Rolled Steel Research Articles

Effect of feed rate during induction hardening on the hardening depth, microstructure, and wear properties of tool-grade steel work roll

Rolls are the most critical yet vulnerable parts of cold rolling mills. It is crucial for them to withstand long rolling campaigns without losing surface roughness or incurring damage. Newly developed rolls are made from tool-grade steel with high roughness, lower wear, and high damage resistance. One of the most important advantages is the elimination of the need for chrome plating, which is currently widely used on standard steel rolls but is ecologically harmful. We investigated a type of steel with 8% chromium for use in cold rolling using light optical microscopy (LOM), X-ray crystallography (XRD), scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), hardness measurements, and tribological tests. In this study, a roll with a diameter of 325 mm was electro-slag remelted and forged, machined to a diameter of 305 mm, and quenched and tempered to simulate industrial roll production. A forged roll was induction heated and hardened at four different feed rates (i.e., 24 mm/min, 30 mm/min, 36 mm/min, and 42 mm/min), tempered at 515℃ for 24h and again at 480℃ for 24h, and dissected for in-depth analysis. We identified a clear relationship between the feed rate of the roll during induction hardening and the depth of hardness, the sizes of carbides, and the wear properties of the roll. By reducing the feed rate of the roll through the inductor, we increased the depth of the hardened layer from 16 mm (at a feed rate of 36 mm/min) to 25 mm (at a feed rate of 24 mm/min), which is a 56.25% increase. Such an increase is expected to extend the lifespan of the working roll without having negative effects on the wear resistance and other important parameters. XRD analysis showed that the sample had a 0.4% residual austenite, which means it had a significantly lower risk of roll damage during operation than standard steel grades

Anisotropy of acoustic properties in thin-sheet rolled low-carbon manganese steel

Thin-sheet rolled low-carbon manganese steel 09G2S with a thickness of 0,8 mm which has strong property anisotropy due to texture and residual stresses, was experimentally studied using SH-wave with horizontal polarization and zero-order symmetric Lamb wave mode. The velocities of elastic wave propagation along the sheet were analyzed as their direction and polarization varied relative to the rolling direction in the range of angles from 0 to 180 degrees. The excitation and reception of normal waves in the sheet were carried out by piezoelectric transducers with dry point contact, providing tangential force application. The results of the research on the anisotropy of acoustic properties, X-ray structural analysis of residual stresses and inverse pole figures, and metallographic studies were obtained.

Development of significantly hard hypereutectoid plain carbon steel through incomplete austenitization based cyclic quenching treatment

AbstractIn this investigation hot rolled steel bars of 1.24 weight % carbon steel are subjected to incomplete austenitization based cyclic quenching treatment. Each cycle consists of inserting the specimen in an electric resistance furnace at a temperature of 894 °C and holding for a short duration (6 minutes), followed by oil quenching to the room temperature. Such a typical thermal cycling results in the evolution of a novel microstructure that comprises of large clusters and blocks of cementite in a matrix of martensite after 3 and 4 cycles. Accordingly, a significantly high hardness (7.13 GPa) is achieved on execution of 3 cycles which envisages a new pathway of incomplete austenitization based cyclic quenching treatment for development of new‐generation plain carbon hypereutectoid tool steel.

The performance evaluation of hybrid roller bearings under lubricant contamination conditions

PurposeThis paper aims to evaluate the dynamic performance of hybrid roller bearings under lubricant contamination.Design/methodology/approachSome steel rollers in traditional cylindrical thrust roller bearings were replaced with ceramic rollers to assemble hybrid roller bearings. Friction experiments were conducted under lubricant contamination using alumina as the contaminant, and simultaneous vibration acceleration signals from the bearings were collected to evaluate their tribological and dynamic performance.FindingsUnder lubricant contamination, hybrid roller bearings with a sufficient number of ceramic rollers exhibit greater wear resistance compared to traditional all-steel bearings. There is a noticeable suppression of energy in both tangential and normal frequency bands of the bearings, with more pronounced suppression observed in higher frequency bands.Originality/valueThis study provides valuable insights for the development of hybrid ceramic bearings.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2024-0291/

Limitations of Electric Drive and Local Control Systems in Asymmetric Rolling of Fine-Grained Steels

Limitations of Electric Drive and Local Control Systems in Asymmetric Rolling of Fine-Grained Steels

