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Roads are currently essential links of communication and economic development. However, these roads are progressively requiring higher quality materials, implying a greater impact on the environment, in order to withstand the high levels of heavy vehicle traffic. Therefore, this research proposes the use of industrial by-products to create bituminous mixtures which are more resistant and durable than traditional ones. The industrial by-products used, are electric arc furnace slag, ladle furnace slag, and cellulose fibers from the papermaking industry. These by-products were physically and chemically characterized to be used to conform with bituminous mixtures. At the same time, bituminous mixtures were conformed with conventional materials, thus being able to compare the physical and mechanical properties of the conformed mixtures through different tests. The results showed how the use of cellulose fibers made it possible to absorb a greater percentage of bitumen, as well as the use of electric arc furnace slag and ladle furnace slag created mixtures, with greater Marshall stability. Therefore, sustainable, durable, resistant, and high waste mixtures were developed in this investigation. [ABSTRACT FROM AUTHOR]

This paper studies the integration of direct reduced iron (DRI) and hot briquetted iron (HBI) into the steelmaking process via an electric arc furnace (EAF). Considering a variety of DRI production techniques distinguished by different reactor types, this paper provides a comparative overview of the current state. It delves into significant challenges, such as the susceptibility of DRI to reoxidation and the necessity of thorough handling to maintain its quality. The effectiveness of several reoxidation mitigation strategies, including the application of thin oxide layers, briquetting, various coatings, and nitride formation in ammonia-based reduction processes, is evaluated. Most existing studies have primarily focused on the reoxidation of DRI rather than on HBI, despite the fact that HBI may undergo reoxidation. The importance of DRI/HBI in offering an alternative to the integrated steelmaking route is highlighted, focusing on how it changes the EAF process compared to those for melting scrap. This paper also identifies several research prospects for further DRI/HBI applications in steel production. [ABSTRACT FROM AUTHOR]

The arc furnace is an important equipment in the production of manganese ferroalloys. In the smelting process, it produces high temperature flue gas above 700 K, which has high utilization value. During the pelleting process, moisture exists on the surface and inside of the pellets, which, if directly fed into the arc furnace, will lower the temperature of the furnace, affecting the production, and will also cause the pellets to burst, resulting in pressure fluctuations in the furnace and other hazards. The preheating shaft kiln reduces the moisture content of the pellet while preheating the pellet by utilizing high temperature flue gas. In this paper, through the establishment of porous media and shrinking core coupling mathematical model, to achieve the prediction of the heating and drying process of the pellets of various particle sizes, which is in good agreement with the production monitoring data. The results show that 9~11 mm pellets have the best preheating effect in terms of tail gas temperature, pellet temperature and preheating time. [ABSTRACT FROM AUTHOR]

The global steel industry is integral to the development of modern infrastructure, yet it stands as one of the most significant contributors to greenhouse gas (GHG) emissions worldwide. This dichotomy brings forth the imperative for an in-depth analysis of GHG inventory practices and the pursuit of sustainable production methods. This mini-review paper addresses the current methodologies for GHG accounting within the steel sector, emphasizing the critical role of accurate and transparent emissions data as the basis for effective climate change mitigation strategies. Evaluating the prevalent carbon-intensive blast furnace-basic oxygen furnace (BF-BOF) production route, this paper contrasts traditional practices with innovative reduction initiatives, particularly those aligned with the emergence of green steel. We delve into the advancements in electric arc furnace (EAF) technology, direct reduced iron (DRI) processes utilizing green hydrogen, and the potential of carbon capture, utilization, and storage (CCUS) systems. The analysis extends to a critical examination of the challenges and opportunities these technologies face, including economic viability, scalability, and the readiness of energy infrastructure to support such a transition. Further, this review highlights the significance of verification and validation in reinforcing the credibility of GHG inventories. We scrutinize the materiality of reported emissions in the context of evolving regulatory frameworks and stakeholder expectations, stressing the need for standardized and rigorous assurance practices. Highlights: • The global steel industry is a major contributor to greenhouse gas emissions, and there is a need for accurate emissions data to address climate change. • Transitioning to green steel production, using technologies like electric arc furnace (EAF) and direct reduced iron (DRI) with green hydrogen, can significantly reduce emissions. • Verification and validation of greenhouse gas inventories are crucial for credibility in the context of evolving regulatory frameworks. [ABSTRACT FROM AUTHOR]

This paper is devoted to electric arc furnace (EAF) modeling using a random differential equation based on the power balance equation. The proposed approach broadens and improves the model through the introduction of stochastic processes in place of existing coefficients. The paper presents a method which enables the estimation of EAF model coefficients with the help of measurement data - voltage and current waveforms recorded during the melting stage of an EAF work cycle. The estimation process is conducted with a Monte Carlo method and genetic algorithm, which is applied iteratively to each of the defined frames of the input signal. The estimated coefficients have been analyzed with respect to their time variability as well as the probability distributions of their values and increments. The results have been extensively visualized. Next, the identification of the stochastic processes representing the model coefficients has been carried out. Based on the previous results and autocorrelation functions, the density functions and parameters of discrete-time stochastic processes were identified. The paper presents solutions validated with statistical tests. [ABSTRACT FROM AUTHOR]

From their perspective the optimal tapping process would be when slag and metal are drained from the furnace at the same rate as being produced and separated in the post tap-hole process. Tangstad et al I . i discussed the optimal tapping process for manganese ferroalloy production in submerged arc furnaces (SAFs) in their paper "Conceptual tapping model of Mn-ferroalloy furnaces". J. D. Steenkamp and Q. G. Reynolds are the Guest Editors for the Furnace Tapping topic in the November 2022 issue of JOM. [Extracted from the article]

