894 resultados para MINING ENGINEERING


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The mining industry is highly suitable for the application of robotics and automation technology, since the work is arduous, dangerous, and often repetitive. This paper presents a broad overview of the issues involved in the development of a physically large and complex field robotic system—a 3500-tonne mining machine (dragline). Draglines are “walking cranes” used in open-pit coal mining to remove the material covering a coal seam. The critical issues of robust load position sensing, modeling of the dynamics of the electrical drive system and the swinging load, control strategies, the operator interface, and automation system architecture are addressed. An important aspect of this system is that it must work cooperatively with a human operator, seamlessly passing control back and forth in order to achieve the main aim—increased productivity.

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Communicating the mining industry’s water use is fundamental to maintaining its social license to operate but the majority of corporate reporting schemes list indicators. The Minerals Council of Australia’s Water Accounting Framework was designed to assist the minerals industry obtain consistency in its accounting method and in the definitions of terms used in water reporting. The significance of this paper is that it shows that the framework has been designed to be sufficiently robust to describe any mining/mineral related operation. The Water Accounting Framework was applied across four operations over three countries producing four commodities. The advantages of the framework were then evident through the presentation of the reports. The contextual statement of the framework was able to explain contrasting reuse efficiencies. The Input-Output statements showed that evaporation was a significant loss for most of the operations in the study which highlights a weakness of reporting schemes that focus on discharge volumes. The framework method promotes data reconciliation which proved the presence of flows that two operations in the study had neglected to provide. Whilst there are many advantages of the framework, the major points are that the reporting statements of the framework, when presented together, can better enable the public to understand water interactions at a site-level and allows for valid comparisons between sites, regardless of locale and commodity. With mining being a global industry, these advantages are best realised if there was international adoption of the framework.

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Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use first- and second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental phenomena tend to be very complex, presenting non-Gaussian distribution and/or non-linear inter-variable relationship. This paper proposes a new approach to the interpolation of spatial data, which can be applied with great flexibility. Suitable cross-variable higher-order spatial statistics are developed to measure the spatial relationship between the random variable at an unsampled location and those in its neighbourhood. Given the computed cross-variable higher-order spatial statistics, the conditional probability density function (CPDF) is approximated via polynomial expansions, which is then utilized to determine the interpolated value at the unsampled location as an expectation. In addition, the uncertainty associated with the interpolation is quantified by constructing prediction intervals of interpolated values. The proposed method is applied to a mineral deposit dataset, and the results demonstrate that it outperforms kriging methods in uncertainty quantification. The introduction of the cross-variable higher-order spatial statistics noticeably improves the quality of the interpolation since it enriches the information that can be extracted from the observed data, and this benefit is substantial when working with data that are sparse or have non-trivial dependence structures.

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Critical stage in open-pit mining is to determine the optimal extraction sequence of blocks, which has significant impacts on mining profitability. In this paper, a more comprehensive block sequencing optimisation model is developed for the open-pit mines. In the model, material characteristics of blocks, grade control, excavator and block sequencing are investigated and integrated to maximise the short-term benefit of mining. Several case studies are modeled and solved by CPLEX MIP and CP engines. Numerical investigations are presented to illustrate and validate the proposed methodology.

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This paper proposes a new multi-resource multi-stage scheduling problem for optimising the open-pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints have been considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times of equipment; equipment-assignment-dependent operation times of blocks; distances between each pair of blocks; due windows of blocks; material properties of blocks; swell factors of blocks; and slope requirements of blocks. It is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level. The model also provides an intelligent decision support tool to account for the availability and usage of equipment units for drilling, blasting and excavating stages.

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Strain-based failure criteria have several advantages over stress-based failure criteria: they can account for elastic and inelastic strains, they utilise direct, observables effects instead of inferred effects (strain gauges vs. stress estimates), and model complete stress-strain curves including pre-peak, non-linear elasticity and post-peak strain weakening. In this study, a strain-based failure criterion derived from thermodynamic first principles utilising the concepts of continuum damage mechanics is presented. Furthermore, implementation of this failure criterion into a finite-element simulation is demonstrated and applied to the stability of underground mining coal pillars. In numerical studies, pillar strength is usually expressed in terms of critical stresses or stress-based failure criteria where scaling with pillar width and height is common. Previous publications have employed the finite-element method for pillar stability analysis using stress-based failure criterion such as Mohr-Coulomb and Hoek-Brown or stress-based scalar damage models. A novel constitutive material model, which takes into consideration anisotropy as well as elastic strain and damage as state variables has been developed and is presented in this paper. The damage threshold and its evolution are strain-controlled, and coupling of the state variables is achieved through the damage-induced degradation of the elasticity tensor. This material model is implemented into the finite-element software ABAQUS and can be applied to 3D problems. Initial results show that this new material model is capable of describing the non-linear behaviour of geomaterials commonly observed before peak strength is reached as well as post-peak strain softening. Furthermore, it is demonstrated that the model can account for directional dependency of failure behaviour (i.e. anisotropy) and has the potential to be expanded to environmental controls like temperature or moisture.

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This paper proposes a new multi-resource multi-stage mine production timetabling problem for optimising the open-pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints are considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times; equipment-assignment-dependent operational times; etc. The model also provides the availability and usage of equipment units at multiple operational stages such as drilling, blasting and excavating stages. The problem is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level.

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This study presents a comprehensive mathematical formulation model for a short-term open-pit mine block sequencing problem, which considers nearly all relevant technical aspects in open-pit mining. The proposed model aims to obtain the optimum extraction sequences of the original-size (smallest) blocks over short time intervals and in the presence of real-life constraints, including precedence relationship, machine capacity, grade requirements, processing demands and stockpile management. A hybrid branch-and-bound and simulated annealing algorithm is developed to solve the problem. Computational experiments show that the proposed methodology is a promising way to provide quantitative recommendations for mine planning and scheduling engineers.

