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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 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 P Malkin, S Thomas, P M. Stone, D Kostyuk

In open pit mining, it is common that the bottleneck to productivity and profit lies in the truck-shovel mining operation, especially as strip ratios and mining intensity have increased with resource depletion and advances in mining equipment capabilities. This paper outlines a study of truck-shovel productivity using a new proprietary discrete event simulation platform for truck-shovel operations called MineDES. The study will specifically address the issue of whether truck queuing at shovels should be considered productive or not, and how mining engineers can determine the optimal truck fleet size for specific operational configurations.The MineDES simulation platform will be described and illustrated, highlighting the features that make it an appropriate tool for conducting the experiments at the heart of this study. The study encompasses a set of experiments, consisting of a number of simple truck-shovel operational scenarios for a benchmark open pit mining operation, which are simulated using MineDES. Each experiment is designed to highlight different factors, which are most important in calculating the ideal truck fleet size and for understanding the marginal productive impact of each additional truck added to the fleet. The scenarios will principally address the issues of how different types and levels of unscheduled equipment downtime and process variation, combined with the traffic delays/congestion arising in more intense mining operations, will affect productivity. The results of the experiments are interpreted using a simple fit-for-purpose cost and revenue model in order to highlight the indicative cost of over- or under-trucked configurations.The study has found that the optimal fleet size that maximises productivity and value will, in the presence of even small process variation, lead to non-zero trucks queuing at shovels on average. As process variations and unscheduled downtime events increase in the truck-shovel system, the required fleet size to optimise productivity and value increases. MineDES provides a convenient platform for quantifying this for real operations.CITATION:Kostyuk, D, Thomas, S, Malkin, P and Stone, P M, 2014. Is truck queuing productive?, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 267–274 (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 E Lima, D Gregory, C Faria, A Lapworth

Open pit mine enterprises are complex systems that depend on multiple parameters such as mineral grade distribution, geotechnical characteristics, economic conditions and engineering requirements, all of which vary in time and space with a different degree of uncertainty. The unpredictable nature of these inputs imposes a risk to mine owners and shareholders which in the worst case can lead to highly undesirable financial outcomes.Desktop studies commonly examine a set of scenarios based on adjusting variables such as commodity prices, mining costs, processing costs, and metal recoveries to understand their relative impact on the economics of a project. It is less common to systematically explore and simulate hundreds of alternative physical designs to understand and compare the financial risk associated with one or more mining projects.This paper presents a risk assessment tool set and methodology that uses web based cloud computing to enable multiple simulations of mine designs to be rapidly and efficiently executed. The methodology includes generating random sets of prices and costs values within their respective probability distributions. Pit designs are then created to maximise the profit for each set of input variables. Various approaches to analysing the results are discussed. Use of the same high performance computing environment for understanding the financial risk associated with the variability of the underlying geological resource model is also discussed, with provided examples using case studies from two of the major mineral producers.CITATION:Lima, E, Gregory, D, Lapworth, A and Faria, C, 2014. Simulating extraction shapes to understand financial risk using high performance computing, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 351–360 (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 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 H Askari-Nasab, E Torkamani, M M. Badiozamani, S P. Upadhyay, M Tabesh

"Decision-making in mining is a challenging task. Optimal decisions regarding shovel and truck allocations, aligned with the optimal short-term production schedules, are crucial in keeping the operations in line with the company’s long-term objectives. In this paper, we present two main modelling components as the means to achieve near-optimal operational plans: a mixed integer linear goal programming model to allocate trucks and shovels to mining faces over a shift-by-shift basis so that operating costs are minimised and resource utilisations are maximised through the planning horizon a discrete-event simulation model to investigate the behaviour of a truck-and-shovel haulage system in the presence of uncertainty within mining operations. The goals integrated into the mathematical model are to: maximise production minimise deviations from the target head grade minimise deviations in tonnage feed to the processing plants from the desired feed minimise operating cost.The mathematical model provides shovel assignments and the target productions as an input to the discrete event simulation model while meeting the desired goals and constraints of the mining operation. We illustrate the applications of the discrete event simulation model by presenting a large-scale oil sands case study. The main contribution of this work thus far is the development, implementation and verification of a simulation model with a link to optimal short-term mine schedule and extraction sequence of mining faces, which assists in achieving a high level of mine plan compliance across short-term planning and operational planning time horizons.CITATION:Askari-Nasab, H, Upadhyay, S P, Torkamani, E, Tabesh, M and Badiozamani, M M, 2014. Simulation optimisation of mine operational plans, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 299–312 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 24, 2014

