Search Results (940)

Steady-state visual evoked potential (SSVEP) paradigms are widely used in brain–computer interface (BCI) systems due to their reliability and fast response. However, traditional static stimuli may reduce user comfort and engagement during prolonged use. This study proposes a dynamic stimulation paradigm combining periodic motion trajectories with speed control. Using four frequencies (6, 8.57, 10, 12 Hz) and three waveform patterns (sinusoidal, square, sawtooth), speed was modulated at 1/5, 1/10, and 1/20 of each frequency’s base rate. An offline experiment with 17 subjects showed that the low-speed sinusoidal and sawtooth trajectories matched the static accuracy (85.84% and 83.82%) while reducing cognitive workload by 22%. An online experiment with 12 subjects participating in a fruit-slicing game confirmed its practicality, achieving recognition accuracies above 82% and a System Usability Scale score of 75.96. These results indicate that coordinated trajectory and speed modulation preserves SSVEP signal quality and enhances user experience, offering a promising approach for fatigue-resistant, user-friendly BCI application. Full article

Addressing the need for contact load detection in wind turbine main bearings during service, a roller contact load measurement method is proposed. An analytical model characterizes the contact load-to-inner bore strain mapping relationship. To overcome the inherent low sensitivity of direct bore strain measurement, bore-to-measurement-point sensitivity analysis was optimized. Multiple structurally optimized sensor brackets were designed to enhance strain measurement sensitivity, and their performance was comparatively evaluated via simulation. To mitigate sensitivity fluctuations caused by roller rotation phase variations, a strain–phase–load calculation method incorporating real-time phase compensation was developed and verified through simulation analysis. A dedicated roller contact load testing system was constructed and experimental validation was conducted. Results demonstrate 95% accuracy in contact load acquisition. This method accurately obtains roller contact loads in wind turbine main bearings, proving crucial for studying bearing mechanical behavior, predicting fatigue life, optimizing structural design, and enhancing reliability. Full article

Railway axles are among the most safety-critical components in rolling stock, as their failure can lead to catastrophic consequences. One of the most subtle damage mechanisms affecting these components is fretting fatigue, which is a particularly challenging damage mechanism in these components, as it can initiate cracks under real service conditions and is difficult to detect in its early stages, which is vital to ensure operational safety and to optimize maintenance strategies. This paper focuses on the development of fretting fatigue damage in solid railway axles under realistic service-like conditions. Full-scale axle specimens with artificially induced notches were subjected to loading conditions that promote fretting fatigue crack initiation and growth. Acoustic emission techniques were used to monitor the damage progression, and post-processing of the emitted signals, by using wavelet-based tools, was conducted to identify early indicators of crack formation. The experimental findings demonstrate that the proposed approach allows for reliable identification of fretting-induced crack initiation, contributing valuable insights into the in-service behavior of railway axles under this damage mechanism. Full article

Corrosion fatigue damage significantly affects the long-term service of marine platforms such as propellers. Fatigue testing of pre-corrosion specimens is essential for understanding damage mechanisms and accurately predicting fatigue life. However, traditional seawater-based tests are time-consuming and yield inconsistent results, making them unsuitable for rapid evaluation of newly developed equipment. This study proposes an accelerated corrosion testing method for ZCuAl₈Mn₁₃Fe₃Ni₂ nickel–aluminum bronze, simulating the marine full immersion zone by increasing temperature, adding H₂O₂, reducing the solution pH, and preparing the special solution. Coupled with the fatigue test of pre-corrosion specimens, the corrosion damage characteristics and their influence on fatigue performance were analyzed. A numerical simulation method was developed to predict the fatigue life of pre-corrosion specimens, showing an average error of 13.82%. The S–N curves under different pre-corrosion cycles were also established. The research results show that using the test solution of 0.6 mol/L NaCl + 0.1 mol/L H₃PO₄-NaH₂PO₄ buffer solution + 1.0 mol/L H₂O₂ + 0.1 mL/500 mL concentrated hydrochloric acid for corrosion acceleration testing shows good corrosion acceleration. Moreover, the test methods ensure accuracy and reliability of the fatigue behavior evaluation of pre-corrosion specimens of the structure under actual service environments, offering a robust foundation for the material selection, corrosion resistance evaluation, and fatigue life prediction of marine structural components. Full article

