Mechanical Properties Of Steel Research Articles

Inhibition of the intergranular brittleness of HR3C heat-resistant steel by strain-aging induced nano-M23C6 dispersion precipitation

M23C6 chromium-rich carbides are common grain-boundary precipitation in Cr-containing steel. The presence of grain-boundary carbides often leads to intergranular brittleness and decreases the steel's mechanical properties. This study proposes a deformation and aging technique to obtain a high-volume-fraction dispersion distribution of the hard nano-M23C6 phase by changing the nucleation sites from grain boundaries to deformation coherent twin boundaries produced during cold deformation. The M23C6 precipitation-strengthened austenitic stainless steel has a strength of up to 1.4 GPa but maintains favorable plasticity (> 11%). This study provides a novel approach for the control of intergranular brittleness in metallic materials.

Effect of N plasma immersion ion implantation (N-PIII) on the microstructure and mechanical properties of 8Cr4Mo4V steel

To enhance the surface hardness and wear resistance of 8Cr4Mo4V steel, nitrogen plasma immersion ion implantation (N-PIII) was carried out, under various nominal implantation energies, in this study. Additionally, the microstructure and mechanical properties of the steel were analyzed. The results indicated that the depth of the nitrogen ion-implanted layer escalated with the specified implantation energy, reaching 140 nm for a 50 keV sample. Nitrogen was present within the implanted layer in the martensite lattice as a solute, and also in the form of nitrides along with alloying elements. Moreover, a nanocrystalline layer approximately 40–70 nm thick also formed at the sample surface. As the implantation energy increased, both the surface roughness and residual stress of the sample initially increased before declining, whereas the surface hardness and modulus exhibited a gradual increase. After the 50 keV N-PIII treatment, the surface hardness of the sample increased by 39 %, which caused a remarkable reduction in the friction coefficient, and the wear amount was also reduced by about 40 %. This work systematically establishes the relationship between the surface microstructures, surface morphology, and mechanical properties of implanted 8Cr steel, and significantly improves its surface hardness and wear resistance.

Effect of Niobium on Mechanical Properties of Steels and High-Entropy Alloys

Effect of Niobium on Mechanical Properties of Steels and High-Entropy Alloys

Experimental investigation into corrosion effect on buckling and low-cycle fatigue performance of high-strength steel bars

The reinforcement in marine RC structures will inevitably be corroded under long-time erosion of chloride ions, which will weaken steel mechanical properties and then structural seismic resistance. The new metallurgical technology is adopted for manufacturing high-strength steel bars (HSSB), but that may affect the corrosion resistance of steel bars at the same time. This paper experimentally investigates the effects of corrosion on monotonic and low-cycle fatigue properties of HSSB HTRB600 and normal strength steel bars (NSB) HRB400E. The HRB400E and HTRB600 steel bars were corroded to different corrosion rates by electrochemical accelerated corrosion technique. The monotonic tensile and compressive, as well as low-cycle fatigue tests of corroded steel bars were conducted to investigate the effects of corrosion on steel mechanical properties, of which corrosion levels (0–20% target corrosion mass loss), slenderness ratios (L/D=6, 8, 10, 12) and strain amplitudes (2%, 4%) are considered. Test results show that, the corrosion morphology of steel bars under electrochemical accelerated corrosion is basically consistent with that observed under natural corrosion. Compared with uncorroded HRB400E and HTRB600 steel bars, 20% corrosion mass loss leads to 38% and 35% decrease in tensile strength, as well as 33% and 28% reduction in buckling stress, respectively. The HTRB600 steel bars present slightly superior monotonic tensile and compressive corrosion resistance than HRB400E steel bars. Corrosion obviously decreases the low-cycle fatigue (LCF) life of steel bars, resulting in reductions of 44% and 36% in LCF life at 20% corrosion mass loss for HTRB600 and HRB400E steel with a L/D of 6, respectively. Moreover, the HTRB600 steel bars present more significant corrosion degradation in total hysteretic dissipated energy, compared with HRB400E steel bars. The combined effect of corrosion and inelastic buckling further exacerbates the deterioration of LCF performance of steel bars. The corresponding deterioration models are proposed to determine the LCF life and energy dissipation capacity of corroded steel bars.