By Y Li, S Ramazan, E Topal

A mine waste dump progression plan can provide a clear outlook of the mining operation. To produce such an output requires detailed placement schedule of the mined material, including the volume (or tonnage) and the allocated dumping location. However, current practise mainly focuses on the ore production, over-simplifying the waste material scheduling. As a result, a rock dump is often treated as a single point in long-term planning, making it difficult to predict the waste dump progression pattern over the life-of-mine. Without such a guidance, it is almost impossible to carry out progressive rehabilitation on the waste rock dumps. The lack of dumping schedule could cause delay in development construction, ie tailing storage facility and run-of-mine pad. Other downstream effect due to the over-simplification is inaccurate estimation of required truck hours, which could have huge financial impact on the operation.In this paper, mixed integer programming (MIP) models of different objective functions, ie maximise truck productivity by minimising the overall haulage distance, minimise required truck deviation between adjacent years, and a hybrid between the two objectives, are utilised to generate the long-term optimum rock placement schedules under the criteria of satisfying site specific conditions. All three MIP models are implemented in a large scale open pit mine. The numerical solutions from the models forms three different rock placement schedules, based on which, the yearly truck requirements are easily calculated and compared. The graphical results show the three corresponding waste dump progression patterns over the life-of-mine, providing the optimised long-term forecast of the operation.CITATION:Li, Y, Topal, E and Ramazan, S, 2014. Optimising the long-term mine waste dump progression and truck hour schedule in a large-scale open pit mine using mixed integer programming, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 335–344 (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 G S. Esterhuizen, M M. Murphy, T S. Bajpayee

The strength reduction method (SRM) has been implemented in the FLAC3D finite difference software and applied to coalmine entry support evaluations. The FLAC3D numerical models have been calibrated against instrumented field sites in varying geologies, depths and field stress conditions. The calibration between the field and model results obtained a satisfactory match for rock deformation and support response. Previous research has also developed good correlations between numerical model stability estimations using the SRM and empirically derived stability estimations using the analysis of roof bolt systems (ARBS) software and the coalmine roof rating (CMRR). The purpose of this paper is to further apply the SRM to investigate how specific geotechnical and support parameters can impact coalmine entry stability. Results from different studies demonstrate how the calibrated models were used to investigate a few of the well-known questions in both mine design and support design. For mine design the impact of strong and weak beds in the roof strata, rotating the principal stresses and weakening the floor on excavation stability is investigated. For support design the impact of support length, support spacing and adding cable bolts to the design is demonstrated. These scenarios are evaluated in developmental coalmine entries for a variety of geology and field stress conditions. Stability factors are calculated for each scenario using the SRM. The SRM allows the impact of each parameter to be quantified and allows the support system to be optimised for given geotechnical conditions.CITATION:Esterhuizen, G S, Murphy, M M and Bajpayee, T S, 2014. Analysis of geotechnical and support parameters on coalmine entry stability using the strength reduction method, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 383–392 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 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 M J. Dunn

