Hot-rolled Steel Research Articles

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.

Effective strategies for improving quenched microstructure and mechanical properties of hot-rolled seamless steel pipes

The containing Ti-Mg-Ca-O composite particles were innovatively used to achieve microstructure refinement and properties improvement of hot-rolled seamless steel pipes, and compared with conventional steel (C# steel). The results show that the C# steel mainly consisted of parallel lath martensite after on-line quenching. Under the same rolling and heat treatment conditions, dominant Ti-Mg-Ca-O composite particles in modified steel (M# steel) were effective nucleation sites of acicular ferrite, dividing the prior austenite grains and refining microstructures. The strength values of the both steels were at the same level, however, the impact energy of M# steel was significantly higher than C# steel, increasing by 28%. This study provides an effective method for further microstructure refinement of hot-rolled seamless steel tubes.

Effects of TRIP and TWIP mechanisms on improved Charpy impact energy of thick hot-rolled duplex lightweight steel plates

Charpy V-notch impact testing serves as a fundamental method for assessing the toughness of conventional steels, but its applicability becomes challenging for duplex (δ-ferrite + γ-austenite) lightweight steels due to their complex microstructures and varied deformation mechanisms. In this study, Charpy absorbed energies of hot-rolled duplex lightweight steel plates, incorporating both transformation-induced plasticity (TRIP) and twinning-induced plasticity (TWIP) mechanisms, were investigated to understand their fracture behavior comprehensively. The microstructural analysis revealed that the D4 (0.4C-15Mn-6Al (wt.%)) steel exhibited lower δ-ferrite volume fraction and superior Charpy absorbed energy than the D2 (0.2C-15Mn-6Al) steel, attributed to its dominance of TWIP mechanism. Conversely, the D2 steel, with many ferrite/austenite interfaces, showed lower strain hardening and absorbed energy. At lower temperatures, both TWIP and TRIP mechanisms operated, but dominant TRIP mechanism along with higher δ-ferrite volume fraction in the D2 steel accelerated crack propagation, further reducing absorbed energy. The superior toughness of the D4 steel, driven by the dominant TWIP mechanism at lower temperature, highlighted its potential for practical utilization of thick hot-rolled lightweight steel plates in automotive, shipbuilding, military, and construction industries.

New route for fabricating low-carbon ductile martensite to optimize the stretch-flangeability of dual-phase steel

Traditional cold-rolling dual-phase steel (CR sheet), limited by poor stretch-flangeability as indicated by the hole expansion rate (HER), faces challenges in manufacturing complex automobile parts. To address this, a new type of hot-rolling dual-phase steel with an 800 MPa grade (manufactured by tyipical thin slab continuous casting and rolling process, TSCCR) was designed to replace the traditional one. The TSCCR sheet, with a lower carbon content of 0.047wt.%, compared to 0.093wt.% in the CR sheets, features 40.6% martensite significantly higher than 28.2% in the CR sheet. This increased martensite content, despite being softer and more ductile due to its low hardness, compensates for the tensile strength in the TSCCR sheet. Furthermore, the TSCCR sheet exhibits a unique heterostructure characterized by uneven carbon distribution from the ferrite/austenite interface to other boundaries/interfaces, estimated by the negligible partition local equilibrium (NPLE) model of ferrite transformation. This unique heterostructure diminishes the mechanical disparity between ferrite and martensite, resulting in a higher yield strength of 568 MPa, compared to 456 MPa in the CR sheet. During uniaxial tension, the ferrite and ductile martensite in the TSCCR sheet initiate cooperative plastic deformation earlier than in the CR sheet, despite initially having fewer favorable slip systems in the TSCCR martensite. The low working hardening rate of the TSCCR sheet facilitates the forming layered structure of ferrite and martensite during necking compared to the CR sheet. Consequently, the HER of the TSCCR sheet sharply increased by 144% compared to the CR sheet. This enhancement in HER can be attributed to the crack initiation area, longer crack propagation path, and higher crack propagation resistance facilitated by the ductile martensite, culminating in superior HER.