Effect of Rotary Swaging on Mechanical Behaviors of Axle Steel Rod.

The short-chain forming process using rotary swaging (RS) is an important method of achieving the manufacturing of lightweight axles. Axle steel, like 42CrMo, is widely used in many types of axles and shafts; however, there is no existing research on rotary-swaged axle steel's mechanical properties. It makes sense to carry out a comprehensive study on the effect of RS on the mechanical behaviors of axle steel rods. In this study, a 42CrMo steel rod was processed by RS through ten passes. The tensile properties, torsion properties, compression properties, and fatigue properties were tested. There was an overall improvement in the torsional and fatigue performance after RS. Combined with a finite element analysis (FEM), the uneven distribution of the dislocations and existence of the elongation material were inferred to have caused the different modes of the mechanical behaviors. Fracture surfaces were analyzed and the results showed that the fracture pattern had changed. There existed a competitive relation between the internal fatigue cracks and external cracks, which could be attributed to uneven strain hardening. This research proved the advantages of RS in the processing of axle parts, which mainly benefitted the torsional working conditions, and provided evidence for a new processing route for lightweight axles with RS.

Effect of Si and Y solution on mechanical properties of 30Cr13 martensitic stainless steel

The effect of alloying element silicon (Si) on yttrium (Y) solid solution in steel has been studied by anhydrous electrolysis experiment and first-principles calculation. The effect of Y and Si solid solution on the mechanical properties of steel were studied by tensile and hardness test. The influence mechanism was analyzed by geometry and electronic structures. The results show that Si can promote Y solid solution in steel. Since the Fe–Y bond energy was less than the Fe–Fe bond, the elastic properties of Fe were reduced by adding Y. The extremely high density of electron clouds around Si improves some of the elastic properties of Fe–Y–Si. Compared with Fe, the Young ‘s modulus of Fe–Y–Si sample was decreased by 4.3 GPa and the hardness of Fe–Y sample was increased by 4.22 HV. Y reduced the interaction of the slip surfaces and Si enhanced it, thus changing the plasticity of the steels.

Tailoring the Microstructure using Quenching and Partitioning Processing in a Commercial Mn-Si-Cr Spring Steel to Improve Tensile Properties

AbstractThis study explores a novel approach to quenching and partitioning (Q&P) heat treatment applied to AISI 9260 spring steel, comprising Fe-0.65C-1.58Mn-1.05Si-0.41Cr (wt.%). Our research focuses on balancing strength and ductility through optimized Q&P pathways, leading to a diverse microstructure that includes martensite, bainite, carbide, and retained austenite. Advanced X-ray diffraction and scanning electron microscopy techniques were employed to analyze the complexities of this microstructure. A key aspect of this study is the precise control of partitioning temperature and time, crucial for modulating lattice distortion and dislocation density within martensitic and bainitic structures. Optimal partitioning temperature promotes carbon distribution into austenite, tempering lattice distortions, and dislocation densities. Concurrently, carbide precipitation and segregation contribute to the refinement of the bainite phase. The sample quenched at 125 °C and partitioned at 350 °C (Q&P-125/350) demonstrates notable mechanical properties: a yield strength of 950 ± 15 MPa, an ultimate tensile strength of 1710 ± 15 MPa, and an elongation of approximately 9.7%. These results are partly attributed to the effect of silicon in preventing cementite coarsening and the effective distribution of carbide. Our findings highlight the potential of Q&P heat treatment in developing tailored microstructures with enhanced mechanical properties in steel, without relying on costly alloying elements. This approach presents new avenues for the design and application of high-performance materials.

