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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]

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]

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 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]

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]

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]

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]

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 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]

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]

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]

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]

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 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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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 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]

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]

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]

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.

The physicochemical transformations and electromagnetic properties of a composite based on the dust of electrical arc steel-making furnaces and a carbon-containing material (hydrolysis lignin) have been studied. The complex dielectric permittivity of the studied material was measured by the resonator method during heating to 800°C. At room temperature, the effective values of the magnetic permeability and loss of the composite mixture were calculated by solving the Bruggeman equation according to the effective medium theory. The magnetic permeability during heating was found by orthogonal regression. The numerical model of heating a dense packing from several layers of studied material grains was constructed by the finite element method with consideration of the real properties and physicochemical transformations. [ABSTRACT FROM AUTHOR]

This paper presents new directions in the modeling of electric arc furnaces. This work is devoted to an overview of new approaches based on random differential equations, artificial neural networks, chaos theory, and fractional calculus. The foundation of proposed solutions consists of an instantaneous power balance equation related to the electric arc phenomenon. The emphasis is mostly placed on the conclusions that come from a novel interpretation of the equation coefficients. [ABSTRACT FROM AUTHOR]

• Inherent uneven distribution of microwaves leads to the localized thermal effect. • Microwave heating is non-uniform, power and sample composition are not the primary factors. • The promotion of microwaves on reaction is mainly attributed to the localized thermal effect. • The activation energy decreases from 223.7 to 47.5 kJ/mol in the localized thermal regions. Microwave heating provides a cleaner pyrometallurgical method for separating zinc from electric arc furnace dust (EAFD, a solid waste generated during steel production with excellent dielectric properties). Despite its undisputed heating efficiency, the impact of microwave heating characteristics on the zinc removal process from EAFD remains unclear. This paper focuses on ZnO, one of the primary components of EAFD, and develops an electromagnetic-thermal-chemical reaction model to analyze the effects of microwave power and graphite addition on heating behavior, reduction reactions, field distributions, and reaction kinetics. The results indicate that the heat generated from the interaction between microwaves and materials exhibits inherent non-uniformity, leading to the localized thermal effect and making the error of general temperature measurement methods. Increasing microwave power and adding graphite enhance heating efficiency and promote the reduction reaction but also result in significant internal-external temperature disparity and worse temperature distribution. At 1000 W, with 1.2 times the stoichiometric amount of graphite addition, the temperature measurement error reaches approximately 200 °C, potentially affecting the kinetic results to a certain degree. The non-isothermal kinetics results from simulations indicate that the localized thermal region exhibits a lower average activation energy of 47.5 kJ/mol compared to experimental results, suggesting that the lower activation energy of the ZnO reduction reaction during microwave heating is primarily caused by the localized thermal effect rather than the non-thermal effect. Additionally, in the energy distribution, the higher proportion of return loss during heating underscores the importance of a well-designed microwave heating system. [ABSTRACT FROM AUTHOR]

