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Decarbonization and decontamination of the iron and steel industry (ISI), which contributes up to 15% to anthropogenic CO2 emissions (or carbon emissions) and significant proportions of air and water pollutant emissions in China, are challenged by the huge demand for steel. Carbon and pollutants often share common emission sources, indicating that emission reduction could be achieved synergistically. Here, we explored the inherent potential of measures to adjust feedstock composition and technological structure and to control the size of the ISI to achieve carbon emission reduction (CER) and pollution emission reduction (PER). We investigated five typical pollutants in this study, namely, petroleum hydrocarbon pollutants and chemical oxygen demand in wastewater, particulate matter, SO2, and NOx in off gases, and examined synergies between CER and PER by employing cross elasticity for the period between 2022 and 2035. The results suggest that a reduction of 8.7%–11.7% in carbon emissions and 20%–31% in pollution emissions (except for particulate matter emissions) could be achieved by 2025 under a high steel scrap ratio (SSR) scenario. Here, the SSR and electric arc furnace (EAF) ratio serve critical roles in enhancing synergies between CER and PER (which vary with the type of pollutant). However, subject to a limited volume of steel scrap, a focused increase in the EAF ratio with neglection of the available supply of steel scrap to EAF facilities would lead to an increase carbon and pollution emissions. Although CER can be achieved through SSR and EAF ratio optimization, only when the crude steel production growth rate remains below 2.2% can these optimization measures maintain the emissions in 2030 at a similar level to that in 2021. Therefore, the synergistic effects between PER and CER should be considered when formulating a development route for the ISI in the future.

Steel scraps are renewable resources and indispensable iron resources for the iron and steel industry. In the context of carbon peaking and carbon neutrality, it is crucial to reconstruct the technology system for steel scrap recycling and utilization and innovate the management mode of steel scrap resources, so as to fundamentally crack the bottleneck of high-quality recycling and utilization of steel scraps for the green and low-carbon transformation of the iron and steel industry. This study analyzes the development status of the global steel scrap industry by comparison, predicts the changing trend of raw steel output and steel scrap resources in China, and proposes the possible existence of full steel scrap smelting in China around 2060. Moreover, the development directions of standardization, informatization, digitalization, and intelligentization of the steel scrap industry are summarized. The pressing problems and challenges regarding steel scrap recycling and utilization in China are systematically sorted out in terms of standards and institutional system, precise classification and recycling, material design based on extended producer responsibility (EPR), and digital identity parsing. On this basis, a new “4F5Z” pattern is innovatively proposed for the high-quality recycling and utilization of steel scrap resources, and its organizational framework and implementation strategy are clearly given. Specifically, the EPR system should be implemented in a coordinated manner toward a possible era of full steel scraps and from the aspects of the full life cycle, full production process, and full industrial chain (“4F”) of steel materials, thus to realize the sorted management, recycling, and reuse of steel scrap resources. Meanwhile, the digitalization, informatization, labelling, and networking of full production process management should be strengthened and gradually transition to the robotization of high-quality steel scrap dismantling and recycling (“5Z”). Furthermore, to provide a solid guarantee for the full implementation of the “4F5Z” pattern, we propose the following suggestions: (1) improving the system, technology, and management for EPR implementation in the iron and steel industry, (2) strengthening the construction of a standards system for the steel scrap industry, (3) strengthening the digital labelling and analysis of the entire industrial chain and the whole life cycle of iron and steel materials, and (4) reinforcing the sorted collection, recycling, and reuse of steel scraps in key industries.

Scrap steel serves as the primary alternative raw material to iron ore, exerting a significant impact on production costs for steel enterprises. With the annual growth in scrap resources, concerns regarding traditional manual inspection methods, including issues of fairness and safety, gain increasing prominence. Enhancing scrap inspection processes through digital technology is imperative. In response to these concerns, we developed CNIL-Net, a scrap-quality inspection network model based on object detection, and trained and validated it using images obtained during the scrap inspection process. Initially, we deployed a multi-camera integrated system at a steel plant for acquiring scrap images of diverse types, which were subsequently annotated and employed for constructing an enhanced scrap dataset. Then, we enhanced the YOLOv5 model to improve the detection of small-target scraps in inspection scenarios. This was achieved by adding a small-object detection layer (P2) and streamlining the model through the removal of detection layer P5, resulting in the development of a novel three-layer detection network structure termed the Improved Layer (IL) model. A Coordinate Attention mechanism was incorporated into the network to dynamically learn feature weights from various positions, thereby improving the discernment of scrap features. Substituting the traditional non-maximum suppression algorithm (NMS) with Soft-NMS enhanced detection accuracy in dense and overlapping scrap scenarios, thereby mitigating instances of missed detections. Finally, the model underwent training and validation utilizing the augmented dataset of scraps. Throughout this phase, assessments encompassed metrics like mAP, number of network layers, parameters, and inference duration. Experimental findings illustrate that the developed CNIL-Net scrap-quality inspection network model boosted the average precision across all categories from 88.8% to 96.5%. Compared to manual inspection, it demonstrates notable advantages in accuracy and detection speed, rendering it well suited for real-world deployment and addressing issues in scrap inspection like real-time processing and fairness. [ABSTRACT FROM AUTHOR]