This study introduces a time-efficient rotating bending fatigue testing system featuring 11 dual-end spindles, enabling simultaneous testing of 22 specimens. Designed for high-throughput fatigue life (S–N curve) assessment, the system theoretically allows over 93% reduction in total test duration, with 87.5% savings demonstrated in validation experiments using AISI 304 stainless steel. The PLC-based architecture provides autonomous operation, real-time failure detection, and automatic cycle logging. ER16 collet holders are easily replaceable within one minute, and all the components are selected from widely available industrial-grade parts to ensure ease of maintenance. The modular design facilitates straightforward adaptation to different station counts. The validation results confirmed an endurance limit of 421 MPa, which is consistent with the established literature and within ±5% deviation. Fractographic analysis revealed distinct crack initiation and propagation zones, supporting the observed fatigue behavior. This high-throughput methodology significantly improves testing efficiency and statistical reliability, offering a practical solution for accelerated fatigue life evaluation in structural, automotive, and aerospace applications. Full article

Spot-welding joints are widely used in modern industries, and their fatigue life is crucial for the safety and reliability of structures. This paper proposes a method for predicting the fatigue life of spot-welding joints by integrating traditional structural stress methods and machine learning algorithms. Systematic fatigue tests were conducted on Q&P980 steel spot-welding joints to investigate the influence of the galvanized layer on fatigue life. It was found that the galvanized layer significantly reduces the fatigue life of spot-welding joints. Further predictions of fatigue life using machine learning algorithms, including Random Forest, Artificial Neural Networks, and Gaussian Process Regression, demonstrated superior prediction accuracy and generalization ability compared to traditional structural stress methods. The Random Forest algorithm achieved an R² value of 0.93, with lower error than traditional methods. This study provides an effective tool for the fatigue life assessment of spot-welding joints and highlights the potential application of machine learning in this field. Full article

Background/Objectives: Cardiorespiratory fitness (CRF) is of great interest in children and adolescents. Due to the limited availability of cardiopulmonary exercise testing, simple and reliable alternatives are needed. A stair climbing test (SCT) for the assessment of CRF developed at the Department of Pediatric Cardiology of the LMU University Hospital in Munich showed a strong correlation with VO₂max. The aim of this study is to prove its feasibility in a non-clinical setting and to analyse its results in a larger study population. Methods: During the “Hand aufs Herz” study, a comprehensive cardiovascular examination was carried out on 922 pupils and siblings (13.2 ± 7.8 years) at a high school in Bavaria. The SCT was performed to evaluate CRF: participants had to run up and down a total of four floors (14.8 m) as quickly as possible without skipping steps or holding on to the banister. Absolute time has been normalized over the standard height of 12 m to allow comparisons with different settings. An SCT Index was calculated to adjust results to the different weights of participants and the exact height of the staircase. Results: The SCT proved to be easily feasible and safe in non-clinical contexts. Out of 922 participants, 13 (1.4%) were not able to perform the test, and 3 (0.3%) had to interrupt it following fatigue or stumbling. A total of 827 participants aged from 9 to 17 years (13.1 ± 2.1 years, 45.8% girls) had a mean absolute SCT time of 53.4 ± 6.2 s and 43.3 ± 5.1 s when normalized over 12 m. Conclusions: The SCT represents a simple, cost- and time-saving test that allows a rapid and solid assessment of cardiorespiratory fitness in children and adolescents. We could demonstrate that it is safe and feasible in non-clinical contexts. Its short duration and universal applicability are valuable advantages that could facilitate the establishment of a repetitive cardiovascular screening in the pediatric population, particularly in outpatient departments or settings with low-resource systems. Full article

This study examines the effectiveness of energy-based models for fatigue life prediction of additively manufactured acrylonitrile butadiene styrene (ABS)/graphene nanoplatelet (GNP) composites. The effects of varying GNP weight percentages and filament raster orientations on the fatigue life of the samples were investigated theoretically. The required stress and strain values for use in energy-based models were obtained by solving two sets of Neuber and Ramberg–Osgood equations, utilizing the available values of notch strength reduction factors at each load level and the average Young modulus for each composite material. Results revealed that none of the studied energy-based models could accurately predict the fatigue life of the samples across the entire high- and low-cycle fatigue regimes, with strong dependence on the stress ratio (R). Instead, a novel fatigue life prediction model was developed by combining two existing energy-based models, incorporating stress ratio dependence for cases with negative mean stress. This model was tested for R values roughly between −0.22 and 0. Results showed that, for all samples at each raster orientation, most of the predicted fatigue lives fell within the upper and lower bounds, with a factor of ±2 across the entire range of load levels. These findings highlight the reliability of the proposed model for a wide range of R values when mean stress is negative. Full article

