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Thermal hysteresis in fusion welding causes significant weld deterioration in medium- and high-carbon steels. Therefore, the development of an effective alternative welding process is required. Friction stir welding (FSW) is a solid-state welding process performed in an atmosphere that reduces the risks associated with melting and solidification of metals, making it an effective alternative method. Furthermore, it facilitates a flexible in-process control of heat input, which can be achieved by controlling the welding parameters. Considering these, the authors conducted a series of studies to elucidate the characteristics of FSW for medium- and high-carbon steels, including high-strength tempered steels.

This paper presents the results of applying FSW to 1.4 GPa-grade tempered JIS-S55C steel plates. Five distinct weld types were created by varying the welding parameters, including tool rotation and welding speed. The temperature of the interface between the tool and in-process material was measured using a thermal imaging camera. The microstructure of the welds was evaluated using optical microscopy and field-emission scanning electron microscopy (FE-SEM) with an electron-backscatter diffraction (EBSD) measurement system. The mechanical properties of the welds were evaluated through Vickers hardness and tensile tests. Digital image correlation analysis was employed to analyze the local deformation during the tensile test.

Fe-9 mass%Ni alloy is widely used as a cryogenic steel owing to its excellent low-temperature strength and toughness. However, Ni is an expensive element, with medium-Mn steel considered an inexpensive alternative. Considering the Fe-10%Mn-0.1%C alloy is brittle at low temperatures, the application of intercritical annealing with two-step hot rolling could lead to toughening. Herein, the effect of intercritical annealing on the toughness of a Fe-10%Mn-0.1%C alloy with elongated prior-austenite grains (PAGs) formed via a two-step hot-rolling process was investigated. Intercritical annealing was performed on the specimens with and without two-step hot rolling. For both specimens, intercritical annealing resulted in softening of α'-martensite and an increase in the amount of retained austenite. In the specimen not subjected to the two-step hot rolling process, the fracture morphology transitioned from ductile to intergranular with a decrease in the temperature. Intercritical annealing improved the toughness when ductile fracture occurred. In the case of intergranular fracture, the effect of intercritical annealing on the toughness was negligible. In the two-step hot-rolled specimen with elongated PAGs, the fracture morphology transitioned from ductile to separation fracture with ductile fracture, and intercritical annealing improved the toughness at all temperature ranges. The improvement in toughness during separation fracture is attributed to the expansion of the plastic zone owing to ductile crack progression and the formation of sub-cracks, which promote the strain-induced transformation of retained austenite and ε-martensite.

The effect of MnS inclusions on the localized corrosion of low-alloy steel in a 0.5 mol/kg (3 %) NaCl solution was investigated to propose countermeasures for inhibiting localized corrosion initiated by MnS inclusions. Low alloy steels without MnS inclusions did not corrode in a 0.5 mol/kg (3 %) NaCl solution, regardless of the addition of Cu. That is, no matrix improvement effect due to solute Cu was confirmed. Slight corrosion occurred in the Cu containing steel with MnS inclusions; however, the MnS inclusions remained. Cu_7.2S₄ precipitated on the MnS in contact with a 0.5 mol/kg (3 %) NaCl solution. Therefore, Cu_7.2S₄ precipitates on the MnS inclusions during immersion, which could suppress the localized corrosion initiated by the MnS inclusions because Cu sulfide is not dissolved based on potential-pH diagram. The addition of Cu in a 0.5 mol/kg (3 %) NaCl solution does not improve the corrosion resistance of the matrix due to solute Cu but does suppress localized corrosion initiating from MnS by precipitating Cu sulfide on MnS.

Under certain conditions, the whole roll flatness meter outputs a bimodal waveform signal, which is clearly different from the conventional unimodal waveform signal. Since detection relies on the extraction of crest values and the values of the two waveforms do not have the same linearity, the presence of the two waveforms of different channels will clearly give rise to errors in the calculated flatness distribution. To develop an effective extraction method, it is necessary to accurately analyze the evolution of the waveforms. In this paper, the finite element method is used to calculate the load of the sensor, the stress distribution of each analysis surface and the deformation of the sensor mounting hole during the real-time detection to analyze the mechanism of the waveforms. The results show that unimodal and bimodal waveforms are produced under different strip tension and wrap angle conditions. In addition, the radial stress of the roll surface always presents two stress wave distributions. With increasing strip tension or wrap angle, the phase difference between the two waves increases. The stress distribution will change the deformation trend of the mounting hole and affect the stress distribution state of the sensor. When the phase difference of the stress waves exceeds the covering range of the sensor, the output signal changes from a unimodal waveform to a bimodal waveform. Finally, by setting up an experimental platform with variable tension and wrap angle, the relationship between the output waveforms and the working conditions in the simulation is reproduced.