There has been remarkable progress in the field of Deep Learning and Computer Vision, but there is a lack of freely available labeled data, especially when it comes to data for specific industrial applications. However, large volumes of structured, semi-structured and unstructured data are generated in industrial environments, from which meaningful representations can be learned. The effort required for manual labeling is extremely high and can often only be carried out by domain experts. Self-supervised methods have proven their effectiveness in recent years in a wide variety of areas such as natural language processing or computer vision. In contrast to supervised methods, self-supervised techniques are rarely used in real industrial applications. In this paper, we present a self-supervised contrastive learning approach that outperforms existing supervised approaches on the used scrap dataset. We use different types of augmentations to extract the fine-grained structures that are typical for this type of images of intrinsically unordered items. This extracts a wider range of features and encodes more aspects of the input image. This approach makes it possible to learn characteristics from images that are common for applications in the industry, such as quality control. In addition, we show that this self-supervised learning approach can be successfully applied to scene-like images for classification.

A circular steel economy based on recycling scrap is severely hampered by the increasing accumulation of Cu returning from more and more electrified products, which severely limits processing, application, and safety of steels. As of yet, no viable strategies for its removal have been developed, and the increasing Cu contamination can only be diluted with fresh primary iron. This is not only evoking CO2 emissions from conventional reduction processes, but also merely delays the problem until global demands allow for a circular steel economy. However, the ongoing transformation toward green steel making may offer pathways to overcome this complex metallurgical challenge. It is demonstrated that Cu can be effectively evaporated from Fe–Cu–O melts—representing Fe ore mixed with Cu‐contaminated steel scrap—during hydrogen plasma‐based smelting reduction. This evaporation is found to be strongly influenced by the Cu activity determined by the concentration of oxygen in the liquid, with a critical O concentration of about 22 wt%. Even without the presence of hydrogen, Cu concentrations can thereby be drastically reduced from 1 to less than 0.1 wt%. Potentials and challenges for leveraging these fundamental findings on a laboratory scale for future industrial production of green steel are outlined and discussed. [ABSTRACT FROM AUTHOR]

In this work, an object detection method using variable convolution-improved YOLOv8 is proposed to solve the problem of low accuracy and low efficiency in detecting spanning and irregularly shaped samples. Aiming at the problems of the irregular shape of a target, the low resolution of labeling frames, dense distribution, and the ease of overlap, a deformable convolution module is added to the original backbone network. This allows the model to deal flexibly with the problem of the insufficient perceptual field of the target corresponding to the detection point, and the situations of leakage and misdetection can be effectively improved. In order to solve the issue that small target detection is susceptible to image background and noise interference, the Sim-AM (simple parameter-free attention mechanism) module is added to the backbone network of YOLOv8, which enhances the attention to the underlying features and, thus, improves the detection accuracy of the model. More importantly, the Sim-AM module does not need to add parameters to the original network, which reduces the computation of the model. To address the problem of complex model structures that can lead to slower detection, the spatial pyramid pooling of the backbone network is replaced with focal modulation networks, which greatly simplifies the computation process. The experimental validation was carried out on the scrap steel dataset containing a large number of targets of multiple shapes and sizes. The results showed that the improved YOLOv8 network model improves the AP (average precision) by 2.1%, the mAP (mean average precision value) by 0.8%, and reduces the FPS (frames per second) by 5.4, which meets the performance requirements of real-time industrial inspection. [ABSTRACT FROM AUTHOR]