The relationship between slag structure and viscosity is studied, employing Raman spectroscopy for the five-component slag system of MnO-SiO2-CaO-Al2O3-MgO and its subsystems. This study aims to investigate the influence of variations in slag composition on viscosity, which is crucial for optimizing industrial processes. Based on industrial slag compositions produced in a silicomanganese submerged arc furnace, 17 slags with a fixed content of MnO of 10 wt% are synthesized with varying contents of SiO2 of 33 to 65 wt%; CaO within the range of 14 to 40 wt%; and fixed contents of Al2O3 and MgO of 17 and 6 wt%, respectively. The slag compositions are divided into four groups, ranging from low basicity (0.38) to high basicity (0.80), with each group containing the four slag systems of MnO-SiO2-CaO, MnO-SiO2-CaO-Al2O3, MnO-SiO2-CaO-MgO, and MnO-SiO2-CaO-Al2O3-MgO, with fixed basicity. Additionally, a five-component composition with the lowest basicity of 0.28 is considered. Raman spectroscopy measurements are performed in the wavenumber range of 200 to 1200 cm − 1 using a green source laser with a 532 nm wavelength. The high-wavenumber region of the Raman spectra (800 to 1200 cm − 1 ) is deconvoluted to quantitatively investigate the effect of each oxide on the slag structure and the degree of polymerization (DOP) of the silicate network. Results indicate that measured NBO/T increases with increasing basicity, demonstrating a reduction in DOP of the silicate structure. This depolymerization effect is more pronounced in slags containing Al2O3 compared to those without it. In a group of slags with similar basicity, the substitution of SiO2 with Al2O3 leads to further depolymerization. In contrast, substituting CaO with MgO has little effect on the silicate structure in slags without Al2O3 but causes depolymerization in slags containing Al2O3. To study the relationship between structure and viscosity, viscosity data obtained from FactSage are used as reference values. The predictions of slag viscosity using the Raman-structure model and the NBO/T viscosity model are then compared to the FactSage results. The adjustable parameters of the Raman-structure model are re-determined using the FactSage data for the studied slag compositions. The NBO/T viscosity model employs both calculated NBO/T values from the slag compositions and measured NBO/T values from the deconvolution results. The findings of this study reveal good agreement between the predictions of the Raman-structure model and the FactSage viscosity data. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess the level of contamination of the common dandelion—Taraxacum officinale—with selected metals (Mn, Fe, Ni, Cu, Zn, Cd, and Pb) and to demonstrate that this plant can be used in passive biomonitoring of industrial sites. Two sample transects (the first was near a forest, an area potentially uncontaminated by analytes [A], while the second ran near a steel mill, a contaminated area [B]), each about 1.5 km long, located in Ozimek, Opole Province, Poland, were used in this study. Metals in plant and soil samples were determined by atomic absorption spectroscopy (AAS). Based on the analysis of the obtained results to determine the concentration of metals, plants at site A were more contaminated with Mn (240 mg/kg d.m.) and those at site B with Fe (635 mg/kg d.m.). Mean Pb values (8.39 mg/kg d.m.) were higher at the industrial site (B) and statistically significant at the forest site (A), together with Mn and Fe at the p < 0.001 level. The BCF values for T. officinale showed that Cu (0.473) and Zn (0.785) accumulated to an average degree on both transects. This shows that dandelion is heavily loaded with these metals. Both dandelion and soil samples showed the highest concentrations of Mn, Fe, and Zn, especially in the polluted area B, which is the result of pollution not only from the smelter (dust from electric arc furnaces in steel smelting, extraction installations in production halls transmitting pollutants into the air from molding sand, or waste from molding and core masses dumped on the heap and blown by the wind from the landfill) but also from the high anthropopressure caused by human activity—for example, heating processes or road transport. Our results confirmed that Taraxacum officinale can be successfully used as a herbal plant in passive biomonitoring to assess the quality of the environment, but it must be collected from uncontaminated areas if we want to use it like a medicinal plant. [ABSTRACT FROM AUTHOR]

The present paper reveals methodology of a research and the results of noise level measurements with respect to fluctuations of active power during EAF operation in one of the melt shops in Poland. In the current stage of experiment, the authors focused themselves on finding the optimum moment to start feeding of foaming material with the aim to obtain the most efficient slag foaming with the fastest coverage of electric arcs at the lowest losses of foaming material. Achieved results indicate that relation between the level of emitted noise and fluctuations of active power during melting can be utilised to define the moment to start feeding of slag foaming materials into the furnace. [ABSTRACT FROM AUTHOR]

Copyright of Chemical Industry / Hemijska Industrija is the property of Association of Chemical Engineers 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.)

