To address the challenges in predicting ductile fracture of 3Cr13MoV martensitic stainless steel under complex loading conditions, the fracture mechanisms were systematically investigated through mechanically testing under multi-axial stress states and microscopic damage evolution analysis. Based on the evolutionary processes of voids, a novel uncoupled ductile fracture prediction model was proposed. This model introduced maximum shear stress and maximum principal stress as damage evolution correction factors and quantitatively revealed the induction mechanism of maximum principal stress on void coalescence under stress triaxiality control. Finite element simulations and experimental validation showed that the model accurately predicts behavior across various stress levels.
Aluminum dross is a waste of the aluminum industry, and its improper disposal can pose negative environmental impacts. The metallurgical effects of utilizing nitrided aluminum dross in the smelting process of rebar steel are systematically investigated. Firstly, resistance furnace experiments were performed to evaluate the effects of nitrided aluminum dross addition on the oxygen content, aluminum content, and nitrogen content in steel, as well as the corresponding aluminum yield and nitrogen yield. Secondly, an analysis was conducted on the characteristics of inclusions resulting from the addition of nitrided aluminum dross to steel. Finally, based on the laboratory experimental parameters, industrial trials were conducted in steel plant. The laboratory results showed that as nitrided aluminum dross addition increased from 0.5 to 2.0 g per kilogram of molten steel, w[O] (reduction in oxygen content) increased from 0.0017 to 0.0028 wt.
Al-free-ODS and 4Al-ODS steels were fabricated to investigate the influence of Al addition on the microstructure, tensile and impact properties. The morphology, crystal structures and interface coherency with matrix of nano-oxide particles were characterized. The results show that the number density of nano-oxide particles in 4Al-ODS steel increased from 1.1 × 1023 to 1.3 × 1023 m−3, while the average size slightly increased from 8.2 ± 1.6 to 9.3 ± 1.6 nm compared to those in Al-free-ODS steel. Y2(Zr0.6Ti0.4)2O7 and additional YAlO3 nano-oxide particles were found in 4Al-ODS steel with better coherent relationship with the matrix. At room temperature to 1273 K, all tensile test results showed that the strength of 4Al-ODS steel consistently increased without a significant reduction of elongation. The total elongation tested at 973 K was about 49
The use of biochar can reduce fossil CO2 emissions from direct reduced iron (DRI)-based electric arc furnace (EAF) steelmaking. The effect of slag B2 basicity and FeO concentration on the interaction between pinebark-based biochar and TiO2- and V2O5-bearing DRI-based EAF slag was examined. For this, a carbonaceous material slag module (CSM) was prepared by placing a slag briquette on a biochar substrate, and the CSM underwent optical dilatometry (OD) at 1773 K in an argon atmosphere to assess the slag swelling index. It revealed that the slags with a B2 basicity of 1.5 and an FeO concentration of 40 wt.
To simultaneously enhance remanence (Br) and coercivity (Hcj) of NdFeB magnets, a powder-state regulation based on the characteristic columnar grain structure is developed. By matching the average powder particle size with the short-axis dimension of the columnar grains, the powder can be transformed from sharp-edged fragments into quasi-spherical particles with well-defined morphology during jet milling. The improved magnetic field alignment behavior originates from the synergistic optimization of particle size distribution and particle morphology. In addition, the quasi-spherical particles retain complete coverage of the rare-earth-rich (RE-rich) phase, which transforms into a uniform and continuous liquid phase during the heating stage of sintering. This effectively inhibits abnormal grain growth caused by direct contact between main-phase grains and weakens the intergranular magnetic exchange coupling. As a result, the Br increases from 1.462 to 1.481 T, while the Hcj is markedly improved from 823.86 to 1073.8 kA/m. The results demonstrate that tailoring powder characteristics based on the columnar crystal structure enables the formation of quasi-spherical particles uniformly coated with RE-rich phase, thereby optimizing the microstructure of NdFeB magnets and enhancing the magnetic properties.
