steel research international最新文献

Seven types of inclusions are observed in the Al-deoxidized steel followed by Ti-deoxidized steel, while ten types of inclusions are found in Al–Ti simultaneous deoxidized steel. Three special inclusions are only found in Al-deoxidized steel followed by Ti-deoxidized steel as Al₂TiO₅–Ti_xO_y, Al₂TiO₅–Al₂O₃–TiS, and Al₂TiO₅–Al₂O₃–Ti_xO_y–TiS. The precipitation order of inclusions in Al–Ti-deoxidized steel is very dependent on the value of [%Ti]/[%Al] or [%S]/[%O]. The critical value of [%Ti]/[%Al] for the precipitation of inclusions from large to small is Ti_xO_y > Al₂TiO₅ > Al₂O₃, and the critical value of [%S]/[%O] for the precipitation of inclusions from large to small is TiS > Ti_xO_y. The critical value of [%Ti]/[%Al] for the precipitation of Ti_xO_y prior to Al₂TiO₅, and the precipitation of Al₂TiO₅ prior to Al₂O₃ has a close relationship with the content of [%Al]. In addition, the critical value of [%S]/[%O] for the precipitation of TiS prior to Ti_xO_y inclusions increases with an increasing content of [%O] and increased with the decreasing of temperature. The precipitation order of inclusions in the two types of steel is Al₂TiO₅ or Al₂O₃ → Ti₃O₅ → TiO₂ → Ti₂O₃ → TiS.

Bright-band defects frequently occur on as-cast strips in the twin-roll strip-casting process, particularly at low-casting speeds, with intervals of ≈200 mm. Additionally, the cast-rolling force also exhibits minor fluctuations. With increasing casting speeds, the spacing between bright-band defects widens, and the severity of these defects diminishes. When the casting speed reaches a certain threshold, defects almost entirely disappear. Detailed analysis of the underlying causes of this phenomenon is essential for effectively preventing defect formation. In this study, the numerical simulation method is employed to analyze casting rolls’ thermal deformation and the melt pool's solidification behavior, based on the production site equipment and process conditions. The causes of defects in as-cast strips are thoroughly analyzed based on simulation results, in conjunction with variations in the cast-rolling force. In this study, it is demonstrated that the thermal deformation of casting rolls and the position of the solidification endpoints collectively contribute to the fluctuations in cast-rolling force and are the primary causes of bright-band defects. Fundamental principles for preventing defects are provided based on actual on-site production. Furthermore, simulation results contribute to establishing a theoretical basis for selecting process parameters and controlling cast-rolling force during production.

Hot rolling processes have been extensively used to produce round bars by reducing the cross-sectional area of continuously cast steel. The current trend toward increasing productivity often requires a more aggressive reduction per pass. Establishing safe and optimized hot rolling parameters must be determined to avoid damage while deforming the specific steel composition. Understanding the damage mechanism during the metal forming process is vital for product quality. Herein, a combined experimental and simulation approach is developed to track the evolution potential damage during hot bar rolling. Hot tension tests are conducted on as-cast vanadium microalloyed 15V38 steel at different hot rolling temperatures and strain rate conditions to develop Johnson–Cook-type material model. A thermomechanical finite element model is developed to simulate potential damage trends in a 12-pass square-to-round and 8-pass round-to-round standard industrial hot rolling process, employing damage criteria. Results are illustrated by creating a damage map at each rolling pass to determine the critical hot rolling conditions for damage initiation. Several parametric studies are also performed to illustrate the application of the suggested methodology for hot rolling process optimization. Results show that the probability of the damage initiation is higher at higher pass reductions and lower temperatures.

Numerical fluid simulations using the Reynolds stress model and water model experiments are conducted to test different designs of tundish turbulence inhibitors (A, B, C, D, and E) for their effectiveness in removing nonmetallic inclusions from steel. The results reveal a unique flow pattern, with a mushroom-like shape forming around the entry jet. The acceleration of small eddies within this mushroom is a significant factor in inclusion removal. This discovery has practical implications for the steel industry, leading to a longer residence time in the entry jet mushroom and improved inclusion flotation performance. Additionally, the turbulent kinematic viscosity and Reynolds stress fields in the flow mushroom influence the tracer's local dispersion rate and the interactions of the inclusions in this region. These findings are further validated using a tundish water model to track the dynamics of amine particles injected into the ladle shroud, enhancing their practical relevance.

Hot rolling is a critical thermomechanical processing step for nonoriented electrical steel (NOES) to achieve optimal mechanical and magnetic properties. Depending on the silicon and carbon contents, the electrical steel may or may not undergo austenite–ferrite phase transformation during hot rolling, which requires different process controls as the austenite and ferrite show different flow stresses at high temperatures. Herein, the high-temperature flow behaviors of two nonoriented electrical steels with silicon contents of 1.3 and 3.2 wt% are investigated through hot compression tests. The hot deformation temperature is varied from 850 to 1050 °C, and the strain rate is differentiated from 0.01 to 1.0 s⁻¹. The measured stress-strain data are fitted using various constitutive models (combined with optimization techniques), namely, Johnson–Cook, modified Johnson–Cook, Zener–Hollomon, Hensel–Spittel, modified Hensel–Spittel, and modified Zerilli–Armstrong. The results are also compared with a model based on deep neural network (DNN). It is shown that the Hensel–Spittel model results in the smallest average absolute relative error among all the constitutive models, and the DNN model can perfectly track almost all the experimental flow stresses over the entire ranges of temperature, strain rate, and strain.