The mechanical properties of structural steel rebar are a very important factor for durable, sustainable, and resilient design of reinforced concrete structures. In developing countries, steel rebars are often manufactured from unsegregated steel scrap using manual rolling mill, which affects the quality of the final manufactured product and raises several concerns. Various earlier studies have been conducted on controlling the quality of steel rebar in various countries, yet quality issues of steel rebar are still pending in local industry. Therefore, this study aims to explore the mechanical properties of steel rebar manufactured with steel scrap having various chemical composition at different finishing rolling temperatures (FRT). Steel rebars were manufactured at an industrial kiln using various carbon contents (0.25%, 0.27% and 0.30%), replicating full-scale scenarios. Specimens for each type of steel were manufactured at FRT of 640⁰C, 680⁰C, 720⁰C, 760⁰C and 800⁰C. Various tests including tension, bending, hardness and microstructural examination were performed on the manufactured steel rebars. It was observed that by increasing the FRT, the average grain size in the steel rebar increased, leading to a decrease of the ultimate tensile strength, yield strength, and hardness. Conversely, the elongation and modulus of toughness increased with the increase in the average grain size due to a decrease in total grain boundary area owing to lower resistance to dislocation motion. By increasing the carbon content, inter-lamellar spacing between cementite strips in pearlite decreased, which increased the hardness, ultimate tensile strength, and yield strength, whereas the elongation and modulus of toughness decreased. The weight per unit length, yield, and ultimate strengths of the tested rebars satisfied the ASTM A615 limits. This study educates the local rolling mills stakeholders about possible causes of variations in mechanical properties of locally manufactured steel rebar and suggests solutions towards proper monitoring and mitigating harmful effects. The main findings of this study highlight that the manufacturing of rebars from scrap at various FRT affects the stress-strain behavior of steel rebar and its overall structural stability. Moreover, microstructural analysis assists in understanding the role of FRT on yield and ultimate strengths of rebars due to changes in the average grain size.

The current nature of steel design and production is a response to meet increasingly demanding applications but without much consideration of end-of-life scenarios. The scrap handling infrastructure, particularly the characterization and sorting, is unable to match the complexity of scrapped products. This is manifested in problems of intermixing and contamination in the scrap flows, especially for obsolete scrap. Also, the segmentation of scrap classes in standards with respect to chemical compositions is based on tolerance ranges. Thus, variation in scrap composition exists even within the same scrap type. This study applies the concept of expected value of perfect information (EPVI) to the context of steel recycling. More specifically, it sets out to examine the difference between having partial and full information on scrap composition by using a raw material optimization software. Three different scenarios with different constraints were used to appraise this difference in terms of production and excess costs. With access to perfect information, production costs decreased by 8–10%, and excess costs became negligible. Overall, comparing the respective results gave meaningful insights on the value of reestablishing the compositional information of scrap at the end of its use phase. Furthermore, the results provided relevant findings and contribute to the ongoing discussions on the seemingly disparate prioritization of economic and environmental incentives with respect to the recycling of steel. [ABSTRACT FROM AUTHOR]

In this work, an object detection method using variable convolution-improved YOLOv8 is proposed to solve the problem of low accuracy and low efficiency in detecting spanning and irregularly shaped samples. Aiming at the problems of the irregular shape of a target, the low resolution of labeling frames, dense distribution, and the ease of overlap, a deformable convolution module is added to the original backbone network. This allows the model to deal flexibly with the problem of the insufficient perceptual field of the target corresponding to the detection point, and the situations of leakage and misdetection can be effectively improved. In order to solve the issue that small target detection is susceptible to image background and noise interference, the Sim-AM (simple parameter-free attention mechanism) module is added to the backbone network of YOLOv8, which enhances the attention to the underlying features and, thus, improves the detection accuracy of the model. More importantly, the Sim-AM module does not need to add parameters to the original network, which reduces the computation of the model. To address the problem of complex model structures that can lead to slower detection, the spatial pyramid pooling of the backbone network is replaced with focal modulation networks, which greatly simplifies the computation process. The experimental validation was carried out on the scrap steel dataset containing a large number of targets of multiple shapes and sizes. The results showed that the improved YOLOv8 network model improves the AP (average precision) by 2.1%, the mAP (mean average precision value) by 0.8%, and reduces the FPS (frames per second) by 5.4, which meets the performance requirements of real-time industrial inspection.

This paper examines the centuries-long history of the castle Kamenica, situated above the identically named settlement in the Croatian Zagorje region, not far from Lepoglava. It was first mentioned in writing in 1311. It was built in the second half of the 13th century at the latest, by an unknown Zagorje noble, as a fortified residence and centre of the identically named estate. Between 1399 and 1405, Kamenica became the property of Herman II of Celje, whose descendants held it until 1456. Although no source directly mentions the fall of Kamenica, it likely happened during the war for the Celje succession, and the castle was first mentioned as a ruin in 1459, when King Matthias Corvinus donated it to John Vitovac. During the time it was under the Vitovacs (1459–88), Kamenica was permanently abandoned, and its holdings were combined with the neighbouring Trakošćan estate into the joint Trakošćan-Kamenica estate, which was formally seated in Trakošćan, but factually in the fortified manor Klenovnik. The existing, meagre architectural elements suggest Kamenica was a small castle (castrum) dating from the second half of the 13th century. It consisted of a trapezoidal core at the top of a steep, conical eminence, formed of a walled, fortified house with a smallish courtyard protected by a wooden palisade, and a fortified, circular suburb, raised around the core with a combination of wooden palisades and earthen ramparts.

