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Steel is an indispensable material of the modern society and yet the production of steel is one of the largest anthropogenic CO2 emission sources on the planet. The conventional blast-furnace-basic-oxygen-furnace (BOF) process is responsible for generating 85% of the steel industry’s total CO2 emissions, which is the result of a high coal consumption rate for the reduction of iron ores and for providing the heat necessary for the high-temperature process. In order to meet the climate goal set by the Paris Agreement, the iron and steel industry must drastically decrease its CO2 emissions and aim at achieving net-zero emissions by 2050. Bioenergy is a form of renewable energy, and if it is managed sustainably throughout its life cycle, it can be considered carbon-neutral. Replacing fossil fuels with biofuels consumed during the steelmaking processes is one way to decrease CO2 emissions. However, this approach has not been widely adopted by steelmakers over the world due to the high price and the limited availability of wood-based biofuels. Hydrochar is a coal-like solid material that is produced from the hydrothermal carbonization (HTC) of biomass. It has attracted great interest from steelmakers due to its coal-like properties and the fact that it can be produced from a wide range of organic waste streams that can be found in almost every country. Previous studies focused on the use of hydrochar for the blast furnace process. This thesis therefore examines the potential use of hydrochar in the direct-reduction-electric-arc-furnace (DR-EAF) process, and particularly in two applications where the use of fossil coal is difficult to abate—the coal-based direct reduction of iron ore and the carburization of liquid steel in the EAF. This thesis begins with a characterization study of a hydrochar produced from lemon peel waste (LPH) and its comparison with a fossil reference material (anthracite) and two bio-reference materials (charcoal). The results reveal that LPH is a h, Stål är ett oumbärligt material i det moderna samhället, men produktionen av stål representerar samtidigt en av de största antropogena CO2-utsläppskällorna på planeten. Den konventionella processen som kombinerar en masugn med en konverter genererar 85 % av stålindustrins totala CO2-utsläpp. Detta är orsakat av en hög kolförbrukningshastighet för att reducera järnmalm och för att tillhandahålla den värme som krävs för denna högtemperaturprocess. För att klara klimatmålen i Parisavtalet måste stålindustrin drastiskt minska sina CO2-utsläpp och sikta på att uppnå nettonollutsläpp till 2050. Bioenergi är en form av förnybar energi, som om den hanteras på ett hållbart sätt under hela sin livscykel, kan betraktas som koldioxidneutral. Därför är det positivt att ersätta fossila bränslen med biobränslen som förbrukas under ståltillverkningsprocesserna i syfte att minska CO2-utsläppen. Detta tillvägagångsätt har dock inte använts i stor utsträckning av ståltillverkare i världen, på grund av det höga priset och den begränsade tillgågen på träbaserade biobränslen. Hydrochar är ett kolliknande fast material som framställs från en hydrotermisk förkolning av biomassa. Materialet har uppmärksammats av ståltillverkare på grund av dess kolliknade egenskaper och det faktum att det kan produceras från ett brett utbud av organiska avfall som finns tillgängligt i nästan alla länder. Tidigare studier har fokuserat på användningen av hydrochar för masugnsprocessen, medan denna avhandling fokuserar på att studera den potentialla användningen av hydrochar i electriska ljusbågsugnar som chargeras med direktreduktionspellets (DR-EAF). Dessutom för speciellt två tillämpningar där användningen av fossilt kol är svår att minska, nämligen den kolbaserade direkta reduktionen av järnmalm och uppkolningen av flytande stål i ljusbågsugnen. Inledningsvis så presenteras resultaten av en karaktäriseringsstudie av hydrochar framställt från citronskalsavfall (LPH) och resultaten jämförs med ett fossilt r, OSMET 3.0

The present work aims to answer three essential research questions (RQs) that have previously not been explicitly dealt with in the field of applied machine learning (ML) in steel process engineering. RQ1: How many training data points are needed to create a model with near-upper-bound predictive performance on test data? RQ2: What is the near-upper-bound predictive performance on test data? RQ3: For how long can a model be used before its predictive performance starts to decrease? A methodology to answer these RQs is proposed. The methodology uses a developed sampling algorithm that samples numerous unique training and test datasets. Each sample was used to create one ML model. The predictive performance of the resulting ML models was analyzed using common statistical tools. The proposed methodology was applied to four disparate datasets from the steel industry in order to externally validate the experimental results. It was shown that the proposed methodology can be used to answer each of the three RQs. Furthermore, a few findings that contradict established ML knowledge were also found during the application of the proposed methodology., QC 20240115

The European Union has set an ambitious target to limit the global temperature increase to less than 2°C. To fulfill this goal, the carbon emissions level should be reduced to 80–95% of the 1990 level by 2050. One of the most energy-intensive industries worldwide is the iron and steel industry. One approach to tackling this issue is to eliminate fossil-based reducing agents and utilize hydrogen to produce iron. Moreover, massive quantities of carbon and iron-bearing residues are generated at different stages of the steelmaking processes. In this research, the influence of hydrogen and water vapor on the reduction of acid iron ore pellets was studied in conditions simulating an operating blast furnace. Pellets reduced in a hydrogen-containing gas were found to achieve a higher reduction rate and extent, and also resulting in higher surface area and porosity. Additionally, several side streams from iron and steelmaking were used to produce cold bonded briquettes for use in a blast furnace utilizing an ettringite \((\mathrm{C}_{3}\mathrm{A}•3\mathrm{C\bar{S}}•32\mathrm{H})\) -based binder. The ettringite-based binder was produced primarily using ladle slag and used as an alternative to ordinary Portland cement as a binder in briquettes. Briquettes produced using ettringite-based binder were found to possess several technical, environmental, and economic advantages, including excellent compression and drop damage resistance compared to reference briquettes made using ordinary Portland cement, especially after 2 and 7 days of curing. Moreover, laboratory tests were conducted to assess the suitability of self-reducing and slag-forming briquettes produced from side streams to be used in an electric arc furnace. Briquettes were made using organic and inorganic binders. Tests were carried out to assess the mechanical, chemical, and thermal properties through a series of tests, including a thermogravimetric analyzer (TGA) coupled with a mass spectrometer (MS), dilato, Tiivistelmä Euroopan Unioni on asettanut kunnianhimoisen tavoitteen rajoittaa maapallon lämpötilan nousu alle 2 °C:seen. Jotta tavoitteeseen päästäisiin, vuoteen 2050 mennessä hiilidioksidipäästöjä tulisi vähentää 80–95 % verrattuna vuoden 1990 tasoon. Yksi maailman energiaintensiivisimmistä teollisuuden aloista on raudan ja teräksen valmistus. Eräs keino on vähentää fossiiliperäisten pelkistysaineiden käyttöä ja hyödyntää vetyä raudan valmistuksessa. Lisäksi valtavat määrät hiiltä ja rautaa sisältäviä sivuvirtoja muodostuu eri vaiheissa teräksen valmistuksen prosessiketjua. Tässä työssä on tutkittu vedyn ja vesihöyryn vaikutusta happamien rautapellettien pelkistymiseen masuunia jäljittelevissä olosuhteissa. Vetyä sisältävässä kaasuatmosfäärissä pelkistetyt pelletit pelkistyivät nopeammin ja saavuttivat korkeamman pelkistysasteen suuremman BET pinta-alan ja huokoisuuden ansiosta. Lisäksi useita raudan ja teräksen valmistuksen sivuvirtoja käytettiin kylmäpuristettujen masuunibrikettien valmistuksessa hyödyntäen ettringiitti \((\mathrm{C}_{3}\mathrm{A}•3\mathrm{C\bar{S}}•32\mathrm{H})\) -pohjaista sideainetta. Ettringiitti-pohjainen sideaine valmistettiin etupäässä senkkakuonasta ja sillä korvattiin perinteinen Portland-sementti briketin sideaineena. Ettringiitti-pohjaisesta sideaineesta valmistetuissa briketeissä havaittiin useita teknisiä, taloudellisia ja ympäristöön liittyviä etuja verrattuna Portland-sementistä valmistettuihin referenssibriketteihin kuten erinomainen puristuslujuus ja vähäinen vaurioalttius pudotuksessa erityisesti 2 ja 7 päivän kovettumisen jälkeen. Lisäksi selvitettiin sivutuotevirroista valmistettujen itsepelkistyvien ja kuonaa muodostavien brikettien soveltuvuutta valokaariuuniprosessiin laboratoriokokein. Briketeissä käytettiin sekä orgaanisia että epäorgaanisia sideaineita. Mekaanisia, kemiallisia ja korkealämpötilaominaisuuksia arvioitiin tekemällä erilaisia testejä kuten termogravimetria (TGA) yhdistettynä massaspektrometriin (MS) sekä di