The hot deformation behavior (T = 800–1100 °C, $��\dot{\epsilon }�$ = 0.01–10 s⁻¹) of 40CrNiMo steel for wind turbine pulley shafts was studied by Gleeble-3800 thermomechanical simulator. A constitutive equation and hot processing map are established based on the friction and temperature correction curves. The most available hot processing parameters are determined by combining microstructure analysis. The temperature fields and effective strain fields under different deformation conditions are simulated by Deform-3D software. The results indicate that the effect of friction on the flow curves is greater than that of temperature rise, the activation energy Q of hot deformation for 40CrNiMo steel calculated based on the theoretical calculation is 368.292 kJ mol⁻¹. The constitutive model based on strain compensation has high accuracy, with an average relative error of 6.65% and a correlation coefficient of 0.987. The optimum hot processing interval is at a deformation temperature of 950–1050 °C and a strain rate of 0.03–0.25 s⁻¹, which has a high-power dissipation value and avoids the instability region. Additionally, numerical simulation results show that the temperature field distribution is uniform in this deformation range, and the standard deviation of the effective strain is low, making it suitable for hot processing.

Hydrogen-induced cracking (HIC) in high-strength 45CrNiMoVA steel is investigated using smooth and notched cylindrical specimens by performing uniaxial tensile tests. Specimens with different notch geometries are used to analyze the interacting effects of the stress concentration factor and HIC micromechanism. The results show that hydrogen charging reduces the elongation at fracture and the ultimate tensile strength of smooth tensile specimens. The microscopic fracture mode changes from ductile dimples with some quasicleavage fracture without hydrogen to a mixture of brittle quasicleavage and intergranular cracking with hydrogen. For notched specimens with a lower notch root radius, significant stress concentration occurs at the notch root, which enriches hydrogen in these highly stressed regions. This causes a lower notch tensile strength and greater susceptibility to hydrogen embrittlement. Microfracture observations show that the area fraction of the intergranular cracking surface increases gradually, and the brittle zone moves farther away from the notch root upon decreasing the notch root radius, causing the embrittlement index to remain high. These results will help determine the applicability of existing steel for hydrogen service and also provide guidance for developing new high-strength martensitic steels that can resist hydrogen embrittlement.

A fluorine-free quaternary CaO–Al₂O₃–SiO₂–MgO refining slag for SWRS82B coil steel is studied by considering the requirements of the steel wire. Laboratory experiments are conducted to study the equilibrium and kinetics of steel–slag reactions. The physical and chemical properties of refining slags, including the melting temperature, viscosity, and MgO solubility, are estimated by FactSage7.2 calculation. The cleanliness of SWRS82B steel refined by slags with a basicity of 1 and C/A ratio in the range of 1.36–7.13 is studied systematically. The plasticity of inclusions is studied by phase diagram and Young modulus calculation. Deoxidizing capacity and desulfurization capacity of refining slags are discussed by kinetic calculation of steel–slag reactions based on FactSage7.2 macro-editing and the kungliga tekniska högskolan model. Slag with a composition of 42%CaO–47%SiO₂–4%Al₂O₃–7%MgO has the best refining effect, in which impurity elements are lowest and plastic inclusions with the smallest size and least quantity are obtained. The impurity elements oxygen and sulfur in steel can be controlled for 29 and 75 ppm, respectively. The average size of inclusions is 1.54 μm. The majority of inclusions are in a liquid state at 1600 °C and Young modulus of the inclusions ranges from 99.78 to 152.87 GPa.

Classification of cast iron alloys based on graphite morphology plays a crucial role in materials science and engineering. Traditionally, this classification has relied on visual analysis, a method that is not only time-consuming but also suffers from subjectivity, leading to inconsistencies. This study introduces a novel approach utilizing convolutional neural networks—MobileNet for image classification and U-Net for semantic segmentation—to automate the classification process of cast iron alloys. A significant challenge in this domain is the limited availability of diverse and comprehensive datasets necessary for training effective machine learning models. This is addressed by generating a synthetic dataset, creating a rich collection of 2400 pure and 1500 mixed images based on the ISO 945-1:2019 standard. This ensures a robust training process, enhancing the model's ability to generalize across various morphologies of graphite particles. The findings showcase a remarkable accuracy in classifying cast iron alloys (achieving an overall accuracy of 98.9 ± 0.4%—and exceeding 97% for all six classes—for classification of pure images and ranging between 84% and 93% for semantic segmentation of mixed images) and also demonstrate the model's ability to consistently identify and graphite morphology with a level of precision and speed unattainable through manual methods.

The API K55 grade steel is widely utilized in seamless pipes for oil and gas exploration, especially as casing pipes for wellbores. Traditionally, this steel is processed using hot rolling followed by quenching and tempering to achieve the desired dimensional and microstructural characteristics, balancing high strength with ductility. This article introduces an alternative method to attaining the required tensile properties for API K55 grade steel by employing a biphasic microstructure (ferrite/martensite) achieved through quenching post-intercritical austenitizing heat treatment to high-strength-low-alloy steel. Thermodynamic simulations and dilatometric experiments revealed that increasing the austenitizing temperature enhances austenite formation, decreasing significantly its carbon content, which facilitates martensitic transformation and increases the M_s and M_f temperatures. A complete phase transformation mapping was presented, highlighting how the austenitizing temperature influences martensitic transformation kinetics during the quenching heat treatment. It was concluded that austenitizing at 750 °C, followed by quenching and short tempering at 650 °C, produced a biphasic microstructure with 30% ferrite and 70% martensite, providing a favorable balance between mechanical strength and ductility that meets the API K55 grade requirements, surpassing traditional methods in the industry.