Search Results (1,048)

In this study, a novel direct laser beam turning (DLBT) approach is proposed for the precision machining of AISI 308L austenitic stainless steel, which eliminates the need for cutting tools and thereby eradicates tool wear and vibration-induced surface irregularities. A nanosecond-pulsed Nd:YAG fiber laser (λ = 1064 nm, spot size = 0.05 mm) was used, and Ø1.6 mm × 20 mm cylindrical rods were processed under ambient conditions without auxiliary cooling. The experimental framework systematically evaluated the influence of scanning speed, pulse frequency, and the number of laser passes on dimensional accuracy and material removal efficiency. The results indicate that a maximum diameter reduction of 0.271 mm was achieved at a scanning speed of 3200 mm/s and 50 kHz, whereas 0.195 mm was attained at 6400 mm/s and 200 kHz. A robust second-order polynomial correlation (R² = 0.99) was established between diameter reduction and the number of passes, revealing the high predictability of the process. Crucially, when the scanning speed was doubled, the effective fluence was halved, considerably influencing the ablation characteristics. Despite the low fluence, evidence of material evaporation at elevated frequencies due to the incubation effect underscores the complex photothermal dynamics governing the process. This work constitutes the first comprehensive quantification of pass-dependent diameter modulation in DLBT and introduces a transformative, noncontact micromachining strategy for hard-to-machine alloys. The demonstrated precision, repeatability, and thermal control position DLBT as a promising candidate for next-generation manufacturing of high-performance miniaturized components. Full article

Magnetic gears (MGs) are attracting increasing attention in power transmission systems due to their contactless operation principles, low frictional losses, and high efficiency. However, the broad application potential of these technologies requires a comprehensive evaluation of engineering parameters, such as material selection, energy efficiency, and structural design. This review focuses solely on solid-core magnetic gear systems designed using laminated electrical steels, soft magnetic composites (SMCs), and high-saturation alloys. This review systematically examines the topological diversity, torque transmission principles, and the impact of various core materials, such as electrical steels, soft magnetic composites (SMCs), and cobalt-based alloys, on the performance of magnetic gear systems. Literature-based comparative analyses are structured around topological classifications, evaluation of material properties, and performance analyses based on losses. Additionally, the study highlights that aligning material properties with appropriate manufacturing methods, such as powder metallurgy, wire electrical discharge machining (EDM), and precision casting, is essential for the practical scalability of magnetic gear systems. The findings reveal that coaxial magnetic gears (CMGs) offer a favorable balance between high torque density and compactness, while soft magnetic composites provide significant advantages in loss reduction, particularly at high frequencies. Additionally, application trends in fields such as renewable energy, electric vehicles (EVs), aerospace, and robotics are highlighted. Full article

Internal crack defects in high-strength low-alloy (HSLA) steels during continuous casting pose significant challenges to downstream processing and product reliability. However, due to the inherent class imbalance in industrial defect datasets, conventional machine learning models often suffer from poor sensitivity to minority class instances. This study proposes a predictive framework that integrates conditional tabular generative adversarial network (CTGAN) for synthetic minority sample generation and CatBoost for classification. A dataset of 733 process records was collected from a continuous caster, and 25 informative features were selected using mutual information. CTGAN was employed to augment the minority class (crack) samples, achieving a balanced training set. Feature distribution analysis and principal component visualization indicated that the synthetic data effectively preserved the statistical structure of the original minority class. Compared with the other machine learning methods, including KNN, SVM, and MLP, CatBoost achieved the highest metrics, with an accuracy of 0.9239, precision of 0.9041, recall of 0.9018, and F1-score of 0.9022. Results show that CTGAN-based augmentation improves classification performance across all models. These findings highlight the effectiveness of GAN-based augmentation for imbalanced industrial data and validate the CTGAN–CatBoost model as a robust solution for online defect prediction in steel manufacturing. Full article

Based on experimental data regarding the local distribution of metallic impurities in raw selenium and the composition of its vapor phase, the potential composition of the vapor–droplet suspension that leads to reduced condensate quality due to impurities with low partial vapor pressures relative to selenium, as well as metals with vapor pressures comparable to selenium, has been hypothesized. Due to selenium’s high aggressiveness towards structural materials and based on economic feasibility, the use of low-alloy steel of ordinary quality for the technical design of the distillation process, instead of alloyed steel, has been thermodynamically justified. A method has been developed, and a device to refine selenium has been manufactured, which differs from existing ones by the inertial purification of the vapor phase from droplet suspension. The development is protected by a security document (patent KZ No. 37275). Based on the completed developments, an industrial prototype of such equipment has been designed and implemented in production. Full article