The paper presents a novel decision support system designed to improve the efficiency and effectiveness of decision-making for electric arc furnace (EAF) operators. The system integrates two primary tools: the EAF Simulator, which is based on advanced mechanistic models, and the EAF Optimiser, which uses data-driven models trained on historical data. These tools enable the simulation and optimisation of furnace settings in real time and provide operators with important insights. A key objective was to develop a user-friendly interface with the Siemens Insights Hub Cloud Service and Node-RED that enables interactive management and support. The interface allows operators to analyse and compare past and simulated batches by adjusting the input data and parameters, resulting in improved optimisation and reduced costs. In addition, the system focuses on the collection and pre-processing of input data for the simulator and optimiser and uses Message Queuing Telemetry Transport (MQTT)communication between the user interfaces and models to ensure seamless data exchange. The EAF Simulator uses a comprehensive mathematical model to simulate the complex dynamics of heat and mass transfer, while the EAF Optimiser uses a fuzzy logic-based approach to predict optimal energy consumption. The integration with Siemens Edge Streaming Analytics ensures robust data collection and real-time responsiveness. The dual-interface design improves user accessibility and operational flexibility. This system has significant potential to reduce energy consumption by up to 10% and melting times by up to 15%, improving the efficiency and sustainability of the entire process. [ABSTRACT FROM AUTHOR]

The temperature of hot metal (HM) is crucial for the energy input and smelting in the electric arc furnace (EAF) steelmaking process with HM and scrap as the charge structure. However, due to the influence of many factors in the heat dissipation in HM transportation before the EAF steelmaking process, the temperature drop of HM before charged is usually fluctuating and uncertain. This situation is not conducive to the input energy control and energy optimization of the EAF steelmaking process. In this paper, a three-dimensional numerical model of a 90-ton hot metal ladle is established to simulate the heat transfer characteristic of HM transportation through ANSYS Fluent 2023 and verified by on-the-spot testing and sample analysis. The effects of ambient temperature, air velocity, slag thickness and furnace cover thickness on the temperature drop of HM are investigated and quantitatively analyzed in 30 numerical schemes. The results indicate that slag thickness is the most influential factor, followed by furnace cover thickness, air velocity and ambient temperature. In the case of 50 min transport time, the temperature drop of HM is 55.2, 15.06, 12.08, 10.38, 10.29 and 10.26 °C when the slag thickness is 0, 50, 100, 150, 200 and 250 mm, respectively. While HM is not covered by slag, the furnace cover can also greatly reduce the temperature drop. Based on the simulated data, a prediction model of HM temperature drop is obtained through the multi-factor coupling analysis and mathematical fitting. This study can help develop targeted insulation measures and determine the temperature of HM, which is expected to control the input energy for deep energy-saving optimization in the EAF steelmaking process. [ABSTRACT FROM AUTHOR]

In this paper, a non-linear programming method allowing for the optimization of the structure of high-current circuits that supply resistance-arc furnaces was presented. In the case of resistance-arc furnaces, two types of asymmetries most often occur: structural and operational ones. The structural asymmetry is related to the construction of a bifilar high-current busduct, which leads to the so-called short network. Knowing the parameters of the high-current busduct allows one to determine the operating characteristics of the arc furnace. It is also necessary to know the energy consumed in individual steps of the arc furnace operation. The method proposed in this paper makes it possible to establish guidelines for the modernization of a short network in order to eliminate asymmetry. The presented method was verified on a real object by conducting experimental tests on a furnace with a power of 12 MVA. Experimental tests were first carried out for a furnace with asymmetry, and then, by conducting simulation tests, guidelines for changing the design of the short network were determined. The measurements carried out after the modernization of the short network confirmed that the furnace was in a symmetrical operating condition and confirmed the correctness of the calculation method proposed in this paper. [ABSTRACT FROM AUTHOR]

Steel slag is one of the most common waste products from the steelmaking industry. Conventional methods of slag disposal can cause negative impacts on humans and the environment. In this paper, the process of steel and steel slag production, physical and chemical properties, and potential options of slag recycling were reviewed. Since steel is mainly produced through an electric arc furnace (EAF) in Malaysia, most of the recycling options reviewed in this paper focused on EAF slag and the strengths and weaknesses of each recycle option were outlined. Based on the reports from previous studies, it was found that only a portion of EAF slag is recycled into more straightforward, but lower added value applications such as aggregates for the construction industry and filter/absorber for wastewater treatments. On the other hand, higher added value recycling options for EAF slag that are more complicated such as incorporated as raw material for Portland cement and ceramic building materials remain at the laboratory testing stage. The main hurdle preventing EAF slag from being incorporated as a raw material for higher added value industrial applications is its inconsistent chemical composition. The chemical composition of EAF slag can vary based on the scrap metal used for steel production. For this, mineral separation techniques can be introduced to classify the EAF slag base on its physical and chemical compositions. We concluded that future research on recycling EAF slag should focus on separation techniques that diversify the recycling options for EAF slag, thereby increasing the waste product's recycling rate. [ABSTRACT FROM AUTHOR]

In the iron and steel industry, evaluating the energy utilization efficiency (EUE) and determining the optimal energy matching mode play an important role in addressing increasing energy depletion and environmental problems. Electric Arc Furnace (EAF) steelmaking is a typical short crude steel production route, which is characterized by an energy-intensive fast smelting rhythm and diversified raw charge structure. In this paper, the energy model of the EAF steelmaking process is established to conduct an energy analysis and EUE evaluation. An association rule mining (ARM) strategy for guiding the EAF production process based on data cleaning, feature selection, and an association rule (AR) algorithm was proposed, and the effectiveness of this strategy was verified. The unsupervised algorithm Auto-Encoder (AE) was adopted to detect and eliminate abnormal data, complete data cleaning, and ensure data quality and accuracy. The AE model performs best when the number of nodes in the hidden layer is 18. The feature selection determines 10 factors such as the hot metal (HM) ratio and HM temperature as important data features to simplify the model structure. According to different ratios and temperatures of the HM, combined with k-means clustering and an AR algorithm, the optimal operation process for the EUE in the EAF steelmaking under different smelting modes is proposed. The results indicated that under the conditions of a low HM ratio and low HM temperature, the EUE is best when the power consumption in the second stage ranges between 4853 kWh and 7520 kWh, the oxygen consumption in the second stage ranges between 1816 m3 and 1961 m3, and the natural gas consumption ranges between 156 m3 and 196 m3. Conversely, under the conditions of a high HM ratio and high HM temperature, the EUE tends to decrease, and the EUE is best when the furnace wall oxygen consumption ranges between 4732 m3 and 5670 m3, and the oxygen consumption in the second stage ranges between 1561 m3 and 1871 m3. By comparison, under different smelting modes, the smelting scheme obtained by the ARM has an obvious effect on the improvement of the EUE. With a high EUE, the improvement of the A2B1 smelting mode is the most obvious, from 24.7% to 53%. This study is expected to provide technical ideas for energy conservation and emission reduction in the EAF steelmaking process in the future. [ABSTRACT FROM AUTHOR]

