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By R. V. Ramani, V. T. Burgos, J. A. McClay

Model testing is a two part operation; first, to assure the valid¬ity of the mathematical statements and second, to evaluate the accuracy of the computer model for predictive purposes. Verification of both the conceptual and computational aspects can be achieved through the use of input data for which output results are available for comparison. In this dissertation, two test problems were selected for model testing from the Economic Evaluation Reports of the U.S. Bureau of Mines, Process Evaluation Group. Verification Data Set I Input data for this test was selected from an economic analysis of a hypothetical 1,056,000-ton-per-year mine in a 48-inch bituminous coal seam (Process Evaluation Group-Report No. 72-27, 1972). The mine was scheduled to operate five days per week, three shifts per day, 220 days per year with an estimated life of 20 years. Coal reserves covered an area of 6.4 square miles with an expected recovery rate of 70%. Production was achieved through 4 continuous miner sections with an average production rate of 400 tons per shift. The cost summary in the report included a breakdown of equipment and labor requirements. A depreciation schedule listed the expected capital expense per year of operation, assuming capital replacement with identical units and no change in the unit cost. Supply and oper¬ating costs were listed in both gross annual figures and cost per ton of production. The operating and investment costs were projected over the 20 year mine life and a discounted cash flow analysis performed to determine

Jan 1, 1975

By F. Vasilikou

Commercial deployment of Carbon Capture Utilization and Storage (CCUS) requires field testing of a scale that can stress the geologic reservoirs. One such reservoir of interest consists of unminable coal seams that exhibit favorable characteristics and depositional environments and lower pressure and temperature than other, deeper, reservoirs. Such conditions can reduce compression costs while utilizing the action of adsorption that offers a more effective carbon dioxide (CO2) bonding than free storage or solution. To ensure the success of such tests, a number of parameters should be accurately determined, such as the seam geometry and stratigraphy, coal porosity and permeability parameters as well as optimum injection conditions. In essence the CO2 injection model should be calibrated for the reservoir characteristics using all available data. History matching calibrations are based on gas and water production from existing wells prior to injection. This paper will present reservoir models that were developed for a pilot--scale 907 tonnes (1000 tons) CO2 injection test that was performed in 2009 through one legacy coalbed methane production well in Russell County, Virginia, USA. The model incorporates a number of individual coal seams about 0.3 m (1ft) in thickness located at depths ranging from 300 to 700 m (1,000 to 2,200 feet). Model calibration was performed through history matching to prior production data, and subsequently the model was utilized to develop different injection scenarios. The developed model was used after injection to calculate CO2 plume distribution patterns that were monitored at the injection test. The paper will present model data and assumptions with a special emphasis on the effect of hydraulic fractures and the skin factor to the coalbed methane (CBM) production model.

Aug 1, 2013

By O. Guyot, A. Broussaud, J. Björkman, P. Söderman, P. O. Samskog

Model-Based Expert Control systems (MBEC) are on-line supervisory dynamic optimization systems which combine the ability of a phenomenological model to generate a large amount of information about the state of the process and predict its evolution, with the flexibility of a rules-based approach to take plant constraints into account and apply a complex control strategy. For its new concentrator started in 1995 in Kiruna (Sweden), LKAB has implemented a progressive grinding flowsheet with closed-circuit autogenous grinding followed by closed-circuit pebble grinding with ore pebbles. The standard for instrumentation in this new plant is very high. The control hardware consists of a Distributed Control System (DCS) through which the operators interact with the plant, supplemented by a site-level Management Information System (MIS). A state-of-the-art MBEC system was imbedded in the MIS by the authors before plant start-up. It consists of several modeling and expertise software modules: a phenomenological process model and a Kalman filter estimate continuously the state of the process, an optimizer calculates an optimum feedrate, while rules-based modules establish production targets and key process set-points. The decision to install the MBEC system as an integral part of the new plant before start-up illustrates the current maturity of the technology, i.e., enough know-how was accumulated through former projects to design and develop the system to a large extent without accessing the plant. The feasibility and the power of dynamic optimization systems were previously demonstrated in Kiruna pre-existing concentrator by the authors. First, a MBEC system was installed on the three existing pebble mill circuits, providing both an increase in quality (stabilised size distribution) and a 10% increase in capacity. An on-line expert control system with limited modeling capabilities was also installed in the existing flotation plant, with the aim of stabilizing phosphorous content in the concentrate and optimizing collector additions. Both objectives have been achieved.