Determination of Friction Characteristics of Corn Ears at Varying Factors in Mechanical Peeling

ABSTRACTIn view of the low bract removal and high corn ear damage in the operation of the current peeling device, this work aimed to accurately measure the coefficients of friction (COFs) involved between peeling rollers and corn ears during the corn peeling. Consequently, the movement state of corn ear in a peeling device and the friction behavior involved were analyzed, and the mechanical model was established. Friction tests were conducted by using the modified tilting table, the modified direct shear apparatus, and the self‐built rolling friction apparatus. The value range and change rule of the COFs between corn ears and peeling rollers were obtained. Linear regression models were described for the COFs depending on moisture content. The results show that the coefficient of static friction (COSF) was 0.391–1.396, the coefficient of sliding friction (CODF) was 0.398–1.318, and the coefficient of rolling friction (CORF) was 0.119–0.377. All COFs were positively correlated with moisture content. Besides, the COFs of two rubber rollers were significantly larger than that of the steel roller. Among the two rubber rollers, the COFs were higher between the fish scale rubber roller and bare corn ears and were lower between the fish scale rubber roller and corn ears with bracts. This meant that the fish scale rubber roller was more likely to cause seed damage under the same conditions. Knowledge concerning these coefficients is believed to provide data support for the improvement and optimization of corn peeling devices.

Novel quaternary ammonium Gemini surfactant as a highly efficient inhibitor for the corrosion of steel in HCl and H2SO4 solutions

Ethyl-bis(octadecyl dipolyoxyethylene ammonium chloride) (E-BODAC) was a novel quaternary Gemini surfactant and was first found and identified as an excellent inhibitor with excellent surface activity and suitability. The ethoxy group enhances its hydrophilicity, and facilitates a dense adsorption film on metal surface. The inhibitive action and mechanism of E-BODAC on cold rolled steel (CRS) in HCl and H2SO4 solutions was studied in detail by theoretical and experimental methods. The surface activity and degree of polymerization of the surfactant are tightly related to the anti-corrosion properties. HCl has a lower critical micelle concentration (CMC) than H2SO4 solutions. The hydrophilic group in E-BODAC is the preferred site for donating and accepting electrons, with chemical interactions occurring among O, C, and Fe. The addition of E-BODAC obeys Langmuir isotherm, which can drastically reduce the diffusion of H3O+, Cl−/SO42−. E-BODAC has superior corrosion inhibition performance and lower dosage, and the inhibition efficiency for CRS reaches 92.9% in 1.0 M HCl with only 10 mg L−1 of E-BODAC and 91.5% in 0.50 M H2SO4. The inhibition is through physical and chemical adsorption to form a protective film that covers the reaction site, blocking the corrosion reaction. CLSM, SEM, AFM, XPS, and time-of-flight secondary ion mass spectrometer (TOF-SIMS) provide evidence of the adsorption of E-BODAC, efficiently slowing down the corrosion of CRS surface. E-BODAC always shows higher efficiency in HCl than in H2SO4, which is attributed to the re-dissolution of the adsorbed film in the H2SO4 solution. Besides, SO42− ions are larger and migrate more slowly than Cl− ions, resulting in weak adsorption on the metal surface. The assessment of E-BODAC's suitability and durability in different corrosive environments provides the opportunity to determine its optimum conditions and applicability to maximize its corrosion inhibition effect.

Exploring health hazards from toxic elements in well water samples within prism steel rolling mill, Ikirun, Osun State, Nigeria

Exploring health hazards from toxic elements in well water samples within prism steel rolling mill, Ikirun, Osun State, Nigeria

