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This study reports a case of cold cracking along welds, which arises from solidification cracking within the crater during the laser welding of high-strength steel sheets. In this investigation, we aimed to delineate the factors influencing cold cracking that originates from solidification cracking in the crater. This was achieved by using steel sheets whose mechanical properties (tensile strength: 0.6 to 1.5 GPa) and chemical composition (carbon content: 0.20 to 0.55%) were individually adjusted. The evaluation method involved performing laser welding in a stitch pattern on an oiled steel sheet, with variations in welding length. The evaluation focused on the maximum welding length at which cold cracking occurred (L_MAX). The results indicated that while a high tensile strength of the steel sheet marginally increased the L_MAX, the impact remained limited. Conversely, the carbon content of the steel sheet significantly influenced cold cracking; the L_MAX for carbon contents of 0.30% and 0.45% was substantially greater than that for 0.20%. However, an unusual behavior was observed at a carbon content of 0.55%, where the L_MAX was smaller than that for 0.45%, despite the significant hardening of the weld metal. This phenomenon was hypothesized to occur because the tensile residual stresses in the welds decreased as martensitic transformation starting temperature lowered and the expansion strain during the transformation increased with higher carbon content.

Reasonable gas flow distribution plays a decisive role in the smooth operation of blast furnace smelting, but it is difficult to detect the gas flow distribution in blast furnace in real time. An intelligent prediction and identification system of central gas flow distribution based on infrared image of blast furnace and cross-beam temperature measurement is constructed(C-GFD). The system is mainly composed of two models, namely the image model and the prediction and recognition model. In the image model, three kinds of derived parameters, namely, central gas flow area, temperature and offset, are extracted by the image entropy and neighbourhood valley-emphasis (ENVE) Otsu, thermodynamic heat transfer and grey scale centroid algorithms, and then the statistical relationship between the change of image information and the distribution of gas flow is investigated. In the prediction and recognition model is established by the algorithms based on convolutional neural network long and short-term memory (CNN-LSTM) and Euclidean-weighted fuzzy C-mean clustering (E-FCM) to complete the prediction of the three types of derived parameters, and the prediction data is transferred to the recognition model to complete the recognition of the central gas flow distribution pattern. The test results show that the system provides real-time and reliable gas flow reference information for blast furnace operators with 95% accuracy in model prediction and more than 90% accuracy in pattern recognition of various types of central gas flow distribution.

To develop a H₂ production and CO₂ fixation process using scrap iron, the characteristics of iron and steel particles that react efficiently were investigated. The reaction of commercial pure iron and alloyed steel powders were compared, and their reactivity was evaluated based on the specific surface area, apparent density, and crystal lattice strain. The efficient reactivity in porous iron powders was attributed to crevice corrosion. To investigate the effect of alloy composition, we added Ni to pure iron powder by pretreatment, which resulted in enhanced H₂ production and CO₂ fixation. The results indicated that galvanic corrosion contributes to Fe oxidation, because Fe is less noble than Ni based on their electrode potentials. This study provides guidelines for improving the efficiency of reactions that produce H₂ while fixing CO₂ using steel scrap.

In steel rail production, complex deformations can induce non-uniform changes in cross-sectional profiles along the rail's length, resulting in unevenness and safety implications. It is essential to perform dimensional testing to ascertain compliance with standard requirements. Currently, profile inspection results are manually evaluated, posing efficiency challenges and a lack of standardized criteria.To address this challenge, this paper proposes an online automatic steel rail segmentation and evaluation method (online-ASE) based on pattern matching and complex networks to enable automatic rail profile assessment. This method initially utilizes offline high-dimensional time series data for conducting Toeplitz Inverse Covariance-based Clustering (TICC) training and constructs a standard quality characterization pattern library through distinct inverse covariance structures between abnormal and normal high-dimensional quality characterization indicators of steel rails. When applied online, the Viterbi shortest path dynamic programming algorithm is utilized to match steel rail data with the pattern library, swiftly identifying anomalous rail segments. Additionally, the algorithm computes the contribution of steel rail quality parameters to the segmentation results using complex network betweenness centrality, thereby explaining the reasons for segment formation. These explanations provide a reference basis for subsequent steel rail repairs. Finally, the effectiveness of the proposed method is validated using real-world steel rail data from a specific steel factory in China.

Vanadium composite electrogalvanized (Zn–V hydroxide) steel sheets were prepared by electroplating using a horizontal flow cell. The structure of the Zn-V plating layer depended on the flow rate of electrolyte and the current density, and the performance of Zn-V steel sheets depended on the structure of plating films. The Zn-V plating films composed of two-phase structure without cracks showed the high corrosion resistance and high adhesion. The two-phase layer consisted of the field-oriented fiber and non-field oriented texture. The field oriented fiber phase was mainly formed from the amorphous V compound. The V compound in the non-field oriented phase seems to hydrogen evolution during Zn-V composite plating. The Zn-V steel sheets had a black and low-gloss appearance compared to the conventional electrogalvanized steel sheet (EG). Since the V compound in the non-field oriented texture was black and the field oriented texture formed the surface roughness, the lightness and gloss of the Zn-V steel sheets decreased with increasing V content in plating films.