Jan 1, 1995

By B. Bergmark, O. Guyot, A. Broussaud, C. Bouché

The Boliden Aitik concentrator in Sweden processes 2,000 t/h (2,200 stph) of low-grade copper ore. The plant consists of five grinding lines that feed four bulk-flotation banks with a scavenger-concentrate regrind mill und a column cleaner circuit with a regrind mill. The authors installed a model-based expert optimizing control system to maximize copper recovery in the bulk-flotation circuit while maintaining an appropriate copper grude in the cleaner feed. The optimizing control system uses on-line assays and calculates and implements set points for cell pulp levels, air rates and reagent- addition rates. It combines the power of a dynamic population-balance model that estimates mineral liberation in each stream, an optimizer that computes appropriate set points and a rule-based module that implements the strategy. The benefits have been evaluated over a period of three months. The model-based expert optimizing control system generates a measurable increase in copper recovery, around 0.5%, and an optimized bulk-concentrate grade. The need to maintain the optimizing control system and other practical aspects are discussed.

Jan 1, 2000

The Boliden Aitik concentrator in Sweden processes 2,000 tph of low grade copper ore. The plant consists of five grinding lines feeding four bulk flotation banks with a scavenger concentrate regrind mill, and a column cleaner circuit with a regrind mill. The authors installed a model-based expert, optimizing control system to maximize copper recovery in the bulk flotation circuit while maintaining an appropriate copper grade in the cleaner feed. The optimizing control system uses on-line assays and calculates and implements set points for cell pulp levels, air rates and reagent addition rates. It combines the power of a dynamic population balance model which estimates mineral liberation in each stream, an optimizer which computes appropriate set points and a rule-based module which implements the strategy. The benefits have been evaluated over three months. The model-based expert, optimizing control system generates a measurable increase in copper recovery, around 0.5 per cent and an optimized bulk concentrate grade. The need to maintain the optimizing control system and other practical aspects are discussed.

Jan 1, 1998

By André Desbiens, Jocelyn Bouchard, René del Villar

"The metallurgical performance of the column flotation process is determined by the concentrate grade and recovery. Although the former can be continuously measured using an on-stream analyzer, the latter must be estimated by a material balance calculation based on seldom verified steady-state assumptions. Consequently, the automatic control and optimization of flotation columns should be performed using secondary variables having a strong influence on the metallurgical performance, such as froth depth, gas hold-up or bubble surface area flux and bias. The aim of this paper is to present a model-based automatic control strategy using froth depth and bias measurements obtained from virtual sensors developed at Laval University. Preliminary pilot plant results on two-phase (water– air) and three-phase system (water – minerals – air) will be presented and eventual industrial implementation of such a strategy as well as the possibility of achieving effective real-time optimization from bias and froth depth measurements will also be discussed.INTRODUCTIONFlotation columns have been widely studied and used in mineral processing for about twenty years. Although a great deal of work has been accomplished to understand the influence of different variables such as froth depth (H), bubble surface area flux (Sb) and bias (Jb) on the metallurgical performance, the measurement of some of these variables is still difficult to be performed – except at the laboratory level – because in most cases, no commercial device yet exists.As a result of this, it is almost impossible to achieve neither efficient control nor optimization of the process at the industrial level, even in open-loop operation. This paper aims at presenting a simple control strategy of froth depth and bias. Description of the sensors used to achieved measurements, preliminary pilot plant results for froth depth control, eventual industrial applications and possibilities for process optimization are also treated."

