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By W. R. Reed, J. P. Rider

"The Pittsburgh Mining Research Division of the U.S. National Institute for Occupational Safety and Health (NIOSH) recently developed a series of models using computational fluid dynamics (CFD) to study airflows and respirable dust distribution associated with a mediumsized surface blasthole drill shroud with a dry dust collector system. Previously run experiments conducted in NIOSH’s full-scale drill shroud laboratory were used to validate the models. The setup values in the CFD models were calculated from experimental data obtained from the drill shroud laboratory and measurements of test material particle size. Subsequent simulation results were compared with the experimental data for several test scenarios, including 0.14 m3/s (300 cfm) and 0.24 m3/s (500 cfm) bailing airflow with 2:1, 3:1 and 4:1 dust collector-tobailing airflow ratios. For the 2:1 and 3:1 ratios, the calculated dust concentrations from the CFD models were within the 95 percent confidence intervals of the experimental data. This paper describes the methodology used to develop the CFD models, to calculate the model input and to validate the models based on the experimental data. Problem regions were identified and revealed by the study. The simulation results could be used for future development of dust control methods for a surface mine blasthole drill shroud. IntroductionIn surface mines, production drilling is an essential process in blasting to fracture the hard rock overburden for removal. During the process, considerable amounts of respirable dust are produced. Past sampling at the shroud area of blasthole drills had documented time-weighted-average respirable dust concentrations ranging from 8.68 to 95.15 mg/m3 (Organiscak and Page, 1995) and 1.04 to 52.30 mg/m3 (Listak and Reed, 2007). These high dust concentrations, which may contain silica, can lead to respirable dust overexposures for the miners working nearby. These overexposures can lead to silicosis, an occupational lung disease that has no cure and is ultimately fatal.Two basic methods are used to control drilling dust: a wet suppression system or a dry collection system (Cecala et al., 2012). Dry drilling techniques using a dust collection system are preferred in rural mining locations where a constant water supply is not available, and in the case of rotary drilling where water is associated with accelerated bit wear due to bearing degradation and hydrogen embrittlement. In addition, dry drilling eliminates freezing-related issues with water in colder climates. Dry dust collectors are highly effective at removing dust, especially the finer material, as long as they are properly operated and maintained (Listak and Reed, 2007; Organiscak and Page, 2005)."

Nov 1, 2016

By A. P. Sasmito

It is well known that underground miners are exposed to one of the most dangerous working environments on earth. As mine delve deeper, the geological factor, mine position and climate condition as well as heat generation from mining machine give rise to the mine operating temperature. This, in turn, has an adverse effect on the environment and thus leads to higher operating costs. Careful estimation and design of air flow rate, spray system, cooling load and additional ventilation auxiliary equipment are of importance to ensure safety, comfort and productivity whilst maintaining low operating cost. A computational fluid dynamics simulation approach is employed to examine underground mine ventilation in a 36 m cul-de-sac of tunnel of coal mine. The model predictions in the turbulent range were validated by comparison with published data. Different turbulence models were tested to select one that yields adequate accuracy and is computationally efficient. Effects of the following parameters are evaluated: tunnel geometry, air flow rate and inlet air temperature. The objective of the simulation is to arrive at an optimal strategy for ventilation and thermal comfort at low cost.