Utsläppen av växthusgaser ökar över hela världen och nya tekniker används för att minska utsläppen. 7% av utsläppen kommer från stålsektorn. 25% av världens stålproduktion görs via återvinningstekniken ljusbågsugn. Genom återvinningsprocessen släpps det ut 500kg CO2 per ton producerat flytande stål. En möjlighet att sänka dessa direkta utsläppär att koppla ljusbågsugnsprocessen med biomassa förgasnings och koldioxidavskiljning. Den föreslagna lösningen i denna avhandling är att utnyttja avgaserna från stålsmältningen i förgasningsprocessen och skapa värdefulla produkter. Projektet utvärderar den tekniska genomförbarheten i form av energieffektivitet och kolutnyttjande. Den föreslagna processen simulerades med Aspen Plus. Ett problem med ljusbågsugnens avgaser är fluktuationen i sammansättningen. Tre fall avavgassammansättning undersöktes. Fall 1 var den genomsnittliga avgassammansättningen, medan fall 2 och 3 var extrema med högt CO- respektive CO2-innehåll. Resultatet visade att syntetsgassammansättningen starkt beror på förgasningsmedlet. I samtliga fall ökade energieffektiviteten och de direkta utsläppen minskade, jämfört med nuvarande process. Fall 1 visade generellt högst effektivitet och kolutnyttjande, medan det CO2 rika fallet (fall 3) hade lägst. Ett kontinuerligt flöde av förgasningsmedel krävs för att driva förgasningsprocessen. Eftersom ljusbågsugn är en satsvis process, sker luftförgasning när avgaser inte är tillgängliga. Det önskade resultatet av luftförgasning är att producera syntetsgas som liknar avgasförgasningens syntesgas. Resultaten visade att luftinfiltration i avgaser är gynnsamt för mer liknande syntesgas ., Greenhouse gas emissions are increasing worldwide, and new techniques are being adopted to suppress the emissions. The steel sector is responsible for 7% of the emissions. 25% ofthe world’s steel production is made through the recycling technique EAF. Throughout the recycling process, 500 kg CO2 gets emitted per ton of liquid steel produced. An opportunity to lower these direct emissions is to couple the EAF process to biomass gasification and CO2 utilisation process. The proposed solution in this thesis is to utilise the off-gases in the gasification process and create high-valuable products. The project evaluates the technical feasibility via energy efficiency and carbon utilisation. The proposed process was simulated using Aspen Plus. A problem with the off-gases from EAF gasification is the fluctuation in composition. Three cases of off-gas composition were therefore investigated. Case 1 was the average off-gas composition, while cases 2 and 3 were extreme with high CO and CO2 content, respectively. The result showed that the syngas composition strongly depends on the gasifying agent. In all cases, the energy efficiency increased, and the direct emissions decreased. Case 1 generally showed the highest efficiency and carbon utilisation, while the CO2 heavily case (case 3) had the lowest. A continuous flow of gasifying agents is required to run the gasification process. Since EAF is a batch process, air gasification runs when off-gases are unavailable. The desired outcome of air gasification is to produce syngas similar to off-gas gasification. The results showed that air infiltration in off-gases is favourable for more similar syngas composition.

Steelmaking in the Electric Arc Furnace (EAF) generates around a 40 wt. % of slag, a solid by-product which might contain relatively high amounts of iron (about 35 wt. % in iron oxides (FeO-Fe2O3)) and other valuable metals, such as manganese (approx. 6 wt. % as MnO) and chromium (approx. 2.5 wt. % as Cr2O3). Although steel slags find today many applications, mainly as road-making aggregate, the development of new, sustainable, metal recovery methodologies from slag is fundamental to prevent the permanent loss of valuable alloying elements and to enhance the circular economy of the steelmaking sector. This study explores thermodynamically the potential of hydrogen gas as a reducing agent to replace the carbonaceous substances currently used in key metallurgical processes of steel by-product valorisation, aiming at reducing the related CO2 emissions and at maximizing the metallic recovery. Process modelling of the reduction of iron oxides present in EAF slag (Fe-O-X system, where X= Si, Mg, Ca, Al) was performed using the FactSage software. Energy and mass balance calculations were obtained during the reduction of the input slag mixture at 1750 °C by injection of variable amounts of hydrogen gas at room temperature. The results were compared with those obtained analogously by the addition of variable amounts of carbon powder. The results of this study will allow us to understand the chemical reactions and the basic thermodynamic aspects of the processes occurring during the hydrogen-based reduction of EAF steel slags to reduce the CO2 emissions from the established process metallurgy and by-product valorisation routes.

Steel production is today one of the most CO2-demanding activities and causes 8% of the global emissions of GHG. It is crucial for the industry to reduce its emissions radically in order to be in line with the goals of the Paris Agreement and the Science-Based Target initiative. Ovako AB, one of the leading producers of high-strength engineering steel, has been at the forefront when it comes to sustainability initiatives within the industry. Heavy investments are being made into sustainable steel production methods and technologies and to make this viable, the company has, from January 1st, 2022, started to put a price premium on their steel products of 30 € per tonne. This study aims to answer the question of how Ovako's customers, based on the three different industries of mining, automotive, and bearing, experience this price premium and how a green steel can justify this surcharge. Furthermore, this case study aims to understand the extent to which those customers require carbon neutrality when sourcing steel. Connected to the findings from the innovation theories and the literature, this study aims to answer the question of how sustainable innovations may influence future competitiveness regarding engineering steel. To answer these questions, interviews with key individuals from different customers of Ovako were conducted. Moreover, focus groups at Ovako with relevant employees have been held at the same time as a literature study has been conducted. Based on the answers obtained from the data collection, a thematic analysis has been performed where overarching themes have been identified. Additionally, a carbon impact calculator has been used to calculate the carbon reduction potential of using a carbon-neutral engineering steel in three different applications connected to the three industries investigated, namely a complete bearing, a drill bit, and a final drive unit. The results from the calculations as well as the answers obtained regarding the research qu

The steel industry is on its way towards more environmentally friendly steelmaking. To achieve the ambitious goals of significant CO₂ emissions reduction, new processes, practices, sources of on-line data, and digitalization together with automation will be required. To address these issues, this paper discusses optical emission spectroscopy (OES) as an on-line data acquisition method for industrial electric arc furnaces and ladle furnaces. The current state of the OES as a measurement method in the steel industry together with prospects of new applications are presented with examples based on the authors’ prior research.

Structural health monitoring (SHM) in an electric arc furnace is performed in several ways. It depends on the kind of element or variable to monitor. For instance, the lining of these furnaces is made of refractory materials that can be worn out over time. Therefore, monitoring the temperatures on the walls and the cooling elements of the furnace is essential for correct structural monitoring. In this work, a multivariate time series temperature prediction was performed through a deep learning approach. To take advantage of data from the last 5 years while not neglecting the initial parts of the sequence in the oldest years, an attention mechanism was used to model time series forecasting using deep learning. The attention mechanism was built on the foundation of the encoder–decoder approach in neural networks. Thus, with the use of an attention mechanism, the long-term dependency of the temperature predictions in a furnace was improved. A warm-up period in the training process of the neural network was implemented. The results of the attention-based mechanism were compared with the use of recurrent neural network architectures to deal with time series data, such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The results of the Average Root Mean Square Error (ARMSE) obtained with the attention-based mechanism were the lowest. Finally, a variable importance study was performed to identify the best variables to train the model., This work has been funded by the Colombian Ministry of Science through grant number 786, “Convocatoria para el registro de proyectos que aspiran a obtener beneficios tributarios por inversión en CTeI”. This work has been partially funded by the Spanish Agencia Estatal de Investigación (AEI)—Ministerio de Economía, Industria y Competitividad (MINECO), and the Fondo Europeo de Desarrollo Regional (FEDER) through the research project DPI2017-82930-C2-1-R, and by the Generalitat de Catalunya through the research project 2017-SGR-388., Peer Reviewed, Postprint (published version)

The electric arc furnace has been the subject of extensive research due to its complex and chaotic nature. Machine learning methods provide a powerful forensic examination of industrial processes as they exclude numerous assumptions and involve irregularities present in industrial conditions. In this study, different machine learning and data processing methods were used to evaluate the energy efficiency parameters of the electric arc furnace process. The dataset was collected over five years, in a steelmaking factory, with 42 features. This data was split into training and test sets, which were used for training and evaluation, respectively. With extensive data management, the data quality and machine learning model performance were improved. It was found that selected models display similar performance, yet the artificial neural network shows greater flexibility when changing targets. The results indicate that a data-centric rather than model-centric approach is better for improving model performance. Using the partial dependence plot and SHAP method, insight was gained into each parameter's correlation with the target. It was found that the amount of hot heel (melted steel left in the furnace, to be re-heated) was the main factor disturbing the data quality and model performance. It was also demonstrated that data for total oxygen consumption should be divided from the oxygen used into refining and natural gas. This highly improves model performance. Employing a data-centric machine learning model to control and optimize main process parameters (with a small capital investment) leads to lower energy consumption for industrial processes.