Jan 1, 2003

By John A. Herbst

Mineral processors have evolved from "handbook-based" decision makers to "model-based" decision makers. With this evolution have come significant improvements through increasing productivity, decreasing capital and operating costs and increasing product quality. This paper traces the development of model-based decision-making technology over the last 40 years and documents the benefits resulting from systems optimization using these tools. Some speculation is ventured concerning the future of model-based decision-making tools and their use in the field of mineral processing.

Jan 1, 2000

By David K. Melgaard

Electroslag Remelting (ESR) is a complex process used to produce high quality specialty alloy materials. The quality can be directly correlated to variances in melt rate and immersion depth. Conventional ESR furnaces control these quantities using two independent control loops using proportional changes in current for melt rate and driving the electrode up and down to match a voltage set point for immersion depth. However it is well known that the control loops are highly coupled, i.e. changing the current to account for melt rate deviations changes the voltage depth relationship and vice verse. In addition the noise in measurements of the ESR process can be considerable, forcing conventional controllers to use highly damped responses. A new model-based controller has been developed to embody the coupling and improve responsiveness by using estimates from a reduced-order linear ESR model and the typical process measurements to control melt rate and immersion depth simultaneously. Kalman filtering is used to optimally combine the model estimates of eight process states and the measurements of voltage, current, position and mass to estimate the instantaneous melt rate and immersion depth. Several ESR melts under steady state and transient conditions were conducted to evaluate the performance of the new controller. This paper will discuss the design of the new ESR model and controller and will present experimental results demonstrating its much improved control and responsiveness. While this controller was developed for the ESR process, the effectiveness of model-based control in managing such a complex process with relatively simple equations suggests the approach could be employed for many other processes as well.

Jan 1, 2006

By J. A. Herbst, R. Zaragoza

Conventional control schemes in use today are not able to produce satisfactory control when high-frequency disturbances are present in the flotation feed. An advanced model-based control scheme is presented here as a promising solution to this control problem. The main feature of this control scheme is the real time identification of the unknown disturbances in the first few cells of the flotation circuit. This information is used to control the rest of the flotation plant in a feedforward fashion. This control scheme also provides flexibility to meet any metallurgical, economical, or management objective.

Jan 1, 1987

By S. Banisi, M. Pourkani, A. R. Laplante, A. Partoazar

"Canadian experience in industrial modeling of grinding, classification, and flotation kinetics was applied at the Sarcheshmeh copper mine, which processes 40,000 t/d of ore at 0.9 % Cu, in an effort to improve capacity and metallurgical performance. Mcivor's functional performance analysis was applied to ball mill cyclone circuits to maximize circuit capacity. Plitt's cyclone model was applied to predict how apex wear would affect classification performance, as part of a predictive maintenance program whereby the optimum wear period is determined for cast iron apexes. The flotation flowsheet was improved using Agar's optimization criteria. The impact of these technologies has been nothing short of spectacular, with an improved capacity of 1 S to 20""/o, and increased recoveries.1-IntroductionThe Sarcheshmeh copper ore body, which may rank as third or fourth largest in the world, contains 1 billion tonnes averaging 0.90 % copper and 0.03 % molybdenum. It is located southeast of Iran and has been processing 40,000 t/d of ore since 1982. The mine produces 100,000 tonnes of copper and 2,200 tonnes of molybdenum concentrate per year. After three stages of crushing, the ore with a Fso of 12. 7 mm is fed to 8 parallel ball mills in closed circuit with cyclones to produce a product 70""/o finer than 7 S microns. The concentrate of the first stage of flotation is reground and the tailings constitute the main component of the plant final tailings. A concentrate with an average grade of 31 % Cu is obtained after cleaning and re-cleaning stages. Total recovery of the plant varies between 83 and 87 % depending on the operating conditions and ore type.To improve the overall performance of the plant, it was first decided to evaluate the performance of grinding, classification and flotation. Measures were then taken to improve performance using the following criteria: (i) The improvements should be of the types that have resulted in significant improvements in other plants (e.g. Shannon et al, 1993); and (ii) The proposed improvements must be achievable with the manual operation presently used at Sarcheshmeh. The outcome of this study could also help in making decisions on the implementation of automatic control systems in the Sarcheshmeh copper mine."