Increasing the use of steel scrap and enhancing its recycling utilization are important strategies for fostering the low-carbon and environmental-friendly growth of the iron and steel industry in China. However, the current steelmaking processes cannot efficiently remove the residual elements in the scrap, such as Cu, Sn, As, and Sb. As a result, the above elements are recycled and accumulate in the scrap, which will eventually have a negative impact on the properties of steel. Currently, there are few studies on Sb removal from molten steel. To remove the residual element Sb in molten steel, the CaO-SiO2-Al2O3 refining slag system containing CaC2 was used, and the effect of the CaC2 content in the molten slag, slag quantity, smelting temperature, and initial Sb and C contents in molten steel on the Sb removal ratio in the steel was investigated, and the mechanism of Sb removal by the aforementioned refining slag system was discussed in order to provide some experimental and theoretical basis for industrialization practice. When the smelting time is 5~10 min, the removal ratio of Sb from molten steel is at its peak and can reach 45.8%. The "Sb-reversion" phenomenon will appear in the molten steel when the smelting period is progressively extended. In molten steel, CaC2 will preferentially react with O and S, and as the smelting temperature decreases, the distribution ratio of Sb, LSb, improves. An increased initial Sb content in molten steel and slag quantity are beneficial to improving the removal ratio of Sb, but an increased initial C content in molten steel is detrimental to the progress of the Sb removal reaction. The removal reaction of Sb from molten steel by CaC2 is a reversible reaction, and the diffusion of the products from the interface is the limiting factor of the overall reaction. [ABSTRACT FROM AUTHOR]

In the field of metallurgy, there are many factors that influence the final quality of cast iron. These are mainly charge materials, chemical composition and metallurgical preparation up to the final casting process. Even small deviations from metallurgical processing lead to fluctuations in melt quality and the occurrence of casting defects. Charge materials have a significant impact on the quality of cast iron, especially steel scrap, which is increasingly used from an economic and ecological point of view, especially when melting cast iron in electric furnaces. Cast iron produced from a higher proportion of steel scrap in the charge has a higher hardness and tensile strength. On the other side, these cast irons have a higher tendency of chillout, brittleness, shrinkage, pearlitic microstructure, stresses and higher purity due to the difference in hardness at different wall thicknesses of the castings. It is the high hardness that is the problem in the final machining of castings. These negative properties are recorded mainly in heavy thick-walled castings with a higher tensile strength and hardness. This negative effect is mainly due to the nitrogen content in the steel scrap. Based on this knowledge, operating melts were realized in the foundry's operating conditions. The influence of steel scrap in the charge and the possibility of eliminating its negative effects on the properties of cast iron were investigated. [ABSTRACT FROM AUTHOR]

• Difficulties related to uncertainty of input is addressed with more information. • With the right compositional information, steelmaking can be fully scrap-based. • Perfect information on scrap chemistry increases scrap utilization. • More scrap in a production heat saves on valuable alloys. Uncertainties with respect to the chemical composition of scrap limit its suitability as an input to recycling. This study offers an alternative approach in dealing with this concern and explores the hypothetical case where this uncertainty is nonexistent. The effect of fully knowing the scrap composition is simulated using an optimization software adopted to scrap-based, stainless-steel production. Through the systematic implementation of this information-driven model in the studied cases, the results suggest that with access to perfect information, recycling incentives can be realized. Essentially, the steel scraps' consumption increased since it was possible to select and combine scrap quantities with varying composition profiles to achieve the targeted product compositions. This also meant that elements already in the scrap were allocated in a manner that was less dependent on pure alloy additions. Being able to demonstrate the value of information on scrap composition could rationalize upgrades on current scrap management systems. [ABSTRACT FROM AUTHOR]

This paper shows the trend of the world crude steel production in the first two decades of the 21st century. From 2000 to 2020, the world steelmaking continuously increased (total production of 28.5 billion t steel), but decreased in 2008 (1,6 %) and 2009 (7,7 %) because of the global financial and economic crises. For more than fifty years, the primary steelmaking processes are those by means of two technologies: oxidation of pig iron (product from blast furnace) in basic oxygen converters by means of technical oxygen, and smelting of old ferrous (steel scrap) in the electro arc furnaces. For the production of quality steel, the secondary metallurgy procedures (treatment of steel in ladle) play a greater role. In 2000, global steel production was 847.2 million t (basic oxygen converters share was 58.2 % and the electro arc furnaces 33.8 %), while in 2020, production reached 1.8775 billion t steel, which is an increase of 2.2 times. By 2020, the production of steel by steelmaking processes was 73.2 % by basic oxygen converters, 26.3 % by electro arc furnaces, 0.3 % by Siemens-Martin furnaces, and 0.2 % by other procedures of steel production. Primacy in steelmaking is in countries and companies from Asia (73.9 % of the world’s output). The recycling degree of steel in the period from 2011 to 2019 was 34–37 %. China is the largest world steelmaking country (since 1996). China had an increase in steelmaking of 8.3 times in the period from 2000 to 2020 (from 127.2 Mt up to 1.064 Gt). China produced 56.6 % of the world’s steel. From 2000 to 2020, a share of continuous casting was increased by about 10 % (from 87 to 96.6 %). [ABSTRACT FROM AUTHOR]