Experimental investigations of the effectiveness of the pretreatment of the acid leaching process of a representative sample of electric arc furnace dust (EAF dust) and characterization of a representative sample were performed. As EAF dust is globally defined as hazardous solid industrial waste, and it contains a high percentage of zinc and other useful components, in this paper, the application of pretreatment will be carried out in order to increase the efficiency of the further process of acid leaching, all with the aim of using EAF dust as a secondary raw material for metal valorization. The pretreatment involved the application of a simple process of leaching the EAF dust sample with distilled water. Under the following defined optimal leaching conditions: time—30 min, ratio of solid to liquid phase—1:10, temperature—ambient, and stirring speed—500 rpm, a reduction in the content of water-soluble components was achieved, namely, 83% Cl, 92% K, 74% Na, 14% Cd, 15% Ca, and 19% F. The application of the pretreatment enables significantly better filtration of the suspension and increases the leaching efficiency of zinc and other useful components in the further process of leaching EAF dust with a sulfuric acid solution, compared with the process of direct acid leaching of EAF dust. [ABSTRACT FROM AUTHOR]

Electric arc furnace (EAF) is one of the most disturbing loads in the power system as it is highly time‐varying and nonlinear. In this paper, new models based on the instantaneous EAF voltage and current, recorded from EAFs in Mobarakeh steel company in Isfahan/Iran are proposed. The focus of this paper is on developing efficient models based on the Schwarz model where three modified types are proposed. The original Schwarz model has four constant parameters. Unlike the original Schwarz model which uses invariant parameters, the time‐varying nature of the arc's parameters is considered in the proposed models. The first modified model has two constant model orders and two time‐varying coefficients. Additionally, to further enhance the model's accuracy, in the second modified model, six parameters include three constant model orders, and three time‐varying coefficients exist. The third model uses all the original model's parameters as time‐series parameters. The parameters of the time‐varying model are derived using autoregressive moving average (ARMA) models. The accuracy of the proposed model is evaluated by calculating the active power, harmonics, instantaneous flicker, and short‐term flicker. Finally, three MATLAB codes are provided to generate the model parameters time series. [ABSTRACT FROM AUTHOR]

This paper is devoted to studying the thermochemical properties of carbon sources (laboratory-scale conventional coke, biocoke with 5 wt.%, and 10 wt.% wood pellet additions) and the influence of these properties on foamy slag formations at 1600 °C. Thermogravimetric analysis (TGA) conducted under air unveiled differences in mass loss among carbon sources, showing an increasing order of coke < biocoke with 5 wt.% wood pellets < biocoke with 10 wt.% wood pellets. The Coats–Redfern method was used to calculate and reveal distinct activation energies among these carbon sources. Slag foaming tests performed using biocoke samples resulted in stable foam formation, indicating the potential for biocoke as a carbon source to replace those conventionally used for this process. Slag foaming characters for biocoke with 5 wt.% wood pellets were improved more than coke. Using biocoke with 10 wt.% wood pellets was marginally worse than coke. On the one hand, for biocoke with 5 wt.% wood pellets, due to increased reactivity, the foaming time was reduced, but it was sufficient and optimal for slag foaming. Conversely, biocoke with 10 wt.% wood pellets reduced foaming time, proving insufficient and limiting the continuity of the foaming. This study highlights that thermochemical properties play a significant role, but comprehensive assessment should consider multiple parameters when evaluating the suitability of unconventional carbon sources for slag foaming applications. [ABSTRACT FROM AUTHOR]

Steelmaking is one of the most energy-intensive industries, so improving control efficiency helps to reduce the energy used to produce a tonne of steel. Mutual influences between the phases of an electric arc furnace in available electrode movement control systems cause unproductive electrode movements as a reaction to the redistribution of currents among the phases of a three-phase power supply system due to changes in arc length in one of the phases. The nonlinearity of the characteristics of an electric arc furnace significantly complicates the ability to provide autonomous electrode movement control. The approach proposed in this paper, based on the formation of a matrix of mutual influences with variable coefficients, significantly improves the per-phase autonomy of the electrode movement control system. Nonlinear dependences of the mutual influence coefficients as a function of the current increment in the phase in which the disturbance occurred are obtained. Thus, it is possible to practically eliminate unproductive electrode movements in existing control systems by avoiding the traditional use of a dead zone, which reduces the control quality in the zone of small disturbances. The complex of experiments performed using the mathematical model demonstrate that the mutual influence improves the dynamic properties of the electrode movement system in certain operating modes. [ABSTRACT FROM AUTHOR]

Hydrogen has the potential to decarbonize a variety of energy-intensive sectors, including steel production. Using the life cycle assessment (LCA) methodology, the state of the art is given for current hydrogen production with a focus on the hydrogen carbon footprint. Beside the state of the art, the outlook on different European scenarios up to the year 2040 is presented. A case study of the transformation of steel production from coal-based towards hydrogen- and electricity-based metallurgy is presented. Direct reduction plants with integrated electric arc furnaces enable steel production, which is almost exclusively based on hydrogen and electricity or rather on electricity alone, if hydrogen stems from electrolysis. Thus, an integrated steel site has a demand of 4.9 kWh of electric energy per kilogram of steel. The carbon footprint of steel considering a European sustainable development scenario concerning the electricity mix is 0.75 kg CO2eq/kg steel in 2040. From a novel perspective, a break-even analysis is given comparing the use of natural gas and hydrogen using different electricity mixes. The results concerning hydrogen production presented in this paper can also be transferred to application fields other than steel. [ABSTRACT FROM AUTHOR]