Jan 1, 1998

By Sushanta Majumder

The physico-chemical characteristics of raw materials used for the production of iron ore pellets have a strong influence on the productivity of pelletization operations and on the quality of pellets. Since iron ores from different sources are used for making iron ore pellets and since the quality of the ores varies with time, there is a need to optimize and control pellet plant operations on a regular basis to achieve optimum productivity while maintaining pellet quality within the desirable specifications. In order to achieve this objective, a model-based on-line optimization system was implemented on two industrial scale induration furnaces. The optimization system consists of a rigorous mathematical model of the induration process, a model for the permeability of the bed of pellets, a statistical model for the quality of iron ore pellets and an optimization module based on sequential quadratic programming. The rigorous model is tested on-line using the wind-box temperature available real-time. The process was optimized to enhance induration furnace productivity for the given constraints on pellet quality parameters such as the cold compressive strength (CCS) and Tumble Index (TI), and other equipment design parameters. Process variables such as induration machine speed, cold air flow rate and hood temperature profile were used as the optimization variables. The on-line optimization system was successfully implemented in two industrial induration furnaces and lead to enhanced productivity. Details of the on-line optimization system and results of process optimization will be presented.

Sep 1, 2012

By Terre Lane, Kevin Gunesch, Rick Moritz

Global Resource Engineering Ltd. (GRE) ha aplicado un análisis estadístico avanzado a una base de datos existente de pruebas metalúrgicas para aumentar sustancialmente la certeza del modelo de recuperación. Esta mejora, resultó en un valor presente neto (VPN) más alto para el proyecto, y una certeza mayor en el modelo económico de mina.

Sep 1, 2017

By Lucas Breder Teixeira

Esse trabalho discute a modelagem termo-mecânica fisicamente não linear de materiais refratários considerando os efeitos de danificação utilizando o Método dos Elementos Finitos. Inicialmente é feita uma descrição geral dos materiais refratários com foco em suas características termo-mecânicas, destacando principalmente suas propriedades elásticas e comportamento de amolecimento, e demonstrando sua considerável dependência da temperatura. Algumas considerações são feitas com relação à evolução dos modelos de simulação numérica aplicados a refratários, iniciando-se com os modelos lineares elásticos até o uso de modelos constitutivos complexos. O modelo de fissuração distribuída utilizado para calcular a perda de rigidez elástica é então apresentado, juntamente com a fundamentação matemática pertinente e sua relação com os parâmetros físicos do material. Para ilustrar a aplicabilidade do modelo alguns exemplos são apresentados, discutindo-se suas principais capacidades com relação ao projeto de estruturas refratárias.

Oct 30, 2017

By Ramon Santos Corrêa

Com a descoberta de poços de petróleo cada vez mais profundos, as tolerâncias das propriedades mecânicas dos tubos de aço utilizados para este fim estão mais restritas. Somando-se a isso, o mercado pressiona por redução de custos e agregação de valor nos produtos ofertados. Por outro lado, a maturidade de interconexão alcançada pelos sistemas industriais, permitiu a disponibilização de dados mais precisos dos processos e a utilização de ferramentas computacionais avançadas de análise e modelagem de dados. Este trabalho tem como objetivo prever as propriedades mecânicas dos tubos após o processo de revenimento, a partir da composição química do aço, parâmetros dimensionais dos tubos e parâmetros do processo. O acompanhamento on-line da tendência das propriedades mecânicas permitiu uma operação preventiva no forno de revenimento, possibilitando a redução do lead time do processo, visto o tempo médio de 2 dias para o recebimento dos resultados do laboratório. A definição pela utilização das Redes Neurais Artificiais se baseou em trabalhos relacionados ao tema e casos de sucesso aplicados na indústria. Observou-se que os resultados obtidos a partir dos modelos obtiveram índices de assertividade superiores aos de outras técnicas utilizadas para este fim. Além disso, foi possível a criação de um único modelo para cada propriedade mecânica considerando todas as famílias de aço produzidas na Vallourec, facilitando os processos de calibração e sustentabilidade dos modelos.