USE OF UNMANNED TRANSPORTATION VEHICLES IN DELIVERY OF ROLLED METAL PRODUCTS AND NAVIGATION PROBLEMS

The article offers a comprehensive analysis of unmanned automotive vehicles in logistics, focusing particularly on the transportation of rolled steel products. It discusses key aspects of integrating and operating UAVs, highlighting their economic efficiency, safety, and environmental sustainability. Current safety issues in transporting rolled steel, including cargo securing methods and inertial force considerations, are thoroughly examined. Detailed insights into modern navigation technologies and safety systems like LiDAR and radars applied in unmanned vehicles are provided. Additionally, the article presents data on leading Russian companies in UAV development and implementation, such as Evocargo, KamAZ, SberAutoTech, and Starline, detailing their achievements and prospects in this field. Purpose. An investigation into the present status and future prospects of employing unmanned vehicles in logistics, with a specific focus on transporting rolled steel products. Methodology. Conducting an analysis of regulatory documents and standards, examining practical experience and case studies, performing a comparative analysis of navigation technologies, and engaging in theoretical analysis and synthesis. Results. For successful integration of unmanned vehicles into the delivery of rolled steel products, it is recommended to launch pilot projects on key routes, develop infrastructure for charging and refueling stations, establish regulatory frameworks, and collaborate with industry partners. Practical implications. The results are advantageous for entities engaged in the logistics and transportation of rolled steel products. Integrating unmanned vehicles can enhance delivery efficiency and safety, as well as reduce CO₂ emissions, which are critical for sustainable development and cost reduction.

Effect of preheating substrates and process parameters on cladding track geometry fabricated by laser cladding

Laser cladding (LC) is an advanced technique used for repairing large-scale components, such as rotors and valves, in thermal power plants and steel rolling mills. This technology is designed to facilitate efficient repairs, minimize repair costs, conserve materials, reduce processing time, and ensure adequate dilution between the substrate material and the deposited coating, while also enhancing corrosion resistance. In this research, the effects of preheating substrates and input process parameters on the geometric accuracy of single-track deposits, as well as the microstructure composition of multi-track deposits, were investigated. The Taguchi method was used to design an L9 orthogonal experimental array. The impact of process parameters, including substrate temperature, laser power, and scanning speed, on the morphology of a single track (track width, height, penetration depth, and dilution) was evaluated through ANOVA statistical analysis. SS316L stainless steel, recognized for its wear resistance, was used as the deposition material. The findings reveal that substrate temperature is the most critical factor influencing the dilution of the coating. Additionally, the microstructure of the deposited layers were systematically analyzed.

Assessment of former austenite structure in hot rolled steel in terms of its texture after martensitic transformation

Textures of medium carbon steel, hot rolled and then quenched, have been determined by Electron backscatter diffraction (EBSD). To ensure representativeness of results, a rather large treated scan covered about a thousand of prior grains, each containing several thousands of measurement points. Considering inter-phase orientation relationships peculiar to martensitic steels, textures of the high temperature phase (austenite) have been assessed in terms of the transformation textures. Thus, deformed and recrystallized states of austenite dependent on the rolling conditions can be distinguished. To verify EBSD data, martensite textures were measured by an independent method of EBSD whereas morphology of the prior grains was revealed by means of chemical etching.

Efficient and stable hydrogen evolution and antibiotic degradation in all-pH-scale water/alkaline seawater using Fe-Co phosphide hollow nanocages fabricated from metallurgical solid waste

The utilization of seawater, a plentiful and cost-effective resource, instead of freshwater for H2 production through electrolysis has garnered significant attention. Herein, we present the synthesis of open-structured Fe-Co phosphide (FCP) nanocages for the overall seawater electrolysis, employing metallurgical solid waste (steel rolling sludge, SRS) as the precursor material. The FCP nanocages demonstrate exceptional catalytic activity for the hydrogen evolution reaction (HER) in all pH scales, achieving performance comparable to that of Pt/C catalysts at high current densities. The electrolyzer assembled with FCP||FCP requires 1.57 and 1.68 V to achieve current densities of 10 and 100 mA cm−2, respectively. Furthermore, the assembled FCP electrolyzer showcases over 100 h of cycling stability and nearly 100% Faradaic efficiency. Crucially, it can be powered by commercially available silicon solar panels, operating under an intensity of 100 mW cm−2, and by wind-driven sources, rendering it highly promising for real-world applications. The seawater hydrogen evolution system coupled with levofloxacin (LEV) degradation was constructed for the first time. The oxidation potential of LEV oxidation reaction (LEVOR) was significantly lower than that of oxygen evolution reaction (OER), indicating that the LEV degradation reaction occurred preferentially and achieved a removal efficiency of 98.57% within 60 min. This study provides effective strategies for valorizing SRS and offers insights into the fabrication of high-performance catalysts.

