A slag prediction model in an electric arc furnace process for special steel production

In the steel industry, there are some parameters that are difficult to measure online due to technical difficulties. In these scenarios, soft-sensors, which are online tools that aim forecasting of certain variables, play an indispensable role for quality control. In this investigation, different soft sensors are developed to address the problem of predicting the slag quantity and composition in an electric arc furnace process. The results provide evidence that the models perform better for simulated data than for real data. They also reveal higher accuracy in predicting the composition of the slag than the measured quantity of the slag.The project leading to this research work has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 820670

Book of abstracts of the 15th International Symposium of Croatian Metallurgical Society - SHMD \u272022, Materials and metallurgy

Book of abstracts of the 15th International Symposium of Croatian Metallurgical Society - SHMD \u272022, Materials and metallurgy, Zagreb, Croatia, March 22-23, 2022. Abstracts are organized in four sections: Materials - section A; Process metallurgy - Section B; Plastic processing - Section C and Metallurgy and related topics - Section D

Book of abstracts of the 15th International Symposium of Croatian Metallurgical Society - SHMD \u272022, Materials and metallurgy

Book of abstracts of the 15th International Symposium of Croatian Metallurgical Society - SHMD \u272022, Materials and metallurgy, Zagreb, Croatia, March 22-23, 2022. Abstracts are organized in four sections: Materials - section A; Process metallurgy - Section B; Plastic processing - Section C and Metallurgy and related topics - Section D

Estudo de escórias de refino primário de aços com vistas a redução do consumo energético em fornos elétricos a arco

As indústrias siderúrgicas almejam aliar a máxima produtividade com um menor custo, neste contexto, no processo de produção de aço em uma aciaria elétrica uma série de fatores necessita de um melhor entendimento para alcançar as metas exigidas (máxima produtividade e menor custo). Um destes fatores que tem efeito direto sobre os custos é a escória espumante no refino primário, que além de favorecer o rendimento metálico, melhora a eficiência energética do FEA. O objetivo geral do presente trabalho é estudar as escórias de refino primário visando a redução do consumo energético, avaliando a espumação e os diferentes parâmetros que a afetam, utilizando a termodinâmica computacional (software FactSage 6.4) e dados industriais. A metodologia desenvolvida buscou especificamente: a) avaliar a saturação de MgO para o sistema CaO-SiO2-FeO-Al2O3-MgO através da termodinâmica computacional; e para os dados industriais: b) encontrar relações entre a composição química da escória e o consumo de energia elétrica; c) utilizar os diagramas de saturação isotérmicos (ISD’s) para avaliar o consumo de energia elétrica, avaliando a posição das corridas analisadas; d) encontrar relações entre os harmônicos de tensão e o consumo de energia elétrica; e) encontrar relações entre os harmônicos de tensão e a composição química da escória. Com relação à análise dos dados obtidos, pode-se concluir que: 1) a análise de saturação de MgO realizada no programa FactSage 6.4 apresentou os resultados esperados com relação à variação de composição química, a comparação entre os diagramas ternários e ISD’s; 2) o menor gasto de energia elétrica foi encontrado para as seguintes faixas de composição química: FeO entre 27,5 e 30% em massa, basicidade binária entre 3,0 e 3,2, MgO entre 5,5 e 6,5% em massa; 3) os ISD’s podem ser utilizados para a análise do consumo energético; 4) o teor de FeO de menor desvio padrão dos harmônicos foi de 29%; 5) quanto maior a variação dos THDv’s (distorção harmonica total de tensão), maior o gasto energético.Steelmaking industries aim to combine maximum productivity with a lower cost, in this context, in the steel production process in an electric steel plant a number of factors needs a better understanding to achieve the required goals (maximum productivity and lower cost). One of these factors that have a direct effect on costs is the foamy slag in the primary refining, which in addition to promoting the metal yield improves the energy efficiency of FEA. The overall objective of this work is to study the primary refining slag aimed at reducing energy consumption, evaluating the foaming and the different parameters affecting it, using computational thermodynamics (FactSage 6.4 software) and industrial data. The methodology consisted of: a) evaluate the MgO saturation for the CaO-SiO2-FeO-Al2O3-MgO system by computational thermodynamics; and with industrial data: b) find relationships between the chemical composition of the slag and the consumption of electricity; c) use the isothermal saturation diagrams (ISD) to assess the energy consumption, evaluating the position of the analyzed heat; d) find relationships between the voltage harmonics and power consumption; e) find relationships between the voltage harmonics and the chemical composition of the slag. Regarding the analysis of the data, it can be concluded that: 1) the MgO saturation analysis in FactSage 6.4 program presented the results expected in relation to the variation in chemical composition, the comparison between the ternary diagrams and ISD's; 2) the lowest power consumption was found for the following chemical composition ranges: FeO between 27.5 and 30%, binary basicity between 3.0 and 3.2, MgO 5,5 e 6,5%; 3) ISD's can be used for the analysis of energy consumption; 4) the FeO content of less harmonic standard deviation was 29%; 5) the greater the variation of THD's largest energy expenditure