Aging railroad bridges present complex challenges due to advancing deterioration and outdated design assumptions. This study develops a comprehensive analytical approach for assessing an aging steel truss railroad bridge through finite element (FE) modeling, sensitivity analysis, and model updating, supported by field testing. An initial FE model of the bridge was created based on original drawings and field observations. Field testing using a laser Doppler vibrometer captured the bridge’s dynamic response (vibrations and deflections) under regular train traffic. Key structural parameters (material properties, section properties, support conditions) were identified and varied in a sensitivity analysis to determine their influence on model outputs. A hybrid sensitivity analysis combining log-normal sampling and a genetic algorithm (GA) was employed to explore the parameter space and calibrate the model. The GA optimization tuned the FE model parameters to minimize discrepancies between simulated results and field measurements, focusing on vertical deflections and natural frequencies. The updated FE model showed significantly improved agreement with observed behavior; for example, vertical deflections under a representative train were matched within a few percent, and natural frequencies were accurately reproduced. This validated model provides a more reliable tool for predicting structural performance and fatigue life under various loading scenarios. The results demonstrate that integrating field data, sensitivity analysis, and model updating can greatly enhance the accuracy of structural assessments for aging railroad bridges, supporting more informed maintenance and management decisions. Full article

High-speed trains have revolutionized modern transportation with their exceptional speeds, yet the essence of this technological breakthrough resides in the train’s wheels. These components are engineered to endure extreme mechanical stresses while ensuring high safety and reliability. In this paper, we selected the rim and web as representative components of the wheel and conducted a comprehensive and systematic study on their microstructure and mechanical properties. The wheels are typically produced through integral forging. To improve the mechanical performance of the wheel/rail contact surface (i.e., the tread), the rim is subjected to surface quenching or other heat treatments. This endows the rim with strength and hardness second only to the tread and lowers its ductility. This results in a more isotropic structure with improved fatigue resistance in low-cycle and high-cycle regimes under rotating bending. The web connects the wheel axle to the rim and retains the microstructure formed during the forging process. Its strength is lower than that of the rim, while its ductility is slightly better. The web satisfies current property standards, although the microstructure suggests further optimization may be achievable through heat treatment refinement. Full article

The evaluation of open-ended questions is typically performed by human instructors using predefined criteria to uphold academic standards. However, manual grading presents challenges, including high costs, rater fatigue, and potential bias, prompting interest in automated essay scoring systems. While automated essay scoring tools can assess content, coherence, and grammar, discrepancies between human and automated scoring have raised concerns about their reliability as standalone evaluators. Large language models like ChatGPT offer new possibilities, but their consistency and fairness in feedback remain underexplored. This study investigates whether ChatGPT can provide stable and fair essay scoring—specifically, whether identical student responses receive consistent evaluations across multiple AI interactions using the same criteria. The study was conducted in two marketing courses at an engineering school in Chile, involving 40 students. Results showed that ChatGPT, when unprompted or using minimal guidance, produced volatile grades and shifting criteria. Incorporating the instructor’s rubric reduced this variability but did not eliminate it. Only after providing an example-rich rubric, a standardized output format, low temperature settings, and a normalization process based on decision tables did ChatGPT-4o demonstrate consistent and fair grading. Based on these findings, we developed a scalable algorithm that automatically generates effective grading rubrics and decision tables with minimal human input. The added value of this work lies in the development of a scalable algorithm capable of automatically generating normalized rubrics and decision tables for new questions, thereby extending the accessibility and reliability of automated assessment. Full article