The meltdown behaviors and mutual interactions among multiple direct reduced iron (DRI) pellets immersed in a molten steel bath were investigated, with the aim of improving melting efficiency and reducing energy consumption. A 3D transient model was developed by coupling the volume of fluid approach with the enthalpy–porosity method to resolve heat transfer and solid–liquid phase change of DRI after immersion. Model credibility was assessed using the predicted complete melting time of the solid phase. The results showed that increasing inter-particle spacing and preheating temperature noticeably shortens the melting time: When the spacing increases from 2 to 10 mm, the complete melting time decreases by 19.83
Head-end deviation at the finishing entry is strongly influenced by asymmetric roughing transfer-bar geometry, whereas direct measurements of strip posture and head-end shape are generally unavailable before biting at the first finishing stand (F1). To characterize this incoming asymmetry, the exit centerline curve of the second roughing stand (R2) is used as an upstream measurable descriptor and converted into a transfer-bar state representation. The centerline curve is classified into L-, C-, and S-type dominant camber patterns and parameterized by the signed head-end camber amplitude, camber length, global offset, and global deflection angle. These descriptors are introduced into a three-dimensional finite element model of the entry edger roll-strip-mill roll system. A representative industrial case is used for load-level validation, and the average relative error of the F1 total rolling force is 8.39
The efficient comprehensive utilization of vanadium–titanium magnetite is still a major challenge. In the context of low-carbon development, the low-temperature reduction separation is an appropriate process path. Sodium-based additives can significantly lower the reduction temperature. However, the high addition ratios reported in existing studies tend to exacerbate equipment corrosion and environmental concerns. The high-temperature characteristics of different sodium-based additives and the reduction thermodynamics, kinetics, and reduction separation effects assisted by these additives were thus examined to provide a reference for the application of the low-temperature reduction process utilizing low-proportion sodium-based additives. The results showed that Na2CO3 had the best reduction effect. The low melting point of NaOH exacerbated material adhesion to the reduction equipment. NaCl did not promote the reduction of FeTiO3, and the introduced Cl element would affect the composition of the flue gas. The S element introduced by Na2SO4 would enter the solid reduced product and form Fe1−xS. Under low-temperature and low-proportion additives conditions, the water leaching-magnetic separation effect was poor. Melting separation proved to be the preferred option, as it also circumvented the environmental issues associated with water leaching. After reduction (Na2CO3 content of 9 wt.
Accurate determination of the relationship among composition, process, and properties is crucial for predicting the yield strength of HRB400E rebar and enhancing the stability of its yield strength. Four yield strength prediction models of HRB400E rebar built using the random forest (RF) algorithm are compared, and a reverse process design is conducted based on the optimal model. The first model is an RF model driven solely by industrial big data, the second is an RF model with optimized hyperparameters (optimized RF model), the third combines physical metallurgy (PM) with industrial big data (PM-RF model), and the fourth is a dual-driven model of optimized PM and industrial big data (optimized PM-RF model). In the establishment of the optimized RF and optimized PM-RF models, a dynamic hyperparameter optimization algorithm was introduced, employing the Optuna optimization framework to optimize the curve parameters of an improved particle swarm optimization (PSO) algorithm with sigmoid-like inertial weight (Optuna-S-PSO). During the establishment of the PM-RF and optimized PM-RF models, the newly introduced input parameters, including ferrite grain size ( d_ ) and the fraction of precipitated phases in ferrite ( f_p- ), were calculated using the PM model. The results demonstrate that the application of the Optuna-S-PSO algorithm, along with the inclusion of PM parameters, significantly improves the models’ prediction accuracy. Among these, the optimized PM-RF model exhibited the highest yield strength prediction accuracy, with the coefficient of determination, root mean square error, and mean absolute error values of 0.856, 4.00 MPa, and 3.31 MPa, respectively. Based on this model, the SHapley Additive exPlanation (SHAP) method was used to comprehensively analyze the effects of composition, rolling parameters, and microstructure on the material’s yield strength. Ultimately, the yield strength fluctuation range of multi-specification HRB400E rebar is effectively reduced by reversely designing the rolling speed based on the optimized PM-RF model.
Traditional basic oxygen furnace (BOF) decarburization kinetic models often neglect material transport between zones and therefore fail to capture the dynamic evolution of carbon. To overcome these limitations, a modified kinetic model is proposed based on a multi-field coupled diffusion mechanism. First, candidate kinetic models for the BOF blowing process are reviewed. A three-zone framework that explicitly incorporates process control parameters is then selected based on industrial applicability and predictive accuracy. Within this framework, inter-zone diffusion flux terms are introduced to formulate carbon mass-transfer equations between the jet impact, emulsion, and slag–metal reaction zones. Diffusion driven by carbon concentration gradients is used to represent mass-transfer processes induced by intense convection and emulsification in the melt pool. The key diffusion coefficients, which cannot be measured directly, are identified by parameter inversion using industrial smelting data, and a “primary-to-secondary, stepwise optimization” calibration strategy is proposed. Using 9199 heats for training and 2300 heats for independent validation, the calibrated model accurately reproduces the nonlinear decrease in carbon content during the middle and final stages of blowing. Compared with the baseline kinetic model, the hit rate of end-blowing temperature–sampling–oxygen carbon predictions within the ± 0.025
WTaNbMo/Inconel 718 composite coatings were successfully fabricated using magnetic field-assisted laser cladding. Numerical simulations of the magnetic field-assisted laser cladding process were conducted to elucidate the influence of the magnetic field on the temperature and flow fields of the molten pool. The applied magnetic field enhanced melt convection, which promoted heat exchange with the laser beam and led to a more uniform energy distribution, thereby improving both the macroscopic forming quality and the microstructure of the coating. Furthermore, the influence of Inconel 718 content on the microstructure, hardness, and corrosion resistance was systematically investigated. Experimental results demonstrated that increasing the Inconel 718 content effectively eliminated micro-defects and significantly improved the corrosion resistance, albeit with a concomitant reduction in coating hardness. An optimal balance between hardness and corrosion resistance was achieved at 30 wt.