Aug 1, 2013

By W. R. Reed, J. P. Rider

"The National Institute for Occupational Safety and Health (NIOSH) Office of Mine Safety and Health Research (OMSHR) has recently developed a series of models utilizing computational fluid dynamics (CFD) to study airflows and respirable dust distribution associated with a medium-sized surface blasthole drill shroud with a dry dust collector system. CFD models were constructed in ANSYS FLUENT Version 15. Previously run experiments conducted in the NIOSH full-scale drill shroud laboratory were utilized to validate the models. The setup values in CFD models were calculated using experimental data obtained from the drill shroud laboratory and measurements of test material particle size. Subsequent simulation results were compared with the experimental data for test scenarios, including 0.14 m3/s (300 cfm) bailing airflow with 2:1, 3:1, and 4:1 dust collector-to-bailing airflow ratios and 0.24 m3/s (500 cfm) bailing airflow cases with 2:1, 3:1 and 4:1 dust collector-to-bailing airflow ratios. For the 2:1 and 3:1 ratios, results showed the calculated dust concentrations from the CFD models were within the 95% confidence intervals of the lab experimental dust concentrations. This paper describes the methodology used to develop the CFD models, to calculate the model dust input, and to validate the models based on experimental data. Problem regions were identified and revealed by the simulation of a dry dust collector system. The simulation results could be used for future development of dust control methods for a surface mine blasthole drill shroud. INTRODUCTION In surface mines, production drilling is an essential process in blasting which fractures the hard rock overburden for removal. Holes with a predetermined pattern, diameter, and depth are drilled into the overburden to introduce explosives. During the drilling process, considerable amounts of respirable dust are produced. Past research conducting area sampling at blasthole drills has documented time-weighted average respirable dust concentrations ranging from 8.68 to 95.15 mg/m3 [1] and 1.04 to 52.30 mg/m3 [2]. These high dust concentrations, which may contain silica, can lead to respirable dust over-exposures for the drill operator, drill helper, and other personnel in the vicinity. These over-exposures can lead to silicosis, an occupational lung disease that has no cure and is ultimately fatal. In order to prevent the development of silicosis to mine workers, the Mine Safety and Health Administration (MSHA) regulates the exposure to respirable dust. For metal/nonmetal (M/NM) mines, MSHA has adopted the threshold limit values recommended in 1973 by the American Conference of Governmental Industrial Hygienists (ACGIH) [3]. The total airborne dust standard is 10 mg/m3. However, if the sample contains greater than 1 percent quartz (the most common form of crystalline silica), a respirable dust standard is calculated with the following equation: Respirable dust standard = (10 mg/m3) / (% respirable quartz + 2)"

Jan 1, 2016

By Alexandra Anderson

A computational fluid dynamic (CFD) model has been developed using ANSYS Fluent 17.0 to help identify areas of high wear within the refractory lining of a secondary lead reverberatory furnace. Once a base case simulation was validated using data from an operational furnace, areas of potentially high refractory wear were determined through the calculation of the temperature and velocity distributions within the furnace and on the hot face of the refractory lining. The CFD model was used to assess whether the predicted areas of high refractory wear could be minimized through changes burden geometry. The results showed that shape of the burden geometry greatly affected the overall flow patterns and heat transfer within the furnace.

By A. J. Williams, T. N. Croft, M. Cross

"The computational modelling of extrusion and forging processes is now well established. In this work a novel approach is described which utilises finite volume methods on unstructured meshes. This technique can be used to solve simultaneously for fluid flow, heat transfer and non-linear solid mechanics and their interactions. The approach involves the solution of free surface non-Newtonian fluid flow equations in an Eulerian context to track the behaviour of the workpiece and its extrusion/forging, and the solution of the solid mechanics equations in the Lagrangian context to predict the deformation/stress behaviour of the die. Some preliminary examples of this approach will be discussed.IntroductionThe computational modelling of extrusion and forging processes is now well established. Within the last 20 years the finite element method has become the most commonly used technique to simulate metal forming processes [1]-[4]. The Lagrangian and Eulerian type of formulation have been the two major approaches to this problem.Lagrangian methods are efficient and suitable for handling non-linear problems in which small strains prevail, boundary conditions do not change with the course of deformation, and where mesh distortion is not a critical factor in the analysis. Unfortunately, the above points are essential to any accurate metal forming analysis. The problems of mesh distortion and element entanglement pose a serious drawback on the use of such methods. Some automatic remeshing techniques have been developed for Lagrangian finite element analyses of metal forming problems [5]-[7]. However, these methods are not robust and efficient enough to remedy the mesh distortion problems in general. An alternative is to update the mesh manually but this is not always possible, and even when it is feasible it involves major interaction by the user. In addition, remeshing is usually applied to the whole domain which is not necessary and increases CPU time. The complexities associated with remeshing also affect the ability to parallelise the code."