Electrical Arc Furnaces (EAFs) consume time‐varying power. This causes mechanical torque variations in the nearby small scale synchronous generators (SSSGs) and reduces their life expectancy. In this paper, an appropriate EAF model is implemented and verified by using field measurements. Moreover, an actual distribution system to which an SSSG is connected to supply industrial loads including an EAF is investigated based on time‐domain simulation studies. To enhance dynamic performance of the SSSG adjacent to an EAF load, two novel approaches are presented in this paper. The first method is utilized for proper adjustment of governor controller parameters. Analytical and simulation‐based studies are accomplished to determine proper parameters of the SSSG conventional governor controller to mitigate the mechanical oscillations caused by EAF. These comprehensive investigations reveal that the governor PI controller proportional parameter should be adjusted as small as possible to mitigate the SSSG oscillations; while, the oscillations are fairly independent of integrator parameter. Besides, the integrator parameter should be set as high as possible to improve the SSSG dynamic performance. Moreover, a new modified SSSG governor controller including steady‐state and transient control loops is developed and a novel control strategy is proposed to enhance steady‐state and transient performance of SSSG. Finally, robustness and effectiveness of the proposed controller and its parameters are investigated using field measured EAF current signals for various transients. It should be noted that the proposed strategies of this paper can be also applied to similar cases where a nonlinear time varying load is connected to an SSSG. [ABSTRACT FROM AUTHOR]

Non-metallic inclusions are one of the many factors influencing the strength of materials operating under variable loads. Their influence on the strength of the material depends not only on the morphology of the impurities themselves, but it is also closely related to the microstructure of the material. This microstructure is the matrix for non-metallic inclusions. This article discusses the results of a study investigating the effect of non-metallic inclusions on the fatigue strength of structural steel during rotary bending. The study was performed at 12 heats produced in an industrial plant's 140-ton electric furnaces. Six heats were desulphurised, and six were refined with argon. This paper presents the bending fatigue strength of steel hardened and tempered at different temperatures, subject to the relative volume of inclusions. This paper also presents the dimensional structure of non-metallic inclusions divided by different two technologies. The research shows that the main fraction of non-metallic inclusions is Al2O3; the most numerous were impurities with a diameter of less than 2 µm; argon refining does not affect the proportion of non-metallic inclusions of large dimensions (with a diameter of over 15 µm); the influence of non-metallic inclusions on the strength of the steel is also related to the microstructure of the steel constituting the matrix of inclusions. [ABSTRACT FROM AUTHOR]

Transmission system operators (TSO) should be able to assess power quality levels in a network in order to properly address the mitigation of power quality problems. High flicker levels might be a serious power-quality problem in transmission networks and are usually caused by arc-furnace operation. TSO can assess flicker levels in real time only at nodes where power-quality measurements are available. As for the rest of the system, a TSO could calculate flicker levels, if a reliable and relatively simple method is available. Besides, proper summation of flicker levels originating from several flicker sources remains an issue to tackle. The paper proposes a simple method for the calculation of flicker levels at all nodes of a transmission network based on the known flicker values at multiple flicker-sources and based on the known network topology. Different flicker summation coefficients are compared and the one that gives the smallest error is chosen. The proposed method enables a TSO to continuously assess flicker levels at all network nodes and to investigate the consequences of network changes on flicker levels. The method was verified on the Slovenian transmission network where the results of flicker calculation were compared with available flicker measurements. [ABSTRACT FROM PUBLISHER]

This paper describes the development of a boundary model for the off‐gas water vapour in an industrial steelmaking electric arc furnace (EAF). The solution addresses the mechanistic components of a complete EAF water detection framework. The boundary model has been implemented on an industrial alternating current (AC) EAF. The model specifies upper and lower limits in real‐time of the expected EAF off‐gas water vapour leaving the furnace, and it provides a valuable on‐line monitoring tool to the operator on what boundary to expect for the off‐gas water vapour in different circumstances. An essential data required for the framework is the EAF off‐gas composition. So, in this work, an off‐gas analyzer with a human machine interface (HMI) and a supervisory control and data acquisition (SCADA) system was installed in the first step. Then, in order to evaluate the developed water leak detection framework and verify the obtained results, industrial trials were designed in which a certain amount of water was intentionally added into the furnace by increasing the electrode spray water flow rate. Moreover, we have shown how the presented framework can be used to appropriately adjust the alarm setting values in control/emergency shutdown systems of industrial EAF to enhance the safety and availability of the plant. [ABSTRACT FROM AUTHOR]

The effect of Al and Ti additions on the microstructure and properties of CoNiFe alloys was studied in this paper. The investigations were conducted on four specially designed and produced arc furnace alloys (from 3 to 5 components, with medium to high entropy). Samples in various states were analyzed, i.e., as-cast, after homogenization, after solution heat treatment, and after solution heat treatment and aging. The obtained samples were characterized by: SEM observations, EDS, XRD, TEM analyses, and finally, hardness measurements. The solid solution strengthening coming from the addition of 5 at. pct. Al was negligible, while the effect from the 5 at. pct. of Ti addition was significant. The precipitation hardening effect related to the presence of the (CoNi)3Ti phase caused by the Ti addition is comparable with the total effect of the Al and Ti addition, which caused the precipitation of (NiCo)3AlTi. [ABSTRACT FROM AUTHOR]

This paper describes methods and approaches for numerical simulation of liquid metal flows in a direct current (DC) arc furnace with a bottom electrode. The model for numerical simulation takes into account an actual bottomelectrode arc furnace and is based on magnetohydrodynamic equations. The distributions of the Lorentz force, temperature, and the vortex flow velocity are presented. The method to control and reduce the vortex flow intensity in a liquid metal volume by changing the furnace bottom position is worked up. The results of the numerical simulation show a possibility to reduce a negative influence of the vortex flow of a liquid metal up to 50%. [ABSTRACT FROM AUTHOR]

The stochastic and nonlinear characteristics of electric arc furnaces (EAFs) lead to power quality challenges in the power system. In studying EAF behaviors, having optimized characteristics/models, selecting a suitable and optimum model that adapts to the actual characteristics of EAFs, and investigating simulation software's capability for implementing EAF models are essential. However, the literature shows a research gap in investigating EAF simulations in various software products based on different models. This paper studies several time-domain models, such as piece-wise linear, modified piece-wise linear, hyperbolic, exponential, and exponential-hyperbolic models, for EAF modeling and simulation. The optimal estimation of parameters for the introduced models is necessary to adapt actual EAF characteristics. Thus, one of the studies taken in this paper is optimizing the EAF model's characteristics. The proposed optimization problem is solved using the genetic algorithm (GA) and particle swarm optimization (PSO). Moreover, the optimized models are simulated in DIgSILENT and EMTP-RV to investigate different EAF models from the viewpoint of accuracy and efficiency. The optimization of different EAF models' characteristics and comparison of EMTP-RV and DIgSILENT in simulating EAF behavior are the contributions of this paper. The proposed method is validated based on the actual data of a realistic EAF-based steel company in Iran. The obtained results show that the modified piece-wise linear model has the most accuracy in identifying the EAF behavior. The test results based on DIgSILENT and EMTP-RV simulations imply that the EAF could be simulated with high accuracy using modified piece-wise linear and piece-wise linear models. In general, EMTP-RV has expressed more accuracy in simulating different EAF models, and the simulation execution speed of EMTP-RV is around 2.5 times faster than DIgSILENT. In contrast, DIgSILENT is more suitable to facilitate the power system studies of EAF according to its extensive study tools and library. [ABSTRACT FROM AUTHOR]

