Search Results (790)

Traditional navigation relies on visual alignment with leading lights, a task typically monitored by bridge officers over extended periods. This process can lead to fatigue-related human factor errors, increasing the risk of maritime accidents and environmental damage. To address this issue, this study explores the use of convolutional neural networks (CNNs), evaluating different training strategies and hyperparameter configurations to assist officers in identifying deviations from proper visual leading. Using video data captured from a navigation simulator, we trained a lightweight CNN capable of advising bridge personnel with an accuracy of 86% during night-time operations. Notably, the model demonstrated robustness against visual interference from other light sources, such as lighthouses or coastal lights. The primary source of classification error was linked to images with low bow deviation, largely influenced by human mislabeling during dataset preparation. Future work will focus on refining the classification scheme to enhance model performance. We (1) propose a lightweight CNN based on SqueezeNet for night-time ship navigation, (2) expand the traditional binary risk classification into six operational categories, and (3) demonstrate improved performance over human judgment in visually ambiguous conditions. Full article

Modern aerospace engineering places increasing emphasis on materials that combine low weight with high mechanical performance. Fiber metal laminates (FMLs), which merge metal layers with fiber-reinforced composites, meet this demand by delivering improved fatigue resistance, impact tolerance, and environmental durability, often surpassing the performance of their constituents in demanding applications. Despite these advantages, inspecting such thin, layered structures remains a significant challenge, particularly when they are difficult or impossible to access. As with any new invention, they always come with challenges. This study examines the effectiveness of the fundamental anti-symmetric Lamb wave mode (A0) in detecting weak interfacial defects within Carall laminates, a type of hybrid fiber metal laminate (FML). Delamination detectability is analyzed in terms of strong wave dispersion observed downstream of the delaminated sublayer, within a region characterized by acoustic distortion. A three-dimensional finite element (FE) model is developed to simulate mode trapping and full-wavefield local displacement. The approach is validated by reproducing experimental results reported in prior studies, including the author’s own work. Results demonstrate that the A0 mode is sensitive to delamination; however, its lateral resolution depends on local position, ply orientation, and dispersion characteristics. Accurately resolving the depth and extent of delamination remains challenging due to the redistribution of peak amplitude in the frequency domain, likely caused by interference effects in the acoustically sensitive delaminated zone. Additionally, angular scattering analysis reveals a complex wave behavior, with most of the energy concentrated along the centerline, despite transmission losses at the metal-composite interfaces in the Carall laminate. The wave interaction with the leading and trailing edges of the delaminations is strongly influenced by the complex wave interference phenomenon and acoustic mismatched regions, leading to an increase in dispersion at the sublayers. Analytical dispersion calculations clarify how wave behavior influences the detectability and resolution of delaminations, though this resolution is constrained, being most effective for weak interfaces located closer to the surface. This study offers critical insights into how the fundamental anti-symmetric Lamb wave mode (A0) interacts with delaminations in highly attenuative, multilayered environments. It also highlights the challenges in resolving the spatial extent of damage in the long-wavelength limit. The findings support the practical application of A0 Lamb waves for structural health assessment of hybrid composites, enabling defect detection at inaccessible depths. Full article

This review critically examines the effects of moisture absorption on the mechanical and fatigue properties of natural fiber composites (NFCs), with a focus on tensile strength, elastic modulus, and long-term durability. Moisture uptake can cause reductions in tensile strength of up to 40% and in elastic modulus by 20–30% depending on fiber type, mass fraction (typically in the range of 30–60%), and surface treatments. The review highlights Ithat while surface modifications (e.g., alkaline and silane treatments) significantly mitigate moisture-induced degradation, their effectiveness is highly sensitive to the processing conditions. Additionally, hybridization strategies and optimized fiber orientations show promise in enhancing fatigue resistance under humid environments. Despite substantial progress, major challenges remain, including the lack of standardized testing protocols and the limited understanding of multiscale aging mechanisms. Future research directions include developing predictive models that couple moisture diffusion and mechanical deterioration, implementing advanced in situ monitoring of damage evolution, and exploring novel bio-based treatments. By addressing these gaps, NFCs can become more reliable and widely adopted as sustainable alternatives in structural applications. Full article

In actual service, asphalt pavement is subjected to freeze–thaw cycles and ultraviolet radiation (UV) over the long term, which can easily lead to mixture aging, enhanced brittleness, and structural damage, thereby reducing pavement durability. This study focuses on the influence of freeze–thaw cycles and ultraviolet aging on the performance of recycled asphalt mixtures. Systematic indoor road performance tests were carried out, and a fatigue prediction model was established to explore the comprehensive effects of recycled asphalt pavement (RAP) content, environmental action (ultraviolet radiation + freeze–thaw cycle), and other factors on the performance of recycled asphalt mixtures. The results show that the high-temperature stability of recycled asphalt mixtures decreases with the increase in environmental action days, while higher RAP content contributes to better high-temperature stability. The higher the proportion of old materials, the more significant the environmental impact on the mixture; both the flexural tensile strain and flexural tensile strength decrease with the increase in environmental action time. When the RAP content increased from 30% to 50%, the bending strain continued to decline. With the extension of environmental action days, the decrease in the immersion Marshall residual stability and the freeze–thaw splitting strength became more pronounced. Although the increase in RAP content can improve the forming stability, the residual stability decreases, and the freeze–thaw splitting strength is lower than that before the freeze–thaw. Based on the fatigue test results, a fatigue life prediction model with RAP content and freeze–thaw cycles as independent variables was constructed using the multiple nonlinear regression method. Verification shows that the established prediction model is basically consistent with the change trend of the test data. The research results provide a theoretical basis and optimization strategy for the performance improvement and engineering application of recycled asphalt materials. Full article

