45 resultados para Roasting (Metallurgy)


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Water reporting is becoming increasingly common amongst minerals companies. The Minerals Council of Australia’s (MCA) Water Accounting Framework (WAF), co-developed by the Centre for Water in the Minerals Industry (CWiMI), provides a standard set of terms for water reporting. The WAF was established due to the need of the minerals industry to report on its water management consistently, rather than report using company-specific terms which can cause confusion and makes company comparisons impossible. The WAF consists of two models: The Input-Output Model, which represents interactions between a site and its surrounding community and environment, and the Operational Model, which represents the interactions within a site.

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The Minerals Council of Australia’s (MCA) Water Accounting Framework (WAF) is an industry lead initiative to enable cross company communication and comparisons of water management performance. The WAF consists of two models, the Input-Output Model that represents water interactions between an operation and its surrounding environment and the Operational Model that represents water interactions within an operation. Recently, MCA member companies have agreed to use the Input-Output Model to report on their external water interactions in Australian operations, with some adopting it globally. The next step will be to adopt the Operational Model. This will expand the functionality of the WAF from corporate reporting to allowing widespread identification of inefficiencies and to connect internal and external interactions. Implementing the WAF, particularly the Operational Model, is non-trivial. It can be particularly difficult for operations that are unfamiliar with the WAF definitions and methodology, lack information pertaining to flow volumes or contain unusual configurations. Therefore, there is a need to help industry with its implementation. This work presents a step-by-step guide to producing the Operational Model. It begins by describing a methodology for implementing the Operational Model by describing the identification of pertinent objects (stores, tasks and treatments), quantification of flows, aggregation of objects and production of reports. It then discusses how the Operational Model can represent a series of challenging scenarios and how it can be connected with Input-Output Model to improve water management.

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Poor mine water management can lead to corporate, environmental and social risks. These risks become more pronounced as mining operations move into areas of water scarcity and/or increase climatic variability while also managing increased demand, lower ore grades and increased strip ratios. Therefore, it is vital that mine sites better understand these risks in order to implement management practices to address them. Systems models provide an effective approach to understand complex networks, particularly across multiple scales. Previous work has represented mine water interactions using systems model on a mine site scale. Here, we expand on that work by present an integrated tool that uses a systems modeling approach to represent mine water interactions on a site and regional scale and then analyses the risks associated with events stemming from those interactions. A case study is presented to represent three indicative corporate, environmental and social risks associated with a mine site that exists in a water scarce region. The tool is generic and flexible, and can be used in many scenarios to provide significant potential utility to the mining industry.

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The mining industry faces three long term strategic risks in relation to its water and energy use: 1) securing enough water and energy to meet increased production; 2) reducing water use, energy consumption and emissions due to social, environmental and economic pressures; and 3) understanding the links between water and energy, so that an improvement in one area does not create an adverse effect in another. This project helps the industry analyse these risks by creating a hierarchical systems model (HSM) that represents the water and energy interactions on a sub-site, site and regional scales; which is coupled with a flexible risk framework. The HSM consists of: components that represent sources of water and energy; activities that use water and energy and off-site destinations of water and produced emissions. It can also represent more complex components on a site, with inbuilt examples including tailings dams and water treatment plants. The HSM also allows multiple sites and other infrastructure to be connected together to explore regional water and energy interactions. By representing water and energy as a single interconnected system the HSM can explore tradeoffs and synergies. For example, on a synthetic case study, which represents a typical site, simulations suggested that while a synergy in terms of water use and energy use could be made when chemical additives were used to enhance dust suppression, there were trade-offs when either thickened tailings or dry processing were used. On a regional scale, the HSM was used to simulate various scenarios, including: mines only withdrawing water when needed; achieving economics-of-scale through use of a single centralised treatment plant rather than smaller decentralised treatment plants; and capturing of fugitive emissions for energy generation. The HSM also includes an integrated risk framework for interpreting model output, so that onsite and off-site impacts of various water and energy management strategies can be compared in a managerial context. The case studies in this report explored company, social and environmental risks for scenarios of regional water scarcity, unregulated saline discharge, and the use of plantation forestry to offset carbon emissions. The HSM was able to represent the non-linear causal relationship at the regional scale, such as the forestry scheme offsetting a small percentage of carbon emissions but causing severe regional water shortages. The HSM software developed in this project will be released as an open source tool to allow industry personnel to easily and inexpensively quantify and explore the links between water use, energy use, and carbon emissions. The tool can be easily adapted to represent specific sites or regions. Case studies conducted in this project highlighted the potential complexity of these links between water, energy, and carbon emissions, as well as the significance of the cumulative effects of these links over time. A deeper understanding of these links is vital for the mining industry in order to progress to more sustainable operations, and the HSM provides an accessible, robust framework for investigating these links.