Jan 1, 2001

By M Philip Schwarz

"This paper reviews the status of computational modelling of a variety of common metals reduction processes, namely the blast furnace, rotary kiln and fluidised bed, and one new process not yet commercialised, namely smelting-reduction as in the HIsmelt Process. In each case, the last decade has seen the emergence of the capability to simulate the processes using multi-phase reacting computational fluid dynamics techniques. In some cases this capability is still in the process of being developed, and the next few years will see the maturing of the modelling techniques. As they become established, it will be possible to apply them to further refine the older technologies such as blast furnaces and rotary kilns, and assist in the optimisation, commercialisation and acceptance of the newer technologies such as fluidised bed and molten bath reduction. The development of a computational fluid dynamic model of bath smelting-reduction is described in some detail to illustrate how a large number of complex and interacting phenomena can be successfully simulated within a CFD framework. IntroductionPyrometallurgical reduction processes, such as the iron blast furnace, have become increasing more sophisticated through the centuries, so that today they are often highly efficient. There are continuing pressures, however, to refine existing processes and develop new ones. The imperatives are often economic, given that the long-term trend in the price of metals is always downward. In recent times, there has been the additional need to improve the environmental impact of metal production. Given that they almost inevitably require the use of carbon, metal reduction processes are large sources of greenhouse gases, and even a relatively small improvement in efficiency can be valuable in reducing CO2 production. Local environmental issues, such as the need to control of particulate emissions, are also driving incremental improvements in equipment.In addition to the economic and environmental drivers mentioned above, new process development is also being driven by the need to process new ores, and the need to produce unrefined metal in a form more compatible with alternative routes for downstream processing. An example of the latter is the production of DR! (Direct Reduced Iron) as a feed for EAF Electric Arc Furnace) in mini-mills.Further improvement of processes that have already been honed by continual plant experimentation over many years is not an easy task. To deliver further gains in efficiency, throughput, or product quality requires a highly sophisticated tool: one such tool· is computational modelling."

Jan 1, 2001

By J. Abrahams, A. Nesbitt

Over the past half-century, researchers have commented on the complexities of ion-exchange processes, but have been forced to use gross assumptions to simplify the associated mathematics sufficiently for mathematical models to be of practical use, given the available computational power. This paper reviews the development of increasingly complex models as computational power has increased over the past half-century, from the direct application of Fick's Law in 1947, through to today's models requiring finiteelement methods. The assumptions required for and the associated limitations of the various models are presented and the associated computational complexities are discussed. A case study is presented in which a continuous loss of capacity in an acid resin was observed over about sixty cycles of loading and elution. Resin poisoning does not explain this observation. This paper presents the capacity loss data, speculates on possible causes of the phenomenon, discusses why conventional kinetic and equilibrium mechanisms cannot explain it and concludes that the need to develop a more rigorous model is apparent. The significance of this observation is that standard tests done for a new resin application could significantly overestimate the commercial performance of the resin concerned, highlighting the importance of computer simulation in this field of process engineering.

Jan 1, 2005

By Jancar T, de Guzman M M, Matthews B, Tu J. Y

The use of computational simulation to predict the performance of existing equipment or for the design of improved mineral processing equipment will be referred to as Computational Mineral Processing (CMP) in this paper. The emphasis will be on solving the governing equations for liquid solid flows in complex geometric domains to obtain, typically, the three-dimensional distributions of velocity and pressure for the liquid phase and the velocity and concentration for the solid phase. The underlying technology, computational fluid dynamics (CFD), is very well-developed in other industries (aircraft, car and chemical) and forms a vital part of product design and analysis. The subsequent design of improved mineral processing equipment may also involve finite element structural analysis (FESA). Computational fluid dynamics (CFD) and finite element structural analysis (FESA) are part of the generic discipline of Computational Engineering and Science (CES). Ciment and Scherlis (1993) define CES as `The systematic application of computing systems and computational solution techniques to mathematical models formulated to describe and simulate phenomena of scientific and engineering interest'. Increasing computer power (Kaufmann and Smarr, 1993), is a dominant factor determining the rapid growth of industrial utilisation of CES. This increase is happening at both the supercomputer and the workstation level. Indeed, today's typical workstation, a Hewlett-Packard 735, is as powerful as a CDC 7600, the leading supercomputer in 1970. Future computer architectures are expected to become increasingly parallel (Gartner Group, 1990) allowing a sustained performance of a teraflop (a million megaflops) to be achieved well before the Sydney Olympics in the year 2000. It is recognised that the modem development of most disciplines in the physical sciences rests on the three complementary strategies of experimentation, analysis and computational simulation. As the 21st century is approached the volume of computational simulation, both fundamental and applied, is growing dramatically and the role of experimentation is diminishing. In the area of equipment design, CES provides the following advantages over experimental testing and measurement: 1. lead time in design and development is significantly reduced; 2. CES can simulate conditions not reproducible in experimental tests; 3. CES provides detailed and comprehensive information; and 4. CES is more cost-effective and time-efficient. The ultimate benefit for industry is greater productivity and hence greater profitability. The broader issues in relation to CFD are discussed by Fletcher (1993b). In the five- to ten-year time frame, growth in computer power will make it practical to combine CFD and FESA with optimisation procedures to produce a design process that is almost fully computerised. It is expected that fully automatic