Aug 16, 2017

By Maritha Andrade, Gustavo Mello, Marco Aurélio Perim, Arthur Quintão Andrade, Joeli Cuzzuol, Eduardo Kuhl

Este artigo apresenta os resultados da utilização da simulação de processos para a análise de alternativas na gestão de tomada de decisão envolvendo a logística de cabotagem (navios e barcaças) para o transporte de bobinas entre duas das unidades da ArcelorMittal (Tubarão e Vega), além da logística rodoviária para armazenagem e abastecimento de bobinas na unidade produtiva de Vega. O estudo, iniciou-se com o mapeamento dos processos e fluxos produtivos afim de identificar os limites iniciais e finais para representação na solução. Foi feita uma avaliação do carregamento e descarregamento das embarcações, retorno das embarcações, processo de carregamento dos caminhões, descarregamento e armazenagem das bobinas nos armazéns, além do abastecimento das bobinas para a produção na unidade de Vega. O estudo possibilitou avaliar a capacidade produtiva do sistema, o dimensionamento dos recursos envolvidos (navios, barcaças, frotas de caminhões, capacidade necessária para armazenagem externa), os gargalos do processo, as restrições e os possíveis cenários como alternativa para alcançar os objetivos desejados.

Oct 1, 2019

By Malu Braga Leal

Este trabalho propõe o controle e monitoramento da corrosão em escapamentos de automóveis pela modelagem e mapeamento termo-fluidodinâmico do escapamento utilizando o programa computacional de análise de volumes finitos ANSYS. A corrosão no escapamento do automóvel é produzida e catalisada pelos gases de combustão do motor que fluem aquecidos pelo escapamento. Ao se propor a utilização de uma rede de sensores ópticos nas regiões mapeadas pelo modelo obtido fluido dinâmico do escapamento do automóvel, tem-se uma ferramenta em tempo real para a visualização das regiões de maior gradiente térmico e mais suscetíveis à corrosão pelos gases de combustão no escapamento. A utilização do mapa termo fluidodinâmico do escapamento pelo programa ANSYS possibilita, assim, um maior controle das condições de corrosão no escapamento de um automóvel e na escolha de materiais mais adequados para a sua produção e funcionamento.

Aug 16, 2017

By Elisa Araujo Santos Darsie

A busca na melhoria da qualidade dos aços, principalmente no caso de aços limpos, fez com que o distribuidor de lingotamento continuo também seja empregado para a remoção das inclusões responsáveis por prejudicar as propriedades mecânicas dos aços. Uma melhor eficiência desta função do distribuidor pode ser atingida com o conhecimento das características do escoamento do banho metálico de modo que se possam propor modificações na configuração do distribuidor. Esses fenômenos de escoamento e remoção de inclusões podem ser simulados mediante a utilização da modelagem física. O objetivo deste trabalho é avaliar quatro configurações internas de distribuidor por meio da qualificação do escoamento via ensaio de linhas de fluxo e quantificação de inclusões passantes pelo veio com o ensaio de remoção de inclusões. As variáveis de controle utilizadas neste estudo são: velocidade de lingotamento, presença de barreiras e presença de tubo longo. Os resultados apresentados para o distribuidor em questão mostram que para os casos com o tubo longo, o uso da barreira torna o escoamento predominantemente ascendente eliminando o curto-circuito e favorável a remoção de inclusões passando de 29,76 para 24,29% de inclusões passantes pelo veio. Enquanto que para os casos sem tubo longo, o uso da barreira proposta diminuiu o contato do aço com a escória sobrenadante, aumentou o curto-circuito e aumentou também o percentual de inclusões passantes pelo veio de 2,56 para 3,01%.