The development of multifunctional conductive hydrogels with rapid self-healing capabilities and powerful sensing functions is crucial for advancing wearable electronics. This study designed and prepared a polyvinyl alcohol (PVA)–borax hydrogel incorporating carbon nanotubes (CNTs) and biomass carbon nanospheres (CNPs) as dual-carbon fillers. This hydrogel exhibits excellent conductivity, mechanical flexibility, and self-recovery properties. Serving as a highly sensitive piezoresistive sensor, it efficiently converts mechanical stimuli into reliable electrical signals. Sensing tests demonstrate that the CNT/CNP/PVA–borax hydrogel sensor possesses an extremely fast response time (88 ms) and rapid recovery time (88 ms), enabling the detection of subtle and rapid human motions. Furthermore, the hydrogel sensor also exhibits outstanding cyclic stability, maintaining stable signal output throughout continuous loading–unloading cycles exceeding 3200 repetitions. The hydrogel sensor’s characteristics, including rapid self-healing, fast-sensing response/recovery, and high fatigue resistance, make the CNT/CNP/PVA–borax conductive hydrogel an ideal choice for multifunctional wearable sensors. It successfully monitored various human motions. This study provides a promising strategy for high-performance self-healing sensing devices, suitable for next-generation wearable health monitoring and human–machine interaction systems. Full article

As high-speed electric multiple units (EMUs) advance in speed and complexity, quasi-static design methods may underestimate the fatigue risks associated with high-frequency dynamic excitations. This study quantifies the contribution of gear meshing-induced vibrations (2512 Hz) to fatigue damage in EMU gearbox housings, revealing resonance amplification of local stresses up to 1.8 MPa at 300 km/h operation. Through integrated field monitoring and bench testing, we demonstrated that gear meshing excites structural modes, generating sustained, very high-cycle stresses (>10⁸ cycles). Crucially, fatigue specimens were directly extracted from in-service gearbox housings—overcoming the limitations of standardized coupons—passing the very high-cycle fatigue (VHCF) test to derive S-N characteristics beyond 10⁸ cycles. Results show a continuous decline in fatigue strength (with no traditional fatigue limit) from 10⁸ to 10⁹ cycles. This work bridges the gap between static design standards (e.g., FKM) and actual dynamic environments, proving that accumulated damage from low-amplitude gear-meshing stresses (3.62 × 10¹¹ cycles over a 12 million km lifespan) contributes to a 16% material utilization ratio. The findings emphasize that even low-magnitude gear-meshing stresses can significantly influence gearbox fatigue life due to their ultra-high frequency, warranting design consideration beyond current standards. Full article

In the context of increasing the complexity and intelligence of modern power systems, traditional maintenance approaches for circuit breakers have shown limitations in meeting both reliability and economic requirements. This paper proposes a multi-sensor data fusion fault detection method based on the RF-Adaboost algorithm for spring-operated circuit breakers. By integrating pressure, speed, coil current, and energy storage motor sensors into the mechanism, multi-source operational data are acquired and processed via denoising and feature extraction techniques. A fault detection model is then constructed using the RF-Adaboost classifier. The experimental results demonstrate that the proposed method achieves over 96% accuracy in identifying typical fault states such as coil voltage deviation, reset spring fatigue, and closing spring degradation, outperforming conventional approaches. These results validate the model’s effectiveness and robustness in diagnosing complex mechanical failures in circuit breakers. Full article

The design of custom abutments (CA) can affect the mechanical reliability of implant-supported restorations. The purpose of the study was to evaluate the influence of design parameters on the fatigue limit of CA and to compare optimized custom designs with the reference abutment (RA). A morse-tapered dental implant, an anatomical abutment, and a connector screw were digitalized using microcomputed tomography. A cone beam computed tomography scan was obtained from one of the authors to virtually place the implant-abutment assembly in the upper central incisor. Ten design parameters were selected according to the structural geometry of the RA and the implant planning. A reverse-engineered RA model was created in SOLIDWORKS and was modified considering a Taguchi orthogonal array to generate 36 CAs with ±20% dimensional variations. Finite element analysis was conducted in ABAQUS, and fatigue limits were estimated using Fe-safe. ANOVA (α = 0.1) identified the most influential parameters. Von Mises stress values ranged from 229 MPa to 302 MPa, and 94.4% of the CAs had a higher fatigue limit than the RA. Three parameters significantly affected the fatigue performance of the implant system. The design process of custom abutments includes critical design parameters that can be optimized for longer lifetimes of implant-abutment restorations. Full article