Transient behavior in grounding systems related to electric arc furnaces (EAF) might be studied using an approach to Kron’s circuit model to solve Maxwell’s differential equations in electromagnetic field theory. This paper presents a circuit model designed using Kron’s approach implemented in alternative transient program (ATP). The model is suitable to describe accurately the behavior of real complex grounding systems dealing with continuous operation of an EAF. Some ideas about the behavior of the power quality are evaluated by simulation of the grounding system in ATP. [ABSTRACT FROM AUTHOR]

Shape memory alloys (SMAs) are smart materials with unique properties of superelasticity and shape memory effect. These properties are the consequence of thermoelastic martensitic transformation, which can occur under thermal or mechanical deformation. Cu-Al-Ag alloys have high temperatures of martensite transformation, unlike other SMAs, which makes them suitable for use in specific applications. In this paper, Cu- 10Al-1Ag alloy was prepared by melting pure metals in an electric arc furnace and casting the melt in a cylindrical mold. The microstructure of the as-cast and quenched material was determined by optical microscopy (OM) and scanning electron microscopy (SEM) equipped with energy dispersive analysis (EDS). X-ray diffraction (XRD) analysis was performed to identify crystal phases in the microstructure, while transformation temperatures were determined by differential scanning calorimetry (DSC). The hardness of Cu-Al-Ag SMA was also determined with a microhardness tester. The results showed partially formed martensite in the as-cast state, and fully formed martensite structure, 18R-type, in the quenched Cu-10Al-1Ag alloy. [ABSTRACT FROM AUTHOR]

Conventionally, DC arc furnaces are fed by thyristor rectifiers to control the level of current or power transferred to the load. With the advancement of high-power transistors, other structures such as diode rectifiers and DC choppers have been introduced and developed for the feeding system of DC electric arc furnaces. In this paper, the effect of different power supply systems on power quality indexes is discussed. In this regard, two types of feeding systems are considered, including a power supply system based on thyristor rectifiers and a power supply system based on diode rectifiers and DC choppers. In addition, different control methods, including constant current control (CCC) and constant power control (CPC), on DC electric arc furnaces are applied. For evaluating the power quality indexes, voltage and current harmonic distortion, unbalance of voltage and current, and power factor on the AC side are investigated for different power supply systems. Simulation results were performed with PSCAD/EMTDC software. It is shown that the power supply systems with diode rectifiers and DC choppers have superiority in comparison to the types based on thyristor rectifiers. According to the results, the average current THD is reduced from 16.55% in the thyristor rectifier to 8.40% in the chopper rectifiers with the CCC method and from 19.27% in the thyristor rectifier to 7.38% in the chopper rectifiers with the CPC method. Moreover, the average voltage THD is reduced from 5.67% in the thyristor rectifier to 3.02% in the chopper rectifiers with the CCC method. The result is similar to the CPC method. Furthermore, for a specific power supply system, the harmonic distortion is lower in the case of the CPC method than in the CCC method. [ABSTRACT FROM AUTHOR]

To optimize the stainless steel plant dust (SSD) reduction process for recovering valuable metals, a good kinetics understanding is required. In this paper, the thermodynamics of carbothermal reduction of SSD were analyzed. In addition, the non-isothermal kinetics of SSD carbothermal reduction, combined with thermogravimetric analysis, XRD, and SEM–EDS were studied by applying the Flynn–Wall–Ozawa (FWO) and Málek models. Thermodynamics and kinetic analysis results illustrate that below 950°C, the main reduction reaction is direct reduction between SSD and carbon. As the temperature increases, indirect reduction leads the reduction process of hematite due to CO formation. The reaction is highly temperature dependent and the reduction rate increases with temperature increments. The activation energy initially increased; it was 151.69 kJ/mol when the reduction rate (α) was 0.1. In the middle stage of the reaction, it slightly decreased from 343.76 kJ/mol when α ≥ 0.3, before continually increasing when α ≥ 0.6. The reduction process is a multistep reaction. The controlling step in the initial stage (α ≤ 0.2) is a shrinking core mode with the integral form 1 − (1 − α)3. As the reaction proceeds (0.2 ≤ α ≤ 0.6), the reduction is controlled by a chemical reaction expressed by (1 − α)−1 − 1. In the later stage (α ≥ 0.6), the reaction is a chemical reaction described by (1 − α)−2. [ABSTRACT FROM AUTHOR]

The advantages of a static var compensator (SVC) for electric arc furnace (EAF) and ladle melt furnace (LMF) applications are well known. The SVC minimizes the impact of the EAF and LMF on the utility and improves the efficiency of both furnaces. In this application, it was desirable to quantify the performance of the SVC. This paper describes power quality measurements that were taken on the electrical distribution system to evaluate the performance of the SVC. The purpose of the power quality measurements was to monitor the voltage regulation, harmonics, flicker, and other power quality quantities at the 138-kV utility point of common coupling (PCC), as well as the 34.5-kV system serving the SVC, EAF, and LMF. The measurements and subsequent analysis established a baseline for the SVC performance and identified areas of concern. This paper describes the analysis of the measurements and evaluation of the SVC performance. [ABSTRACT FROM PUBLISHER]

As increasing data-driven control strategies are applied in electric arc furnace systems, the problem of novelty detection has drawn more attentions than before. The presence of outliers should be the main obstacle in practical applications for these advanced control techniques. To this end, this paper proposes a dynamically selective support vector data description model to discover novelties in electric arc furnace. In this model, support vector data description plays the role of base detector. Artificial outliers are generated with two objectives, one is to assist the dynamic selection, and the other is to optimize two parameters of support vector data description. Then clustering technique is used to determine the validation set for each test point. Finally, a probabilistic method is used to compute the competence of base detectors. In contrast to other novelty ensembles that have parallel structures, our ensemble model has a dynamic selection mechanism that could facilitate the mining of the potential of base detectors. Three synthetic and three real-world datasets are used to validate the effectiveness of the proposed detection model. Experimental results have approved our method by comparing it with several competitors. [ABSTRACT FROM AUTHOR]