Influence of prior austenite grain size on martensite-austenite islands morphology and decomposition characteristics during two-step tempering in Mn-Ni-Mo steel

Martensite-austenite (M/A) islands are typical in the quenched microstructure of Mn-Ni-Mo steel, frequently utilized for fabricating reactor pressure vessels (RPV). These islands can decompose into harmful long rod-shaped Fe3C carbides during tempering above 600°C, quantifying the negative effect of M/A island decomposition on mechanical properties and indicating a potential issue in RPV fabrication. To address this issue, the present study investigates a two-step tempering process on three different prior austenite grain size (PAGS) specimens (5 µm, 47 µm, and 119 µm). The effect of PAGS on M/A island decomposition characteristics during sub-600°C tempering and their impact on precipitated carbide morphology is investigated. A preliminary pre-tempering treatment at 200°C, 350°C, and 500°C for 2 hours was followed by a 3-hour final tempering step at 650°C. The findings revealed unique temperature-dependent decomposition characteristics of M/A islands. For example, at 200°C, partial M/A island decomposition took place, resulting in long rod-shaped carbides during final tempering. Meanwhile, the 350°C pre-tempering specimen revealed aggregated carbide precipitates of varying sizes in former M/A island locations. In contrast, the 500°C pre-tempering specimen showed coarse globular carbides and the absence of carbide precipitate clustering. This result can be attributed to the decrease in surface energy associated with the carbide-matrix interface as size increases. After tempering, all specimens produced three types of precipitates: rod-shaped Fe3C carbides, rhombus-shaped Mn7C3, and globular-shaped Mn23C6 carbides. The formation of long rod-shaped carbides during M/A island decomposition reduces the critical cleavage stress for micro-crack initiation, jeopardizing steel mechanical properties. Aggregated carbides cause the simultaneous formation of numerous micro-voids in close proximity, which eventually merge to form a large crack, resulting in material failure. When compared to other pre-tempered and directly tempered specimens, pre-tempering at 500°C produced the most favorable microstructure in terms of impact properties.

Multi-task prediction of hot rolled steel mechanical properties based on CA-MMCE

The accurate prediction of mechanical properties of multi-task hot rolling steel is of great significance to the development of manufacturing, construction, and other industries, and can effectively improve the efficiency of continuous quality control of the hot rolling process. Aiming at the problem that the existing deep models lack interpretability in the field of steel rolling, the hot rolling process was deeply analyzed, and the temperature fluctuation was integrated into the input features as a process variable through feature augmentation to obtain the correlation between features. In order to solve the problem that the conventional Attention mechanism only focuses on the overall global information, a Convolutional Attention mechanism (CA) is proposed to focus on local feature information and improve the ability of the network to extract local key features. At the same time, so as to solve the negative transfer problem of the multi-task model, a Multi-gate Mixture of Convolutional Experts (MMCE) is proposed, which uses multi-gate to adjust the influence of each convolutional expert network on different tasks to capture the correlation between tasks. Thus, it can ensure that multiple tasks can be accurately predicted. Experimental results show that, compared with the existing models, the proposed model achieves excellent prediction performance in multi-task prediction and is advanced.

Assessing the feasibility of laser ablation coating removal (LACR) on legacy bridge steel: Coating removal and adhesion, and effects on mechanical properties

The application of protective organic coatings is one of the most effective and commonly used corrosion mitigation strategies. To maintain the protective nature of coatings on long-term-exposed surfaces such as steel bridge components, coatings must be periodically removed and reapplied. A relatively new method called laser ablation coating removal (LACR), which incorporates a high energy nanosecond pulsed laser beam in combination with a high efficiency filtration system, allows for safe and effective removal of coatings and contamination from metal surfaces. In this study, LACR cleaning is tested on legacy bridge steel components to investigate the effect on substrate cleanliness and steel mechanical properties. These bridge sections were never blasted and contain a 20–100 μm thick mill-scale layer (iron oxide) below several coating layers (including lead-rich coatings). The top micron of the oxide layer is melted by LACR and also thermally insulates the underlying steel and prevents any melting within the metallic substrate. The resulting surfaces are analyzed using microscopy, hardness testing, tensile, and fatigue testing, and it is shown that LACR does not cause any measurable detrimental effects to the bulk mechanical properties of the bridge steel, as well as effectively removes all paint coatings. Furthermore, adhesion testing on LACR-cleaned substrates shows excellent adhesion, qualifying above adhesion requirements for coated steel.

