Long-term steel reinforcement corrosion greatly impacts reinforced concrete structures, particularly in marine and coastal settings. Concrete failure leads to human casualties, requiring extensive demolition and maintenance, which represents an inefficient use of energy and resources. This study utilizes microscopic observation, atomic force microscopy (SKPM), electrochemical experiments, and XPS analysis to investigate the corrosion behavior of 500CE and 500E under identical conditions. We compared 500E with 500CE, supplemented with 0.94% Cr, 0.46% Mo, 0.37% Ni, and 0.51% Cu through alloying element regulation to obtain a finer ferrite grain and lower pearlitic content. The results indicate that 500CE maintains a stable potential, whereas 500E exhibits larger grain sizes and significant surface potential fluctuations, which may predispose it to corrosion. In addition, despite its more uniform microstructure and stable electrochemical activity, 500E shows inferior corrosion resistance under prolonged exposure. The electrochemical corrosion rate of 500CE in both the pristine and passivated states and for various passivation durations is slower than that of 500E, indicating superior corrosion performance. Notably, there is a significant increase in the corrosion rate of 500E after 144 h of exposure. This study provides valuable insights into the chloride corrosion phenomena of low-alloy corrosion-resistant steel reinforcement in service, potentially enhancing the longevity of reinforced concrete structures.

As the pace of human development in the ocean accelerates, the demand for corrosion-resistant building materials in marine engineering projects is constantly increasing. The development of high-performance corrosion-resistant materials and their mechanism research has gradually become the latest hotspot in the field of metal materials. Through cyclic dry–wet testing, electrochemical techniques, morphological characterization, and compositional analysis, this study simulated the impact of varying manganese content on weathering steel corrosion resistance in chloride environments. The results indicated that, compared to low-manganese weathering steel, the average rust layer thickness of high-manganese weathering steel increased by 22.5%. Additionally, manganese was found in the rust as MnO/MnO₂, acting as a catalyst to promote electron transfer, which led to a decrease in the α/γ* ratio in the high-manganese weathering steel, thereby accelerating the corrosion reaction.

The corrosion behaviors in chloride environment of two commercial low-alloy steel bars were studied. Through cyclic wetting tests, accelerated corrosion experiments ranging from 1 to 576 h were conducted on low-alloy bars and original bars. Techniques such as OM, SEM, EDS, AFM, and XRD were employed to characterize the corrosion emergence and expansion behaviors of these bars in a simulated marine wetting and sun exposure environment. The designed low-alloy corrosion-resistant rebar achieved a 500 MPa yield strength. In each corrosion cycle, its corrosion loss and rate were lower than those of same-strength ordinary rebars. Analysis of the rust layer’s macro and micro morphology and alloy element distribution revealed alloy elements had little effect at corrosion initiation. In later corrosion, their enrichment led to a denser rust layer, effectively blocking corrosion expansion and chloride salt infiltration. After 72 h of accelerated corrosion, the corrosion rate growth of both bars slowed. The inner rust layer’s electrochemical potential increased, and local corrosion pits turned into uniform corrosion. The inner rust layer of the rebar formed more stable chromic acid with ionic compounds, reducing corrosion sensitivity. This study offers insights into steel bar corrosion and alloy element roles, guiding the preparation of low-alloy corrosion-resistant steel bars.

During electron beam cold hearth melting (EBCHM) of Ti-6wt%Al-4wt%V titanium alloy, aluminum volatilization causes compositional segregation in the ingot, significantly degrading material performance. Traditional methods (e.g., the Langmuir equation) struggle to accurately predict aluminum diffusion and compensation behaviors, while computational fluid dynamics (CFD), although capable of resolving multiphysics fields in the molten pool, suffer from high computational costs and insufficient research on segregation control. To address these issues, this study proposes a CFD-machine learning (backpropagation neural network, CFD-ML(BP)) approach to achieve precise prediction and optimization of aluminum segregation. First, CFD simulations are performed to obtain the molten pool’s temperature field, flow field, and aluminum concentration distribution, with model reliability validated experimentally. Subsequently, a BP neural network is trained using large-scale CFD datasets to establish an aluminum concentration prediction model, capturing the nonlinear relationships between process parameters (e.g., casting speed, temperature) and compositional segregation. Finally, optimization algorithms are applied to determine optimal process parameters, which are validated via CFD multiphysics coupling simulations. The results demonstrate that this method predicts the average aluminum concentration in the ingot with an error of ≤3%, significantly reducing computational costs. It also elucidates the kinetic mechanisms of aluminum volatilization and diffusion, revealing that non-monotonic segregation trends arise from the dynamic balance of volatilization, diffusion, convection, and solidification. Moreover, the most uniform aluminum distribution (average 6.8 wt.%, R² = 0.002) is achieved in a double-overflow mold at a casting speed of 18 mm/min and a temperature of 2168 K.

In order to gain insight into the changes of the organization and hardness of 500 MPa steel-grade low-temperature-resistant steel bars (HRB500DW) for liquefied nature gas (LNG) storage tanks during the continuous cooling phase transformation process, the effects of different rolling temperatures and cooling speeds on the organization of the phase change law, microstructure and hardness were studied. The results show that the critical phase transformation points A_C1 and A_C3 of the test steel were 702 and 880 °C, respectively. The organization of the test steel was polygonal ferrite and pearlite when the cooling rate was 1–2 °C/s. At a cooling speed of 5 °C/s, a small amount of bainite started to be produced in the region of a large deformation of rolling, and at 15 °C/s, some slate martensite started to be produced. At a cooling speed of 10 to 25 °C/s, the organization was mainly bainite. At a cooling rate of 40 °C/s, continuous pre-eutectic reticulated ferrite was formed at the austenite grain boundaries, reducing material properties. As the cooling speed increased, the hardness of the matrix organization of the test bars increased. The lower initial rolling temperature led to the expansion of the martensitic transformation zone. For rebar producers, the initial rolling temperature of 1050 °C was better than the initial rolling temperature of 1000 °C.

In the field of low-temperature-resistant steel bars in the liquefied natural gas (LNG) ultra-low-temperature environment, matching the strength and toughness of the material has become a key technical difficulty. In this paper, a duplex low-temperature-resistant steel bar was developed and designed, which adopts a continuous water-penetrating rolling process and a self-tempering process to effectively control the microstructure proportion of it at room temperature and effectively cope with ultra-low-temperature tensile failure at −163 °C. We studied the failure mechanism of 500 MPa steel grade low-temperature-resistant steel bars at tensile temperatures from 25 °C to −163 °C. We define a mixed microstructure of ferrite and pearlite (F + P) as the core of the material and tempered martensitic (TM) as the border of the material. It was found that the core and border microstructure had different response characteristics at different tensile temperatures. It is proved that, through the duplex microstructure design, it can meet the design requirements for the 500 MPa steel grade of low-temperature-resistant steel bars. By clarifying the effects of microstructure deformation, dislocation distribution, precipitated phase, and inclusions on the low-temperature resistance of steel bars under low-temperature tensile fracture, the deformation models of core and border microstructure under different tensile temperatures were constructed, and the methods for optimizing the production process of subsequent steel mills were given. After the optimization, the low-temperature toughness of the 500 MPa steel grade steel bar will be further guaranteed.