure features such as capacity decay or expiration (limited lifespan of trucks), precedence relationships over time (rail construction before a new plant or non-linear expansions due to economies of scale) or mutually exclusive option sets (choices of plant size). By not including these features, a strategic mine scheduling model for a capital-sensitive operation is unable to be optimised to deliver maximum value or profitability.This paper presents several results of MILP optimisation using advanced capital expenditure modelling for mining operations and supply chains. Results of the study demonstrate that optimising capital expenditure at the same time as optimising the mining schedule allows for minimisation of capital purchasing, optimal timing for those purchases and optimal scheduling around them. Overall, this results in an increase in net present value.CITATION:Blackwell, L, 2014. Capital expenditure modelling for strategic mine scheduling, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 315–322 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By J McCluskey, N Barros

"Long-term strategic planning at BHP Billiton’s Western Australia Iron Ore business aims for sustainable value maximisation of its large, long-life, low-cost, expandable mineral inventory and supply chain infrastructure. While mine plans are key components of this value equation, this objective requires a whole-of-business approach through comprehensive consideration and optimisation of the full value chain. Only through a system view do we believe that the value proposition of a set of plans is truly optimised.The fundamental considerations include: mineral inventory information, given its intrinsic uncertainty and risk/knowledge horizon a marketing view of future quality premium/discount based on overall market quality load whole of supply chain optimisation on a throughput accounting basis alternative sequences of capital decisions closure costs with significant magnitude of total movement requiring optimisation as part of the plan. In addition, the plan provides a view of acceptable uncertainty levels at different times in the future.BHP Billiton Iron Ore uses a structured Life of Asset planning process that supports the business with the optimisation of its maximum value proposition through a non-deterministic scenario-based optimisation approach on an annual basis. This is a key input to each year’s medium-term plans and budgets, including activities identified through a value of information approach that resolve the key uncertainties and steadily improve confidence in the plan.CITATION:McCluskey, J and Barros, N, 2014. Life of asset planning, uncertainty and value optimisation of the iron ore business – from exploration, to market, to closure, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 33–40 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 24, 2014

By B King

Processing expansion options and mining fleet purchases are major cost items that receive due focus in most cost management analyses. If these items are not needed, they can significantly reduce a project’s short-term capital spend and improve profitability and value to shareholders. When conditions change prior to purchasing equipment, the purchase may no longer represent the best decision for the project.This paper outlines a structured approach for making major cost decisions to improve the value of a project, determining which items should be kept and which should be eliminated.CITATION:King, B, 2014. Cost management optimisation, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 7–12 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By K G. van den Boogaart, M Lehmann, U Mueller

Geometallurgical parameters are descriptions of the mineralogy and microstructure of the ore determining its mineralogical and microstructural characteristics. From a conditional geostatistical simulation of such properties, a processing model can compute recovery, equipment usage, processing costs, and thus the monetary value for mining and processing a block with certain processing parameters. The output can be used for optimising mining sequences or finding optimal processing parameters by solving the corresponding stochastic optimisation problem.The approach requires two properties of the simulation not provided by established geostatistical techniques:Many relevant geometallurgical parameters are from non-Euclidean statistical scales such as (mineral) compositions, (grain size) distribution, (grain) geometry, and (stratigraphic type) categorical, which might produce nonsensical values (for example, negative proportions, negative facies probablities, planar grains) when simulated with standard geostatistical techniques.Due to the nonlinearity of processing, the entire conditional distribution of the geometallurgical parameters is relevant, not only its mean and variance. The geostatistical simulation needs to reproduce the joint conditional distributions of all the geometallurgical parameters.The multipoint conditional geostatistical simulation technique discussed here allows for jointly simulating dependent spatial variables from various sample spaces. The technique combines an infill simulation, similar to the one used in multipoint geostatistics, with a new form of distributional regression to estimate conditional distributions of arbitrary scales from different information sources, including training images, training models and observed data. The distributional regression is based on a generalisation of logistic regression and is related to both Bayesian Maximum Entropy geostatistics and high order cumulants.The method ensures that simulated data reside in the set of possible values and honour the characteristics of the joint distribution to be reproduced. The computational effort is substantial, but affordable for a useful application with standard problems: from processing-aware block value prediction and block processing optimisation as shown in the test application to a mathematically completely defined simulated model situation with a complex processing model.CITATION:van den Boogaart, K G, Tolosana-Delgado, R, Lehmann, M and Mueller, U, 2014. On the joint multipoint simulation of discrete and continuous geometallurgical parameters, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 379–388 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By M Astorga, J Jackson, J Gaunt