Steel scrap melting kinetics is a key factor that affects the scrap ratio and temperature trajectory of Basic Oxygen Furnace steelmaking process and the productivity and energy utilization of Electric Arc Furnace steelmaking process. In this paper, the interface between steel scrap and melt is analyzed and a novel theoretical model of steel scrap melting in iron-carbon bath is established. Moreover, the effects of bath temperature, bath carbon content, preheating temperature and characteristic length of steel scrap on the melting rate of steel scrap, mass transfer coefficient of carbon, heat transfer coefficient and interface carbon concentration were investigated. The results show that the ultimate steady melting rate increases from −2.04 × 10−4 to −3.32 × 10−3 m/s with the increases of bath temperature from 1793 K to 1873 K, the ultimate steady heat and mass transfer coefficient first increase and subsequently decrease, are in the range of 1.04 × 105 to 2.86 × 105 W/m2/K and 0 to 2.89 × 10−4 m/s, respectively. As the bath carbon content increase from 1.0 wt% to 4.0 wt%, the ultimate steady melting rate increases from −8.85 × 10−5 to −3.23 × 10−4 m/s, the ultimate steady heat transfer coefficient first increases and subsequently decreases, is in the range of 7.59 × 104 to 1.01 × 105 W/m2/K. Furthermore, the ultimate steady mass transfer coefficient and the ultimate steady interface carbon content gradually decreases from 1.40 × 10−4 to 5.21 × 10−5 m/s and from 0.73 to 0.69 wt%, respectively. With the increase of preheating temperature and characteristic length of steel scrap, the ultimate steady melting rate, heat transfer coefficient between steel scrap and melt, mass transfer coefficient and interface carbon concentration remain almost constant, about −8.85 × 10−5 m/s, 8.40 × 104 W/m2/K, 1.40 × 10−4 m/s and 0.70 wt%, respectively.

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Increasing the use of steel scrap and enhancing its recycling utilization are important strategies for fostering the low-carbon and environmental-friendly growth of the iron and steel industry in China. However, the current steelmaking processes cannot efficiently remove the residual elements in the scrap, such as Cu, Sn, As, and Sb. As a result, the above elements are recycled and accumulate in the scrap, which will eventually have a negative impact on the properties of steel. Currently, there are few studies on Sb removal from molten steel. To remove the residual element Sb in molten steel, the CaO-SiO2-Al2O3 refining slag system containing CaC2 was used, and the effect of the CaC2 content in the molten slag, slag quantity, smelting temperature, and initial Sb and C contents in molten steel on the Sb removal ratio in the steel was investigated, and the mechanism of Sb removal by the aforementioned refining slag system was discussed in order to provide some experimental and theoretical basis for industrialization practice. When the smelting time is 5~10 min, the removal ratio of Sb from molten steel is at its peak and can reach 45.8%. The ”Sb-reversion” phenomenon will appear in the molten steel when the smelting period is progressively extended. In molten steel, CaC2 will preferentially react with O and S, and as the smelting temperature decreases, the distribution ratio of Sb, LSb, improves. An increased initial Sb content in molten steel and slag quantity are beneficial to improving the removal ratio of Sb, but an increased initial C content in molten steel is detrimental to the progress of the Sb removal reaction. The removal reaction of Sb from molten steel by CaC2 is a reversible reaction, and the diffusion of the products from the interface is the limiting factor of the overall reaction.

In the field of metallurgy, there are many factors that influence the final quality of cast iron. These are mainly charge materials, chemical composition and metallurgical preparation up to the final casting process. Even small deviations from metallurgical processing lead to fluctuations in melt quality and the occurrence of casting defects. Charge materials have a significant impact on the quality of cast iron, especially steel scrap, which is increasingly used from an economic and ecological point of view, especially when melting cast iron in electric furnaces. Cast iron produced from a higher proportion of steel scrap in the charge has a higher hardness and tensile strength. On the other side, these cast irons have a higher tendency of chillout, brittleness, shrinkage, pearlitic microstructure, stresses and higher purity due to the difference in hardness at different wall thicknesses of the castings. It is the high hardness that is the problem in the final machining of castings. These negative properties are recorded mainly in heavy thick-walled castings with a higher tensile strength and hardness. This negative effect is mainly due to the nitrogen content in the steel scrap. Based on this knowledge, operating melts were realized in the foundry’s operating conditions. The influence of steel scrap in the charge and the possibility of eliminating its negative effects on the properties of cast iron were investigated.