Detection of the islanding condition of distributed energy resource (DER) is a crucial protection concern as per IEEE standards. Industrial motors, arc furnaces, EV fast-charging station, etc., are loads of serious concern that adversely affect the proper functioning of conventional anti-islanding protection schemes. This paper introduces a novel anti-islanding protection scheme for three-phase inverter-based DER located near/within the premises of a modern industrial consumer. In this work, a modified passive intelligent islanding detection method is employed which uses discrete wavelet transform for extraction of six features from input signals (d-axis voltage, V d and frequency, f) and support vector machine for classification. Models of various loads and equipment are developed and are connected to IEEE 13 bus system to create the test system. Test cases are generated by considering various load conditions and the occurrence of different events in the test system. PSCAD/EMTDC is used for simulation. Reduction in the non-detection zone and detection time compared to the existing methods proves the robustness of the proposed method. [ABSTRACT FROM AUTHOR]

The publication presents heat and electricity management in the Polish steel industry. The paper is based on actual data on heat and electricity consumption and intensity by processes in the steel industry in Poland in Industry 4.0 conditions. Two steel production processes are used in Poland: EAF Electric Arc Furnace and BOF Basic Oxygen Furnace. The analysis is an analysis of actual data is used to characterise the electricity and heat consumption by processes in the Polish steel industry. The analysis shows that the EAF technology is always more electricity intensive and the BOF technology more heat intensive. On the basis of conducted analysis, it can be concluded that pro-environmental innovations in the steel industry should first aim to reduce the electricity consumption of EAF technology and the heat consumption of BOF. An analysis of data for Poland for the period 2004–2020 shows that both cases occurred. The study shows that the heat consumption of BOF technologies has been steadily decreasing since 2010, and the electricity consumption of EAF technologies has been decreasing throughout the period under review. It can be concluded from this that the Polish steel industry is adapting to pro-environmental requirements and, through the introduction of technological innovations, is moving towards the concept of sustainable steel production according to green steel principles. The decrease in energy intensity (means electricity) of steel produced according to EAF technology is an important issue, as the high energy intensity of EAF processes affects the overall energy intensity of the steel production in Poland. In the future, the use of new innovative technological solutions, including solutions based on Industry 4.0 principles, should help the Polish steel industry to further reduce the level of electricity and heat consumption. The driving force behind the investment is the boom in the steel market. The authors made a short-term forecasts of steel production (2022–2025). The annual forecasts determined and analyses made were used to determine the heat and energy consumption of the Polish steel industry up to 2025. [ABSTRACT FROM AUTHOR]

World's energy sources like petrochemical oils, natural gas and coal cause global warming and environmental pollution. Therefore, the traditional energy sources must be replaced by the renewable energy resources. Biodiesel has been recognized as one of the effective, green, renewable and sustainable fuels. This paper investigates the production of biodiesel from sunflower oil by using electric arc furnace dust (EAFD) as a heterogeneous solid catalyst. Four reaction variables, i.e., the reaction time, methanol-to-oil (M/O) molar ratio, reaction temperature and EAFD loading, were chosen to determine their effect on biodiesel production. The effect of the all reaction variables on the biodiesel yield was evaluated using response surface methodology. A relation has been developed representing the biodiesel conversion as a function of all the independent variables. Reaction conditions optimization have been studied for the biodiesel yield maximization and the reaction conditions minimization. The optimum biodiesel yield equals 96% at reaction temperature of 57 °C, methanol-to-oil molar ratio of 20:1, reaction time of 1 h and EAFD loading of 5%. [ABSTRACT FROM AUTHOR]

This review aims to show the significance of the use of secondary carbon bio-carriers for iron and steel production. The term 'secondary carbon bio-carriers' in this review paper refers to biomass, torrefied biomass, biochar, charcoal, or biocoke. The main focus is on torrefied biomass, which can act as a carbon source for partial or complete replacement of fossil fuel in various metallurgical processes. The material requirements for the use of secondary carbon bio-carriers in different metallurgical processes are systematized, and pathways for the use of secondary carbon bio-carriers in four main routes of steel production are described; namely, blast furnace/basic oxygen furnace (BF/BOF), melting of scrap in electric arc furnace (scrap/EAF), direct reduced iron/electric arc furnace (DRI/EAF), and smelting reduction/basic oxygen furnace (SR/BOF). In addition, there is also a focus on the use of secondary carbon bio-carriers in a submerged arc furnace (SAF) for ferroalloy production. The issue of using secondary carbon bio-carriers is specific and individual, depending on the chosen process. However, the most promising ways to use secondary carbon bio-carriers are determined in scrap/EAF, DRI/EAF, SR/BOF, and SAF. Finally, the main priority of future research is the establishment of optimal parameters, material quantities, and qualities for using secondary carbon bio-carriers in metallurgical processes. [ABSTRACT FROM AUTHOR]

The tapping process of submerged arc furnaces, like the Mn-ferroalloy production process, is when you drain the liquid metal and slag from the furnace. The optimal tapping process is when slag and metal is drained from the furnace at the same rate as it is produced, and the slag and metal is being separated in the post-tap hole process. Industrially, this is not always the case. Based on published articles, this paper discusses the total tapping process that contains the consecutive steps of flow from back electrodes to the tap electrode and flow from the tap electrode through the tap hole and runner, and into the ladle system. It focuses on an overall summary of which elements may affect the tapping; however, it should be noted that this is not a mathematical model. The main information is regarding materials and zones in the furnaces, as well as knowledge from computational fluid dynamics (CFD) modeling work. [ABSTRACT FROM AUTHOR]

This paper describes the development of "heats" and input variables selection models that are incorporated into a water detection framework for an industrial steelmaking electric arc furnace (EAF). The selection models in this work are developed based on latent variable methods. The latent variable methods used in this work are multiway principal component analysis (MPCA) and multiway projection to latent structures (MPLS). The particular problems related to latent variable methods discussed in this paper include data preprocessing, including alignment, unfolding method, centering, and scaling. The outcome of the heats selection model is heats with normal operation and the outcome of the input variables selection model is variables that are highly correlated with the off‐gas water vapour. The water detection framework and developed models are useful in practical settings for the prediction of water leakage and the design of appropriate fault detection and diagnosis strategies. [ABSTRACT FROM AUTHOR]