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The Central Queensland Mine Rehabilitation Group (CQMRG) has hosted mine site rehabilitation inspections combined with technical workshops for more than 20 years. It was recognised at CQMRG's anniversary meeting in April 2013 that the vast body of knowledge held by rehabilitation and closure planning practitioners was being lost as senior rehabilitation experts retire from the industry. It was noted that even more knowledge could be readily lost unless a knowledge management platform was developed to capture, store and enable retrieval of this information. This loss of knowledge results in a significant cost to industry. This project was therefore undertaken to review tools which have the capability to gather the less formal knowledge as well as to make links to existing resources and bibliographic material. This scoping study evaluated eight alternative knowledge management systems to provide guidance on the best method of providing the industry with an up-to-date, good practice, knowledge management system for rehabilitation and closure practices, with capability for information sharing via a portal and discussion forum. This project provides guidance for a larger project which will implement the knowledge management system to meet the requirements of the CQMRG and be transferrable to other regions if applicable. It will also provide the opportunity to identify missing links between existing tools and their application. That is, users may not be aware of how these existing tools can be used to assist with mine rehabilitation planning and implementation and the development of a new platform will help to create those linkages. The outcomes of this project are directed toward providing access to a live repository of rehabilitation practice information which is Central Queensland coal mine-specific, namely: highlighting best practice activities, results of trials and innovative practices; updated legislative requirements; links to practices elsewhere; and informal anecdotal information relevant to particular sites which may be of assistance in the development of rehabilitation of new areas. Solutions to the rehabilitation of challenging spoils/soils will also be provided. The project will also develop a process which can be applied more broadly within the mining sector to other regions and other commodities. Providing a platform for uploading information and holding discussion forums which can be managed by a regional practitioner network enables the new system to be kept alive, driven by users and information needs as they evolve over time. Similar internet-based platforms exist and are managed successfully. The preferred knowledge management system will capture the less formal and more difficult to access knowledge from rehabilitation and mine closure practitioners and stakeholders through the CQMRG and other contributors. It will also provide direct links, and greater accessibility, to more formal sources of knowledge with anticipated cost savings to the industry and improved rehabilitation practices with successful transitioning to closure and post-mining land use.

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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 reports work on the automation of a hot metal carrier, which is a 20 tonne forklift-type vehicle used to move molten metal in aluminium smelters. To achieve efficient vehicle operation, issues of autonomous navigation and materials handling must be addressed. We present our complete system and experiments demonstrating reliable operation. One of the most significant experiments was five-hours of continuous operation where the vehicle travelled over 8 km and conducted 60 load handling operations. Finally, an experiment where the vehicle and autonomous operation were supervised from the other side of the world via a satellite phone network are described.

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This paper reports work involved with the automation of a Hot Metal Carrier — a 20 tonne forklift-type vehicle used to move molten metal in aluminium smelters. To achieve efficient vehicle operation, issues of autonomous navigation and materials handling must be addressed. We present our complete system and experiments demontrating reliable operation. One of the most significant experiments was five-hours of continuous operation where the vehicle travelled over 8 km and conducted 60 load handling operations. We also describe an experiment where the vehicle and autonomous operation were supervised from the other side of the world via a satellite phone network.

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The most important aspect of modelling a geological variable, such as metal grade, is the spatial correlation. Spatial correlation describes the relationship between realisations of a geological variable sampled at different locations. Any method for spatially modelling such a variable should be capable of accurately estimating the true spatial correlation. Conventional kriged models are the most commonly used in mining for estimating grade or other variables at unsampled locations, and these models use the variogram or covariance function to model the spatial correlations in the process of estimation. However, this usage assumes the relationships of the observations of the variable of interest at nearby locations are only influenced by the vector distance between the locations. This means that these models assume linear spatial correlation of grade. In reality, the relationship with an observation of grade at a nearby location may be influenced by both distance between the locations and the value of the observations (ie non-linear spatial correlation, such as may exist for variables of interest in geometallurgy). Hence this may lead to inaccurate estimation of the ore reserve if a kriged model is used for estimating grade of unsampled locations when nonlinear spatial correlation is present. Copula-based methods, which are widely used in financial and actuarial modelling to quantify the non-linear dependence structures, may offer a solution. This method was introduced by Bárdossy and Li (2008) to geostatistical modelling to quantify the non-linear spatial dependence structure in a groundwater quality measurement network. Their copula-based spatial modelling is applied in this research paper to estimate the grade of 3D blocks. Furthermore, real-world mining data is used to validate this model. These copula-based grade estimates are compared with the results of conventional ordinary and lognormal kriging to present the reliability of this method.