Jan 1, 1995

By A. J. Paul, K. O. Yu

"Today, foundries are moving towards the use of models and design tools to gain a competitive advantage in producing castings of high desired quality. This leads to a growing alliance between foundries, software developers and researchers seeking to model, visualize and understand the phenomena taking place during the casting process. In addition, there is a need to develop affordable techniques to produce parts in small lot sizes. This leads to the development of a Flexible Manufacturing System consisting of: (1) up-front computer-aided engineering; (2) computer integrated proto typing with solid freeform fabrication; and (3) fabrication of the actual mold and related equipment to cast the part.This paper discusses some of the developments that are taking place today in the areas of modeling the physical phenomena during the casting process as well as towards developing a Flexible Manufacturing System for producing cast parts. Areas that require most work involve prediction of defects and mechanical properties using simplified analyses. In addition, electronic data sharing for collaborative engineering between geographically dispersed team members is also discussed. Case studies are presented showing successes as well as failures.IntroductionCasting, one of the oldest forms of metalworking, has recently seen a flurry of developments in the area of solidification modeling. These developments have come about after the realization that, in order to stay competitive, foundries need to reduce their scrap rate and production costs, and increase casting quality. Even though this is not new knowledge for foundry engineers, the tools to help them achieve this goal are just being developed and put in place for use by foundries. Several state-of-the-art software packages are currently available to analyze the solidification behavior in complex shaped castings. These packages make use of several different approaches for solving the various problems associated with casting processes. The overall architecture of a comprehensive solidification modeling system is shown in Figure 1."

Jan 1, 1994

By Hani Henein, J. Barry Wiskel

"The easy accessibility and power of the PC, as well as the education of our engineering students in the use of these tools, are compelling reasons for developing computer aided instructional (CAI) tools. There are a wide range of areas in the engineering curriculum where students must learn the steps and the process of applying judgement in problem solving. In the typical course instruction, · an instructor introduces theory to students; the application of the theory to solving problems is often demonstrated in the abstract. Students therefore spend a significant amount of time learning how to apply the theory to problem solving. Additional time and effort must then be spent to get students to the point of learning concepts and integrating this knowledge. A number of computer aided packages have therefore been developed for use in several courses in the materials science and engineering curriculum that encompass both calculational and instructional capabilities. This paper presents an overview of some of these packages which include the solution of a non-linear equation, the instruction of binary diffusion couples, an introduction of crystallography, an introduction to heat transfer and the solution of thermodynamic stability diagrams. The context in which these CAI Tutorials were developed and are being used will be discussed. The pitfalls in the development of these packages will also be discussed. The use of the tutorials has important implications on the expectations from an engineering education of both instructor and student.IntroductionTraditionally, it is quite routine to teach engineering students how to use a computer (the PC today for undergraduates) as a tool in performing engineering calculations or in simulating a process or a unit operation. This often takes the form of one course in computer programming, whether it is Fortran, Visual basic or a spreadsheet, and another course in numerical computation. However, the materials and electronic revolution have brought about considerable advances in computer power and speed, and accessibility. Today, the manipulation of digital images, movies, and speech are commonplace on a desktop PC.' Many mathematical models that were executed only on workstations can now be readily handled on a PC. Concurrently, more of our students own a PC even if their curriculum does not require them to purchase one. Today, virtually every university student has been introduced to the PC in either their elementary or high school education. Hence, the increased capabilities and accessibility of the PC and the familiarity of students with this tool make it compelling to explore its use as an educational tool for our engineering students. This is not a traditional role of a computer in our engineering curriculum."