Mechanical properties of Q355 hot-rolled steel during the entire fire process

This study conducts steady-state tests to comprehensively examines the mechanical properties of Q355 hot-rolled steel throughout the entire fire process, including the cooling stage. Results show that the mechanical properties at the fire-cooling stage are influenced by both the peak heating temperature (Tp) and the tensile test temperature (Tt). Within a specific threshold value of Tp, the mechanical properties at the cooling stage of fire resemble those observed in the heating stage. However, when Tp surpasses this threshold value, notable disparities emerge between the mechanical properties of steel at the cooling and heating stages. The threshold temperatures for elastic modulus, ultimate strength, and ultimate strain are all 600 °C, while that for the yield strength f0.2 is 400 °C. A cooling stage influence coefficient is used to quantitatively portray the variance in mechanical properties between the cooling and heating stages of fire. Calculation formulas for the fire cooling stage influence coefficients were provided for the elastic modulus, yield strength f0.2, ultimate strength, and ultimate strain, respectively. Finally, a constitutive model for the entire fire process of Q355 steel was established.

Wet H2S corrosion and degradation of pipeline in amine regeneration system

AbstractThe paper presents the results of non‐destructive testing examinations, metallographic tests and risk assessment of degradation related to corrosion of amine regeneration unit in a desulphurisation system. Intensive corrosion resulting from acid gases environment upon water condensation causes perforation of the pipeline. Detailed analysis reveals cracking related to the mechanism of wet H2S. Hydrogen penetration, resulting from the wet H2S process, causes a decrease in mechanical properties of steel and an increase in hydrogen content inside steel. Corrosion results mostly from high stream velocity, the presence of acid gases (with high ammonia content), the presence of amine and low stream temperature.

Study on Influence of Rare Earth Ce on Micro and Macro Properties of U75V Steel.

Non-metallic inclusions in steel have great influence on the continuity of the steel matrix and the mechanical properties of steel. The precipitation sequence of Ce inclusions in molten steel is predicted by thermodynamic calculations. The results show that Ce content will affect the precipitation sequence of rare earth inclusions in molten steel, and the formation of CeO2, Ce2O3 and CeAlO3 will be inhibited with the increase in Ce content. Our laboratory smelted the test steel without rare earth additive and the test steel with rare earth Ce additive (0.0008%, 0.0013%, 0.0032%, 0.0042%). It was found that the MnS inclusions and inclusions containing Al, Ca, Mg and Si oxides or sulfides in the steel after rare earth addition were modified into complex inclusions containing CeAlO3 and Ce2O2S. The size of inclusion in steel was reduced and the aspect ratio of inclusion was improved. The addition of Ce also improved the grain size of U75V steel and significantly refined the pearlite lamellar spacing. After mechanical property testing of the test steel, it was found that when Ce is increased within 0.0042%, the tensile and impact properties of U75V steel are also improved.

Predictive Quality Analytics of Surface Roughness in Turning Operation Using Polynomial and Artificial Neural Network Models

The variability of the material properties of steel from different suppliers causes problems in achieving the required surface quality after turning. Therefore, the manufacturer needs to estimate the resulting quality before starting production, especially if it is an expensive, small-batch production from stainless steel. Predictive models will make it possible to estimate the surface roughness from the mechanical properties of steel and thus support decision making about supplier selection or acceptance of a material supply. This research presents a step-by-step decision-making procedure, which enables the trained staff to make quick decisions based on commonly available information in the Mill Test Certificate (MTC). A new multivariate second-order polynomial model and feedforward backpropagation artificial neural network (ANN) models have been developed using input variables from the MTC: Tensile Strength, Yield Strength, Elongation, and Hardness. Models were used to enhance the methodological robustness in formulating the decision if the predicted surface roughness is outside the required range, even before accepting the delivery. Both models can accurately predict surface roughness, while the ANN model is more accurate than the polynomial model; however, the predictive model is sensitive to the accuracy of the input data, and the model’s prediction is valid only under precisely defined conditions.