Weathering steel (WS) is widely used in bridge construction due to its high corrosion resistance, durability, and low maintenance requirements. This paper reviews the performance of WS bridges in Canadian climates, focusing on the formation of protective patina, influencing factors, and long-term maintenance strategies. The protective patina, composed of stable iron oxyhydroxides, develops over time under favorable wet–dry cycles but can be disrupted by environmental aggressors such as chlorides, sulfur dioxide, and prolonged moisture exposure. Key alloying elements like Cu, Cr, Ni, and Nb enhance corrosion resistance, while design considerations—such as drainage optimization and avoidance of crevices—are critical for performance. The study highlights the vulnerability of WS bridges to microenvironments, including de-icing salt exposure, coastal humidity, and debris accumulation. Regular inspections and maintenance, such as debris removal, drainage system upkeep, and targeted cleaning, are essential to mitigate corrosion risks. Climate change exacerbates challenges, with rising temperatures, altered precipitation patterns, and ocean acidification accelerating corrosion in coastal regions. Future research directions include optimizing WS compositions with advanced alloys (e.g., rare earth elements) and integrating climate-resilient design practices. This review highlights the need for a holistic approach combining material science, proactive maintenance, and adaptive design to ensure the longevity of WS bridges in evolving environmental conditions. Full article

65 Mn is a high-quality carbon structural steel that exhibits excellent mechanical properties and machinability. It finds broad applications in machinery manufacturing, agricultural tools, and mining equipment, and is commonly used for producing mechanical parts, springs, and cutting tools. Fe901 is an iron-based alloy that exhibits excellent hardness, structural stability, and wear resistance. It is widely used in surface engineering applications, especially laser cladding, due to its ability to form dense and crack-free metallurgical coatings. To enhance the surface hardness and wear resistance of 65 Mn steel, this study employs a laser melting process to deposit a multi-layer Fe901 alloy coating. The phase composition, microstructure, microhardness, and wear resistance of the coatings are investigated using X-ray diffraction (XRD), optical microscopy, scanning electron microscopy (SEM), Vickers hardness testing, and friction-wear testing. The results show that the coatings are dense and uniform, without visible defects. The main phases in the coating include solid solution, carbides, and α-phase. The microstructure comprises dendritic, columnar, and equiaxed crystals. The microhardness of the cladding layer increases significantly, with the multilayer coating reaching 3.59 times the hardness of the 65 Mn substrate. The coatings exhibit stable and relatively low friction coefficients ranging from 0.38 to 0.58. Under identical testing conditions, the wear resistance of the coating surpasses that of the substrate, and the multilayer coating shows better wear performance than the single-layer one. Full article

This study investigates the thermal response and surface modification of low-carbon manganese-alloyed 20GL steel during electrolytic plasma hardening. The objective was to evaluate the feasibility of surface hardening 20GL steel—traditionally considered difficult to quench—by combining high-rate surface heating with rapid cooling in an electrolyte medium. To achieve this, a transient two-dimensional heat conduction model was developed to simulate temperature evolution in the steel sample under three voltage regimes. The model accounted for dynamic thermal properties and non-linear boundary conditions, focusing on temperature gradients across the thickness. Experimental temperature measurements were obtained using a K-type thermocouple embedded at a depth of 2 mm, with corrections for sensor inertia based on exponential response behavior. A comparison between simulation and experiment was conducted, focusing on peak temperatures, heating and cooling rates, and the effective thermal penetration depth. Microhardness profiling and metallographic examination confirmed surface strengthening and structural refinement, which intensified with increasing voltage. Importantly, the study identified a critical cooling rate threshold of approximately 50 °C/s required to initiate martensitic transformation in 20GL steel. These findings provide a foundation for future optimization of quenching strategies for low-carbon steels by offering insight into the interplay between thermal fluxes, surface kinetics, and process parameters. Full article

Accurate measurement uncertainty quantification and its propagation are critical for dimensional compliance in precision manufacturing. This study presents a novel framework that examines the evolution of measurement error along the axial length of CNC-turned components, focusing on spatial and material-specific factors. A systematic experimental comparison was conducted between a manual Digital Vernier Caliper (DVC) and an automated Coordinate Measuring Machine (CMM) using five engineering materials: Aluminum Alloy 6061, Brass C26000, Bronze C51000, Carbon Steel 1020 Annealed, and Stainless Steel 304 Annealed. Dimensional measurements were taken from five consecutive machining zones to capture localized metrological behaviors. The results indicated that the CMM consistently achieved lower expanded uncertainty (as low as 0.00166 mm) and minimal propagated uncertainties (≤0.0038 mm), regardless of material hardness or cutting position. In contrast, the DVC demonstrated significantly higher uncertainty (up to 0.03333 mm) and propagated errors exceeding 0.035 mm, particularly in harder materials and unsupported zones affected by surface degradation and fixture variability. Root-sum-square (RSS) modeling confirmed that manual measurements are more prone to operator-induced error amplification. While the DVC sometimes recorded lower absolute errors, its substantial uncertainty margins hampered measurement reliability. To statistically validate these findings, a two-way ANOVA was performed, confirming that both the measurement system and machining zone significantly impacted uncertainty, as well as their interaction. These results emphasize the importance of material-informed and zone-sensitive metrology, highlighting the advantages of automated systems in sustaining measurement repeatability and dimensional stability in high-precision applications. Full article