Jan 1, 2000

By Robert M. Owen

Recent advances in coring technology and in the development of shipboard and/or in situ geochemical geochemical analysis systems have greatly improved our ability to collect and analyze exploration samples, particularly for marine placer exploration programs. The potential benefit of these improvements cannot be fully realized, however, until we also develop more efficient methods of data reduction and interpretation. Specifically, there is a need to provide prospectors with rapid and useful interpretations of the raw geochemical data so that they can exploit promising results and otherwise optimize the exploration program while the exploration vessel is still at sea. The goal of this project has been to identify and/or develop computer software which is capable of making the necessary data reduction calculations and which can be run on conventional desk-top computers. All work on this project has been supported through a research grant from MMTC-CSD to The University of Michigan. The first stage of this effort involved an evaluation of commercially available (i.e., "off the shelf") software to determine its suitability for use in marine placer exploration applications. Various commercial software packages, each purportedly capable of making different types of statistical and/or mathematical calculations, were tested by evaluating their performance in handling geochemical data sets representative of actual marine placer locations. These data sets include the positions and results of chemical analyses of suites of sediment samples collected from areas of known or suspected marine placers along the Bering Sea coast of Alaska. The evaluation of each commercial program involved a comparison between the results obtained from using the test program

Jan 1, 1991

By J J. Culberson

The past 10 years has seen use of computers become widespread in the mining/exploration industry (including coal, precious and base metals, oil/gas and industrial minerals). This paper will concentrate on the use of computers as a tool to provide technical solutions (including data management, mine planning and operational support) to this industry rather than the use of computers to aid accounting, maintenance and inventory (æcommercialÆ) applications. This paper will review the processes and benefits of the use of computers in mining. We then review the use of technical computing locally here in New Zealand and see what business benefits local users have found from using computers in mining. We have, in research for this paper, spoken with mining software vendors from around the world to find out what is currently the æbest practiceÆ in the industry. The paper will then list what those vendors see as the ultimate improvement on the cards for the future of mining software.

Jan 1, 2000

By R. R. Tatiya

"The ultimate aim of a mine design is to determine the development work involved and resources required by adopting one or more specific alternatives. A part of the process is the production of mining plans/designs, an outline of the amount of work and costs involved as well as a prediction of the revenues expected. The paper aims to examine these aspects of mine design using the computer models developed. These models are capable of designing and performing economic analysis for one or more stopes for a continuous orebody. IntroductionTatiya and Allen (1987) have described ’defining stope boundaries using a computer.’ Using the stope boundaries defined or even hypothetical ones, algorithms have been prepared to design the layouts of the following stoping methods: 1. sublevel stoping (longitudinal as well as transverse);2. DTH (Down-the-hole) stoping; and3. flat back cut and fill stoping with posts and pillars.Tatiya (1989) presented this work at the 21st symposium on the application of computers and operations research in the mineral industry (APCOM). Economic analysis of a stope is the additional feature incorporated with these algorithms.The system has been tested by an economic analysis of the three stoping methods modeled for a small portion of a deposit of a copper mining complex. The deposits at this mining complex form lenses of varying shapes and sizes, having low copper content. These chalcopyrite lenses are steeply inclined with a thickness in the range of 5 m to 60 m. The strata are competent and suitable for underground mining.In different sections of the mines different sets of equipment are used to perform the basic unit operations. Some of the ore handling levels in the mines are trackless, the rest are tracked."

Jan 1, 1998

By A. K. Bhowmick

Size reduction is very energy intensive and is the single most power-intensive operation in mineral processing plants. Research has shown that only a small part of the energy is utilized efficiently. One of the major thrusts of all equipment manufacturers has been to improve this efficiency. Choosing the right equipment to maximize energy utilization in any comminution application has always been the utmost criteria. Due to the high energy cost and depletion of good grade minerals, it is becoming essential to optimize all the subsystems within a given comminution system for the overall economic success of such ventures. Bradley Pulverizer Company of Allentown, Pennsylvania recognized this and started offering its Feeder Controller in 1988 for automatic feed control. After its first successful operation, Bradley made this as a part of all of their grinding system standard offering. It was also recognized that the Feeder Controller was just a beginning and more automation and controls would be required for an overall, efficient grinding system.