Virtually all large ships are recycled today on the beaches of Asia. The United Kingdom was once the world's biggest shipbreaker, but its industry had dwindled to virtual extinction by 1995. Why did the UK industry decline and conversely, given its problems, how did it in fact survive as long as it did? No significant study has been done previously of the UK industry as a whole and therefore reliance has been placed on primary sources. UK shipbreaking boomed from 1946 to 1962 as throughout this period UK ships were generally only broken up in the UK. European shipbreakers lasted a few years longer than their UK counterparts because arguably the UK had been cosseted too much by both home market protection and steel industry support. [ABSTRACT FROM AUTHOR]

The purpose of this study is to examine the variables that influence both the Circular Economy (CE) and pro-environmental behavior in steel recycling manufacturing companies in Thailand. To develop and examine a model using structural equation modeling (SEM), we used a set of CE indicators proposed in previous studies. The variables identified in this study were determined through responses from stakeholders in the steel manufacturing and scrap management industries. A questionnaire-based survey was used to analyze the study target's (foundries, castings, and steel recycling manufacturers) behavior. Respondents contended that they value long-term relationships with suppliers. Quality control has a sizable impact on lean manufacturing techniques. Recycling costs and environmental concerns both have an effect on how behavioral control is perceived. It is critical for society to be educated about the circular economy and its practices. Environmental commitment is the most critical factor in the circular economy's success. The findings indicate that the most significant influence on the Circular Economy is the social willingness to recycle (CE). The study investigates the relationship between social willingness to recycle (SWR) and lean manufacturing techniques (LMT) and the success of circular economy practices. Environmentally responsible behavioral practices both promote and contribute to high levels of productivity. The CE's promotion is critical in light of the current trend toward globalization. We propose that steel manufacturers must continue to innovate in technical or non-technical ways, most notably through the use of efficient equipment such as pre-shredders, shredders, and power plants that accelerate long-term mineral resource savings.

Three melts of ferrite-pearlitic nodular cast iron with different charge composition were used for fatigue tests. Wöhler fatigue curves and fatigue strength were obtained, and microstructure and fracture surfaces were investigated. The aim of the paper is to determine the influence of charge composition on microstructure, mechanical and fatigue properties of synthetic nodular cast irons and their micromechanisms of failure. Fatigue tests were realised at low frequency sinusoidal cyclic push-pull loading (stress ratio R = −1) at ambient temperature (T = 20 ±5°C). They were carried out with using the fatigue experimental machine Zwick/Roell Amsler 150HFP 5100 at frequency f ≈ 120 Hz. The results of fatigue tests at low frequency cyclic loading are compared with fatigue properties at high frequency cyclic loading.

Steel and cast-iron products, due to their low price and beneficial properties, are the most widely used among metals, their consumption has become an indicator of the economic development of countries. The characteristics of iron raw materials, in relation to current metallurgical requirements, are presented in the present this article. The globalization of the trade and development of steelmaking technologies have caused significant changes in the quality of raw materials in the last half-century, forcing improvements in processing technologies. In many countries, standard concentrates (at least 60% Fe) are almost twice as rich as those processed in the mid-20th century. Methods of quality assessment have been improved and quality standards tightened. The quality requirements for the most important raw materials - iron ores and concentrates, steel scrap, major alloy metals, coking coal, and coke, as well as gas and other energy media - are reviewed in the present paper. Particular attention is paid to the quality testing methodology. The quality of many raw materials is evaluated multi-parametrically: both chemical and physical characteristics are important. Lower-quality parameters in raw materials equate to significantly lower prices obtained by suppliers in the market. The markets for these raw materials are diversified and governed by separate sets of newly introduced rules. Price benchmarks (e.g. for standard Australian metallurgical coal) or indices (for iron concentrates) apply. Some raw materials are quoted within the framework of the commodity market system (certain alloying components and steel scrap). The abandonment of the long-established system of multi-annual contracts has led to wide fluctuations in prices, which have reached a scale similar to that of other metals. [ABSTRACT FROM AUTHOR]

The article presents the research results of omitting the steel scrap component from the production process of synthetic gray cast iron. The quality of synthetic iron produced in electric induction furnaces (EIF) is influenced by numerous factors. Its characteristic attributes are high values of mechanical properties (Rm, HB), but also its tendency to form chill out and shrinkages, foundry stress and sensitivity to hardness change at different casting wall thicknesses. Possibilities of offsetting and eliminating such negative effects were tested by introducing metallurgical countermeasures based on the properties of flake graphite alloys.