Application of digital twin for industrial process control: A case study of gauge-looper-tension optimized control in strip hot rolling

Background During the hot rolling process, the performance of most control systems gradually degrades due to equipment aging and changing process conditions. However, existing gauge-looper-tension control method remain restricted by a lack of intelligent parameter maintenance strategies. Methods To address this challenge and enhance the smart manufacturing capabilities of strip hot rolling, based on the digital twin method, this paper proposes a data-driven optimized control method for the gauge-looper-tension system of strip hot rolling. First, a hot rolling process model is constructed based on a digital twin method to serve as an evaluation and optimization platform. Subsequently, relevant data are collected to calculate the Hurst index for identifying the performance of the controller during the rolling process. Additionally, for controllers with poor Hurst index values, the crayfish optimization algorithm is employed for adjusting controller parameters to maximum the Hurst index. Results A real case of hot rolling steel production was used to validate the proposed data-driven optimized control method. Experimental results demonstrate that the proposed evaluation method can effectively recognize the state of gauge-looper-tension controller. Moreover, after optimizing the controller parameters through crayfish optimization algorithm (COA), the value of Hurst index showed significant improvement. Conclusions The proposed digital twin -based optimized control method effectively enhance the manufacturing capability and maintain strategy of hot rolling steel production. Through the proposed method, the Hurst index of gauge-looper-tension system increasing from 0.574 to 0.862.

Seismic in-plane behavior of composite masonry walls strengthened with cold rolled steel sheets

The seismic behavior of masonry walls strengthened by cold rolled steel sheets is numerically evaluated in this study using finite element modeling in ABAQUS. Cold-rolled steel sheets cover two sides of an unreinforced masonry wall and are bolted together to form a composite masonry wall. The behavior of the composite masonry walls is compared to that of the corresponding unreinforced masonry walls with various failure mechanisms. The finite element models of the unreinforced masonry walls are validated through experimental data in the literature. Then, cold-rolled steel sheet-strengthened walls are simulated, and variations in strength, ductility, and failure mode are investigated. A thorough sensitivity analysis is conducted on the effects of the aspect ratio, boundary condition, axial load ratio, steel sheet thickness, and connection bolt configuration on the in-plane strength and failure mode of the walls. It is observed that the steel sheets affect the local and global behavior of the masonry walls and change their failure modes. The use of through-thickness bolts to connect steel sheets to the masonry wall provides a composite action between steel sheets and the masonry wall against in-plane lateral loads. The cold-formed steel sheets not only resist a portion of the lateral load but also significantly increase the lateral strength of the masonry walls and the ductility of the whole wall system. Based on the analysis results it can be concluded that strengthening masonry walls with cold-rolled steel sheets is a promising technique for the seismic improvement of existing conventional masonry buildings and for the design of new masonry buildings.

Assessing strength of ferrite and martensite in five dual phase and two martensitic steels via high throughput nanoindentation to elucidate origins of strength

This paper describes the main findings from an experimental investigation into overall and local strength of four dual-phase (DP) steels classified based on their tensile strength (TS) levels from DP590, to 780, to 980, to 1180, a martensitic steel (MS) 1700, and a high-strength low-alloy (HSLA) steel in rolled and additively manufactured (AM) conditions. The DP steels and the MS steel consist of ferrite and martensite, while the HSLA steel is solely martensitic. High throughput nanoindentation mapping is employed to measure the mechanical hardness of individual phases contributing to strength of the steels. A clustering methodology for correlating measured hardness and phase maps is conceived to infer hardness per phase. With increasing fractions of martensite, the hardness values of both ferrite and martensite are found to increase with more rapid increase in the hardness of ferrite than martensite. The phases increasingly dislocate with the fraction of martensite as rationalized by crystal plasticity modeling of strength of the steels. Initial slip resistances and a set of hardening parameters associated with the slip in ferrite and martensite are established to model the flow stress behavior of the steels. In modeling the co-dependent nature of crystallographic slip in ferrite and martensite, the initial dislocation densities are inferred and correlated with the measured hardness values. The hardness of martensite in the rolled HSLA steel is comparable to the hardness of martensite in the MS steel, while martensite in the AM HSLA steel is softer owing to the tempering occurring during the AM process.