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In 2002, Phillip Di Bella’s childhood passion for coffee and keen entrepreneurial spirit led him to establish a small coffee roasting warehouse in in the inner suburbs of Brisbane (Di Bella, 2012). With a keen sense of direction and passion for his coffee products and providing unparalleled customer service, Di Bella Coffee quickly grew to become a key player in the coffee roasting scene. This passion for the ultimate coffee experience is evident in the firm’s logo ‘Di Bella Coffee Inspires Passion’. Phillip Di Bella stated that ‘the common denominator of this company is about inspiration and passion. We are not a coffee company, we are a people company. You know, are we inspiring you from the moment you walk in the door to the moment you leave. If you are not feeling inspired then we haven’t done our job properly as a company’. Fundamentally, providing the ultimate coffee experience, as detailed in the following case is one in which focuses on the coffee consumption experience, not the coffee itself. Over that last 10 years Di Bella Coffee has constantly strived for the ultimate coffee, while expanding business operations into the booming Asian coffee market, establishing headquarters in Shanghai in 2010. In 2011, Di Bella Coffee commenced their second international venture with the launch of operations in India (Di Bella Coffee, 2012); followed shortly by the creation of a new category of coffee, set to revolutionise to coffee industry. The fusion of two traditional forms of coffee; espresso coffee and instant coffee, to create a third category- espresso instant, led to the development of TORQ by Di Bella.

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This article addresses the new conditions under which teachers are making the choice to teach. Our core contention is that the reorganisation of schools according to the logic of the corporation, as described in Deleuze's ‘Postscript’, is changing the flows and forces on the primary surface of ‘the classroom’. These changes block the usual movements of teaching to discipline, normalise and individualise, which was the role of the school as precursor to the factory. Blocked from repeating, or returning, teaching as it has always been done, teachers must actively re-will to teach; teachers cannot use order words to name themselves and direct flows and forces as they have usually been done. While many choices to teach will be undertaken, the most popular being that of choosing to teach toward the corporation, the repetition of teaching toward enclosed spaces becomes less compelling. Like Nietzsche's Zarathustra, teachers, who have the courage to actively choose, face a new dawn in which teaching cannot be what it once was. In that moment they must choose to repeat that choice an infinite number of times, the choice of eternal return, and it is from here that new times might begin.

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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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The Ok Tedi copper orebody consists of porphyry and skarn orebodies. The skarn orebodies, identified by different mineralogy, are the source of high intermittent fluorine levels in the mill concentrates. This paper discusses the results of the work undertaken to characterize the various fluorine-bearing minerals in samples of final copper concentrates and the distribution of fluorine amongst the minerals. Quantification of each mineral in mill feed and various flotation streams at Ok Tedi enables an understanding of the quantitative response of fluorine-bearing minerals to flotation. The metallurgical behavior of fluorine in the flotation process is also discussed.

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Extracellular polysaccharides are as structurally and functionally diverse as the bacteria that synthesise them. They can be present in many forms, including cell-bound capsular polysaccharides, unbound "slime", and as O-antigen component of lipopolysaccharide, with an equally wide range of biological functions. These include resistance to desiccation, protection against nonspecific and specific host immunity, and adherence. Unsurprisingly then, much effort has been made to catalogue the enormous structural complexity of the extracellular polysaccharides made possible by the wide assortment of available monosaccharide combinations, non-carbohydrate residues, and linkage types, and to elucidate their biosynthesis and export. In addition, the work is driven by the commercial potential of these microbial substances in food, pharmaceutics and biomedical industries. Most recently, bacteria-mediated environmental restoration and bioleaching have been attracting much attention owing to their potential to remediate environmental effluents produced by the mining and metallurgy industries. In spite of technological advances in chemistry, molecular biology and imaging techniques that allowed for considerable expansion of knowledge pertaining to the bacterial surface polysaccharides, current understanding of the mechanisms of synthesis and regulation of extracellular polysaccharides is yet to fully explain their structural intricacy and functional variability.

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Despite considerable effort and a broad range of new approaches to safety management over the years, the upstream oil & gas industry has been frustrated by the sector’s stubbornly high rate of injuries and fatalities. This short communication points out, however, that the industry may be in a position to make considerable progress by applying “Big Data” analytical tools to the large volumes of safety-related data that have been collected by these organizations. Toward making this case, we examine existing safety-related information management practices in the upstream oil & gas industry, and specifically note that data in this sector often tends to be highly customized, difficult to analyze using conventional quantitative tools, and frequently ignored. We then contend that the application of new Big Data kinds of analytical techniques could potentially reveal patterns and trends that have been hidden or unknown thus far, and argue that these tools could help the upstream oil & gas sector to improve its injury and fatality statistics. Finally, we offer a research agenda toward accelerating the rate at which Big Data and new analytical capabilities could play a material role in helping the industry to improve its health and safety performance.