The current study deals with optimizing the melting process used in electric arc furnace by heat balance equations. Heat balance is a very important aspect in an arc furnace in which the energy input consists of electrical energy [65%], chemical energy [25%] and exothermic reaction heat [10%]. This energy is optimized with the charge mix, charge quantity, fluxes, fuel used, and O2 used in the burners. The present model considers all these aspects and gives heat distribution in the process. The model spreadsheet gives a reasonable prediction in terms of metal yield, composition, and energy consumption. The model also predicts the amount of iron oxidized in the process. The mass and heat balance model is a useful tool for process analysis and improves the process efficiency of electric arc furnace steelmaking.

Besides iron ore, the main raw material of iron and steel production is steel scrap. This paper presents the quality and sources of creation the iron and steel scrap and estimation of their creation in the future. The content of impurities and trace elements to the scrap is very important and influencing to the quality of the obtained steel. Alloyed steel scrap known composition can often be used as an addition to a metal charge for steel production of the desired composition. Considering the steel scrap formation, the three major groups are elaborated: own scrap or circulation scrap, processing scrap and amortization scrap. The balancing model for estimating of steel scrap creation is based on the calculating the coefficients of the generation circulation, processing and amortization scrap, which are used as the basis for successful modelling.

An experimental investigation is carried out on the strength of lathe waste concrete and behaviour of lathe waste in concrete beams. The lathe waste which is occurred in the powdered form as a raw material which is used in the concrete cubes, cylinders and beams. The Concrete mixes are tested for its compressive strength, split tensile strength and Flexural Strength. The beams were tested for the deflection and cracking. Due to the addition of lathe waste, the powdered form of steel waste when added along with the concrete which tends to attain more strength of the concrete, when compared with the normal conventional concrete. The addition of lathe waste takes place by the percentage of the lathe waste 0%,1%,1.5%,2%,2.5% and tested for its strength and deflection. [ABSTRACT FROM AUTHOR]

This study analyses the impact of the rising availability of steel scrap on the future steel production up to the year 2100 and implications for steel production capacity planning. Steel production processes are energy, resource, and emission intensive, but there are significant variations due to different production routes, product mixes, and processes. This analysis is based on the development of steel demand, using the Steel Optimization Model, which provides a region-detailed representation of technologies, energy and material flows, and trade activities. It is linked to the Scrap Availability Assessment Model which estimates the theoretical steel scrap availability. Aggregated crude steel production is estimated to evolve into an almost balanced split by 2050 between the primary production route using iron ore in the blast oven furnace and the secondary route using mostly steel scrap in the electric arc furnace. By 2060, the share of secondary steel production will exceed the share of primary steel production globally. The results also estimate a global increase in scrap use from 611 Mtonnes in 2015 to 1500 Mtonnes in 2050, with the highest growth being for post-consumer scrap. In 2050, almost 50% of post-consumer scrap is expected to be traded, with the main exporter being China and major importing regions being Africa, India, and other developing Asian countries. The results provide valuable insights on scrap availability and capacity development at the regional level for producers contemplating new investments. Regional availability, quality, and trade patterns of scrap will influence production route choices, possibly in favor of secondary routes. Also, policy instruments such as carbon taxation may affect investment choices and favor more energy-efficient and less carbon-intensive emerging technologies. [ABSTRACT FROM AUTHOR]

The present paper reports fabrication of superior steel compact using nanostructured steel powder generated from industrial steel scrap. Extra low carbon and low carbon steel powders with size of submicron were generated from industrial waste by planetary milling for 5 h. The milled powders are characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) and hardness. Finest particles are obtained after 3 h of milling in both cases. In case of extra-low carbon steel, cold welding and agglomeration is observed after 5 h of milling. However, in case of low carbon steel, no such phenomenon is visible after 5 h of milling. The effect of ball to powder weight ratio (BPR) is studied using BPR of 12:1 and 6:1 for low carbon steel chips by milling for 3 h. A higher yield of 94.29% is obtained when milling conducted at BPR 12:1 than 86.94% yield at BPR 6:1 after milling low carbon steel for 3 h. Lower average particle size of 5–10 μm is obtained when milling is carried out at BPR 12:1 than 15–20 μm at BPR 6:1. In case of low carbon steel, % yield increases from 94.29% to 99.14% as milling time increases from 3 to 5 h. Yttria free and 1 wt% yttria dispersed both extra-low carbon and low carbon steel powders are cold compacted and conventionally sintered at 1100 °C for 1 h. Significant improvement in the hardness was achieved through addition of small amount of yttria with both the steel powder generated from the steel scrap. [ABSTRACT FROM AUTHOR]