The production of AISI 304 stainless steel (a corrosion-resistant alloy prone to solidification defects from high alloy content) particularly benefits from twin-roll strip casting—a short-process green technology enabling sub-rapid solidification (the maximum cooling rate exceeds 1000 °C/s) control for high-performance steels. However, the internal phenomena within its molten pool remain exceptionally challenging to monitor. This study developed a multiscale numerical model to simulate coupled fluid flow, heat transfer, and solidification in AISI 304 stainless steel twin-roll strip casting. A quarter-symmetry 3D model captured macroscopic transport phenomena, while a slice model resolved mesoscopic solidification structure. Laboratory experiments had verified that the deviation between the predicted temperature field and the measured average value (1384.3 °C) was less than 5%, and the error between the solidification structure simulation and the electron backscatter diffraction (EBSD) data was within 5%. The flow field and flow trajectory showed obvious recirculation zones: the center area was mainly composed of large recirculation zones, and many small recirculation zones appeared at the edges. Parameter studies showed that, compared with the high superheat (110 °C), the low superheat (30 °C) increased the total solid fraction by 63% (from 8.3% to 13.6%) and increased the distance between the kiss point and the bottom of the molten pool by 154% (from 6.2 to 15.8 mm). The location of the kiss point is a key industrial indicator for assessing solidification integrity and the risk of strip fracture. In terms of mesoscopic solidification structure, low superheat promoted the formation of coarse columnar crystals (equiaxed crystals accounted for 8.9%), while high superheat promoted the formation of equiaxed nucleation (26.5%). The model can be used to assist in the setting of process parameters and process optimization for twin-roll strip casting. Full article

Body-centered cubic (BCC) metals, extensively utilized in low-alloy high-strength steels and heat-resistant alloys, exhibit a pronounced ductile–brittle transition (DBT) at cryogenic temperatures, marked by a well-defined yet narrow ductile–brittle transition temperature (DBTT) window. This paper overviews the research progress regarding the DBT mechanism of BCC metals. This mechanism was recently found to be related to the mobility of screw dislocation relative to edge dislocation, a decrease in which can induce a critical drop in the proliferation efficiency of dislocation sources. Furthermore, this paper summarizes the current research on the dilute solution softening effect of BCC metals, which has been frequently observed and studied in refractory alloys. The mechanism of this effect involves the low-temperature mobility of screw dislocations that could be promoted by specific solute atoms through kink pair nucleation. This offers a potential strategy for reducing the DBTT of low-alloy steels using a dilute solution, namely microalloying in metallurgy. However, the current understanding of the relationship between the macroscopic ductility of BCC alloys and the dilute solution softening effect is limited. This review aimed to draw attention to this relationship and strengthen related research. Full article

This study investigated the application of Finite Element Analysis (FEA) to optimize the design and material selection for the construction of the telescopic arm of an elevating work platform (EWP) used in agricultural environments. By comparing the structural performance of four materials—Aluminum Alloy (EN-AW 1200), Aluminum Alloy (EN-AW 2014), High-Strength Low-Alloy (HSLA) Steel Fe275JR, and HSLA Steel S700—under simulated operational conditions, this research identified the most suitable material for robust yet lightweight platforms. The results revealed that HSLA Steel S700 provides superior performance in terms of strength, low deformation, and high safety factors, making it ideal for scenarios requiring maximum durability and load-bearing capacity. Conversely, Aluminum Alloy (EN-AW 2014), while exhibiting lower strength compared with HSLA Steel S700, significantly reduces platform weight by approximately 60% and lowers the center of gravity, enhancing maneuverability and compatibility with smaller, less powerful tractors. These findings highlight the potential of FEA in optimizing EWP design by enabling precise adjustments to material selection and structural geometry. The outcomes of this research contribute to the development of safer, more efficient, and cost-effective EWPs, with a specific focus on improving productivity and safety in agricultural operations such as pruning and harvesting. Future work will explore advanced geometries and hybrid materials to further enhance the performance and versatility of these platforms. Full article