Study on microstructure characteristics and hole expansion mechanism of Ti-Nb-V microalloyed 900 MPa hot-rolled ferrite-bainite high hole expansion steel

In this study, a 900 MPa grade hot-rolled ferrite/bainite high hole expansion steel was developed using thermomechanical controlled processing (TMCP) and medium-temperature coiling with a Ti-Nb-V multi-microalloy design. The effects of cooling rates and coiling temperatures on the microstructure, mechanical properties, and hole expansion behavior were systematically investigated. The steel, coiled at 600°C and cooled at a controlled rate (10-25°C/s), demonstrated an excellent balance of strength and ductility, achieving a tensile strength of 901 MPa and elongation of 23%. The microstructure consisted of approximately 62% ferrite and 38% bainite, characterized by a uniform and fine grain distribution. The high coiling temperature increased the content of Ti-Nb-V composite precipitates, while reduced cooling times promoted the formation of smaller precipitates primarily along dislocation lines and grain boundaries. A hole expansion ratio of 77% was achieved due to the optimized grain morphology and phase ratio, with refined grains and high-angle grain boundaries impeding crack propagation. Additionally, the increased presence of secondary precipitates strengthened the soft phase ferrite and enhanced the coordinated deformation between ferrite and bainite. These combined effects significantly improved the steel's resistance to crack propagation during hole expansion, making it a promising material for applications requiring high strength and formability.

Metal additive manufacturing of damage-controlled elements for structural protection of steel members

This paper develops hybrid steel members by integrating additively manufactured, ultra-lightweight, damage-controlled elements (DCEs) into hot-rolled structural steel members. This approach relies on segmenting a structural member into distinct sections; one or two segments are enlarged to be capacity protected; however, anotherend or middle DCE segment is optimized to emulate theconventional member’s strength and stiffness. A small-scale DCE was topologically optimized and then additively manufactured using apowder bed fusion technique through adirect metal laser sintering process of 17-4PH stainless steel andthen was experimentally tested to study the buckling behavior under compression. The experimental testing of the optimized DCE shows acompressive strength of 81,000 times the specimen’s weight with stable post-peak buckling behavior. Numerical simulation confirms experimental results, showing agood correlation in fracture energy. A parametric study on four DCE specimens, scaled up by three, four, five, and six times, was performed and compared to hollow structural sections (HSS) of A500 Gr. C in tensile and compression strengths. The numerical simulation shows a linear relation between the weight ratio and HSS length. Additionally, numerical simulation of conventional member, DCE (scaled by three), and three hybrid members revealed that failure occurred in DCE as intended.

Flexible Cooling Strategy for Hot-Rolled Steel Based on Physical Theories Coupled with Machine Learning

Flexible Cooling Strategy for Hot-Rolled Steel Based on Physical Theories Coupled with Machine Learning

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.

Prediction of Mechanical Properties of Hot-Rolled Strip Steel Based on XGBoost and Metallurgical Mechanism

Prediction of Mechanical Properties of Hot-Rolled Strip Steel Based on XGBoost and Metallurgical Mechanism

Strengthening Triggered by Deformation Twins in a Hot-Rolled High-Mn Steel: The Role of Stacking Fault Energy

Strengthening Triggered by Deformation Twins in a Hot-Rolled High-Mn Steel: The Role of Stacking Fault Energy

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.

Multi-scale sensing and multi-dimensional feature enhancement for surface defect detection of hot-rolled steel strip

ABSTRACT Surface defect detection of hot-rolled steel strip is a crucial process in its production. Aiming at the problem of poor detection accuracy caused by complex shape of defect features and imbalance between object scale and feature scale, this paper proposes a multi-scale sensing and multi-dimensional feature enhancement algorithm. Firstly, a multi-branch residual aggregation module (MRAM) is proposed, which uses the interactive features of different receptive fields between layers to capture global and local texture features, improving the feature extraction capability for defects of different scales. Then, the multi-dimensional attention enhancement head (MAEH) is proposed, which integrates feature information from different prediction branches and realises feature information enhancement in scale, space and channel dimensions for the aggregated information to improve the accuracy and robustness of steel surface defect detection. The results show that the proposed algorithm achieves 82.7% mAP and 89 FPS on the NEU-DET dataset, and 73.3% mAP and 94 FPS on the GC10-DET dataset. Compared with state-of-the-art algorithms, the proposed algorithm has the highest mAP, strong generalisation ability, and good real-time performance, which proves its effectiveness in detecting hot-rolled steel strip surface defects.