Dislocation Strengthening and Texture Evolution of Non-Oriented Fe-3.3 wt% Si Steel in Double Cold Rolling

Dislocation Strengthening and Texture Evolution of Non-Oriented Fe-3.3 wt% Si Steel in Double Cold Rolling

The Study on Annealing Temperature and Rolling Speed Effects in Relation with Microstructure, Mechanical Properties and Surface Quality of Hot Rolled S450J0 Steel

The Study on Annealing Temperature and Rolling Speed Effects in Relation with Microstructure, Mechanical Properties and Surface Quality of Hot Rolled S450J0 Steel

Identifying the social hotspots of German steelmaking and its value chain

Steel production is highly material and energy intensive. As the industry sources large amounts of raw materials globally, the need to assess the sustainability dimensions of the steelmaking process and its value chain is increasing. This paper sets out to investigate the social dimension, by identifying social hotspots tied to the value chain and production of primary steel in Germany. To achieve this, a literature review is conducted, and the Social Life Cycle Assessment (S-LCA) methodology is applied in the form of a social hotspot assessment for the production of 1 t of hot rolled steel coil. Import data for the German steel industry are combined with social data from the social hotspot database, to gain an comprehensive overview of social risks and hotspots tied to the value chain and production of steel. The literature review finds the application of S-LCA in the steel industry to be low overall, with great variety in impact subcategories and indicators assessed. The social hotspot assessment shows a high number of social risks tied to the value chain of the German steel industry. These relate primarily to worker health and safety, delocalization and migration, access to immaterial resources, forced labour, and social benefits/social security. In particular, the extractive industries of iron ore and coal are established as social hotspots. Based on the findings of the literature review and the social hotspot assessment, it is recommended that the following impact subcategories be considered in a full scale S-LCA study on steelmaking including the value chain: Worker health and safety, freedom of association and collective bargaining, delocalization and migration, and forced labour. Furthermore, it is recommended to prioritize the collection of primary data on 16 indicators, that are identified as high risk or very high risk across multiple assessed countries and sectors.

Prediction of mechanical properties of rolled steel based on dual-attention multiscale convolutional neural network

The mechanical properties of carbon steel sheet directly depend on the chemical composition and process parameters of the steel. There is a complex nonlinear relationship between chemical composition, process parameters, and mechanical properties, and the establishment of a model with the ability to automatically distinguish the importance of different parameters, and to have good prediction accuracy and generalisation in different data sets is one of the important issues in the field of carbon steel mechanical properties prediction. In this paper, we proposed a multi-scale convolutional network model based on dual-attention mechanism (DAM-MSDSC), where the dual-attention module mines from features and channels at the same time, making the model focus on the important features. The multiscale feature fusion module effectively improves the model prediction accuracy by mining features from the output of the middle layer of the network to obtain features containing multiscale fusion features. In hot-rolled steel, for the two parameters of carbon content and temperature, it is confirmed that the change of carbon content has a greater impact on TS, while FTT and CT have a greater impact on YS. Through comparative experiments on different datasets, the proposed model had the best prediction performance, in which the correct rates of YS, TS, and EL are 98 %, 98.7 %, and 99.4 %, respectively, in cold rolled steel, and 97.8 %, 98.6 %, and 99.2 %, respectively, in hot rolled steel.

A real-time temperature field prediction method for steel rolling heating furnaces based on graph neural networks

In the billet reheating process during steel rolling, the real-time and accurate prediction of the temperature field is a prerequisite for the dynamic regulation of the heating process, which is crucial for ensuring the quality of billet reheating and reducing the energy consumption of the reheating furnace. The most commonly used finite element thermal field simulation and analysis methods are unable to meet the demand for real-time prediction under dynamic working conditions. Furthermore, traditional machine learning methods struggle to handle irregular data that includes spatial location information, resulting in inaccurate temperature field predictions, which in turn affect the furnace control efficiency and the quality of the product. In light of these limitations, this study proposes a Graph Neural Network (GNN)-based temperature field prediction method for steel rolling reheating furnaces. This method considers the interactions between the nodes within the reheating furnace and constructs a temperature field topology graph to effectively capture these interactions, including heat conduction and convection. Additionally, in the feature fusion and state updating mechanism of the model, we introduce process parameters, such as the air-fuel ratio, as additional inputs to enhance the ability of the GNN to handle complex variables. This enables real-time accurate simulation of the internal temperature distribution of the reheating furnace. The experimental results demonstrate that the model prediction error is controlled within 2.9 % and the response time is maintained within 20 ms, thereby validating the reliability and efficacy of the method in practical applications.