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This paper proposes a new multi-stage mine production timetabling (MMPT) model to optimise open-pit mine production operations including drilling, blasting and excavating under real-time mining constraints. The MMPT problem is formulated as a mixed integer programming model and can be optimally solved for small-size MMPT instances by IBM ILOG-CPLEX. Due to NP-hardness, an improved shifting-bottleneck-procedure algorithm based on the extended disjunctive graph is developed to solve large-size MMPT instances in an effective and efficient way. Extensive computational experiments are presented to validate the proposed algorithm that is able to efficiently obtain the near-optimal operational timetable of mining equipment units. The advantages are indicated by sensitivity analysis under various real-life scenarios. The proposed MMPT methodology is promising to be implemented as a tool for mining industry because it is straightforwardly modelled as a standard scheduling model, efficiently solved by the heuristic algorithm, and flexibly expanded by adopting additional industrial constraints.

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The present paper details the prediction of blast induced ground vibration, using artificial neural network. The data was generated from five different coal mines. Twenty one different parameters involving rock mass parameters, explosive parameters and blast design parameters, were used to develop the one comprehensive ANN model for five different coal bearing formations. A total of 131 datasets was used to develop the ANN model and 44 datasets was used to test the model. The developed ANN model was compared with the USBM model. The prediction capability to predict blast induced ground vibration, of the comprehensive ANN model was found to be superior.

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Seepage control in karstic rock masses is one of the most important problems in domestic hydroelectric engineering and mining engineering as well as traffic engineering. At present permeability assessment and leakage analysis of multi-layer karstic rock masses are mainly qualitative, while seldom quantitative. Quantitative analyses of the permeability coefficient and seepage amount are conducted in this report, which will provide a theoretical basis for the study of seepage law and seepage control treatment of karstic rocks. Based on the field measurements in the horizontal grouting galleries of seepage control curtains on the left bank of the Shuibuya Hydropower Project on the Qingjiang river, a hydraulic model is established in this report, and the computation results will provide a scientific basis for optimization of grouting curtain engineering. Following issues are addressed in the report. (1) Based on the in-situ measurements of fissures and karstic cavities in grouting galleries, the characteristics of karstic rock mass is analyzed, and a stochastic structural model of karstic rock masses is set up, which will provide the basis for calculation of the permeability and leakage amount of karstic rock mass. (2) According to the distribution of the measured joints in the grouting galleries and the stochastic results obtained from the stochastic structural model of karstic rock mass between grouting galleries, a formula for computation of permeability tensor of fracturing system is set up, and a computation program is made with Visual Basic language. The computation results will be helpful for zoning of fissured rock masses and calculation of seepage amount as well as optimization of seepage control curtains. (3) Fractal theory is used to describe quantitatively the roughness of conduit walls of karstic systems and the sinuosity of karstic conduits. It is proposed that the roughness coefficient of kastic caves can be expressed by both fractal dimension Ds and Dr that represent respectively the extension sinuosity of karstic caves and the roughness of the conduit walls. The existing formula for calculating the seepage amount of karstic conduits is revised and programmed. The seepage amount of rock masses in the measured grouting galleries is estimated under the condition that no seepage control measures are taken before reservoir impoundment, and the results will be helpful for design and construction optimization of seepage curtains of the Shuibuya hydropower project. This report is one part of the subject "Karstic hydrogeology and the structural model and seepage hydraulics of karstic rock masses", a sub-program of "Study on seepage hydraulics of multi-layer karstic rock masses and its application in seepage control curtain engineering", which is financially supported by the Hubei Provincial key science and technology programme.

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The attachment of electronic components to printed circuit boards using solder material is a complex process. This paper presents a novel modeling methodology, which integrates the governing physics taking place. Multiphysics modeling technology, imbedded into the simulation tool—PHYSICA is used to simulate fluid flow, heat transfer, solidification, and stress evolution in an integrated manner. Results using this code are presented, detailing the mechanical response of two solder materials as they cool, solidify and then deform. The shape that a solder joint takes upon melting is predicted using the SURFACE EVOLVER code. Details are given on how these predictions can be used in the PHYSICA code to provide a modeling route by which the shape, solidification history, and resulting stress profiles can be predicted.

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In semilevitation melting, a cylindrical metal ingot is melted by a coaxial a.c. induction coil. A watercooled solid base supports the ingot, while the top and side free surface is confined by the magnetic forces as the melting front progresses. The dynamic interplay between gravity, hydrodynamic stress, and the Lorentz force in the fluid determines the instantaneous free surface shape. The coupled nonstationary equations for turbulent flow, heat with phase change, and high-frequency electromagnetic field are solved numerically for the axisymmetric time-dependent domain by a continuous mesh transformation, using a pseudospectral method. Results are obtained for the two actually existing coil configurations and several validation cases.

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A modeling strategy is presented to solve the governing equations of fluid flow, temperature (with solidification), and stress in an integrated manner. These equations are discretized using finite volume methods on unstructured grids, which provide the capability to represent complex domains. Both the cell-centered and vertex-based forms of the finite volume discretization procedure are explained, and the overall integrated solution procedure using these techniques with suitable solvers is detailed. Two industrial processes, based on the casting of metals, are used to demonstrate the capabilities of the resultant modeling framework. This manufacturing process requires a high degree of coupling between the governing physical equations to accurately predict potential defects. Comparisons between model predictions and experimental observations are given.