This paper deals with the utilization of printed circuit board Rogowski coils (PCBRCs) for differential protection of electric arc furnace (EAF) transformers in Mobarakeh Steel Company (MSC), Isfahan, Iran. Because of a high level of current (in the range of 100 kA) in the EAF transformers in the MSC, employment of differential protection is quite challenging. Conventional current transformers (CTs) cannot offer reliable performance for very high current levels. The PCBRCs are a branch of Rogowski coils (RCs) that can be manufactured with high precision using computer‐aided design approaches and have the capability for the measurement of very large currents. In this study, we have designed and manufactured two sets of PCBRCs to measure current in the primary and secondary sides of the EAF's transformers in the MSC. The PCBRCs are followed by a signal condition circuit (SCC) which includes a low‐pass filter, amplifier, and voltage‐to‐current (V‐to‐I) converter block. Thanks to the SCC, the high current of the transformers can be properly sensed and transmitted over a long cable that connects the PCBRCs to the relay. Furthermore, a novel model is suggested for the EAF that includes characteristics of both time and frequency domain models. The suggested model is developed using a large number of recorded data from the MSC and can model the non‐linear and time‐variant behaviours of the EAF. The proposed PCBRCs, SCC, and EAF modelling are evaluated by some simulations and experiments in the MSC. [ABSTRACT FROM AUTHOR]

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Basic Oxygen Furnace (BOF) steelmaking is, worldwide, the most frequently applied process. According to the world steel organization statistical report, 2021, it saw a total production share of 73.2%, or 1371.2 million tons per year of the world steel production in 2020. The rest is produced in Electric Arc Furnace (EAF)-based steel mills (26.3%), and only a very few open-hearth and induction furnace-based steel mills. The BOF technology remains the leading technology applied based on its undoubted advantages in productivity and liquid steel composition control. The BOF technology started as the LD process 70 years ago, with the first heat applied in November 1952 in a steel mill in Linz, Austria. The name LD was formed from the first letters of the two sites with the first industrial scale plants, Linz and Donawitz, both in Austria. The history and development of the process have been honored in multiple anniversary publications over the last few decades. Nevertheless, the focus of the steel industry worldwide is significantly changing following a social and political trend and the requirement for fossil-free energy generation and industrial production to be in accordance with the world climate targets committed to in relation to the decades leading up to 2050. Iron and steel production is one of the major polluters of climate changing greenhouse gases; it must change to renewable primary energy sources and the use of climate-neutral reduction agents. Because it is very obvious that carbon, as the main component for steel strength properties, cannot be eliminated totally from the steel production process, the question arises of where a "zero carbon" approach can lead? This paper will review the ongoing success story of the LD-process, discuss the recent technology advancements, and give an outlook on the future role of the process in the steel industry. [ABSTRACT FROM AUTHOR]

The synergetic utilization of ferruginous gibbsite ores (Al-Fe ores) and ferruginous manganese ores (Mn-Fe ores) by the carbothermic co-reduction roasting–magnetic separation process was proposed as an innovative and green process for the separation and recovery of the valuable metal elements of Mn, Fe and Al from these ores. In this paper, a ferromanganese crude alloy with 72.47% Fe and 10.19% Mn and a high recovery of 85.89% Fe was prepared, which produces an acceptable feed to produce manganese steels with an electric arc furnace. The synergistic co-reduction of the two kinds of complex and refractory minerals was favored to separate Fe, Mn and Al from these ores. The influence of the operating variables on the recovery and separation of valuable metals from Mn-Fe ores and Al-Fe ores is initially studied. Then, the stepwise reduction behaviors of a composite oxide Mn1-xFexO (0 ≤ x ≤ 1) and hercynite (Mn1−yFeyAl2O4, 0 ≤ y ≤ 1) were investigated to clarify that Mn-Fe ores have a positive impact on the reduction of fayalite and hercynite in Al-Fe ores. This study reported a simple green route, the carbothermic co-reduction–magnetic separation process, to economically and effectively treat Al-Fe ores and Mn-Fe ores. [ABSTRACT FROM AUTHOR]

A method of calculating LC parameters of a reactive balancing compensator for AC arc furnaces at the supply voltage asymmetry is the subject of this paper. The developed method is illustrated numerically with the calculation of LC parameters of a balancing compensator for an AC arc furnace approximated by a linear model with fixed parameters. The presented method can be regarded as an initial step toward developing balancing compensation for ultra-high-power AC arc furnaces. The method of calculation of LC parameters of balancing compensators is based in this paper on the Currents' Physical Component (CPC) power theory. [ABSTRACT FROM PUBLISHER]

Copyright of Journal of Mining & Metallurgy. Section B: Metallurgy is the property of Journal of Mining & Metallurgy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the steel industry, the optimization of production processes has become increasingly important in recent years. Large amounts of historical data and various machine learning methods can be used to reduce energy consumption and increase overall time efficiency. Using data from more than two thousand electric arc furnace (EAF) batches produced in SIJ Acroni steelworks, the consumption of electrical energy during melting was analysed. Information on the consumed energy in each step of the electric arc process is essential to increase the efficiency of the EAF. In the paper, four different modelling approaches for predicting electrical energy consumption during EAF operation are presented: linear regression, k-NN modelling, evolving and conventional fuzzy modelling. In the learning phase, from a set of more than ten regressors, only those that have the greatest impact on energy consumption were selected. The obtained models that can accurately predict the energy consumption are used to determine the optimal duration of the transformer profile during melting. The models can predict the optimal energy consumption by selecting pre-processed training data, where the main steps are to find and remove outlier batches with the highest energy consumption and identify the influencing variables that contribute most to the increased energy consumption. It should be emphasised that the electrical energy consumption was too high in most batches only because the melting time was unnecessarily prolonged. Using the proposed models, EAF operators can obtain information on the estimated energy consumption before batch processing depending on the scrap weight in each basket and the added additives, as well as information on the optimal melting time for a given EAF batch. All models were validated and compared using 30% of all data, with the fuzzy model in particular providing accurate prediction results. It is expected that the use of the developed models will lead to a reduction in energy consumption as well as an increase in EAF efficiency. [ABSTRACT FROM AUTHOR]