In the recycling of zinc from electric arc furnace dust using microwave-based furnaces, the use of graphite powder as a reductant results in significant greenhouse gas emissions. In this study, graphite was replaced by a non-carbonaceous reductant in the form of silicon powder. The sample was heated in a microwave-based furnace under 7.5 kW maximum power irradiation at 2.45 GHz. The results clearly indicate that the reaction proceeded between zinc ferrite and silicon powder. The maximum removal rate of zinc obtained was 80% in cases where more than 10 times the stoichiometric amount of silicon powder was used for a heating time of more than 20 min. The apparent activation energy of microwave-based heating was 115.39 kJ/mol lower than that when heating with a conventional furnace. (Authors.), In the recycling of zinc from electric arc furnace dust using microwave-based furnaces, the use of graphite powder as a reductant results in significant greenhouse gas emissions. In this study, graphite was replaced by a non-carbonaceous reductant in the form of silicon powder. The sample was heated in a microwave-based furnace under 7.5 kW maximum power irradiation at 2.45 GHz. The results clearly indicate that the reaction proceeded between zinc ferrite and silicon powder. The maximum removal rate of zinc obtained was 80% in cases where more than 10 times the stoichiometric amount of silicon powder was used for a heating time of more than 20 min. The apparent activation energy of microwave-based heating was 115.39 kJ/mol lower than that when heating with a conventional furnace. (Authors.)

A study is presented of the process and synthesis of value-added ferrous material from EAF (electric arc furnace) slag through reduction and melting using a waste carbon resource of spent coffee grounds. Spent coffee grounds were carbonised at 400 degrees C to obtain transformed spent coffee grounds. Pitch coke has also been used in the current study as a separate carbon source to compare the results obtained from using transformed spent coffee grounds. A two-stages process has been employed in which a relatively low temperature of 1 200 degrees C was used to ensure solid-state reduction followed by melting at 1 550 degrees C. Overall, the performance of transformed-spent coffee grounds was better than that of pitch coke, thus giving rise to the potential utilisation of waste materials like EAF slag and spent coffee grounds as secondary ferrous and carbon resources for iron and steelmaking applications. (Authors.), A study is presented of the process and synthesis of value-added ferrous material from EAF (electric arc furnace) slag through reduction and melting using a waste carbon resource of spent coffee grounds. Spent coffee grounds were carbonised at 400 degrees C to obtain transformed spent coffee grounds. Pitch coke has also been used in the current study as a separate carbon source to compare the results obtained from using transformed spent coffee grounds. A two-stages process has been employed in which a relatively low temperature of 1 200 degrees C was used to ensure solid-state reduction followed by melting at 1 550 degrees C. Overall, the performance of transformed-spent coffee grounds was better than that of pitch coke, thus giving rise to the potential utilisation of waste materials like EAF slag and spent coffee grounds as secondary ferrous and carbon resources for iron and steelmaking applications. (Authors.)

Rice husk ash (RHA) has been used to prepare high-purity silicon by a combination of a silicon preparation process and a refining process. Raw materials including RHA, silica sand and SiO2-CaO-Al2O3 slag were initially pelletised and then smelted in an electric arc furnace. The results show that slag refining and acid leaching have significant influences on purifying Si products. With the addition of slag, the purity of Si increased from 94.96% to 96.47% and the contents of impurities such as Fe and P reduced from 2.06 wt.% and 0.09 wt.% to 0.77 wt.% and 0.05 wt.%, respectively. After acid leaching, the purity of the Si increased to 99.76% and the content of P reduced to 0.029 wt.%. The leaching kinetics analysis results show that the surface chemical reaction model is suitable to describe the extraction process of Fe, Al, and Ca in silicon. (Authors.), Rice husk ash (RHA) has been used to prepare high-purity silicon by a combination of a silicon preparation process and a refining process. Raw materials including RHA, silica sand and SiO2-CaO-Al2O3 slag were initially pelletised and then smelted in an electric arc furnace. The results show that slag refining and acid leaching have significant influences on purifying Si products. With the addition of slag, the purity of Si increased from 94.96% to 96.47% and the contents of impurities such as Fe and P reduced from 2.06 wt.% and 0.09 wt.% to 0.77 wt.% and 0.05 wt.%, respectively. After acid leaching, the purity of the Si increased to 99.76% and the content of P reduced to 0.029 wt.%. The leaching kinetics analysis results show that the surface chemical reaction model is suitable to describe the extraction process of Fe, Al, and Ca in silicon. (Authors.)

The steel industry is in constant need of improving its production processes. This is partly due to increasing competition and partly due to environmental concerns. One commonly used method for improving these processes is through the act of modeling. Models are representations of the reality that can be used to study and test new processes and strategies without costly interventions. In recent years, Machine Learning (ML) has emerged as a promising modeling approach for the steel industry. This has partly been driven by the Industry 4.0 development, which highlights ML as one of the key technologies for its realization. However, these models are often difficult to interpret, which makes it impractical to validate if the model accurately represents reality. This can lead to a lack of trust in ML models by domain practitioners in the steel industry. Thus, the present work investigates the practical usefulness of ML models in the context steel process engineering. The chosen application to answer this research question is the prediction of the Electrical Energy (EE) consumption of Electric Arc Furnaces (EAF). The EAF process was chosen due to its widespread use in the steel industry and due to the difficulty to accurately model the EE consumption using physical modeling. In the present literature, the use of linear statistical models are commonly used even though the EE consumption is non-linearly dependant on multiple important EAF process variables. In addition, the literature does neither investigate the correlations between input variables nor attempts to find the most optimal model with respect to model complexity, predictive performance, stability, and generalizability. Furthermore, a consistent reporting of predictive performance metrics and interpreting the non-transparent models is lacking. These shortcomings motivated the development of a Model Construction methodology and a Model Evaluation methodology that eliminate these shortcomings by considering both t, Stålindustrin är i ständigt behov av att förbättra sina produktionsprocesser. Detta beror dels på ökad konkurrens och dels på miljöhänsyn. En vanligt förekommande metod för att förbättra dessa processer är genom modellering. Modeller representerar verkligheten och kan därmed användas för att undersöka effekten av nya processer och strategier utan kostsamma interventioner. Under de senaste åren har maskininlärning (ML) framhävts som en lovande modelleringsmetod för stålindustrin. Detta har delvis drivits på av Industri 4.0, som lyfter fram ML som en av sina nyckelteknologier. Dessa modeller är dock ofta svåra att tolka, vilket gör det opraktiskt att validera om modellen representerar verkligheten. Detta kan leda till brist på förtroende för ML-modeller som modelleringsverktyg inom stålindustrin. Målet med denna studie är att undersöka om ML modeller är praktiskt användbart inom stålprocessteknik. För att besvara denna forskningsfråga har förbrukningen av elektrisk energi (EE) för ljusbågsugnen valts som inriktning. Processen valdes på grund av dess omfattande användning inom stålindustrin och på grund av svårigheten att exakt modellera EE-förbrukningen med hjälp av metallurgi och termodynamik. I den aktuella litteraturen används vanligtvis linjära statistiska modeller även om EE-konsumtionen är icke-linjärt beroende av flera viktiga processvariabler. Dessutom undersöker inte studierna i litteraturen korrelationerna mellan invariablerna eller försöker hitta den mest optimala modellen med avseende på modellkomplexitet, prediktiv prestanda, stabilitet och generaliserbarhet. Dessutom saknas en konsekvent rapportering av prediktiva prestandamätvärden och tolkning av icke-transparenta modeller. Dessa brister motiverade utvecklingen av en metodik för att skapa ML modeller och en metodik för att utvärdera ML modeller. De båda metodikerna eliminerar dessa brister genom att beakta både de processmetallurgiska aspekterna samt de utmaningar som ML modelleringen medför. Genom anv, Avhandlingen har finansierats av "Hugo Carlssons stipendiefond för vetenskaplig forskning" som tillhandahålls av Jernkontoret. Stipendiumet har betalats ut till doktoranden.

A dynamic, first-principles process model for a steelmaking electric arc furnace has been developed. The model is an integrated part of an application designed for optimization during operation of the furnace. Special care has been taken to ensure that the non-linear model is robust and accurate enough for real-time optimization. The model is formulated in terms of state variables and ordinary differential equations and is adapted to process data using recursive parameter estimation. Compared to other models available in the literature, a focus of this model is to integrate auxiliary process data in order to best predict energy efficiency and heat transfer limitations in the furnace. Model predictions are in reasonable agreement with steel temperature and weight measurements. Simulations indicate that industrial deployment of Model Predictive Control applications derived from this process model can result in electrical energy consumption savings of 1–2%.

Cyanide, among with NOₓ, CO₂, and CO, is one of the adverse compounds that form in the ironmaking and steelmaking industry. High-temperature processes are suitable environments for cyanide formation, and cyanide can form as a result of recombination in electric arc plasma. Even though the cyanides might not survive e.g. the post-combustion process, understanding the formation mechanisms of hazardous materials in the steelmaking industry is important. In this work, the recombination of cyanide in a pilot-scale AC electric arc furnace is studied with optical emissions from the CN molecule. The results show how the optical emissions from the cyanide change in different process steps. Electric input, plasma temperature, and interaction of the arc with solid charge material were observed to have an impact on the CN signal. Additionally, equilibrium composition computation highlights how different sources of carbon change the recombination rate and that the highest recombination occurs at 6821 K.

The electric arc furnace is the main process unit in scrap‐based steelmaking. Owing to its importance, numerous mathematical models for predicting the course of the electric arc furnace process have been developed. This article reviews mathematical process models proposed in the literature, identifying the most common modeling approaches, and uses mathematical descriptions for the main phenomena. Furthermore, the validation of such models is discussed in detail. Finally, the article identifies gaps in the existing knowledge and provides suggestions for the further development of mathematical process models.