With the increasing severity of traffic congestion, the impact of random traffic patterns has emerged as an indispensable factor in the fatigue design and assessment of highway bridges. In this study, an analytical approach has been proposed for modeling the effects of random traffic patterns on fatigue damage. A fatigue damage ratio, referred to as RPEF, is introduced to establish the correlation between damage and traffic characteristics. Two quantitative parameters representing two characteristics of traffic loads, namely the average loading occurrence number (scale parameter) and the vehicle headway COVs (shape parameter), have been found to be excellent indices for clustering the different dimensional randomness of RPEFs. Based on a comprehensive case study, the realization of using equivalent RPEFs to evaluate bridge fatigue damage under mixed traffic conditions was explored. The results indicate that the actual fatigue damage of bridges can be evaluated through the superposition of different traffic pattern effects, provided that the pattern classification number fits the fluctuations in traffic flow. It is necessary to ensure the rationality of traffic pattern classification for structures with spans greater than 50 m, as an overly simplistic traffic pattern classification may lead to an underestimation of fatigue damage. Full article

The Ti-6Al-4V alloy is a typical α + β type titanium alloy and is widely used in the manufacture of aero-engine fans, compressor discs and blades. The working life of modern aero-engine components is usually required to reach more than 10⁸ cycles, which makes the infinite life design based on the traditional fatigue limit unsafe. In this study, through symmetrical loading high-cycle fatigue tests on Ti-6Al-4V titanium alloy, a nonlinear cumulative damage life prediction model was established. Further very-high-cycle fatigue tests of titanium alloys were carried out. The variation law of plastic strain energy in the evolution process of very-high-cycle fatigue damage of titanium alloy materials was described by introducing the internal stress parameter. A prediction model for the very-high-cycle fatigue life of titanium alloys was established, and the sensitivity analysis of model parameters was carried out. The results show that the established high-cycle/very-high-cycle fatigue models can fit the test data well. Moreover, based on the optimized model parameters through sensitivity analysis, the average error of the prediction results has decreased from 59% to 38%. The research aims to provide a model or method for predicting the engineering life of titanium alloys in the high-cycle/very-high-cycle range. Full article

Background: Post-concussion syndrome (PCS) and Functional Neurological Disorder (FND), including Functional Cognitive Disorder (FCD), are two frequently encountered but diagnostically complex conditions. While PCS is conceptualized as a sequela of mild traumatic brain injury (mTBI), FND/FCD encompasses symptoms incompatible with recognized neurological disease, often arising in the absence of structural brain damage. Yet, both conditions exhibit considerable clinical overlap—particularly in the domains of cognitive dysfunction, emotional dysregulation, and symptom persistence despite negative investigations. Objective: This review critically examines the shared and divergent features of PCS and FND/FCD. We explore their respective epidemiology, diagnostic criteria, and risk factors—including personality traits and trauma exposure—as well as emerging insights from neuroimaging and biomarkers. We propose the “Functional Overlay Model” as a clinical tool for navigating diagnostic ambiguity in patients with persistent post-injury symptoms. Results: PCS and FND/FCD frequently share features such as subjective cognitive complaints, fatigue, anxiety, and heightened somatic vigilance. High neuroticism, maladaptive coping, prior psychiatric history, and trauma exposure emerge as common risk factors. Neuroimaging studies show persistent network dysfunction in both PCS and FND, with overlapping disruption in fronto-limbic and default mode systems. The Functional Overlay Model helps to identify cases where functional symptomatology coexists with or replaces an initial organic insult—particularly in patients with incongruent symptoms and normal objective testing. Conclusions: PCS and FND/FCD should be conceptualized along a continuum of brain dysfunction, shaped by injury, psychology, and contextual factors. Early recognition of functional overlays and stratified psychological interventions may improve outcomes for patients with persistent, medically unexplained symptoms after head trauma. This review introduces the Functional Overlay Model as a novel framework to enhance diagnostic clarity and therapeutic planning in patients presenting with persistent post-injury symptoms. Full article