The Ban Houayxai mine (BHX) is a relatively low-grade, low-cost, open pit gold-silver deposit in Laos operated by Phu Bia Mining, a subsidiary of PanAust. The ore production rate at BHX is 4.5 Mt/a, with direct tipping to a semi-autogenous grinding/ball mill circuit with a carbon-in-leach process plant. Approximately 100 000 oz of gold is produced per annum.The operation is located in mountainous terrain with minimal run-of-mine stockpiling. This results in limited capacity for blending from stockpile, with the mill instead reliant upon direct feed ex-pit. Since commissioning in 2012, the plant has seen significant variation in milling rates due to variability in the feed properties of the oxide, transition and primary ores. As part of an ongoing continuous improvement program, an integrated approach was initiated, focusing on maintaining and enhancing production in the future as the proportion of harder primary ore increases. This will specifically focus on direct blending from the loading face using the ore properties and blast fragmentation to maintain mill throughput.This approach was based on the concept of physical assets management, commencing with improving information and knowledge of the condition of the orebody through modelling the characteristics, variability and performance of the feed for processes relevant to throughput. These models are used to support both mine and process plant production planning.The key ore feed characteristics and parameters modelled for the life-of-mine are blastability index, powder factor, crushability or impact resistance and grindability. These predictive spatial models were based on the data from diamond drill holes used in resource definition and geotechnical drilling programs by integrating geotechnical, geological, geochemical and metallurgical data.At the early stages of implementation, the models are being utilised for ore blending decisions to provide guidance and support for budgeting, long-term mine planning, blast design for mill feed and providing the mill with an expectation of performance.CITATION:Jackson, J, Gaunt, J and Astorga, M, 2014. Predicting mill ore feed variability using integrated geotechnical/geometallurgical models, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 165–176 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By B Jones, M Chappell

Installing ground support correctly is not an easy task, whether lack of operator training, poor ground conditions or underperforming equipment. Confirming the quality of installation can help with planning and remedial works and help to maintain a safe working environment. A 2?m bolt with 700?mm of encapsulation will pass a 10?t pull test (assuming ground conditions permit); however, it will not provide any data of the unencapsulated length and thus the ability to withstand corrosion. Complimentary testing in the form of non-destructive testing (NDT) can provide factual data that leads to the assessment of the quality of the encapsulation. By improving the quality of the encapsulation, the risk of corrosion is reduced, the ground support durability is improved and hence the asset life is enhanced.This paper presents a case study of a trial using the NDT system RokTel™. Installations of varying quality were installed and tested. The characteristics tested were corrosion, load and free length. These characteristics can be tested and assessed for cable bolts, thread bar bolts and split sets. The aim of this paper is to present NDT testing as a viable method for assessing installation quality and ongoing performance of the ground support.CITATION:Jones, B and Chappell, M, 2014. A non-destructive testing method for measuring bolt condition, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 307–314 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By R Ahola, M D. Henschel, M A. McParland

With the introduction in recent years of third-generation interferometric synthetic aperture radar (InSAR) techniques, monitoring of mine slopes, benches and surrounding areas has benefitted from increased accuracy and coverage. Fundamental research into point and distributed scattering techniques has pushed the use of InSAR to provide higher spatial and height resolution. In this paper we discuss the operationalisation of third-generation InSAR techniques and show its application to active mining operations.This paper will discuss the use of multiple independent measurements of ground movement obtained from operationally-derived InSAR products over a wide variety of deformation areas within an active open pit mining operation (ie pit slopes, dewatering depressions, tailings containment and waste dumps). A technique that shortens the time between observations (increased observation frequency) and provides ongoing estimates of measurement accuracy will be described. The methodology exploits available satellite data by using multiple satellites and multiple beams. The paper will also examine factors in the design of a mine survey with third-generation InSAR and illustrate some of the necessary engineering trade-offs to efficiently monitor a mine from space.Overall, this paper aims to demonstrate the capabilities and advantages of operational third-generation InSAR techniques for ground movement monitoring of mining operations and provide a framework for proper design of a mine InSAR survey.CITATION:Henschel, M D, Sato, S, Ahola, R and McParland, M A, 2014. Designing interferometric synthetic aperture radar surveys for mine monitoring with accuracy assessment, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 233–238 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By I D. Gregson, A Gandhe, A S. Garcia, K M. MacAndrew