During electric arc furnace (EAF) steelmaking process, burnt lime is charged together with other slag forming materials to attain a specific basicity of the slag and to achieve purification by removing unwanted elements. Herein, fly ash (FA) containing ≈60% CaO generated from pulp/paper mills is tested to partially (15–50%) replace primary lime (PL) in pilot scale EAF trials. The obtained results show good possibilities. It is found that an increased amount of FA instead of PL reduces the required amount of FeSi (up to 3 kg t−1 of scrap) and increases the sulfur content in the final slag. As a result, the amount of required slag/ton of steel can be decreased. However, the phosphorus content in the metal is slightly increased. The replacement ratio of FA will be limited by the acceptable phosphorus level in the final steel, due to higher phosphorus content in FA from pulp and paper mills compared with that in PL. Applications of FA as slag formers can reduce the consumption of natural resources in the metallurgical processes. In addition, it can reduce the amount of wastes from pulp/paper industries sent to landfill, which is important from an environmental point of view., QC 20201228

This study investigates the integration of water electrolysis technologies in fossil-free steelmaking via the direct reduction of iron ore followed by processing in an electric arc furnace (EAF). Hydrogen (H2) production via low or high temperature electrolysis (LTE and HTE) is considered for the production of carbon-free direct reduced iron (DRI). The introduction of carbon into the DRI reduces the electricity demand of the EAF. Such carburization can be achieved by introducing carbon monoxide (CO) into the direct reduction process. Therefore, the production of mixtures of H2 and CO using either a combination of LTE coupled with a reverse water-gas shift reactor (rWGS-LTE) or high-temperature co-electrolysis (HTCE) was also investigated. The results show that HTE has the potential to reduce the specific electricity consumption (SEC) of liquid steel (LS) production by 21% compared to the LTE case. Nevertheless, due to the high investment cost of HTE units, both routes reach similar LS production costs of approximately 400 €/tonne LS. However, if future investment cost targets for HTE units are reached, a production cost of 301 €/tonne LS is attainable under the conditions given in this study. For the production of DRI containing carbon, a higher SEC is calculated for the LTE-rWGS system compared to HTCE (4.80 vs. 3.07 MWh/tonne LS). Although the use of HTCE or LTE-rWGS leads to similar LS production costs, future cost reduction of HTCE could result in a 10% reduction in LS production cost (418 vs. 375 €/tonne LS). We show that the use of HTE, either for the production of pure H2 or H2 and CO mixtures, may be advantageous compared to the use of LTE in H2-based steelmaking, although results are sensitive to electrolyzer investment costs, efficiencies, and electricity prices., QC 20201202

The effect of CaF2 addition on dephosphorization reaction between molten steel and electric arc furnace (EAF) slag using direct reduced iron (DRI) at 1823 K (1550 °C) was investigated. Basicity, the thermodynamic parameter affecting the removal capacity of phosphorus (i.e., phosphate capacity), decreased using DRI due to an increased SiO2 concentration in the slag. To minimize slag volume and maximize dephosphorization efficiency, the CaF2 was added to the slag. As CaF2 content increased (0 to 10 mass pct), dephosphorization efficiency also increased. Thermodynamic analysis in conjunction with slag structural studies using Raman spectroscopy were conducted to explain the complicated phenomena. The results exhibited that even 5 to 6 mass pct CaF2 can improve the dephosphorization efficiency when DRI is used as raw material in an EAF process., QC 20201201

The melting time of scrap is a factor that affects the Electrical Energy (EE) consumption of the Electric Arc Furnace (EAF) process. The EE consumption itself stands for most of the total energy consumption during the process. Three distinct representations of scrap, based partly on the apparent density and shape of scrap, were created to investigate the effect of scrap on the accuracy of a statistical model predicting the EE consumption of an EAF. Shapley Additive Explanations (SHAP) was used as a tool to investigate the effects by each scrap category on each prediction of a selected model. The scrap representation based on the shape of scrap consistently resulted in the best performing models while all models using any of the scrap representations performed better than the ones without any scrap representation. These results were consistent for all four distinct and separately used cleaning strategies on the data set governing the models. In addition, some of the main scrap categories contributed to the model prediction of EE in accordance with the expectations and experience of the plant engineers. The results provide significant evidence that a well-chosen scrap categorization is important to improve a statistical model predicting the EE and that experience on the specific EAF under study is essential to evaluate the practical usefulness of the model., QC 20201111

Machine learning (ML) is a promising modeling framework that has previously been used in the context of optimizing steel processes. However, many of the more advanced ML models, capable of providing more accurate predictions to complex problems, are often impossible to interpret. This makes the domain experts in the steel industry, to a large extent, hesitant to adopt these models. The valuable increase in model accuracy is diminished by the lack of model interpretability. Herein, Shapley additive explanations (SHAP) is applied to an advanced ML model, predicting the electrical energy (EE) consumption of an electric arc furnace (EAF). The insights from SHAP reveal the contributions from each input variable on the EE for every single heat in the prediction domain. These contributions are then evaluated based on process metallurgical experience., QC 20200713

The non-linearity of the Electric Arc Furnace (EAF) process and the correlative behavior between the process variables impose challenges that have to be considered if one aims to create a statistical model that is relevant and useful in practice. In this regard, both the statistical modeling framework and the statistical tools used in the modeling pipeline must be selected with the aim of handling these challenges. To achieve this, a non-linear statistical modeling framework known as Artificial Neural Networks (ANN) has been used to predict the Electrical Energy (EE) consumption of an EAF producing stainless steel. The statistical tools Feature Importance (FI), Distance Correlation (dCor) and Kolmogorov–Smirnov (KS) tests are applied to investigate the most influencing input variables as well as reasons behind model performance differences when predicting the EE consumption on future heats. The performance, measured as kWh per heat, of the best model was comparable to the performance of the best model reported in the literature while requiring substantially fewer input variables., QC 20200219

An existing pyrometallurgical process for tantalum and niobium recovery, mainly from low grade pyrometallurgical residues, was investigated. Melting experiments were carried out in a pilot-scale electric arc furnace to study the material system during the reduction process caused by blowing coke into the liquid mineral melt. During the pyrometallurgical treatment refractory metals such as tantalum and niobium are converted into their carbides and enriched in the molten iron-based metal phase. Titanium is also enriched in the metal phase as an unwanted accompanying element, but most of it remains in oxidic form in the slag and is mainly bound in the mineral perovskite. Cooled down slag samples were analysed using XRF, XRD, SEM and EDX to investigate the formation of mineral phases rich in tantalum during various stages of the reduction process. The results show that the settling of the tantalum-rich iron droplets in the molten slag into the metal phase may play a greater role for the kinetics than the actual reduction reaction caused by blowing in coke. (Authors.), An existing pyrometallurgical process for tantalum and niobium recovery, mainly from low grade pyrometallurgical residues, was investigated. Melting experiments were carried out in a pilot-scale electric arc furnace to study the material system during the reduction process caused by blowing coke into the liquid mineral melt. During the pyrometallurgical treatment refractory metals such as tantalum and niobium are converted into their carbides and enriched in the molten iron-based metal phase. Titanium is also enriched in the metal phase as an unwanted accompanying element, but most of it remains in oxidic form in the slag and is mainly bound in the mineral perovskite. Cooled down slag samples were analysed using XRF, XRD, SEM and EDX to investigate the formation of mineral phases rich in tantalum during various stages of the reduction process. The results show that the settling of the tantalum-rich iron droplets in the molten slag into the metal phase may play a greater role for the kinetics than the actual reduction reaction caused by blowing in coke. (Authors.)

Low-carbon ferromanganese (LC-FeMn) is an essential ingredient for making high-strength low-alloy steel and stainless steel. The conventional industrial-scale silicothermic method for the production of LC-FeMn comprises several energy intensive complex steps consuming about 2 000 kWh/ton. An improved silicothermic process was attempted, which is based on a single step smelting of optimised charge mix in the electric arc furnace. Thermochemical simulation of the smelting process by FactSage 6.4 showed significant effect of the charge mix basicity (B = CaO/SiO2) on Mn, Fe, Si and P distribution between the metal and slag. The optimum basicity was found to be 1.5 at the charge mix ratio 1:1:0.6 Mn ore/lime/SiMn in the smelting tests. Under optimum conditions, the energy consumption was about 690 kWh/ton. This approach has potential benefits for the ferromanganese industry in terms of simpler and energy-efficient process., Low-carbon ferromanganese (LC-FeMn) is an essential ingredient for making high-strength low-alloy steel and stainless steel. The conventional industrial-scale silicothermic method for the production of LC-FeMn comprises several energy intensive complex steps consuming about 2 000 kWh/ton. An improved silicothermic process was attempted, which is based on a single step smelting of optimised charge mix in the electric arc furnace. Thermochemical simulation of the smelting process by FactSage 6.4 showed significant effect of the charge mix basicity (B = CaO/SiO2) on Mn, Fe, Si and P distribution between the metal and slag. The optimum basicity was found to be 1.5 at the charge mix ratio 1:1:0.6 Mn ore/lime/SiMn in the smelting tests. Under optimum conditions, the energy consumption was about 690 kWh/ton. This approach has potential benefits for the ferromanganese industry in terms of simpler and energy-efficient process.