The corrosion of oxide scale on Q370qENH weathering steel and Q355C low-carbon steel within a simulated tropical marine environment was investigated. The results demonstrate that the oxide scales of both steels afforded protective effects to steel substrates at the initial corrosion stage but gradually deteriorated and ultimately failed with prolonged exposure. X-ray diffraction analysis (XRD) revealed the oxide scale composition of both steels to be magnetite (Fe3O4), hematite (α-Fe2O3), and wustite (Fe0.9O), with Q370qENH steel exhibiting a relatively lower mass fraction of Fe3O4 and a relatively higher mass fraction of Fe0.9O. The (Fe7.6Ni0.4)O6.44(OH)9.56Cl1.16 and Fe8O8(OH)8Cl1.35 were detected by XRD within the rust layers of Q370qENH and Q355C steels, respectively, with both compositions classified as akaganeite (β-FeOOH). The rust layer of Q370qENH steel contained NiO, NiFe2O4, Cr(III) oxide, FeCr2O4, and NiCr2O4. Under cyclic wet–dry conditions, the oxide scale failure time was approximately 80 d. Q370qENH steel exhibited lower corrosion mass loss, but it exhibited relatively more severe and wider-spread pitting compared to Q355C steel.
A collaborative framework integrating phase diagram digitization, sparse region identification, molecular dynamics simulations, modified Arrhenius equation fitting, and adaptive multi-source ensemble learning is developed for viscosity prediction of CaF2–CaO–Al2O3/SiO=2 slag systems in electroslag remelting. The methodology overcomes challenges posed by high-temperature measurement limitations and sparse compositional coverage by expanding experimental data through systematic phase diagram analysis and supplementing missing values via molecular dynamics simulations in the liquid phase region and empirical extrapolation. An adaptive ensemble strategy combining categorical boosting, eXtreme gradient boosting, and support vector regression achieves test-set performance metrics: 0.0413 for mean squared error, 0.0886 for mean absolute error, and 0.857 for R2 (coefficient of determination), representing a 5.8-fold increase in compositional–temperature space coverage with minimal experimental cost. Microstructural analysis reveals that Al2O3 functions as a “weak network former” with a critical threshold at 20
As a core high-energy-consuming unit in the steel industry, the steel rolling reheating furnace (SRRF) presents a critical technical challenge in achieving energy savings and carbon emission reduction through accurate energy consumption prediction. The multivariable coupling and high-dimensional nonlinear characteristics of SRRF operational data were addressed by systematically evaluating four feature selection methods: principal component analysis (PCA), process-driven feature engineering, Spearman correlation filtering, and random forest (RF) feature importance. These methods were integrated with two machine learning algorithms, RF and gradient boosting regression tree (GBRT), to develop predictive models for specific energy consumption. Based on 2000 real production data samples collected from a steel plant, a high-quality dataset of 1251 samples was constructed using a combined boxplot–process threshold filtering strategy. To eliminate dimensional inconsistencies, all features were normalized using the min–max scaling method. Experimental results show that using the top nine features identified by RF importance ranking (accounting for approximately 50
To address the excessively rapid degradation issue of magnesium (Mg) alloys, ZK60/hydroxyapatite (HA) composites were fabricated via multi-pass friction stir processing (FSP). The effects of rotational speeds (1300, 1500, 1700 r/min) and FSP passes (1, 3, 5) on the microstructure and comprehensive performance of the composites were investigated through microstructure observation, mechanical property test, electrochemical measurements and antimicrobial assays. Microstructural analysis revealed that grain refinement and uniform HA dispersion are achieved due to the severe plastic deformation and dynamic recrystallization. S1500-3 composite (1500 r/min, 3 FSP passes) exhibits optimal comprehensive properties with the average grain size of 1.53 μm, ultimate tensile strength of 226.3 MPa and microhardness of 65.9 HV0.1. Micro-area electrochemical analysis indicates uniform current density distribution in Hank’s solution while polarization curves reveal a maximum corrosion potential of –1.3397 V, confirming the excellent corrosion resistance of S1500-3 composite. Antimicrobial assays demonstrated that S1500-3 composite exhibited an 87.27
High-manganese twinning-induced plasticity (TWIP) steels exhibit an outstanding combination of strength and ductility; however, their industrial application is limited by pronounced elemental segregation and coarse columnar grains that develop during solidification. Fe–23Mn–0.45C–1Al–1Cu TWIP steels were fabricated through copper-mold injection rapid solidification to systematically examine the effects of rare-earth lanthanum (La) additions (0–0.20 wt.
As metallurgical solid wastes, red mud and converter slag require substantial storage space and pose serious environmental risks. Owing to their abundant Fe and Al contents, red mud can serve as a modifier for converter slag. The phase evolution and degree of polymerisation of the slag before and after modification and leaching were characterised by X-ray diffraction, scanning electron microscopy-energy dispersive spectroscopy, Raman spectroscopy, and Fourier transform infrared spectroscopy. Increasing the red mud addition from 0 to 8 wt.