This paper reports an improved method for sample preparation of a stainless steel sample for inductively coupled plasma mass spectrometry. Conventional digestion methods using a digestion agent containing hydrochloric acid affect chlorine spectral interference such as that by ³⁵Cl¹⁶O⁺ or ⁴⁰Ar³⁵Cl⁺. Alternatively, a microwave digestion method using an acid mixture of nitric acid and hydrofluoric acid can fully eliminate these interferences. The suggested procedure can contribute to more reliable quantification of titanium, vanadium, arsenic, niobium, tin, and antimony in stainless steel samples using a low-resolution quadrupole mass spectrometer.

The contribution of dislocation-slip stability and carbide precipitation morphology to the hydrogen embrittlement (HE) property of tempered martensitic steels with low and high silicon contents (L-Si and H-Si) and oil-quenched martensitic steel (As-OQ), was evaluated by conducting slow strain rate tests. The order of dislocation-slip stability was the H-Si specimen > L-Si specimen > As-OQ specimen. The H-Si and As-OQ specimens had finely dispersed carbides inside prior austenite (γ) grains, whereas the L-Si specimen had coarsely dispersed carbides inside prior γ grains and on the boundaries. Notched specimens were charged with hydrogen in a range of low (0.19-0.31 ppm), medium (1.04-1.49 ppm), and high (2.17-2.33 ppm) hydrogen contents. The H-Si specimen had the highest HE property under the three hydrogen charging conditions. With the low and medium hydrogen charging conditions, the HE property of the L-Si specimen was higher than that of the As-OQ specimen, whereas their HE properties markedly declined to a similar level under the high hydrogen charging condition. The HE property of the L-Si specimen with increased dislocation-slip stability by applying stress relaxation was equivalent to that of the L-Si specimen under the high hydrogen charging condition. These results revealed that increasing dislocation-slip stability improved the HE property in the range of low to medium hydrogen charging. Under the high hydrogen charging condition, dislocation-slip stability did not contribute to improving the HE property, but it was found that the carbide precipitation morphology, particularly coarse carbides precipitated on prior γ grain boundaries, influenced the HE property.

An 11 mass% Cr ferritic/martensitic steel was subjected to a standard heat treatment consisting of normalizing and tempering and subsequently, a thermomechanical treatment (TMT) process involving austenization at 1100 °C for 1 hour, warm-rolling with 93% deformation at 650 °C and tempering at 650 °C for 1 hour. The precipitate phases of the TMT-processed steel were qualitatively analyzed using transmission electron microscopes and energy dispersive X-ray spectrometers in combination of lattice parameter calculation. Nb-rich MC carbides and Nb-rich M(C,N) carbonitrides pre-existing in the normalized-and-tempered steel were also observed in the TMT-processed steel. Eight types of precipitate phases introduced by the TMT were identified in the TMT-processed steel. They are Nd-rich MC carbide with a face-centered cubic crystal structure and lattice parameter a = 1.1408 nm, Cr-rich M₂C carbides/Cr-rich M₂X (Cr₂C type) carbonitrides/Cr-rich M₂X (Cr₂N type) carbonitride with a hexagonal crystal structure, Cr-rich M₇C₃ carbides/Cr-rich M₃C₂ carbide/V-rich M₂(C,N) carbonitride with a simple orthorhombic crystal structure, and Mn-rich M₅C₂ carbide with a base-centered monoclinic crystal structure. Among these identified precipitate phases, Nb-rich MC carbides, Nb-rich M(C,N) carbonitrides, Cr-rich M₂C carbides and Cr-rich M₂X (Cr₂C type) carbonitrides are dominant phases, while the other six precipitate phases are minor phases, in the TMT-processed steel. The identified precipitate phases are also discussed.

In this study, a non-isothermal reduction kinetics model has been developed for a single self-reducing iron ore pellet (SRP) to enhance the understanding of the reduction kinetics especially in the thermal reserve zone (TRZ) of the blast furnace (BF). The model simulates the mass changes and chemical processes during reduction, incorporating the effects of temperature, gas composition, and pellet composition on the reduction kinetics of different iron oxide phases, including Fe₂O₃, Fe₃O₄, and FeO. A mathematical model, comprising a comprehensive set of ordinary differential equations (ODEs), has been developed and solved using numerical methods and MATLAB software. The model has been rigorously validated against previous studies, specifically under non-isothermal conditions. It enables the calculation of mass loss and the reduction extent of specific phases of iron oxide, with the rate constant (k-value) curve across different temperatures. Moreover, the model adaptability is highlighted by its effective application in various BF conditions, as demonstrated by its use with data from the reference plants.

This work aims to study the effect of pH₂O in the atmosphere during hydrogen reduction of iron oxide over a temperature range relevant to industrial practice. To further the industrial context, industrially produced hematite iron ore pellets are utilized. A resistance heated furnace was employed to conduct experiments, in the temperature range 873 K – 1173 K. A water vapor generator was used to control water vapor partial pressure during hydrogen reduction in the range 0-15% pH₂O. The system was carefully designed to ensure precise control of the water content in the reaction gas. Thermal Gravimetric Analysis (TGA) was used to follow the reduction of the iron ore pellets. To understand the reaction mechanisms, Scanning Electron Microscopy (SEM) was used to study the microstructure of partially reduced pellets. Results suggest the reduction rate is profoundly affected by water at 873 K, less so when the temperature is increased. The microstructure is also highly affected by pH₂O at 873 K, at higher temperatures the microstructure is less affected. The influences of gas dilution and chemical reaction rate on these aspects are discussed.