The effect of MgO/CaO ratio on the viscosity and free running temperature of chromium-containing high-titanium blast furnace slag (CaO-SiO₂-Al₂O₃-MgO-TiO₂-Cr₂O₃) was investigated by a rotating crucible viscometer. When the ternary basicity with a fixed (CaO+MgO)/SiO₂ ratio of 1.41 and the temperature was fixed, the MgO/CaO ratio had an obvious influence on the viscosity of slags. Increasing MgO/CaO ratio from 0.34 to 0.44 caused a slight decrease in the viscosity of the slag, and had an opposite effect when MgO/CaO ratio was more than 0.44. The XRD measurements showed that the technology of ‘‘replacing CaO with MgO'' has an effect on the precipitation temperature of perovskite phase and spinel phase. Accroding to the Raman spectroscopy results, with the increase of MgO/CaO ratio from 0.34 to 0.44, the DOP decreased, and then increased as the MgO/CaO ratio increased from 0.44 to 0.56.

Metallurgical industries often discharge slag containing valuable elements that are poorly utilized when producing copper alloys and silicon-manganese alloys. To improve the utilization rate, in this study, a method to mix copper slag with water-quenched silicon-manganese slag and CaO for roasting and modification was proposed. In this work, FactSage 8.0, DSC-TG, and XRD were used to examine the phase change during the modification process and investigate the impacts of the CaO content, roasting temperature, and holding time on the modification effect. The results showed that the addition of water-quenched silicon-manganese slag and CaO could effectively promote the transformation of fayalite to (Mn, Mg, Fe)Fe₂O₄, with the highest conversion rate occurring at a 10% CaO content. An increase in the temperature and prolongation of the time facilitated fayalite transformation, but excessive temperature or time could result in iron loss. The optimal recovery rate and iron grade were achieved with roasting at 1400 °C for 60 min. This method can provide a concentrate suitable for producing copper-containing antibacterial stainless steel and wear-resistant cast iron, and the tailings can be used to produce ceramic materials.

Atomic-scale lattice defects beneath various hydrogen embrittlement fracture process regions, i.e., different fracture modes, were compared for martensitic steel. The crack initiation region containing quasi-cleavage (QC) and intergranular (IG) fracture, the crack propagation region mostly consisting of IG fracture, and the final fracture region completely composed of microvoid coalescence (MVC) were extracted from the same fracture surface and analyzed by low-temperature thermal desorption spectroscopy (L-TDS). The relative shapes of the L-TDS curves were different at the sampling positions, demonstrating at the atomic-scale that the types and numbers of lattice defects formed vary depending on the fracture process and fracture mode.

Knowledge of the viscoelastic properties of suspensions is essential for many industrial processes. Although oscillation and creep testing are widely used to measure the viscoelastic properties of complex fluids, few studies on the correlation between the viscoelastic properties measured using these methods have been published. This study aims to provide insights into the differences between these methods and determine which method is better suited for a particular application. The room-temperature viscoelastic properties of a suspension composed of polyethylene beads dispersed in a silicone oil matrix were measured by oscillation and creep testing and compared. The results of oscillation testing indicated that the suspension showed weakly elastic deformation, whereas the results of creep testing revealed that the suspension was relatively elastic, with the liquid phase showing lower viscosity. In addition, the viscosity measured by oscillation testing was lower than that measured by creep testing. When the imposed flow causes microstructural changes, such as when the shear flow and particle‒particle contact induce aggregation, the analyzed flow property considerably differs between testing methods.

A brace-type seismic damper made of an Fe-15Mn-11Cr-7.5Ni-4Si alloy solidified in the ferrite-austenite (FA) mode and SN490B steel, which can be constructed via welding, was proposed. To realize the proposed seismic damper, gas metal arc welding was applied to produce similar FMS/FMS fillet welds and dissimilar FMS/SN490B fillet weld joints. Based on the Schaeffler diagram, similar and dissimilar welding consumables were designed such that the fillet weld metal solidified in the FA mode without solidification cracking. Sound similar fillet welded joints were obtained using two types of welding consumables with different Cr/Ni equivalent ratios although both the similar fillet weld metals had a coarse columnar austenite grain structure. These displayed higher tensile strengths (716–736 MPa) and marginally lower elongations (67–70%) than the FMS alloy. Moreover, a similar fillet weld metal with a chemical composition almost identical to that of the FMS alloy exhibited a remarkable low-cycle fatigue life (5740 cycles). This was shorter than that of the FMS alloy (9351 cycles) owing to the easier formation of α'-martensite. A dissimilar fillet welded joint with a chemical composition within the austenite region was produced without solidification cracking. The dissimilar fillet weld metal showed high tensile strength (867 MPa) and total elongation (61%). These were comparable to those of similar fillet weld metals.

Recently, remarkable advances have been made in statistical analyses based on deep-learning techniques. Applied studies of deep learning have been reported in various industrial fields, including the iron and steel-making industries. The production of iron and steel requires a variety of processes, such as the processing of ingredients, iron-making, casting, and rolling. Consequently, the data acquired from them are diverse, and various tasks exist that can be assisted by deep-learning algorithms. Hence, providing a summary of the application is helpful for researchers specializing in information science to grasp the current trend of applied studies on deep learning techniques and for researchers specializing in each field of the iron and steel-making industry to understand what types of deep learning techniques are being utilized in other specialized fields. Therefore, in this study, we summarize the current studies on the application of deep learning in the iron- and steel-making fields by organizing them into several categories of processes and analytical methodologies. Furthermore, based on the results, we discuss future perspectives on the development of deep-learning techniques in this field.