Effect of ultrasonic impact treatment on surface residual stress, microstructure and electrochemical properties of the hot-rolled S355 steel

The effects of ultrasonic impact treatment (UIT) on the microstructure, corrosion resistance, and surface residual stress of hot-rolled S355 steel were investigated. In addition, the improving mechanism of the UIT induced corrosion resistance was discussed. The results show that the UIT can effectively improve the corrosion resistance of hot-rolled S355 steel, and corrosion current density reduction is demonstrated. Based on the corrosion morphology, it can be found that after the UIT the corrosion pits became shallower, the oxide layer becomes denser, and more flocculent structures appear on the surface as well as the appearance of dense irregular curved structures. Moreover, the residual tensile stress on the surface of the hot-rolled S355 steel is transformed into residual compressive stress after the UIT. The grains are refined, and the microhardness is increased, which implied that the significant plastic deformation has occurred on the surface of the hot-rolled S355 steel. The findings confirm that dense oxides could be generated on the surface of hot-rolled S355 steel treated by ultrasonic impact since the residual compressive stress is introduced, the plastic deformation is induced, and the grains are refined.

Detection and classification of surface defects on hot-rolled steel using vision transformers

This study proposes a vision transformer to detect visual defects on steel surfaces. The proposed approach utilizes an open-source image dataset to classify steel surface conditions into six fault categories namely, crazing, inclusion, rolled in, pitted surface, scratches and patches. The defect images are first subject to resizing and then fed into a vision transformer subject to different hyperparameter configurations to determine the most optimal setting to render highest classification performance. The performance of the model is evaluated for different hyperparameter configurations, and the most optimal configuration is examined using the associated confusion matrices. It was observed that the proposed model presents a high overall accuracy of 96.39 % for detection and classification of steel surface faults. The study presents a descriptive insight into the vision transformer architecture and in addition, compares the performance of the current model with the results of other approaches suggested for application in literature. Vision transformers can serve as standalone approaches and suitable alternatives to the widely used convolution neural networks (CNNs) by actuating complex defect detection and classification tasks in real-time, enabling efficient and robust condition monitoring of a wide range of defects.

Lifecycle Evaluation of Environmentally Friendly Construction Materials: A Review

Abstract: This approach presumes that practices like using locally sourced materials or products containing recycled content are environmentally beneficial, irrespective of the product’s manufacturing process or disposal methods. The choice and application of sustainable building materials are crucial in the design and construction of green buildings. This chapter aims to provide an overview of sustainable materials and their environmental impacts. Additionally, it explores life cycle assessment (LCA) as a methodological framework for evaluating these materials and examines the limitations of LCA in analyzing the sustainability of building materials. the Life Cycle Assessment (LCA) method was utilized to evaluate the environmental impacts of building materials in different construction systems. The study compared three types of construction systems: reinforced concrete, hotrolled steel, and light steel. Among these, the light steel system had the lowest embodied energy and global warming potential, followed by reinforced concrete and hot-rolled steel. Additionally, the constructions were assessed using the LEED certification system

Effect of Subsequent Continued Heating After Hot Rolling on the Microstructures and Mechanical Properties of Hot-Rolled Super Ferritic Stainless Steels

Effect of Subsequent Continued Heating After Hot Rolling on the Microstructures and Mechanical Properties of Hot-Rolled Super Ferritic Stainless Steels

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.

Analysis of Rolling Force and Friction in Hot Steel Rolling with Water‐Based Nanolubrication

Analysis of Rolling Force and Friction in Hot Steel Rolling with Water‐Based Nanolubrication

Tension fracture delamination analysis on a hot rolled Nb-bearing high-strength steel for vehicle wheel application

A comparative analysis was conducted on post-tensile specimens with and without delamination to investigate the causes of tensile delamination in hot rolled steel with a 600 MPa ultimate tensile strength (UTS) for automotive wheel applications. The tensile specimens were sampled from the hot rolled coils in the transverse direction per ASTM A370 standards, and Tensile tests were performed at room temperature with a constant crosshead speed of 0.5 mm/min. The results indicate that normal segregation is not the sole factor contributing to delamination; rather, the presence of Nb lumps within the central segregation area increased the susceptibility to tensile delamination. The statistical analysis indicates that there is a more intense presence of Nb lumps in specimens with tension delamination, tension delamination will occur during specimen stretching when there are Nb lumps with an average size greater than 6.5 μm and a quantity greater than 3 in the central segregation region. Meanwhile, the sources of lumps are also analyzed indicates that these Nb lumps originate from the ferroniobium alloy added during BOF tapping and ladle refining.

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.