The objective of this study was to identify surface geometric deviations that may adversely affect the operational properties of bearings, including vibration, noise, and service life. A comprehensive prediction model is presented that combines a fundamental trend expressed by a power function with periodic oscillations, whose influence gradually diminishes with exponential decay. The model was calibrated using the experimental data obtained from 17 industrial RA-608-338 rolling bearing rings manufactured from high-carbon, low-alloy 100Cr6 steel. An excellent goodness-of-fit (R² exceeding 0.98) and minimal root-mean-square error (RMSE) were achieved. The proposed procedure provides a clear physical interpretation of the model’s subcomponents, while facilitating straightforward implementation in real production processes for continuous quality control and predictive maintenance purposes. This paper also includes a detailed description of the methodology, data processing, experimental results, comparison of multiple model variants, interactive visualization of the results on a logarithmic scale, and recommendations for practical application. Full article

High-entropy alloys are known for their promising mechanical properties, wear and corrosion resistance, which are maintained across a wide range of temperatures. In this study, a CoCrFeNiCu-based high-entropy alloy, distinguished from conventional CoCrFeNi systems by the addition of Cu, which is known to enhance toughness and wear resistance, was investigated to better understand the effects of compositional modification on processability and performance. The influence of key process parameters, specifically laser power and scan speed, on the processability of CoCrFeNiCu-based high-entropy alloys produced by laser powder bed fusion additive manufacturing was investigated, with a focus of low laser power, which is critical for minimizing defects and improving the resulting microstructure and mechanical performance. The printed sample density gradually increases with higher volumetric energy density, achieving densities exceeding 99.0%. However, at higher energy densities, the samples exhibit susceptibility to hot cracking, an issue that cannot be mitigated by adjusting the process parameters. Mechanical properties under optimized parameters were further evaluated using Charpy impact and (in situ) tensile tests. These evaluations were supplemented by in situ tensile experiments conducted within a scanning electron microscope to gain insights into the behavior of defects, such as hot cracks, during tensile testing. Despite the sensitivity to hot cracking, the samples exhibited a respectable ultimate tensile strength of 662 MPa, comparable to fine-grained steels like S500MC (070XLK). These findings underscore the potential of CoCrFeNiCu-based high-entropy alloys for advanced applications. However, they also highlight the necessity for developing strategies to ensure stable and reliable processing methods that can mitigate the susceptibility to hot cracking. Full article

This study investigates the influence of rare earth element Ce addition on the nanoscale precipitation, microstructure, and mechanical properties of Ti-containing secondary phases in high-strength low-alloy weathering steel. Mechanical property testing and microstructural characterization were performed on experimental samples subjected to rolling-aging treatment. The results demonstrate that the addition of Ce promotes coarsening of nanoscale precipitates, thereby diminishing their precipitation strengthening effect. At a 0.11% Ce content, an increase in inclusions was observed, leading to crack formation during hot deformation. However, Ce addition also refines inclusion size and modifies inclusion types, contributing to steel purification. Through austenite recrystallization zone rolling combined with an isothermal process, a high-strength ferritic weathering steel with nanoscale precipitates was fabricated, exhibiting a yield strength of 635 MPa, tensile strength of 750 MPa, and elongation of 21.2%. Precipitation strengthening plays a critical role in enhancing the room-temperature strength of ferritic steel. Full article

Microbiologically influenced corrosion (MIC) poses significant challenges in oilfield water injection environments, leading to substantial socioeconomic losses. L245 steel, a low-alloy steel widely used in oil and gas pipelines due to its excellent mechanical properties and cost-effectiveness, remains highly vulnerable to MIC during long-term service. This study uses surface characterization and electrochemical techniques to investigate the corrosion behavior of L245 pipeline steel under short-cycle conditions in a symbiotic environment of iron-oxidizing bacteria (IOB) and Shewanella algae (S. algae). Key findings revealed that localized corrosion of L245 steel was markedly exacerbated under coexisting IOB and S. algae conditions compared to monoculture systems. However, the uniform corrosion rate under symbiosis fell between the rates observed in the individual IOB and S. algae systems. Mechanistically, the enhanced corrosion under symbiotic conditions was attributed to the synergistic electron transfer interaction: IOB exploited electron carriers secreted by S. algae during extracellular electron transfer (EET), which amplified the microbial consortium’s capacity to harvest electrons from the steel substrate. These results emphasize the critical role of interspecies electron exchange in accelerating localized degradation of carbon steel under complex microbial consortia, with implications for developing targeted mitigation strategies in industrial pipelines exposed to similar microbiological environments. Full article