"Falls of ground still cause around one-third of all underground mining fatalities. The recent introduction of mechanised room and pillar working into Indian coalmines is an example of the application of new design by measurement and safety monitoring strategies, which can be used to reduce falls of ground risks in mines.Rock Mechanics Technology, now part of Golder Associates UK Ltd (Golder), is providing rock bolt support and pillar design services to the mines using a design by measurement approach. This involves in situ monitoring to confirm support and pillar designs and pillar extraction sequences.Site examples are given of the support designs determined and the monitoring programs undertaken for both design and safety.Routine safety monitoring of roof movement using telltales is also described. A new auto warning telltale has been developed specifically to warn of imminent caving as pillars are extracted.The approach used by Golder has played a major role in ensuring the success of these projects. As a consequence, mechanised room and pillar working is now firmly established in India, and wider application is planned to help meet future demand for coal.The experience confirms that the design by measurement method for this application has important advantages over conventional design approaches using analytical or empirical methods. Firstly, it measures the design performance or outcome rather than trying to calculate or predict it. Secondly, it provides the opportunity for the design to be adjusted to obtain the optimum outcome. Thirdly, it can do this at a local level, so that the support design can be matched to changing conditions to give the most cost-effective design. Finally, it incorporates long-term monitoring of support performance, again at a local level, so that subsequent change can be identified to enable corrective measures to be implemented in a timely manner and to ensure that ground control safety is maintained.CITATION:MacAndrew, K M, Garcia, A S, Gregson, I D and Gandhe, A, 2014. Application of design by measurement for support and pillar design in mechanised room and pillar coal mining in India, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference, pp 65–76 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 5, 2014

By F M. Weir, M Fowler

The design of excavations in rock must, implicitly or explicitly take into consideration the influence of small- and large-scale geological structures. For most sites the complexity of a fractured rock mass is best captured using a 3D fracture system model based on field data. A discrete fracture network (DFN) approach involves stochastic modelling of the ‘smaller scale’, nondeterministic structures. For slope stability or tunnelling projects DFN modelling provides a valuable geotechnical tool for characterisation of a rock mass and identification of likely failure mechanisms.This paper presents a suite of the DFN modelling undertaken for the design of a large open pit in Australia. The proposed pit is to encounter a 160?m thick, high strength, sheared shale unit, which overlies a crystalline basement. DFN modelling was undertaken separately for both the shale and basement units. While the model inputs and development for each unit are briefly presented, the focus of this paper is on the various applications of the DFN modelling.A key advantage of the DFN approach for design studies is its probabilistic application to structural analyses and results. Multiple realisations of the same model were generated for both the shale and basement units, with the stability analysis carried out on each iteration. The generation of a large number of DFN models and analyses allow assessment of wedge volume, factor of safety and proportion of unstable slope for a range of conditions. The DFN modelling at the case study site was also utilised for a number of other purposes. For example, investigation of likely fault lengths in the shale unit and combined rock mass and defect failure. The development of this tool has been influential in improving our understanding of fracture networks for excavation design.CITATION:Weir, F M and Fowler, M, 2014. Rock mass characterisation and analysis for excavation design – a discrete fracture network approach, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 445–456 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By A M. Suchowerska, J P. Carter, J P. Hambleton

"In order to effectively predict the roof collapse of underground openings using continuum models, it is imperative that a realistic failure criterion is used to represent the rock mass. However, for coal mining operations, there is still uncertainty as to the appropriate failure criterion that should be used for the coal measure strata. This study compares stability numbers and collapse mechanisms for a rectangular underground opening predicted based on three commonly used failure criteria: the standard Mohr-Coulomb, Mohr-Coulomb with a tension cut-off and Hoek-Brown. Three methods of analysis are considered: an analytical upper bound method an upper and lower bound finite element formulation the displacement finite element method.The theoretical results are also compared with field measurements of subsidence above longwall coal mining. For the standard Mohr-Coulomb failure criterion, the friction angle governs the shape of the collapse mechanism, and the so-called critical width (the cavity width above which failures extend to the ground surface) ascertained from field observations in the New South Wales coalfields corresponds to a friction angle of approximately 30°. On the other hand, predictions obtained based on the Hoek-Brown failure criterion consistently overestimate the critical width. The results also show that tensile failure governs the stability of the cavity and shape of the collapse mechanism when a tension cut-off is introduced for the Mohr-Coulomb yield criterion.CITATION:Suchowerska, A M, Hambleton, J P and Carter, J P, 2014. Prediction of roof collapse for rectangular underground openings, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference, pp 367–374 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 5, 2014