The paper presents the results of studying the structure and properties of chrome-nickel cast iron samples obtained under production conditions. Cast iron with a given ratio of silicon and chromium smelted in an industrial arc furnace was treated with titanium carbide followed by modification with a complex modifier containing (Scanning electron microscope). As a result of the composition adjustment and appropriate processing, a mixed structure was formed represented by an austenite-ledeburite matrix, iron, chromium and titanium carbides and a small amount of free graphite, both lamellar and spherical. This structure is characterized by higher wear resistance and impact resistance compared to Nihard-2 but at the same time it shows lower hardness. [ABSTRACT FROM AUTHOR]

Innovative emission reduction technologies combined with optimized processes can effectively reduce the environmental pressure in the iron and steel industry (ISI). Identifying and comparatively analyzing the carbon emissions (CE) from steel productions is conducive to achieving China's ambitious carbon reduction targets. In this paper, we investigated two innovative routes: the shaft furnace-induction furnace-basic oxygen furnace route (SF-IF-BOF) and shaft furnace-electric smelting furnace-basic oxygen furnace route (SF-ESF-BOF), alongside two traditional routes: the blast furnace-BOF route (BF-BOF) and SF-electric arc furnace route (SF-ESF). The analysis was based on a functional unit of 1000 kg of crude steel (CS). By establishing the mass and energy balance models and decision criteria, 12 typical smelting scenarios for these routes were analyzed and compared in terms of materials consumption and CE. The results showed that increasing the proportion of scrap was beneficial for reducing CE. Under the condition of a 50% scrap ratio, the CE of the SF-IF-BOF, SF-ESF-BOF, BF-BOF, and SF-EAF routes were 768, 823, 946, and 870 kg, respectively. The SF-IF-BOF route displayed the most significant advantage of CE reduction. In addition, by using 100% zero-carbon electricity substitution, the SF-EAF route exhibited the greatest CE reduction effect of 41% (from 870 to 510 kg/t). While deploying 100% biomass fuels to replace coal, the CE of the BF-BOF route reduced by 80%. Finally, after introducing biomass fuels and zero-carbon electricity, the CE of the SF-IF-BOF route was minimized to a significantly low 13 kg/t (from 768), nearing zero CE. This research is expected to provide a novel solution for further CE reduction in the future of ISI, contributing to environmental sustainability and carbon reduction goals. • Suggestions for solutions to reduce CO2 emissions in the steel industry are provided. • Emissions of the SF-IF-BOF and SF-ESF-BOF compared to the BF-BOF and DRI-EAF routes. • DRI is considered to be generated using COG zero reforming process. • Using zero-C electricity and biomass can reduce CO2 emissions for the steel industry. [ABSTRACT FROM AUTHOR]

At present, the energy and environmental crisis is increasingly prominent, and how to solve the global energy and environmental problems is one of the challenges facing the world today. China is a major producer and consumer of organosilicon, so it is necessary to explore the stage of high energy consumption and high pollution in the organosilicon industrial chain. In 2022, the proportion of submerged arc furnaces of 25000 kVA and higher in China reached 40%. Further expansion of these furnaces in the future is inevitable. However, research on the life cycle assessment of organosilicon manufactured using large-capacity submerged arc furnaces is still blank.Therefore,in this paper, the life cycle assessment method is used to evaluate the synthesis process of chemical grade silicon-organosilicon monomer prepared by large capacity (33000 kVA) submerged arc furnace, and the dominant process in various environmental impacts is defined.At the same time, the measures to improve the production process of organosilicon monomer were put forward. In the production process of 1000 kg organosilicon monomer, global warming potential (GWP) contributed the most (73.43%) to the comprehensive environmental impact, followed by chronic public health impact (HTI, 10.55%). Energy consumption (EN) accounted for 8.50%, while resource consumption (RU) accounted for 7.43%. The contributions of other environmental factors were relatively small (0.09%).The energy consumption and environmental pollution in the production of organosilicon monomer can be reduced by strictly controlling the quality of raw materials into the furnace, using heat pump technology in the distillation unit, and comprehensively utilizing the heat of reaction by-products and steam condensate. [Display omitted] • This study is the first one in China to conduct LCA for the preparation of chemical grade silicon-organosilicon monomer synthesis process in 33000 kVA submerged arc furnace. It provides the best improvement suggestions for reducing the environmental load of the product life cycle process and achieving cleaner production. • In response to the national development policy of large-scale submerged arc furnace, the dominant process of preparing organosilicon monomer based on 33000 kva submerged arc furnace in various environmental impacts was clarified. • The main technical improvement directions are: Strictly control the quality of raw materials for submerged arc furnace; Strictly control the sulfur content and nitrogen content of carbonaceous reductant, and adopt the most suitable flue gas treatment technology route; Smelt with large submerged arc furnace; Use heat pump technology for distillation unit; Optimize the monomer synthesis device. [ABSTRACT FROM AUTHOR]