Sandvik produces about 230 000 tonnes of steel annually by melting in an electric arc furnace, where more than 90% of this steel is casted via continuous casting. When the strands are cast, these strands will be cuts to specific lengths with 2 cm thick cuts by using gas and iron powder. This generates approximately 750 tonnes of steel chips (cutting residues) each year, with a composition from the entire annual production of steel that falls as a residual. The purpose of the work was to review a possible reuse of the cutting residues as a raw material in the electric arc furnace. The problem with the cutting residue is the large reactive surface area, which could cause the material to burn in the electric arc furnace during operation. Since there are a high gas flow in the electric arc furnace during operation, the cutting residue that has a small particle size can also disappear from the furnace with the gas flow to the particle filters. By briquetting the cutting residue, these problems could be minimized and a reuse of the cutting slag as raw material could thus be possible. Therefore the cutting residue was transported to a company that sieved, dried and briquetted the cutting residue. 37 tonnes of cutting residue briquettes have been reused into 18 charges under normal operations with 2 tonnes of cutting residue briquettes in each charge (one charge with only 1 tonne of cutting slag). In order to measure how efficient, the reuse of the cutting residue was, a reference was needed. The reference was based on how the yield of steel for the elements, molybdenum, nickel, copper, cobalt and chromium in the electric arc furnace behaves in daily operation. This yield was used as a basis for calculating the yield when reusing the cutting residue. The results showed that nickel and molybdenum had a consistently good yield. The results for the cobalt and copper was not as clear, but the yields were generally good. In the case of chromium the results are naturally varied, Varje år producerar Sandvik ungefär 230 000 ton stål genom nedsmältning av stålskrot i ljusbågsugnen där mer än 90 % av stålet gjuts via stränggjutning. När strängarna gjuts kapas de till specifika längder med ett 2 cm tjockt snitt med hjälp av syrgas och järnpulver. Detta resulterar i en restprodukt (skärslagg) om ca 750 ton per år, med sammansättningen från den årliga produktionen av stål. Syftet med arbetet var att se över en möjlig återanvändning av skärslaggen som råvara i ljusbågsugnen. Problematiken med skärslaggen är den stora reaktiva ytan vilket kan medföra att materialet börjar brinna i ljusbågsugnen under drift. Skärslaggen har en liten partikelstorlek och kan således följa med till gas- och partikelfilter då det är ett högt gasflöde i ljusbågsugnen under drift. Genom att brikettera skärslaggen kan dessa problem minimeras och en återföring av skärslaggen som råvara kan således vara möjlig. Skärslaggen transporterades till ett företag som siktade, torkade och briketterade skärslaggen. 37 ton skärslaggsbriketter har återförts i 18 försökscharger under normal drift med 2 ton skärslaggsbriketter i varje charge (en charge med enbart 1 ton skärslagg). För att mäta hur effektivt återföringen av skärslaggen var behövdes en referensnivå. Referensnivån baserades på hur utbytet till stål för elementen, molybden, nickel, koppar, kobolt och krom i ljusbågsugnen förhåller sig vid daglig drift. Detta utbyte användes som bas för att beräkna utbytet vid återföringen av skärslaggen. Av resultaten framgår det att nickel och molybden visade genomgående goda utbyten. Utfallet för elementen kobolt och koppar var inte lika tydliga men utbytena var till övervägande del goda. Beträffande krom var resultaten av naturliga skäl varierande, då krom reagerar med slaggen under processens gång. Den övervägande slutsatsen av arbetet var emellertid att det går att återföra skärslagg som råvara i ljusbågsugnen med godtagbara utbyten genom att brikettera den. Analysering av ljusbågsugnssla

SSAB i Oxelösund ska bygga en ljusbågsugn för konvertering av verksamheten från huvudsakligen malmbaserad produktion till skrotbaserad produktion. I samband med byggandet av ljusbågsugnen kommer en ny 130 kV linje byggas och från denna linje kommer ett nytt 30 kV nät byggas för att mata ljusbågsugnen och två stycken skänkugnar. En av dessa skänkugnar är idag (2019) i drift med 10 kV men ska konverteras till 30 kV medan den andra är en ny elektriskt sett identisk ugn. Anslutningen av dessa tre ugnar till det avskilda 30 kV nätet är till för att begränsa spridning av övertoner och flimmer till övriga laster. Ugnarna ska sedan anslutas till ett gemensamt elektriskt filter, för 30 kV nätet. Ljusbågsugnen och skänkugnarna ska vara i drift första kvartalet 2024, på grund av att det är några år in i framtiden är kortslutningsimpedanser osäkra. För att uppfylla termisk- och korttidsströmsdimensionering för kabeln mellan huvudställverk (OT40) och skänkugnsställverk (SU2) fodras enledarkabel med 300 mm2 aluminiumledare och PEX-isolering. Denna dimensionering förutsätter att förläggning sker i triangelformation, temperaturen är högst 35 °C och kabeln förläggs på sådant sätt att den inte påverkas av andra kablar. Maximal kortslutningsström som kabeln klarar av under den maximala bortkopplingstiden är 32,5 kA. Kortslutnings- och spänningsfallsberäkningar är utförda iprogrammet GNU Octave. Högsta och lägsta kortslutningström i respektive ställverk är beräknad. Överströmsskydden ställs in så att selektiv bortkoppling erhålls, med maximal bortkopplingstid 0,9 sekunder. En blockeringslogik används för att försäkra anläggning enmot oselektiv utlösning. Logiken innebär, enligt SSAB:s praxis, att skyddet närmast felstället ska blockera överordnat skydds kortslutningsströmsteg (>> I). Jordfelsskydd dimensioneras efter en nollpunktsresistor om 10 A. Jordfelsskydden är riktade och friges av nollpunktsspänningsskydd för att säkerställa att okynnesutlösning av jordfelsskydden inte upp, SSAB in Oxelösund will build an electric arc furnace to transform business from a mainly ore-based production, with blast furnaces, to a scrap based production. Together with the construction of the electric arc furnace, a new 130 kV overhead line and a 30 kV substation will be built. The 30 kV substation will feed one electric arc furnace and two ladle furnaces. One of these ladle furnaces is currently (2019) being fed with 10 kV, but is going to be converted to 30 kV, while the other one is a new electrically identical furnace. The connection of these three furnaces to the 30 kV grid is done in order to limit the distribution of harmonic distortions and flicker to the other loads. The furnaces on the 30 kV grid will be connected to a common electrical filter. The electric arc furnace and the ladle furnaces will be operational and produce steel in the first quarter of 2024. Since the installation will be performed some years ahead the short circuit impedance is not known. The cable between the main substation (OT40) and the ladle furnace substation (SU2) was being selected according to thermals and short time currents which determined the cable to consist of a single core cable with 300 mm2 aluminium conductor isolated by XLPE-isolation. This is provided that the cable is mountedin a triangle formation along a path with temperatures at maximum 35 C and is placed in such a way that the cable is not influenced thermally by other cables. Short circuit and voltage drop calculations are made in the program GNU Octave. The highest three phase and the lowest two phase short circuit current is calculated in every substation. The overcurrent protection is set to a maximum disconnection time of 0.9 seconds. A blocking logic is being used to further ensure a selectivity in the facility. The logic means, according to SSAB praxis, that the protection closest to the fault blocks the upstream short circuit protection ( I). The earth fault protection is designed around using a neu

Steel mills with electric arc furnaces, such as the José Martí company commonly known as Antillana de Acero; they are industries that use the heat produced by a controlled short circuit to obtain the steel. These steel mills need a stable and high voltage to be able to melt efficiently and at the same time, they are a powerful consumer of active power for the National Electroenergetic System. The objective of this work was the realization of a study of the conditions of the Antillana de Acero company, where the main causes that affect their productivity and the effects that these cause to our SEN were exposed. Three variants were studied, as a solution to these problems and one of them was selected from a technical point of view, with the focus of increasing the productivity of this company from the results obtained in the simulations., RESUMEN Las acerías con hornos de arco eléctrico, como la empresa José Martí comúnmente conocida como Antillana de Acero; son industrias que emplean el calor producido por un cortocircuito controlado para la obtención del acero. Estas acerías necesitan de una tensión estable y elevada para poder fundir de forma eficiente y al mismo tiempo, son un consumidor poderoso de potencia activa para el Sistema Electroenergético Nacional. El objetivo de este trabajo, fue la realización de un estudio de las condiciones de la empresa Antillana de Acero, donde se expusieron las principales causas que afectan su productividad y las afectaciones que ocasionan estas a nuestro SEN. Se estudiaron tres variantes, como solución a estos problemas y se seleccionó una de ellas desde un punto de vista técnico, teniendo como enfoque aumentar la productividad de esta empresa a partir de los resultados obtenidos en las simulaciones.

The mathematical processing results of a number of EAF-135 melts electrical parameters are presented. The influence of the foamy slag formation, molten metal carburization and the harmful impurities oxidation on the change in electrical parameters is analyzed. The methodology for determining the metal oxidation from the electrical melt parameters is characterized. In the presented form, the technique is cumbersome for the rapid assessment of the oxidation process intensity and requires refinement.