By R Bertuzzi

"This paper presents preliminary results of ongoing research being carried out at the University of New South Wales Australia (UNSW) into improved methods for estimating rock mass strength. In this paper the rock mass strength of Hawkesbury Sandstone is assessed. An estimate is first made based on an extensive database of intact rock strength data being collated by the author and the assumption that rock mass strength can be determined following the geological strength-index (GSI) approach. The resulting strength envelope is then compared with nine documented case studies where stress induced failure has occurred in tunnels excavated within Hawkesbury Sandstone. The case studies cover a range of conditions: construction dates from 1880s to 2006 spans from 3.2 to 12.5 m depths from 17 to 124 m excavation methods of drill and blast, roadheader and tunnel boring machine (TBM).Finite element modelling is used to assess the likely magnitudes of the principal stresses that were present at the time of the failures. The finite element models are interrogated to provide the values of major and minor principal stresses in and around the mapped failure zones. Failure and stable points are then compared to the proposed strength envelope(s) of Hawkesbury Sandstone derived using the Hoek-Brown and the spalling criteria. The ability of the Hoek-Brown rock mass strength criterion to differentiate between the ‘failed’ and ‘stable’ zones is considered to be remarkable.CITATION:Bertuzzi, R, 2014. Estimating the rock mass strength of Hawkesbury Sandstone, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference, pp 417–424 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 5, 2014

By P C. Hagan, J Chen, S Saydam

Fully grouted cable bolts have been used in underground mining industry for more than 40 years and are becoming more and more popular especially when severe geological conditions are encountered, such as high stresses and large cross-section excavations. The axial performance of cable bolts are mainly relied on the load transfer process between the cables themselves and surrounding rock masses via grout annulus. Therefore, the selected grouts play a significant role in determining the reinforcement quality for underground openings. In order to better understand the mechanical properties of Stratabinder HP grout, which is one type of cementitious grouts commonly used in Australian underground coalmines, plenty of unconfined compressive tests are conducted on it. Following diverse standards, two different kinds of samples are prepared and tested with the w/c ratio ranging from 0.35 to 0.45. During the test important mechanical properties including uniaxial compressive strength (UCS) values, Young’s modulus, Poisson’s ratios and so forth are recorded. Based on experimental results, the effect of w/c ratio on the mechanical properties of Stratabinder HP grout is studied. Beyond that, influences of sample size on the failure mode, peak strength as well as residual strength of this kind of grout are summarised and analysed.CITATION:Chen, J, Hagan, P C and Saydam, S, 2014. Mechanical properties of cementitious grout serving in fully grouted cable bolting systems, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 269–276 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By J Samosir, L A. Snyman

Northparkes is located 27 km north of the township of Parkes in central New South Wales, Australia. The operations consist of underground block cave mines and an ore processing plant that produces high-grade copper and gold concentrate. Production is currently sourced from the E48 Lift 1 block cave mine and open cut stockpiles. Mining commenced at Northparkes in 1994 as an open cut operation. Underground block cave mining began in 1997. Northparkes was the first mine in Australia to use the highly efficient block cave mining method, which relies on gravity and natural rock stresses to fragment the ore.An issue affecting production in 2011 was the stability of the E48 mine. A small portion of the drives on the extraction level began to deteriorate as the ground support system failed. The problem was temporarily fixed by stopping production in three extraction drives and tight filling selected areas within these drives (and drawpoints) with low-strength concrete. This action provided immediate support and stability whilst allowing time to investigate potential ground support remedies. From these investigations it was decided to use resin injection technology and additional ground support to stabilise the rock in the aforementioned extraction drives as the concrete plug was excavated in a controlled advance and sequence. This made the area safe and ensured the ongoing safe operation of the E48 mine. The redevelopment of one of these drives began late in 2011, with the remainder being progressively redeveloped over the next two years in order to maintain the extraction level stability.This paper looks at the strategies employed to safely re-open previously converged drawpoints and associated extraction drives that were subject to high abutment loading that was possibly associated with premature cave breakthrough.CITATION:Samosir, J and Snyman, L A, 2014. Redevelopment at Northparkes following significant drive closure, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 87–92 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014