A transient numerical model is developed to investigate the influence of AC frequency and slag properties on the transport and entrapment of exogenous and endogenous nonmetallic inclusions (NMIs) during electroslag remelting. The model simulates the remelting of a 500 mm diameter consumable electrode into a 750 mm diameter ingot by coupling electromagnetics, fluid flow, heat transfer, solidification, dynamic ingot growth, and Lagrangian inclusion transport. The results show that thermal buoyancy dominates melt flow in the steel, while the combined effects of the Lorentz force and slag‐induced momentum transfer generate a localized secondary electro‐vortex beneath the slag–metal interface that strongly influences inclusion transport and residence time. Exogenous NMIs preferentially accumulate near the ingot periphery, whereas small endogenous NMIs remain suspended for longer periods, resulting in a more uniform radial distribution. Reducing the AC frequency from 50 to 1 Hz or replacing the CAF 6 slag with CAF 4 weakens the secondary vortex, producing a slightly shallower melt pool, increasing inclusion residence time, and promoting a more uniform NMI distribution throughout the ingot. Model predictions are validated against experimental measurements of the melt pool geometry and radial NMI distribution.
Fe–Mn–Al–C lightweight steels are promising candidates for weight‐sensitive structural components. However, the role of compositional tailoring in governing strength–ductility synergy remains to be fully clarified. In this study, Fe–Mn–Al–C steels with varying Si contents were designed and subjected to solution treatment to systematically investigate the effects of Si on microstructural evolution and tensile deformation behavior. As the Si content increased from 0.2 to 1.5 wt.%, all tested steels retained a single‐phase austenitic structure. The effective grain size increased from 40.5 to 62.4 μm, the fraction of annealing twins rose from 47.9% to 52.5%, and lattice distortion became more pronounced, while stacking fault energy decreased from 44.1 to 41.3 mJ/m 2 . The reduced stacking fault energy promotes the nucleation and sustained multiplication of deformation twins during tensile deformation, strengthens the interaction between dislocation slip and mechanical twinning, and maintains high work‐hardening capability. Si‐induced solid‐solution strengthening, together with TWIP‐assisted dynamic subdivision of austenite grains, suppresses strain localization and enables simultaneous improvement in strength and ductility. Within the investigated composition range, the 1.5Si steel exhibits the optimal strength–ductility combination, with a yield strength of 378 MPa, an ultimate tensile strength of 761 MPa, and an elongation to fracture of 49.1%.
Tensile tests were conducted on 20Cr13/3003 steel–aluminum composite plates, comprising 20Cr13 martensitic stainless steel and 3003 Al─Mn alloy, at temperatures ranging from 25 to 300 °C using a Shimadzu AGX‐V 100 kN universal testing machine. Scanning electron microscopy and electron backscatter diffractionwere used to characterize the fracture morphology and microstructural evolution of the specimens at different temperatures. The results indicate that, as the tensile temperature increases, the strength of the steel–aluminum composite plate decreases monotonically, whereas the elongation first decreases, then increases, followed by a slight decrease and a subsequent increase. Fractographic analysis of the steel–aluminum composite plate at different temperatures reveals that its fracture behavior is strongly temperature‐dependent. As the tensile temperature increases, the fracture mechanism transitions from brittle fracture to ductile fracture. The dislocation structure evolves through competition between deformation‐induced dislocation accumulation and thermally activated dislocation rearrangement and recovery, while recovery and recrystallization become increasingly pronounced at elevated temperatures. At 300 °C, the deformation compatibility between the steel and aluminum layers improves, and interfacial bonding is enhanced. The Goss texture in the steel layer reappears, the texture intensity decreases, and the texture of the aluminum layer becomes nearly random, thereby mitigating stress concentration.
Intergranular oxidation (IGO) in 22MnB5 steel degrades automotive component performance, yet oxygen supply mechanisms under low oxygen potentials remain unclear. This study reveals that IGO occurs exclusively below 900 °C, with the depth exhibiting a C‐curve temperature dependence with a 751 °C nose temperature. Depth evolution follows logarithmic kinetics rather than Wagner’s parabolic law due to grain boundary diffusion channel blockage. Crucially, the oxide scale decomposition‐driven oxygen supply mechanism is systematically quantified for the first time: Under vacuum, oxide scale decomposition releases oxygen that propagates IGO to 26.4 μm after 8 h at 750 °C—a 136% increase over conventional oxidizing conditions—causing monotonic depth growth deviating from classical C‐curve behavior. Focused ion beam–energy‐dispersive X‐ray spectroscopy reveals a core–shell oxide structure (SiO 2 core/Cr 2 O 3 inner shell/MnO outer shell) governed by selective oxidation thermodynamics and diffusion kinetics. Industrial validation confirms 15 μm IGO depth in hot coil slow‐cooling zones, matching laboratory FeO decomposition results. Accordingly, optimized processing—lower coiling temperatures, front‐stage laminar cooling, and forced post‐coil cooling—was validated to suppress IGO below 5 μm. This work establishes a thermodynamic–kinetic framework for IGO in hot stamping steels, bridging fundamental mechanisms with industrial practice to resolve surface quality degradation through targeted process control strategies.
Temperature detection in ironmaking and steelmaking processes is crucial for enhancing quality control, achieving precise closed‐loop control, optimizing production procedures, and reducing carbon emissions. Traditional infrared temperature detection technologies suffer from limitations such as insufficient measurement accuracy, difficulty in separating background interference, and significant response delays, making them inadequate for meeting the stringent requirements of high‐temperature, high‐pressure, and high‐precision real‐time temperature measurement in the steel industry. This article analyzes the current state of online temperature detection technologies in ironmaking and steelmaking processes and examines the temperature measurement requirements across different production stages. Then, a high‐temperature online detection technology system based on multispectral and multi‐information fusion is proposed, incorporating multispectral sensors, noise filtering, image recognition of interference zones, and colorimetric thermometry models. The application of multispectral temperature measurement is demonstrated in key areas including online temperature monitoring of the blast furnace tuyere zone, inside refining furnaces, on the surface of continuous cast slabs, and during the cooling process of wire rods. The proposed online temperature detection technology fuses multispectral radiation data, image‐derived features (e.g., texture and morphology of slag/scale), and process parameters. Compared with prior studies, the main novelties of this work lie in: (1) the real‐time integration of multispectral imaging and deep learning‐based semantic segmentation within a unified system, enabling automatic interference isolation and net‐surface temperature extraction; and (2) the field validation of the same technological framework across multiple key stages of steel production—from ironmaking and steelmaking to continuous casting and rolling—demonstrating its broad adaptability and engineering practicality. This integrated approach is expected to advance the development and application of AI‐enhanced high‐temperature online detection technologies in steel production processes. This article serves as a state‐of‐the‐art review, incorporating representative case studies from the authors’ own research group to illustrate the practical implementation and effectiveness of the proposed technology system.