An Intelligent Monitoring Interface for a Coal-Fired Power Plant Boiler Trips

A power plant monitoring system embedded with artificial intelligence can enhance its effectiveness by reducing the time spent in trip analysis and follow up procedures. Experimental results showed that Multilayered perceptron neural network trained with Levenberg-Marquardt (LM) algorithm achieved the least mean squared error of 0.0223 with the misclassification rate of 7.435% for the 10 simulated trip prediction. The proposed method can identify abnormality of operational parameters at the confident level of ±6.3%

Remanufacturing and Advanced Machining Processes for New Materials and Components

"Remanufacturing and Advanced Machining Processes for Materials and Components presents current and emerging techniques for machining of new materials and restoration of components, as well as surface engineering methods aimed at prolonging the life of industrial systems. It examines contemporary machining processes for new materials, methods of protection and restoration of components, and smart machining processes. • Details a variety of advanced machining processes, new materials joining techniques, and methods to increase machining accuracy • Presents innovative methods for protection and restoration of components primarily from the perspective of remanufacturing and protective surface engineering • Discusses smart machining processes, including computer-integrated manufacturing and rapid prototyping, and smart materials • Provides a comprehensive summary of state-of-the-art in every section and a description of manufacturing methods • Describes the applications in recovery and enhancing purposes and identifies contemporary trends in industrial practice, emphasizing resource savings and performance prolongation for components and engineering systems The book is aimed at a range of readers, including graduate-level students, researchers, and engineers in mechanical, materials, and manufacturing engineering, especially those focused on resource savings, renovation, and failure prevention of components in engineering systems.

Asphalt and Asphalt Mixtures

In recent years, with the rapid development of the world transportation industry, the proportion of asphalt pavement in road engineering is increasing. Therefore, while the demand for asphalt and asphalt mixture is increasing, the quality requirements for materials are also improving. In particular, new materials and new technologies are constantly emerging, and the application technology, theory, and technical specifications of asphalt materials have made great progress

Remanufacturing and Advanced Machining Processes for New Materials and Components

Remanufacturing and Advanced Machining Processes for Materials and Components presents current and emerging techniques for machining of new materials and restoration of components, as well as surface engineering methods aimed at prolonging the life of industrial systems. It examines contemporary machining processes for new materials, methods of protection and restoration of components, and smart machining processes. • Details a variety of advanced machining processes, new materials joining techniques, and methods to increase machining accuracy • Presents innovative methods for protection and restoration of components primarily from the perspective of remanufacturing and protective surface engineering • Discusses smart machining processes, including computer-integrated manufacturing and rapid prototyping, and smart materials • Provides a comprehensive summary of state-of-the-art in every section and a description of manufacturing methods • Describes the applications in recovery and enhancing purposes and identifies contemporary trends in industrial practice, emphasizing resource savings and performance prolongation for components and engineering systems The book is aimed at a range of readers, including graduate-level students, researchers, and engineers in mechanical, materials, and manufacturing engineering, especially those focused on resource savings, renovation, and failure prevention of components in engineering systems

Remanufacturing and Advanced Machining Processes for New Materials and Components

Remanufacturing and Advanced Machining Processes for Materials and Components presents current and emerging techniques for machining of new materials and restoration of components, as well as surface engineering methods aimed at prolonging the life of industrial systems. It examines contemporary machining processes for new materials, methods of protection and restoration of components, and smart machining processes. • Details a variety of advanced machining processes, new materials joining techniques, and methods to increase machining accuracy • Presents innovative methods for protection and restoration of components primarily from the perspective of remanufacturing and protective surface engineering • Discusses smart machining processes, including computer-integrated manufacturing and rapid prototyping, and smart materials • Provides a comprehensive summary of state-of-the-art in every section and a description of manufacturing methods • Describes the applications in recovery and enhancing purposes and identifies contemporary trends in industrial practice, emphasizing resource savings and performance prolongation for components and engineering systems The book is aimed at a range of readers, including graduate-level students, researchers, and engineers in mechanical, materials, and manufacturing engineering, especially those focused on resource savings, renovation, and failure prevention of components in engineering systems

Remanufacturing and Advanced Machining Processes for New Materials and Components

"Remanufacturing and Advanced Machining Processes for Materials and Components presents current and emerging techniques for machining of new materials and restoration of components, as well as surface engineering methods aimed at prolonging the life of industrial systems. It examines contemporary machining processes for new materials, methods of protection and restoration of components, and smart machining processes. • Details a variety of advanced machining processes, new materials joining techniques, and methods to increase machining accuracy • Presents innovative methods for protection and restoration of components primarily from the perspective of remanufacturing and protective surface engineering • Discusses smart machining processes, including computer-integrated manufacturing and rapid prototyping, and smart materials • Provides a comprehensive summary of state-of-the-art in every section and a description of manufacturing methods • Describes the applications in recovery and enhancing purposes and identifies contemporary trends in industrial practice, emphasizing resource savings and performance prolongation for components and engineering systems The book is aimed at a range of readers, including graduate-level students, researchers, and engineers in mechanical, materials, and manufacturing engineering, especially those focused on resource savings, renovation, and failure prevention of components in engineering systems.