Jan 1, 1993

By C. Chapman, M. G. Reading, M. P. Amsden

Ecstall Mining Limited, a subsidiary of Texasgulf Incorporated, operates the Kidd Creek mine, a 10,000- tpd base metal producer, near Timmins, Ontario. Two different ore types are mined and milled copper-zinc and silver-lead-zinc. At the highly automated Ecstall concentrator, the ores are processed by selective flotation in three individual circuits. One of the most important metallurgical tools for process control is a sample system incorporating continuous onstream X-ray analysis. Recently this system was further automated by adding computer control of reagents for two copper-zinc flotation circuits. The computer programs, utilizing optimum seeking methods and smelter contract terms, have increased copper recovery 0.8% and zinc recovery 1.6%, and reduced reagent costs by 12%. Although not anticipated, copper and zinc concentrate grades were improved modestly as well.

Jan 1, 1973

By Thomas E. Finch

Engineering mine design encompasses a range of situations, and each situation has its own range of detail and fineness. The most time consuming, and perhaps repetitive design situation involves evaluation of new or alternate mining methods. Many man years are consumed examing alternatives conjured up at all levels of the design team, from the number crunching engineer to the engineering manager. Many alternatives are intuitively disregarded, some are briefly evaluated and thrown out, and many others are started but not completed due to time constraints. All alternatives have similar input characteristics and evaluation procedures. In the design process, production requirements are known and equipment production capabilities are generated to determine the numbers and costs of an equipment type required to match a given situation. The end result is some comparative figure, typically cost per ton or yard upon which a decision is built. The similarity of input data and problem solving techniques lends design to computer solution. Computer aided equipment evaluation is not new to the mining industry. An existing and accepted technique is exemplified with the programs used by truck manufacturers. Given a haulage profile and production requirements, the number of anyone capacity, horsepower, tire size, gear ratio or similar characteristically identified truck can be determined. This information can be outputted in varying degrees of complexity and the results used with equally varying percentages of credibility by design or production engineers. Most engineers are willing to accept-the computer's effort with relief and a desire for belief. Although inherently more complex, the ultimate end of computer manipulation should be total mine design. This is an extremely large step in the evolution of mine design, and not many engineers, including the authors, believe the results would be directly applicable or necessarily correct. As with computer simulations of an operation, total computer design of mines requires such complex and lengthy input that each mine might be manually designed more quickly and cheaply. The existence of computer programs which initially evaluate a mining system or part of the system is upon us, however.

Jan 1, 1978

By Peter K. Liaw, Niann-i Yu, Wei Zhao

"For a plain-weave Nicalon ™ fiber fabric-reinforced silicon carbide (SiC) ceramic composite, little attentation has been paid to the effect of fabric stacking sequence on its mechanical behavior. In this paper, fiber-fabric stacking sequence effects on the elastic stress distributions, ceramic matrix-cracking stress, effective elastic moduli, and flexural strengths of laminated flexural test bars are quantified. A quantification model is established based on the combination of classical laminated plate theories and a fiber undulation model developed by Chou et al. A FORTRAN program is compiled to implement the modeling, which can be run in a SUN work station. The mechanical performance of a continuous fiber-reinforced ceramic-matrix composite (CFCC) with a [0/30/60] lay-up was analyzed and predicted. The variation in the fiber-fabric stacking sequence can vary the elastic stress distributions along the thickness direction of specimens, magnitude of ceramic matrix-cracking stress, effective elastic moduli of the laminate, and crack initiation sites as well as fracture modes. Moreover, all these factors contribute to scatter in flexural strengths of the CFCC.I. IntroductionWith enhanced fracture toughness and the ability of non-catastrophic (graceful) failure behavior, CFCCs are currently under evaluation for high-temperature structural applications in heat exchangers, combustors, hot-gas filters, boilers components, first walls and high-heat flux surfaces gas turbines, space vehicles and nuclear reactors.[1-8] Extensive applications of CFCCs by industry are still hampered by an insufficient understanding of the mechanical behavior, and sometimes, the lack of a well-developed and widely accepted design philosophy, in addition to the high-production costs."