Aug 8, 2018

By Felipe das Dôres Machado

No processo de fabricação de aço, o distribuidor possui grande importância na questão limpeza inclusionária, principalmente, quando se trata da produção de aços limpos (clean steel). As inclusões podem afetar negativamente as propriedades mecânicas e metalúrgicas do aço. Estudos realizados em modelos físicos e/ou matemáticos vêm sendo aplicados com intuito de propor medidas que melhorem a capacidade do distribuidor na remoção de inclusões presentes no aço. Este trabalho tem como objetivo principal qualificar o escoamento de um distribuidor e quantificar a remoção de inclusões do mesmo. Um modelo físico de um distribuidor de lingotamento contínuo de tarugos construído em acrílico e que respeita a similaridade de Froude e Reynolds é utilizado para os ensaios. A quantificação das inclusões é realizada por meio de um ensaio que envolve um sistema de injeção de partículas de polietileno na entrada no distribuidor e outro sistema de coleta dessas partículas na saída do distribuidor no qual as amostras coletadas, posteriormente, são secadas e pesadas. Com os resultados obtidos pretende-se compreender o efeito dos parâmetros propostos sobre a remoção de inclusões e permitir a utilização de uma ferramenta capaz de avaliar a qualidade de aços no que se refere à passagem de inclusões na saída do distribuidor.

Jul 30, 2018

By Rodrigo Sales

Os principais objetivos de um projeto de Integração e Otimização de Processos (PIO – Process Integration and Optimisation) é de auxiliar no desenvolvimento de uma estratégia integrada de desmonte e cominuição que minimize o custo total por tonelada processada nas etapas de lavra e cominuição das operações, minimize o consumo de energia e maximize a taxa de processamento, produção de metais e lucro da empresa. O projeto consiste na revisão de práticas operacionais, auditoria e amostragem, benchmarking, modelagem e simulações das operações de perfuração e desmonte e cominuição. Isto permite uma análise holística das operações para identificar oportunidades de melhorias e desenvolver estratégias integradas e otimizadas de operação da mina-à-planta. O projeto incluiu o sistema exclusivo da Metso, SmartTag™, para rastrear o minério dos furos de desmonte na mina até a planta concentradora com o objetivo de correlacionar os tipos de minério e de desmonte com os resultados de desempenho da planta. O sistema de modelamento geometalúrgico automatizado chamado GeoMetso™ utiliza a tecnologia de rastreamento de minério SmartTag™ para coletar continuamente dados de desempenho da planta e atualizar automaticamente os modelos preditivos e o modelo de blocos em tempo real. Este sistema é a base para a implementação, validação e melhoria contínua das estratégias integradas e otimizadas de operação, além de auxiliar na reconciliação da mina-à-planta e planejamento de lavra.

Aug 17, 2017

By João Lucas Lautenschlager Cortez Alves

Foi implementado um modelo matemático transiente e tridimensional para prever os campos de temperatura e composição presentes no sólido e poça de fusão durante um processo de soldagem a arco. O modelo foi desenvolvido com base nas equações de conservação macroscópicas de calor, massa e espécies químicas, que foram solucionadas pelo método dos volumes finitos. Os resultados do modelo mostraram boa aderência com soluções analíticas. Foram apresentados os efeitos de mudança na velocidade e potência de soldagem na distribuição de temperatura obtida e no formato da poça de fusão para soldagem em uma chapa de liga Al-6,5%Cu.

Oct 30, 2017