In this paper, a method based on the multiple synchronous reference frame analysis is recommended and implemented to detect time-varying harmonics and interharmonics of rapidly fluctuating asymmetrical industrial loads. The experimental work has been carried out on a typical three-phase alternating current arc furnace installation. In the recommended method, the reference frame is rotated in both directions at speeds corresponding to the positive and negative sequences of all harmonics and all interharmonics 5 Hz apart. To extract the direct current components of the transformed d–q quantities, a low-pass filter is employed. In order to keep the delay of the filter at zero frequency less than a few ms, Kalman estimation technique has been used. Back transformation is then applied for each harmonic and interharmonic component to obtain their positive- and negative-sequences of the associated harmonic and interharmonic in the actual line current waveforms. Parallel computing technique has been applied for the real-time detection of both the phase and the amplitude of all harmonics and interharmonics. This is achieved on NVDIA Jetson TX1 graphics processing unit framework for a sample industrial plant. The developed system is shown to be useful for fast and accurate generation of reference signals for the controllers of the advanced technology power conditioning systems which successfully compensates interharmonics, harmonics, and flicker of the rapidly fluctuating nonlinear industrial loads. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid time-frequency analysis method, specially developed to decompose harmonic subgroups and interharmonics of the electric arc furnace (EAF) currents, which are highly time varying due to the operation principles of the EAFs, is presented. The main objective is accurate perception of harmonics and interharmonics in cases of rapid changes or power quality (PQ) events in power system voltages and currents. Harmonic and interharmonics detection has been achieved using discrete wavelet transform (DWT), which provides time-localization in cases of highly time-varying signals. Although DWT elicits accurate spectral decomposition at low frequencies, and especially at the baseband, bandwidths of the band-pass filters increase which results in loss of accuracy at higher frequencies. In order to avoid this problem, power signals are modulated by complex exponential waveforms, which corresponds to shifting the required harmonic sub-band contents to the baseband, where the accuracy of the DWT is the best. Using the proposed hybrid combination of DWT and complex exponential modulation, time domain waveform of each harmonic sub-band of the EAF currents can be estimated close to ideal values. The method also enables to focus on any required interharmonic sub-band in addition to the harmonics. To optimize the performance of the DWT in cases of PQ events, various windowing approaches are discussed. The proposed harmonic and interharmonic estimation method has been verified on both synthetic data and EAF currents collected from the electricity transmission system. Estimated harmonic and interharmonic waveforms can serve as a good reference in many areas including active power filtering operations, limit violation determinations, etc., in the power system. [ABSTRACT FROM AUTHOR]

The Pyrometallurgy Division at Mintek is known internationally for the development of applications of direct current (DC) arc furnace technology in smelting applications, more specifically in the smelting of primary resources, i.e., chromite, ilmenite, titanomagnetite, nickel laterite and ores containing precious group metals, and secondary resources, i.e., furnace slag or dust. From a furnace containment perspective, either an insulating or a conductive design philosophy can be applied, irrespective of the raw material being processed. In the initial stages of a project, desktop studies are typically conducted which include the selection of a furnace containment design philosophy, specific to the application. To lower the risk associated with incorrect selection of a design philosophy and/or furnace containment system components, it is prudent to conduct tests on laboratory and pilot scale and to transfer the knowledge gained to industrial applications. The paper presents examples of the laboratory and pilot techniques utilized. [ABSTRACT FROM AUTHOR]

Abstract Electric arc furnace (EAF) is one of the most disturbing loads in the power system as it is highly time‐varying and nonlinear. In this paper, new models based on the instantaneous EAF voltage and current, recorded from EAFs in Mobarakeh steel company in Isfahan/Iran are proposed. The focus of this paper is on developing efficient models based on the Schwarz model where three modified types are proposed. The original Schwarz model has four constant parameters. Unlike the original Schwarz model which uses invariant parameters, the time‐varying nature of the arc's parameters is considered in the proposed models. The first modified model has two constant model orders and two time‐varying coefficients. Additionally, to further enhance the model's accuracy, in the second modified model, six parameters include three constant model orders, and three time‐varying coefficients exist. The third model uses all the original model's parameters as time‐series parameters. The parameters of the time‐varying model are derived using autoregressive moving average (ARMA) models. The accuracy of the proposed model is evaluated by calculating the active power, harmonics, instantaneous flicker, and short‐term flicker. Finally, three MATLAB codes are provided to generate the model parameters time series.

This paper evaluates the abilities of fast tap-changer topologies by using insulated-gate bipolar transistors to mitigate flicker generated by the ac electric arc furnaces, based on technical and economic criteria. The design problems derived from the very high powers and currents involved have been solved to a preliminary industrial level. The operation of the best resulting topology is verified on a real 80-MVA arc furnace with a dedicated graphical-mathematical multilevel simulator developed to perform short- and long-term tests. Selected pattern windows of the arc voltage, taken from exhaustive logs of electric variables of a real 80-MVA furnace during a complete meltdown process, have been loaded into the simulator. This novel simulation strategy enables the testing of the proposed compensator under reproduced “real working conditions” with several degrees of flicker severity. The simulator includes an IEC flicker meter capable of checking the flicker level online at any point in the installation. The simple open-loop and closed-loop control tests confirm the new tap changer as a fast and economical competitor to other arc furnace compensators. It manages 16% of the furnace system power at a subcycle or supercycle tap changing rate (between 0 and 10 changes per half cycle), as required. This fast switching capacity reduces the compensating time to the very limited values imposed by the L/R time constant of the furnace installation. [ABSTRACT FROM AUTHOR]

This Special Issue is dedicated to the use of nanomaterials for the modification of asphalt binders to support the analysis of the relevant properties and to determine if the modification indicated a more efficient use of asphalt mixtures' fabrication or their modification in the context of asphalt mixtures' fabrication and the improvement (or lack thereof) of these last ones to constitute effective asphalt pavement layers. Use of Nanomaterials in the Asphalt Industry The review published [[1]] described the effect of using nanosilica, nanoclays, and nanoiron to achieve better, more efficient asphalt mixtures, mechanically and in durability terms, fostering high-performance and long-lasting asphalt pavements. [Extracted from the article]