In addition to the blast furnace converter route, electric steel production in the electric arc furnace (EAF) is one of the two main production routes for crude steel. In 2019, the global share of crude steel produced via the electric steel route was 28%, which in numbers is 517 million metric tons of crude steel. The production and processing of steel leads to the output of a variety of by-products, such as dusts, fines, sludges and scales. At the moment, 10–67% of these by-products are landfilled and not recycled. These by-products contain metal oxides and minerals including iron oxide, zinc oxide, magnesia or alumina. Apart from the wasted valuable materials, the restriction of landfill space and stricter environmental laws are additional motivations to avoid landfill. The aim of the Fines2EAF project, funded by the European Research Fund for Coal and Steel, is to develop a low-cost and flexible solution for the recycling of fines, dusts, slags and scales from electric steel production. During this project, an easy, on-site solution for the agglomeration of fine by-products from steel production has to be developed from lab scale to pilot production for industrial tests in steel plants. The solution is based on the stamp press as the central element of the agglomeration process. The stamp press provides the benefit of being easily adapted to different raw materials and different pressing parameters, such as pressing-force and -speed, or mold geometry. Further benefits are that the stamp press process requires less binding material than the pelletizing process, and that no drying process is required as is the case with the pelletizing process. Before advancing the agglomeration of by-products via stamp press to an industrial scale, different material recipes are produced in lab-scale experiments and the finished agglomerates are tested for their use as secondary raw materials in the EAF. Therefore, the tests focus on the chemical and thermal behavior of t

Electric arc furnaces (EAFs) and ladle furnaces (LFs) are the main recycling units for scrap metal. With lower CO₂ emissions than traditional ore-based steelmaking, the importance of EAFs can be expected to increase in the future. Increasing steel production rates and demand for high-quality and special steels require innovative process control systems to be developed for the steel industry. However, the harsh conditions inside the furnaces set strict requirements for durability and viable data acquisition methods for online measurement systems. In this thesis, the applicability of optical emission spectroscopy (OES) as an online measurement system for industrial EAFs and LFs is discussed, based on the results from pilot-scale and industrial EAFs, and an industrial LF. The electric arc has been characterised with OES, plasma diagnostics, and image analysis in the pilot-scale EAF measurements. These studies highlighted the influence of slag composition on the overall properties of the electric arc, the electrical parameters of the furnace, and the arc length{voltage relation. The majority of the atomic emission lines in the electric arc OES spectra were observed to originate from the slag components.> In the industrial EAF campaign, high alloyed steel grade was observed to have high-quality arc spectra within 30 mins before tapping and higher radiative heat transfer compared with the carbon steel grade. The spectra from the carbon steel grade, on the other hand, were used to observe how spectra evolve during slag foaming. Additionally, the molten bath surface temperature was estimated from the OES spectra. The slag composition was evaluated with OES in the industrial LF campaign, indicating that the CaF₂, MgO, and MnO content of the slag could be evaluated from the spectra.

I detta examensarbete undersöks databasen Plantfacts som innehåller data om stålverk från hela världen. Syftet med detta är att utvärdera om det finns en koppling mellan primärt och sekundärt producerat stål och olika typer av stålverk i downstream-processer. För att utföra detta har databasen formaterats om i Excel med hjälp av Visual Basic for Applications (VBA). Från början var Plantfacts databas sorterad efter ”Plant type”, men efter omstruktureringen är den istället sorterad på ”Site”. Databasen har även jämförts med OECD:s databas, som precis som Plantfacts innehåller värden för ”Nominal Capacity”. Detta för att validera hur riktig Plantfacts data är. Resultatet visade att den Plantfacts data som var till störst nytta för studien var ”Plant type”, ”Country”, ”Site” och ”Nominal Capacity”. Utifrån denna data visade det sig att Kina i särklass var den största producenten, samt att det finns skillnader i vilka stålverkstyper masugnar och ljusbågsugnar är kopplade till. Jämfört med OECD stämmer Plantfacts väl överens för många länder med en medianskillnad på 9,75 %. Ett av de länder som stämmer sämst överens är Kina, där skillnaden mellan databaserna är 45,4 %. Den nya formen på databasen har givit en bättre överblick över produktionskedjan, då det är enkelt att sammanställa produktionen från samtliga platser. Plantfacts data stämmer väl överens med OECD i flertalet länder, men i bl.a. Kina, Indien och Brasilien skiljer det sig stort. Detta gör att man kan ifrågasätta hur sanningsenlig Plantfacts data är, men eftersom den stämmer bra för exempelvis Tyskland så rekommenderas att detta utvärderas land för land istället för globalt. Slutsatsen är att det finns skillnader mellan primärt och sekundärt producerat stål och olika typer av stålverk, eftersom masugnar och ljusbågsugnar följs av olika downstream-processer. Det är därför intressant att kartlägga ytterligare hur detta hänger samman för att kunna skapa policyer som uppmuntrar till ökad återvinning och återanvän, In this thesis the Plantfacts database is investigated, which contains data about steel plants from all over the world. The purpose is to evaluate wheter there is a coupling between primary and secondary steel and different types of steel plants in downstream processes. To achieve this, the database has been reformatted using Visual Basic for Applications (VBA) in Excel. Initially, the Plantfacts database was sorted by ”Plant type” and after the reformatting it is sorted by “Site”. The Plantfacts database is compared with the OECD database, that contains data regarding “Nominal capacity”, just as Plantfacts. This is done to validate how the Plantfacts data seems to compare to reality. The result showed that the columns “Plant type”, ”Country”, ”Site” and ”Nominal Capacity” were the most useful ones. China is the significantly largest producer in the world and there are differences in which steel plant types blast furnaces and electric arc furnaces are related to. Compared with OECD, Plantfacts is consistent for most countries with the median 9,75 %. One of the countries that has the largest difference is China, where the number is 45,4 %. The new form of the Plantfacts database results in a better overview over the production for each site. The Plantfacts data compare well with OECD in many countries, but differ in e.g. China, India and Brazil. This makes it questionable how correct the Plantfacts data are, but since it compares well for e.g. Germany, it is recommended to evaluate this by land instead of globally. The conclusion is that there are differences between primary and secondary steel and steel plant types, because blast furnaces and electric arc furnaces are followed by different downstream processes. Therefore, it would be interesting to further expand this mapping to create policies that enhances recycling and reusing of steel. By investigating downstream processes where the steel used both could be primary or secondary, it would be possible to replace t

La escoria espumosa juega un papel importante en la producción del acero, específicamente durante el afino en el horno de arco eléctrico, donde se utiliza el arco generado por los electrodos para aumentar la temperatura hasta 1600 °C con el fin de hacer el vuelco del acero al horno cuchara. La escoria espumosa se encarga no solo de atrapar las impurezas en forma de óxidos que afectan la calidad del acero sino también permite que la energía del arco eléctrico pase directamente al acero fundido al cubrir los electrodos impidiendo además, el desgaste físico y químico excesivo de los refractarios. Por tal motivo se realiza un estudio de los componentes del proceso en el cual se afecta la generación de la escoria espumosa como la calidad de la materia prima, la disposición de la chatarra en el patio, y el afino en el HEA. Así mismo, se determinan las propiedades fisicoquímicas que afectan la espumación de la escoria como la basicidad binaria, la densidad, la viscosidad, la composición de FeO en la escoria y la saturación de MgO.

Statistical modeling, also known as machine learning, has gained increased attention in part due to the Industry 4.0 development. However, a review of the statistical models within the scope of steel processes has not previously been conducted. This paper reviews available statistical models in the literature predicting the Electrical Energy (EE) consumption of the Electric Arc Furnace (EAF). The aim was to structure published data and to bring clarity to the subject in light of challenges and considerations that are imposed by statistical models. These include data complexity and data treatment, model validation and error reporting, choice of input variables, and model transparency with respect to process metallurgy. A majority of the models are never tested on future heats, which essentially renders the models useless in a practical industrial setting. In addition, nonlinear models outperform linear models but lack transparency with regards to which input variables are influencing the EE consumption prediction. Some input variables that heavily influence the EE consumption are rarely used in the models. The scrap composition and additive materials are two such examples. These observed shortcomings have to be correctly addressed in future research applying statistical modeling on steel processes. Lastly, the paper provides three key recommendations for future research applying statistical modeling on steel processes., QC 20191028