Hexachlorobutadiene (HCBD) is a concerning chemical that is included in the United States Toxic Substances Control Act, and the Stockholm Convention. Knowledge of the sources of HCBD is insufficient and is pivotal for accurate inventory and implementing global action. In this study, unintentional HCBD release and source emission factors of 121 full-scale industrial plants from 12 industries are investigated. Secondary copper smelting, electric arc furnace steelmaking, and hazardous waste incineration show potential for large emission reductions, which are found of high HCBD emission concentrations of > 20 ng/g in fine particulate matter in this study. The highest HCBD emission concentration is observed for the secondary copper smelting industry (average: 1380 ng/g). Source emission factors of HCBD for the 12 industries range from 0.008 kg/t for coal fire power plants to 0.680 kg/t for secondary lead smelting, from which an estimation of approximately 8452.8 g HCBD emissions annually worldwide achieved. The carcinogenic risks caused by HCBD emissions from countries and regions with intensive 12 industrial sources are 1.0-80 times higher than that without these industries. These results will be useful for formulating effective strategies of HCBD control. Recognition on sources of hexachlorobutadiene is needed for their global control. This study clarifies hexachlorobutadiene emission factors from 121 industrial plants assigned to 12 industries and establishes their global emission inventory. [ABSTRACT FROM AUTHOR]

With the shortage of fossil fuels and the increasingly serious problem of environmental pollution, low-carbon industrial production technology has become an effective way to reduce industrial carbon emissions. Electrified steel plants based on electronic arc furnaces (EAF) can reduce most carbon emissions compared with traditional steel production methods, but the production steps have fixed electricity consumption behavior, and impact loads are easily generated in the production process, which has an impact on the stability of the power system. EV has the characteristics of a mobile energy storage unit. When a large number of EVs are connected to the power grid, they can be regarded as distributed energy storage units with scheduling flexibility. Through the orderly scheduling of EVs, the spatial–temporal transfer of EV charging and discharging load can be realized. Therefore, the EV situated in the steel plant's distribution network node has the capacity to be utilized by providing peak shaving and valley filling services for the steel production load. This study proposes an operation optimization scheduling method for EVs and steel plants. Taking the lowest overall operating cost as the objective, an optimal scheduling model considering EVs operation, steel plant, and distributed generator is established. Based on the IEEE-33 node distribution network model considering distributed generators, the proposed model is simulated and analyzed, and the effectiveness of the EV steel plant operation optimization scheduling strategy is investigated. [ABSTRACT FROM AUTHOR]

The Waelz slag generated during electric arc furnace dust processing is an iron-rich product with significant amounts of iron, zinc and copper. About 600–800 kg of the Waelz slag is generated per ton of the dust processed. The Waelz slag samples from two different plants were thoroughly characterized using inductively coupled plasma optical emission spectroscopy (ICP-AES), X-ray diffraction analysis (XRD), chemical phase analysis, Mössbauer spectroscopy and other supporting methods. The phase distribution of iron, zinc and copper was determined in the Waelz slag samples. Low-intensity wet magnetic separation was tested for the iron recovery from the Waelz slag samples. It was found that the Waelz slag samples have complex chemical and mineralogical compositions, which can impede the selective recovery of valuable elements. The obtained results indicate that the chemical and mineralogical composition of the Waelz slag samples has a considerable effect on the magnetic separation indexes. The experiments showed that the iron concentrates with Fe contents of 73% and 46.8% with the metallization degrees of 87.2% and 57.5% and the iron recovery degree of 54.8% and 52.9% were obtained at optimal conditions for two different samples, respectively, without selective segregation of Cu and Zn in the magnetic or non-magnetic fraction. [ABSTRACT FROM AUTHOR]