Jan 1, 1998

By Lindsay D. Norman

Computer models for simulating the construction and for calculating the properties of particulate solids in two- and three-dimensional systems (coverings of circles and packings of spheres, respectively) were developed. By simulating the physical process of constructing circle coverings and sphere packings, in which the circles or spheres were randomly selected from many different distributions of sizes, physically realizable loose random assemblies were simulated whose physical and geometrical properties were predictable with the computer. Many of these properties, such as the number of contacts, are extremely-difficult to measure accurately, or considerable ingenuity is required in their determination. All of these properties were easily and accurately calculated by the computer models for many different coverings and packings constructed from equal, discrete, uniform, and log-normal distributions of particles. In addition to the loose random assemblies, dense random covering and packing constructions were simulated whose properties are ideal upper limits for those of the loose random coverings and packings. The properties of the dense random coverings and packings, heretofore only obtainable by theoretical analysis, were also simply obtained. The statistical geometry of loose random coverings and packings was studied, and several new interpretations of the area-covering or space-filling requirements in these systems were made. In two dimensions, it was found that the properties of all loose random coverings are predictable by taking suitably weighted averages of the corresponding properties of just four kinds of polygons whose edges are defined by connecting the centers of mutually tangent circles in the covering. The distributions of these polygons that permit area-covering were determined, and empirical equations for predicting the density, average coordination number, and average pore area in loose and dense random coverings were formulated. The properties of loose packings were determined by performing a simplicial division of the computer-simulated assemblies to produce a unique set of minimum volume, space-filling tetrahedra whose edges connected the sphere centers in each packing. A simple empirical equation was formulated that permits the calculation of the average number of contacts in any sphere packing, random or regular. Some of the statistical geometrical properties of the simplicial tetrahedra in the computer-simulated packings were analyzed. The tetrahedron edge length distributions in all the loose random packings were nearly identical when the edges were presented in terms of sphere diameters, regardless of the sphere population in the packing. Moreover, the gap lengths in the loose packings were to an excellent approximation representable by a uniform distribution of sizes. The distributions of spheres in tetrahedra resulting from the simplicial division of the loose random packings also existed in the tetrahedra in dense random packings. These observations were employed in developing a unique method for predicting the geometrical properties of loose random packings without simulating the assembled packing. Instead, the space-filling simplicial graph could be predicted for any given density of packing of any sphere population. The cumulative packing properties of these tetrahedra were shown to be nearly identical to those calculated by all loose random packing simulations attempted in this investigation. The simplicial tetrahedra completely describe a packing and can therefore be used to predict all properties of interest.

Jan 1, 1971

Three stages are involved in the complete design and evaluation of an open cut mine. These are:1. design of the optimu,m ultimate pit, and selectionof the optimum mill capacity,2. development of production schedules, with intermediate pit designs, and3. evaluation of the project, based on factors from stages 1 and 2, by means of discounted cash flow analysis.Stage 1 requires relatively complete information on metal distribution, metallurgical performance, and cost factors, which is used to design a series of pits, corresponding to a range of milling rates.For each milling rate considered there is a unique pit design which maximizes operating profitability. The computer outlines this design (in terms of size, shape, and location; tons and grade of ore; and tons of waste), by considering the effect on profitability of mining each block in the mineralized inventory in relation to every other block which would be affected by its removal.The computer selects only those blocks for mining which result in an overall increase in profitability, maintaining pre-determined wall slope conditions throughout.Both operating profitabilities and capital costs increase with throughput, and the two curves will combine to produce a flat peak in net profitabilities at a certain rate, with its associated pit design.Stage 2 can maximize head grades early in the life of the operation. This increases the projected present value, but there are good arguments for maintaining steady head grades throughout the life of the mine.A modification of the programme used in Stage 1 is used here.Stage 3 is a conventional discounted cash flow analysis, using factors obtained in stages 1 and 2. It can be computerised, but a manual treatment is probably just as fast overall.

Jan 1, 1970

By M. P. Hoffman

The U.S. Bureau of Mines is developing a roof bolter with a computer-controlled drill head that will increase the safety of roof bolting in underground coal mines by allowing miners to be relocated to a safe area. To ensure secure anchorage, acceleration and strain data are broadcast from an instrumented drill steel to a data acquisition system. These data are analyzed, correlated, and transformed to pro-vide information about roof strata, then are sent to a supervisory computer executing National Institute of Standards and Technology's real-time control software. The supervisory computer sends setpoint commands to proportional-integral-derivative control loops to control drill thrust, position, revolutions per minute, and torque.

Jan 1, 1994