The paper addresses the issue on improving the intensity of melting in the production of steels using hot briquetted iron (HBI) in the charge that mostly consists of metal waste. An analysis has been performed into the features of melting that uses charge of complex composition. To ensure the boiling of metal bath, it is recommended to introduce to the bath carbon-containing raw materials in the form of steel waste in the amount exceeding 80 %. It was established that applying HBI almost does not reduce the yield of usable metal due to a high content of metal waste that makes up the charge.At the same time, the paper analyses the role of silicon and manganese oxidation process in the refining of liquid steel at melting the alloy wastes used as charge materials in an electric arc furnace. The dependences of equilibrium concentrations of oxygen and silicon at different temperatures in the system Fe‒Si‒O have been given. In addition, the dependence diagram of manganese oxidation products in a liquid iron on the temperature and concentration of manganese in the alloy MnO‒FeO has been constructed. The equilibrium concentrations of oxygen and silicon with carbon deoxidizing capability have been defined, in the field of liquid silicates and in the field of solid SiO2.The high-quality silicon and manganese oxidation when smelting steel made from metal waste and hot briquetted iron (HBI) contributes to the fullest refining of liquid steel through the phases metal-slag or metal-gas.It has been shown that the content of silicon during electrical steel refining drops to traces. Thus, when using metal waste and pellets as charge in the steel-making process, a silicon oxidation reaction does not reach equilibrium. If a sour process is performed, then the oxidation of silicon reaches equilibrium and, under certain conditions for melting the charge under the influence of heat from an electric arc, there may occur a significant reduction of silicon that takes place at a higher tempe, Рассматривается проблема повышения интенсивности плавления в производстве сталей с использованием горячебрикетированных окатышей (HBİ) в шихте, состоящей в основном из отходов метала. Проведен анализ особенности плавления с использованием шихты сложного состава. Для обеспечения кипения металлической ванны рекомендуется добавление в ванну углеродсодержащего сырья в виде отходов стали более 80 %. Было установлено, что при использовании HBİ выход годного металла почти не снижается, что связано с высоким содержанием металлических отходов, составляющих шихты.Одновременно, анализируется роль процесса окисления кремния и марганца в рафинировании жидкой стали при плавлении в электродуговой печи легированных отходов, используемых в качестве шихтовых материалов. Приведены зависимости равновесных концентраций кислорода и кремния при различных температурах в системе Fe–Si–O. Также, построен график зависимости продуктов окисления марганца в жидком железе от температуры и концентрации марганца в сплаве MnO–FeO. Определенны равновесные концентрации кислорода и кремния с раскислительной способностью углерода, в области жидких силикатов и в области твердого SiO2.Качественное окисление кремния и марганца при выплавке стали из металлических отходов и горячебрикетированных окатышей (HBİ) способствует наиболее полному рафинированию жидкой стали через фазы металл – шлак или металл – газПоказано, что во время доводки электростали содержание кремния снижается до следов. Таким образом, в случае использования в качестве шихты металлических отходов и окатышей в сталеплавильном процессе реакция окисления кремния не достигает равновесия. Если проводится кислый процесс, то тогда окисление кремния достигает равновесного состояния и при определенных условиях плавления шихты под действием тепла электрической дуги может происходить значительное восстановление кремния, которое происходит при более высокой температуре (кремневосстановительный процесс). Рекомендован основной процесс плавления шихты из, Розглядається проблема підвищення інтенсивності плавлення у виробництві сталей з використанням гарячобрикетованих окатишів (HBİ) в шихті, що складається в основному з відходів металу. Проведено аналіз особливості плавлення з використанням шихти складного складу. Для забезпечення кипіння металевої ванни рекомендується додавати в ванну вуглецьмістну сировину у вигляді відходів сталі більше 80 %. Було встановлено, що при використанні HBİ вихід придатного металу майже не знижується. Це пов'язано з високим вмістом металевих відходів, складових шихти.Одночасно, аналізується роль процесу окислення кремнію і марганцю в рафінуванні рідкої сталі при плавленні в електродуговій печі легованих відходів, що використовуються як шихтовий матеріал. Наведено залежності рівноважних концентрацій кисню і кремнію при різних температурах в системі Fe–Si–O. Також, побудований графік залежності продуктів окислення марганцю в рідкому залізі від температури і концентрації марганцю в сплаві MnO–FeO. Визначені рівноважні концентрації кисню і кремнію з розкислюючою здатністю вуглецю, в області рідких силікатів і в області твердого SiO2.Якісне окислення кремнію і марганцю при виплавці сталі з металевих відходів та гарячобрикетованих окатишів (HBİ) сприяє найбільш повному рафінуванню рідкої сталі через фази метал – шлак або метал – газ.Показано, що під час доведення електросталі вміст кремнію знижується до слідів. Таким чином, в разі використання в якості шихти металевих відходів та окатишів в сталеплавильному процесі реакція окислення кремнію не досягає рівноваги. Якщо проводиться кислий процес, то тоді окислення кремнію досягає рівноважного стану і при певних умовах плавлення шихти під дією тепла електричної дуги може відбуватися значне відновлення кремнію, яке відбувається при більш високій температурі (кременівідновлювальний процес). Рекомендовано основний процес плавлення шихти з металевих відходів та гарячобрикетованих окатишів в електродуговій печі. При цьому відновлений період плавки має н

The article deals with issues of integrated waste-free processing of electric arc furnaces dust. It is shown that it is possible to obtain a whole range of valuable commodity products on both metal and non-metal bases as a result of the electric arc furnaces dust complex processing. Integrated waste-free processing reduces the arc furnaces dust impact on the environment and produces a number of valuable commercial products. © The Authors, published by EDP Sciences.

The use of secondary raw materials in metallurgical processes such as steelmaking is an important contribution to the circular economy aspired to by EU members and many other countries. The agglomeration of dusts, fines and sludges is an important pretreatment step to enable the use of these materials in subsequent melting processes, such as steelmaking in electric arc furnaces (EAFs). It also reduces the amount of by-products and waste materials that are currently waste for disposal and are landfilled. The presented research is part of the Fines2EAF project, which aims to increase the value of steelmaking residues by internal recycling and use or reuse in the form of agglomerates. The approach followed in this project is the use of a hydraulic stamp press and alternative binder systems to produce cement-free agglomerates. The first results of lab-scale agglomeration tests of six different recipes with varying pressing forces are presented in this paper. It is shown that the addition of fibres from paper recycling has a strong effect on the cold compression stability of the agglomerates, by far exceeding other effects such as increased pressing force. Overall, the agglomerates produced in the lab show promising characteristics, for example, cold compression stability and abrasion resistance, which should allow for use in EAF steelmaking.

A simulator and an algorithm for the automatic creation of operation charts based on process conditions were developed on the basis of an existing comprehensive electric arc furnace process model. The simulator allows direct user input and real-time display of results during the simulation, making it usable for training and teaching of electric arc furnace operators. The automatic control feature offers a quick and automated evaluation of a large number of scenarios or changes in process conditions, raw materials, or equipment used. The operation chart is adjusted automatically to give comparable conditions at tapping and allows the assessment of the necessary changes in the operating strategy as well as their effect on productivity, energy, and resource consumption, along with process emissions.

Fundamental knowledge of the electric arc properties is important for the development of process control of electric arc furnaces. In this work, a pilot-scale AC electric arc has been studied with optical emission spectroscopy together with filtered camera footage. The properties of the arcs were determined with plasma diagnostics and image analysis in order to obtain both the characteristic plasma parameters and the physical form of the arc. The plasma temperatures, ranging from 4500 to 9000 K, were derived individually for three elements. The electron densities of the plasma were between 10¹⁸ and 10²⁰ cm⁻³ and fulfilled the local thermal equilibrium criterion, but the plasma temperatures derived from atomic emission lines for different elements had high and unpredictable differences. The properties of the electric arcs have been studied with respect to the arc length derived from the image analysis. The slag composition, especially the relative FeO content of over 30%, was observed to have a notable effect on the brightness of the arc on slag and thus also on the radiative heat transfer.

Мmodeling of heat transfer in the working space of the electric arc furnace (EAF) of a foundry class with a capacity of 3 tons has shown that with a downtime of 18–20 hours or more, replacing 40 % of the wall lining and 16–20 % of the roof lining by water-cooled elements with a volume structure provides parity with brick lining on the consumption of electricity with a significant saving of refractories. Increasing the depth of the bath at a given melting mass, preloading scrap and using a dispersed aspiration system increases the energy efficiency of the EAF., Моделирование теплообмена в рабочем пространстве дуговой сталеплавильной печи (ДСП) литейного класса вместимостью 3т показало, что при длительности простоев печи 18–20 часов и более, замена 40 % футеровки стен и 16–20 % футеровки свода водоохлаждаемыми элементами с объемной структурой обеспечивает паритет с кирпичной футеровкой по расходу электроэнергии при существенной экономии огнеупоров. Увеличение глубины ванны при данной массе плавки, предварительная загрузка скрапа и применение системы рассредоточенной аспирации повышает энергоэффективность ДСП.

Carbon emissions pose a serious threat to the continued survival of this planet. All sectors of society must, therefore, lower their emissions, this includes the steel industry. The production of steel is based on iron ore reduction by carbon. In an attempt to relieve the steel industry from its inherent fossil dependence an initiative called HYBRIT has been started. It aims to supplant carbon reduction with hydrogen reduction. Currently, there is no economically viable industrial production of steel that uses fossil-free hydrogen as reduction agent. In order to create economic viability for such a process work has to be conducted to innovate and optimize. This study aims to be a part of that optimization process by creating a tool for optimizing the slag system with regards to phosphorus removal. 26843 slag compositions were evaluated using modules written in “Matlab” combined with “Thermo-Calc”. 1583 possible slag compositions were found to be suitable for phosphorus removal. These compositions were then optimized after slag weight in order to minimize slag associated cost. The compositions were tested against two theoretical raw materials with varying initial phosphorus content 250 ppm and 125 ppm. It was found that the initial phosphorus concentration of the raw material has a substantial impact not only on the slag costs but also the slag praxis that should be used.