TiZrTaNb-based high-entropy alloys (HEAs) are research frontier of biomedical materials due to their high hardness, good yield strength, excellent wear resistance and corrosion resistance. Sn, as an essential trace element in the human body that plays a significant role in physiological process. It has stable chemical properties and a low elastic modulus. In this study, a new material, TiZrTaNbSn HEAs, was proposed as a potential biomedical alloy. The Ti35Zr25Ta15Nb15Sn10 biomedical high-entropy alloys (BHEAs) were successfully prepared through an arc melting furnace and then remelted using a German high-temperature and high-pressure apparatus under GPa-level (4 GPa and 7 GPa). The precipitation behavior of the needle-like HCP-Zr5Sn3 phase that precipitates discontinuously at the grain boundary was successfully controlled. The phase constitution, microstructure, and corrosion resistance of the alloy were studied. The results show that the needle-like HCP-Zr5Sn3 phase is eliminated and the (Zr, Sn)-rich nanoprecipitated phase is precipitated in the microstructure under high pressure, which leads to the narrowing of grain boundaries and consequently improves the corrosion resistance of the alloy. In addition, the formation mechanisms of (Zr, Sn)-rich nanoprecipitates in BHEAs were discussed. More Zr and Sn dissolve in the matrix due to the effect of high pressure, during the cooling process, they precipitate to form a (Zr, Sn)-rich nano-precipitated phase. [ABSTRACT FROM AUTHOR]

Industrial process heating furnace operations consume considerable energy in the U.S. manufacturing sector, making it crucial to identify energy efficient strategies due to the growing need to minimize energy usage and emissions. It is important to identify the potential impact of these factors to enable process engineers to operate process heating systems at the maximum possible efficiency. This study examines and identifies the key impact factors that influence the efficiency of process heating systems using MEASUR (v1.4.0), the DOE software tools such as the insulation effectiveness, the burner stoichiometry, cooling medium, thermal storage, and atmospheric gases. Data from a two-fuel-fired heat treatment furnace and an electric arc furnace (EAF) for steelmaking were employed to establish the baseline heat balance models in MEASUR. The fractional factorial design experiment was developed with two-level parameter values and energy efficiency strategies for the heat input into industrial furnaces. The three most significant parameters for the heat input for a fuel-fired industrial furnace, Industrial Furnace A, are excess air percentage or the oxygen percentage in flue gas (OF), average surface temperature (ST), and combustion air temperature (CT). Similarly, for an electric industrial furnace, Industrial Furnace B, the parameters are charge temperature (CHT), average surface temperature (ST), and time open (TO). A comparative analysis was carried out for the fuel-fired and equivalent electric resistance furnaces to identify the prospect of electrification of industrial furnaces relying upon fossil fuels. The study aims to assist industries and designers in making informed decisions regarding industrial furnace upgrades, process optimization, and maintenance investments, resulting in substantial energy and cost savings, and a reduced environmental impact. [ABSTRACT FROM AUTHOR]

The iron and steel industry significantly contributes to global energy use and greenhouse gas emissions. The rising deployment of volatile renewables and the resultant need for flexibility, coupled with specific challenges in electric steelmaking (e.g., operation optimization, optimized power purchasing, effective grid capacity monitoring), require accurate energy consumption and demand forecasts for electric steel mills to align with the energy transition. This study investigates diverse approaches to forecast the energy consumption and demand of an electric arc furnace—one of the largest consumers on the grid—considering various forecast horizons and objectives with limited knowledge on process parameters. The results are evaluated for accuracy, robustness, and costs. Two grid connection capacity monitoring approaches—a one-step and a multi-step Long Short-Term Memory neural network—are assessed for intra-hour energy demand forecasts. The one-step approach effectively models energy demand, while the multi-step approach encounters challenges in representing different operational phases of the furnace. By employing a combined statistic–stochastic model integrating a Seasonal Auto-Regressive Moving Average model and Markov chains, the study extends the forecast horizon for optimized day-ahead electricity procurement. However, the accuracy decreases as the forecast horizon lengthens. Nevertheless, the day-ahead forecast provides substantial benefits, including reduced energy balancing needs and potential cost savings. [ABSTRACT FROM AUTHOR]