To investigate the potential of energy saving and emissions mitigation during 2015–2050 in China’s iron and steel industry (CISI), a comprehensive assessment approach was developed and applied on the basis of the dynamic Material Flow Analysis (MFA) model and the energy consumption and carbon dioxide (CO 2 ) emission model. Four scenarios including the business-as-usual (BAU) scenario, the structure adjustment (STA) scenario, the energy-efficiency improvement (EEI) scenario, and the strengthened policy (STP) scenario have been set to describe future energy saving and carbon mitigation strategies in relation to the development of the iron and steel industry. The modeling results show that China’s steel demand will gradually decrease from 789.35 Mt in 2013 to 440.38 Mt in 2043 and will stabilize at around 450 Mt, and the scrap resources are sufficient to support the promotion of the production structure under all four scenarios. The results also indicate that energy consumption and CO 2 emissions will gradually decline under the synergistic effect of technology promotion and structure adjustment during the period. In the short term, they will depend more on technology improvement; in the long term, particularly after 2040, promotion of the production structure adjustment will be the main force. The selected 35 energy saving technologies (ESTs) contribute to 3.01 GJ/t and 398.22 kg CO 2 /t crude steel when the discount rate of 15% is applied. [ABSTRACT FROM AUTHOR]

The deep decarbonization of the iron and steel industry (ISI) is essential for fulfilling the goal of global net-zero emissions. Existing studies for the multiple transition possibilities and competition of production technologies driven by the variable socioeconomic changes and the deployment of innovative technologies are scarcely discussed before. In this study, we build a dynamic modeling framework to track technological evolution and characterize the carbon neutrality pathways in China's ISI. We project that China's steel demand will decrease, while the scrap available for steel production will grow. Over the 40-year period, the steelmaking process will transform from blast furnace-basic oxygen furnaces (BF-BOFs) to scrap-based electric arc furnaces (scrap-EAFs) and hydrogen-based direct reduced iron electric arc furnaces (DRI-EAFs), and BF-BOFs can be completely phased out by 2060. CO 2 emissions are expected to fall 63%–73% by 2060 in relation to the 2020 level. Production structural adjustment is the most effective measure. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper analysed CO 2 emission pathways for the Japanese iron and steel industry towards 2030, taking into account the likely development of process capacities that could flexibly adapt to a range of projected future crude steel production levels (“optimal capacities”) while maintaining minimum capacity utilisation rates. Coke and pig iron production capacities were optimised to the levels that enable flexible operation for 90–120 Mt-crude steel/y, compared to 110 Mt/y in 2010. Operational constraints were applied to the capacity utilisation rates (minimum of 85%) and the maximum use of coke and pig iron substitutes. This paper also assessed the implications of the aforementioned flexible operation across a range of crude steel production levels on the future scrap balances. This study calculated the optimal capacities for coke ovens and blast furnaces in 2030 to be 29 Mt-coke/y (compared to 43 Mt/y in 2010) and 83 Mt-pig iron/y (compared to 90 Mt/y in 2010). Under these optimal capacities and the aforementioned range for crude steel production levels, the projected total CO 2 emissions were 4–21% below 2010 levels. If the 2030 production level remains at 105 Mt/y, which equals the 2015 production level and the 1973–2015 average, the total emissions will be 9–16% below 2010 levels, depending on the level of emissions reduction effort. These results indicate that the industry is likely to considerably overachieve its voluntary emissions reduction target for 2030 (0.1% below 2010 levels). Moreover, it was found that the lifetime extensions for existing blast furnaces and coke ovens have limited impact on CO 2 emissions while significantly reducing the investment needs. The study also showed that the low crude steel production (90 Mt/y) combined with high pig iron and coke consumption levels to maintain minimum capacity utilisation rates may lead not only to an increase in specific CO 2 emissions per tonne of crude steel but also to a net export of obsolete scrap up to 17 Mt, which is nearly twice the historical high. Towards 2030, Japan would need to consider not only opportunities to maximize the use of steel scrap but also the development of an extended steel scrap trade infrastructure. [ABSTRACT FROM AUTHOR]

The grey irons prepared by adding steel scrap as main raw material were designed. Effect of the steel scrap content on the microstructures, mechanical properties and fracture mechanisms of the HT250 grey irons was studied. The results show that as the steel scrap content increased, the microstructures of the grey irons are improved, and the mechanical properties of the grey irons are therefore increased. The grey iron by adding 100 wt-% steel scrap has the optimal microstructure composed of the small and curved graphite flakes, the refined pearlite colonies and the dispersed MnS and TiN inclusions, also, it has the highest mechanical properties and comprehensive performance. [ABSTRACT FROM PUBLISHER]