Slag is foamed in electric arc furnace during steelmaking to reduce the amount of energy emitted to the furnace walls. The behavior of the electric arc plasma during slag foaming is not very well understood, since it is very hard to obtain empirical data about arc plasma from industrial furnaces. In this work the effect of foaming on the arc plasma is studied by generating electric arc plasma over a foaming slag in laboratory scale. The arc was generated on top of the slag with a system modified from a welding power supply and the foaming of slag was induced by blowing oxygen gas into the slag. The electric arcs were monitored with two cameras filtered to measure different wavelengths and three spectrometers measuring different spectral regions with varying spectral resolution. The first camera was able to detect only the light emitted directly from the arc plasma while the second can detect the high temperature slag surrounding the submerged arc. By comparing the two images, it was possible to differentiate between arc burning inside the foaming slag and free burning arc. The use of plasma diagnostics with optical emission spectrometry provided information about electron temperature and density of the arc plasma. The plasma diagnostics and camera pixel intensities indicate that the arc burning inside foaming slag is constricted and has high plasma temperature. Comparing the free-burning arc on top of the foaming slag and non-foaming slag show that the CO bubbles cause the plasma temperature to fluctuate significantly., QC 20210927

As a result of the presence of non-linear loads, it is possible to verify the increasing of harmonic distortion in electric power systems. When amplified, it can induce the resonance effect. This effect becomes more and more prominent to the technical-scientific community, mainly when the standards of power quality are observed. To analyze and mitigate the effect of harmonic distortion, an active power filter was used in this research. Both the active filter and the distribution system under analysis, in the presence of non-linear loads, were simulated via Real Time Digital Simulator (RTDS). Additionally, details of the filter control system were described. With the insertion of the filter, the harmonic distortions of current and voltage were mitigated, being in compliance with the limits of PRODIST., Os autores agradecem ao Laboratório de Sistemas de Energia Elétrica (LSEE), da Escola de Engenharia de São Carlos (EESC- USP) pela infraestrutura proporcionada, assim como à Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), processo nº 2015/21167-6, pelo suporte financeiro disponibilizado para a realização desta pesquisa., Postprint (published version)

Carbon footprint is the mass of carbon formed in the full cycle of production of one or another kind of product. This carbon is included in greenhouse gases. Carbon monoxide and greenhouse gases (methane and carbon dioxide) are generated at the production of iron and steel. Methane and carbon monoxide burn up to carbon dioxide by the realization of secondary energy resources. Therefore, the carbon footprint at the production of iron and steel is determined by weight of formed carbon dioxide. As the results of analysis of the production processes of iron and steel it was revealed that the tandem of blast furnace with electric arc furnace is characterized by a lower value of integrated through emissions of CO2 than the tandem of blast furnace with an oxygen converter. It is proposed to process the cast iron, made by one blast furnace, at the same time in the oxygen converter and in one or more electric arc furnaces. Moreover in the electric arc furnace is loaded 30 % of iron which are produced in blast furnace, and the remaining 70 % are complemented by metal scrap. In the oxygen converter the part of cast iron (75 – 85 %) is loaded, which are remained after loading in the arc furnace. The converter is applied by the metal scrap for full loading. Calculations of through emission of carbon dioxide for different triads of these units are made. The simultaneous use of oxygen converter with electric arc furnaces for cast iron smelting obtained from one blast furnace helps to reduce confidently the emission of carbon dioxide to 20 % as it follows from the calculations. This suggests that this triad of used units conforms to green technology. Example of the use of marked triad is for a full load of the converter is applied to metal scrap. the calculations through emissions of carbon dioxide for different triads of these units. From these calculations it follows that the simultaneous use of oxygen converters from electric arc furnaces for smelting iron, obtained from one bla

The statistical analysis and material balance of an arc steel melting furnace (EAF) with a capacity of 120 tons for the melted steel of 35GS with filling of charge materials with two and three baskets are performed. Depending on the bulk density of the charge, its permissible volume and mass are estimated, provided that the working space of the furnace is partially filled. For loaded charge materials, the thermophysical properties (thermal conductivity, heat capacity, thermal diffusivity) are determined taking into account the bulk density and the share in the charge. A technique is proposed for calculating the heat transfer coefficient from the products of combustion of natural gas to the surface of a layer of charge materials., Выполнены статистический анализ и материальный баланс дуговой сталеплавильной печи (ДСП) емкостью 120 т для выплавляемой стали 35ГС при завалке шихтовых материалов двумя и тремя корзинами. В зависимости от насыпной плотности шихты оценены ее допустимый объем и масса при условии порционного заполнения рабочего пространства печи. Для загружаемых шихтовых материалов определены теплофизические свойства (теплопроводность, теплоемкость, температуропроводность) с учетом насыпной плотности и доли в загрузке. Рассчитан коэффициент теплоотдачи в объеме слоя шихты с учетом тепловыделения от сжигания природного газа, окисления углерода кокса свободным кислородом газовой среды и оксида железа и угара шихты.

A method for vibrational evaluations of spectrogram data from pilot plant measurements was established for obtaining a consistent analysis of the molten scrap state. Not knowing the meltdown progress inside the furnace results in an inefficient power scheduling, which affects refractory life, process time and energy losses. Hence, there exists potential to control the furnace power so that it is kept high while there is sufficient amounts of scrap inside furnace to absorb the input energy. Thus, harmonic distortions of the electric current and measurements of the sound and vibrations emitted from the furnace were correlated to the molten state of the scrap. By using this method, a reduction in melting time in the order of minutes per heat can be obtained. The method was found to give stable signals and it was judged to be a good candidate for implementation in industry. Furthermore, the developed method is universal and may be applied for other types of signals and combined into intelligent soft sensor systems., QC 20190107

The process industries span multiple industrial sectors and constitute a substantial part of the entire manufacturing industry. Since companies belonging to this family of industries are often very asset intensive, their ability to respond to changes is often limited in the short term. The adaptation of the capabilities of existing processes, and conversely finding products and market segments to match the production system capabilities, are an important part of product- and market development activities in the process industry. The importance to companies in the process industry of having a well-articulated manufacturing strategy congruent with the business strategy is second to none. However, to facilitate manufacturing strategy developments, it is essential to start with an improved characterization and understanding of the material transformation system. To that end an extensive set of variables was developed and related measures and scales were defined. The resulting configuration model, focusing on company generic process capabilities in the process industries, is to be regarded as a conceptual taxonomy and as a proposition available for further testing. The usability of the model was subsequently assessed using “mini-cases” in the forestry industry, where the respondents confirmed that the company’s overall strategy could benefit from this kind of platform as a possible avenue to follow. The model was deployed as an instrument in the profiling of company material transformation systems to facilitate the further development of companies' functional and business strategies. The use of company-generic production capabilities was studied in three case companies representing the mineral, food and steel industries. The model was found by the respondents to be usable as a knowledge platform to develop production strategies. In the final analysis of the research results, a new concept emerged called “production capability configuration": A process-industrial company’, QC 20170116

We consider a resource- and energy-saving technology to improving the transportation process carbonaceous materials pneumatically by using the energy of the acoustic field. The results of testing equipment to create a pneumatic flow modulation on an electric arc furnace, revealed the positive aspects of this technology., Рассмотрена ресурсо- и энергосберегающая технология совершенствования процесса транспортирования углеродсодержащих материалов пневмотранспортом за счет использования энергии акустического поля. Приведены результаты испытаний оборудования для создания модуляционного потока пневмотранспорта на дуговой сталеплавильной печи, выявлены положительные аспекты применения данной технологии.

В работе рассмотрены температурные поля рабочего пространства современной дуговой сталеплавильной печи емкостью 120 тонн (ДСП–120). Температурные поля были получены с помощью компьютерного моделирования в программе SolidWorks Flow simulation. В работе произведен анализ расположения ТСУ по варианту фирмы «Danieli», а также схемы установки горелок рекомендованной авторами., The paper discusses the temperature field of modern electric arc furnace with a capacity of 120 tons workspace (DSP–120). The temperature field were obtained by computer modeling program SolidWorks Flow simulation. The paper produced TSU location analysis according to an embodiment of the company «Danieli», as well as the installation of burners scheme recommended by the authors.

The advantages of using CO2 for the decarburization of high alloy steels have been recognized from environmental and economic view points. The present paper presents the heat and materials balances in the decarburization process with the introduction of CO2 as a diluting gas in Electric Arc Furnace (EAF) process for steel production. The aim is to optimize the amount of CO2 and the materials requirements, which includes the addition of scrap, hot metal and coolant. These estimations are also important to control the bath temperature, thereby prolong the lifetime of the refractory lining of the furnace. The present calculations enable an optimization of the CO2:O-2 ratio and materials input in the decarburization of carbon steel melts. Another important extension of the work is the possibility to enhance the addition of hot metal during steel making process. The present results show that addition of up to 20% hot metal is likely to the energy loss due to the introduction of 50% CO2 for a 110 tons EAF resulting in the saving of electric energy., QC 20160426