Effects of austempering on the microstructure and mechanical properties of high-strength nanostructured bainitic steel containing 3.5 wt% aluminum

This study aims to produce a cost-effective and low-density, high-strength nanostructured bainitic steel by optimizing the austempering process conditions. To do this, a steel containing 0.8C-1.5Mn-0.6 Cr-0.35Mo-3.5Al was selected and the effects of austempering time and temperature on the microstructure and mechanical properties of this steel were studied. Xrd technique was used to recognize the phases present in the microstructure and measure the retained austenite volume fraction and carbon content. Hardness measurements showed that the highest value was obtained from the specimen containing the highest volume fraction of the bainitic ferrite associated with the retained austenite with the highest carbon content, at the completion time of transformation. Such a combination of microstructure and hardness was applied to find the optimum time at different temperatures during the austempering process. The microstructures of the optimal specimens were evaluated through optical microscopy (OM) and field-emission scanning electron microscopy (FESEM), and the average thickness of the bainitic ferrite plates was calculated. Finally, tensile tests were performed on the optimal specimens to assess the fracture surface through FESEM. For high steel with 3.5 wt% Al, the results indicated that it is possible to obtain a microstructure consisting of bainitic ferrite plates with an average thickness of 53 nm surrounded by the carbon-rich retained austenite with a hardness of 561HV, a yield stress of 1614 MPa, an ultimate tensile strength of 1981 MPa, and a total elongation of 9 %.

Исследование температуры концевого фрезерования низколегированной стали в крупнозернистом и ультрамелкозернистом состояниях

The paper presents the results of the study of the end milling temperature of low-alloy steel depending on the cutting modes and the type of crystalline structure. The experiment was carried out on a PROMA FHV-50PD universal milling machine. The blanks were processed using a 12-12D-30C-75L-4F HRC55 carbide milling cutter. No cooling was used during processing. The obtained data were statistically analyzed to identify the dependence of the end milling temperature of low-alloy steel on the processing modes and the steel crystalline structure. When creating a mathematical model of cutting temperature, the authors carried out a bootstrap analysis to identify the significance of the parameters of the processing modes. The mathematical model was chosen using the Akaike informative criterion. It was found that mathematical models of the temperature dependence on processing modes for both types of crystalline structure include the cutting depth in the second power. At the same time, for steel in an ultrafine-grained state, both the cutting depth and the feed are statistically significant. It was not possible to detect the influence of cutting speed on temperature in the studied range of processing modes. Thus, when milling this group of materials, the force component primarily determined by the cutting depth exerts the predominant influence on the temperature regime. The level of cutting temperature when processing steel in an ultrafine-grained state is generally higher than when processing steel in a coarse-grained state, which should be associated with the increased physical and mechanical properties of steel with an ultrafine-grained crystalline structure.

Акустические свойства мартенситно-стареющей стали XM-12 после энергетических воздействий

The study of the acoustic properties of maraging steels operated under various energy force and temperature actions is a critical task, since it is the method of acoustic structuroscopy that provides the most reliable connection with the structure, stress-strain state and mechanical properties of steels. The paper is devoted to research of the acoustic properties of the 15-5 PH maraging steel samples under various types of heat treatment under the conditions of mechanical tensile and cyclic loads. Samples of the 15-5 PH maraging steel were studied in three structural states: solid solution annealing and subsequent aging at 470 and 565 °C; during tensile tests; during cyclic tension-compression loading. The research used a unique scientific installation “Information-measuring complex for investigation of acoustic properties of materials and products”. It implements the acoustic mirror-shadow multiple reflections method using electromagnetic-acoustic and piezoelectric transducers based on polyvinylidene fluoride film to excite and receive waves and allows determining the velocity of wave propagation with an error of no more than 2 m/s. The acoustic (wave velocity, elastic moduli, electromagnetic-acoustical (EMA) transformation coefficients, acoustic anisotropy coefficients, acoustoelastic coupling coefficients) and electromagnetic (coercive force and electrical conductivity) characteristics of the samples were examined. The samples were studied in the initial state (before loading); stepwise in the process of tensile loads and subsequent unloading; after tensile tests; during cyclic tension-compression loading. It was revealed that the following acoustic parameters of 15-5 PH steel samples are the greatest structural sensitivity to mechanical tensile load and cyclic loading: transverse wave velocity, Poisson’s ratio, double EMA-transformation coefficient, and acoustic anisotropy coefficient.