The geotechnical model is the cornerstone of any mining geotechnical design and as such the confidence level and reliability of the geotechnical model is paramount. The geotechnical model confidence level needs to be commensurate with the level of design that is being applied or study that is being undertaken. The geotechnical model is made up of several components and the reliability of the data underlying these components ultimately determines the reliability of the geotechnical model.Data reliability is linked to the quantity of data collected, the spatial distribution of the data collected, quality of the data collection and the interpretation of the data. In a typical project, there is an opportunity to improve data reliability through the scoping, prefeasibility, feasibility and final design and implementation stages.Currently, very little quantitative guidance exists in the literature on assessing the confidence level of geotechnical studies, although there have been attempts by various authors (Haile, 2004; Haines, Swart and Kruger, 2006; Read and Stacey, 2009; Dunn, Basson and Parrott, 2011) to qualitatively describe what level of geotechnical data is required. Recently a number of authors (Read, 2013; Fillion and Hadjigeorgiou, 2013; Thomas, 2013) have outlined methods that could be applied to assess the reliability of some types of geotechnical data that are used in the development of geotechnical models.This paper briefly discusses some of the factors influencing data reliability and the geotechnical model confidence and some of the tools available.CITATION:Dunn, M J, 2014. Geotechnical models and data confidence in mining geotechnical design, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 127–134 (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 Duran

When dealing with rocks in the geotechnical profession, a common activity involves providing an estimate of the intact strength. The tactile approach and descriptions of strength that apply to soils is well documented, can be readily checked through the use of a pocket penetrometer and are known to provide reliable estimates of strength. Moreover, although different soil strength classification systems are present, the bounds between classification classes are compatible across almost all documented classification systems. However, this is not the case for rock strength materials. There are numerous systems within the literature, some with different concepts, and almost all have different bounds to each strength classification. In this paper, the author presents seven classification systems for estimating intact rock strength and highlights issues in their implementation. Example cases are presented to discuss the typical concerns confronting field strength estimates.CITATION:Duran, A, 2014. Comparison of field estimated strengths, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 101–106 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

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

The design work undertaken by Rock Mechanics Technology (now part of Golder Associates (Golder)) has played a major part in successfully establishing mechanised room and pillar working in Indian coalmines, both for the development of new districts and for the re-establishment of old districts prior to pillar extraction on panel retreat.Golder has used appropriate design of pillars, extraction sequences and final snook sizes to minimise ground control risks during pillar extraction. Where the strata will not cave reliably, partial extraction systems leaving either a crush pillar or a substantial yield pillar have been adopted.Remote monitoring of selected pillars during the extraction process using stress cells, extensometry and convergence measurements provides confirmation of pillar behaviour and verification of designs.A new telltale device, giving a visible warning of impending caving, is now installed at all Indian pillar extraction sites and is proving very successful.CITATION:MacAndrew, K M, Garcia, A S and Gregson, I D, 2014. Coalmine pillar design and performance during mechanised pillar extraction in India, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 347–358 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By T J. Sullivan, H Pinkster, G Swarbrick

From 2002 to 2006, longwall mining was undertaken directly beneath the Cataract Tunnel, which is a 100-year-old, heritage-listed tunnel in Hawkesbury Sandstone responsible for delivering 20 per cent of Sydney’s annual water supply. At one location, undermining resulted in movement of at least 350 mm along a known fault that transects the tunnel. During this movement, the continued operation of the tunnel was ensured through a careful system of planning, monitoring and management.Of key importance to the success of the operation was the use of advanced numerical modelling to guide operations at all levels, including feasibility assessment, pre-mine mitigation works, monitoring design, operation performance and post-mining condition. This allowed many aspects of the potential impacts to be explored, including joint movements, rock mass deformations and changes in permeability. A key challenge was to successfully model near-field influences on adverse geological structure due to very far-field effects. This paper explains the model’s conceptual development, calibration, performance and limitations.Modelling provided the confidence to manage the impacts of large mining-induced movement on key infrastructure and ultimately predicted fault movement accurately. The fault movement remains one of the highest ever recorded due to mine subsidence.CITATION:Swarbrick, G, Sullivan, T J and Pinkster, H, 2014. Longwall mining beneath critical infrastructure – prediction versus performance of the Cataract Tunnel, New South Wales, Australia, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 157–166 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014