Developing the optimal chemical composition of heat-resistant Cr-Ni steel for aerospace equipment

The object of research in this work is the processes of forming the microstructure and mechanical properties of heat-resistant steels depending on their chemical composition. The microstructure and high-temperature mechanical properties of austenitic heat-resistant chrome-nickel steels of the proposed chemical composition were investigated in the work. The microstructure study determined the grain size and topography of inclusions in steels. Based on the results of mechanical tests, a multifactorial experiment was planned, which made it possible to establish the relationship between the mechanical properties of steels with alloying elements selected as factors. The obtained regression equations were used to estimate the quantitative influence of each alloying element on the corresponding mechanical properties. Analysis of the results of the experiment made it possible to determine the optimal chemical composition of steel for gas turbine engines used in the aerospace industry, as well as in the metallurgy of titanium production. It is shown that the state of solid solution and heat-resistant niobium and molybdenum carbides (chromium carbides dissolve at a temperature of 950 °C) are an important factor that significantly affects the structure, mechanical, and service properties of heat-resistant steel. The austenite structure is provided by the required amount of nickel. The resulting indicators of heat resistance of steels of different compositions, tested at temperatures of 850 °C, 950 °C, and 1050 °C, proved the superiority of steel with a higher content of carbon and chromium and a lower content of nickel. The mechanism of steel strengthening and the influence of alloying with carbon, chromium, and nickel on it have been determined. The optimal chemical composition of heat-resistant steel on an iron-nickel basis for operation at a temperature of 950 °C has been established

Dynamic mechanical properties and constitutive model establishment of QSTE420 steel

The uniaxial tensile tests of QSTE420 steel under different strain rates were carried out using an electronic universal material testing machine, a high-speed tensile testing machine and a split Hopkinson tension bar (SHTB) device, the engineering stress-strain curves of steel within the range of 0.001– 1000 s−1 were obtained and the mechanical properties of steel at different strain rates were analyzed. The results show that in the static strain rate range of 10−3– 10−2 s−1, the yield strength and tensile strength of QSTE420 steel exhibit minimal variation, fluctuating between 430– 434 MPa and 507– 515 MPa, respectively; while the uniform elongation and elongation at break remain approximately at 12% and 35%, respectively. In the high strain rate range of 10−1– 103 s−1, both yield strength and tensile strength exhibit a consistent increase in direct correlation with the tensile rate. Specifically, the yield strength increases from 444 to 607 MPa and the tensile strength increases from 523 to 640 MPa as the strain rate escalates from 10−1 to 103 s−1. Moreover, the elongation at break demonstrates a general increasing trend and reaches its peak value of 45.65% at 100 s−1. The morphology of fracture surfaces under different strain rates are observed by Scanning Electron Microscopy (SEM). The fracture appearance analysis reveals numerous dimples in the fracture, indicating a ductile fracture. Furthermore, the comparison demonstrates that steel exhibits enhanced plasticity at a strain rate of 100 s−1. Based on the experimental results, the Johnson-Cook constitutive model was established and modified. The modified Johnson-Cook model exhibits a higher determination coefficient (R2) compared to the original version, signifying an improved fitting accuracy.

The Influence of Heatmap Correlation-based Feature Selection on Predictive Modeling of Low Alloy Steel Mechanical Properties Using Artificial Neural Network (ANN) Algorithm

The Influence of Heatmap Correlation-based Feature Selection on Predictive Modeling of Low Alloy Steel Mechanical Properties Using Artificial Neural Network (ANN) Algorithm