The performance of SBS (Styrene Butadiene Styrene) modified asphalt mixtures can be enhanced through the addition of fibers including basalt, ceramic, and glass. This study investigates whether a reduced SBS content of 3%, combined with 0.3% fiber reinforcement can match or exceed the performance of a traditional 7% SBS mixture. A comparative analysis was carried out by examining both performance efficiency and life cycle costs across ceramic, basalt, and glass fiber-reinforced mixtures. Maintenance requirements for each scenario were factored into the life cycle analysis. To assess structural integrity, 3D finite element simulations were conducted using the Burger’s logit model while focusing on fatigue and rutting damage. Findings indicate that basalt and ceramic fiber mixtures deliver better asphalt mixtures, thereby outperforming the 7% SBS mix by requiring fewer maintenance interventions. However, due to the higher cost of ceramic fiber mixtures at 831 Eur/m³, basalt fiber emerges as the more cost-effective option, achieving a performance efficiency gain of 20% with reduced costs at 532 Eur/m³. Among the fiber-reinforced variants, glass fiber showed the least improvement in performance, with a difference in 11% and 13% when compared to ceramic fiber and basal fiber, respectively. Full article

The intentional yaw offset of wind turbines has shown potential to redirect wakes, enhancing overall plant power production, but it may increase fatigue loading on turbine components. This study analyzed fatigue loads on the NREL 5 MW reference wind turbine under varying yaw offsets using blade element momentum theory, dynamic blade element momentum, and the converging Lagrange filaments vortex method, all implemented in OpenFAST. Simulations employed yaw angles from −40° to 40°, with turbulent inflow generated by TurbSim, an OpenFAST tool for realistic wind conditions. Fatigue loads were calculated according to IEC 61400-1 design load case 1.2 standards, using thirty simulations per yaw angle across five wind speed bins. Damage equivalent load was evaluated via rainflow counting, Miner’s rule, and Goodman correction. Results showed that the free vortex method, by modeling unsteady aerodynamic forces, yielded distinct differences in damage equivalent load compared to the blade element method in yawed conditions. The free vortex method predicted lower damage equivalent load for the low-speed shaft bending moment at negative yaw offsets, attributed to its improved handling of unsteady effects that reduce load variations. Conversely, for yaw offsets above 20°, the free vortex method indicated higher damage equivalent for low-speed shaft torque, reflecting its accurate capture of dynamic inflow and unsteady loading. These findings highlight the critical role of unsteady aerodynamics in fatigue load predictions and demonstrate the free vortex method’s value within OpenFAST for realistic damage equivalent load estimates in yawed turbines. The results emphasize the need to incorporate unsteady aerodynamic models like the free vortex method to accurately assess yaw offset impacts on wind turbine component fatigue. Full article

Grain boundary weakening in high-temperature environments significantly influences the fatigue crack growth mechanisms of nickel-based superalloys, introducing challenges in accurately predicting fatigue life. In this study, a dislocation-density-based crystal plasticity phase-field (CP–PF) model is developed to simulate the fatigue crack growth behavior of the GH4169 alloy under both room and elevated temperatures. Grain boundaries are explicitly modeled, enabling the competition between transgranular and intergranular cracking to be accurately captured. The grain boundary separation energy and surface energy, calculated via molecular dynamics simulations, are employed as failure criteria for grain boundary and intragranular material points, respectively. The simulation results reveal that under oxygen-free conditions, fatigue crack propagation at both room and high temperatures is governed by sustained shear slip, with crack advancement hindered by grains exhibiting low Schmid factors. When grain boundary oxidation is introduced, increasing oxidation levels progressively degrade grain boundary strength and reduce overall fatigue resistance. Specifically, at room temperature, oxidation shortens the duration of crack arrest near grain boundaries. At elevated service temperatures, intensified grain boundary degradation facilitates a transition in crack growth mode from transgranular to intergranular, thereby accelerating crack propagation and exacerbating fatigue damage. Full article

The accumulation of fatigue damage is primarily caused by cyclic plastic deformation. In low-cycle fatigue, cyclic plastic deformation is the dominant deformation mode. In high-cycle fatigue, although most deformation is elastic, plastic deformation may still occur in localized regions of stress concentration and plays a critical role in the initiation of fatigue cracks. Considering that cyclic plastic deformation can be characterized by hysteresis loops, this study modifies the flow stress equation and the cyclic plastic deformation relationship based on stress–strain hysteresis loops at half-life cycles under different strain amplitudes. An improved model for life prediction that incorporates the effects of strain amplitude is proposed. The results of experiments on 310S stainless steel and 1045 carbon steel demonstrate that the model achieved prediction errors within a factor of two and provided reliable predictions for both high-cycle and low-cycle fatigue life across the entire ε-N curve. Full article

Vibration control constitutes a critical consideration in structural design, as excessive oscillations may precipitate fatigue damage, operational instability, and catastrophic failures. Dynamic vibration absorbers (DVAs), serving as passive control devices, demonstrate remarkable efficacy in mitigating structural vibrations across engineering applications. This study systematically investigates the design of DVAs for vibration suppression of a cantilevered plate through integrated theoretical modeling, parameter optimization, structural implementation, and experimental validation. Key methodologies encompass receptance coupling substructure analysis (RCSA) for system dynamics characterization and H∞ optimization for absorber parameter identification. Experimental results reveal 74.2–85.7% vibration amplitude reduction in target mode, validating the proposed design framework. Challenges pertaining to boundary condition uncertainties and manufacturing tolerances are critically discussed, providing insights for practical implementations. Full article

Impact Drilling Technology is one of the most effective methods for enhancing the penetration rate and efficiency in hard rock formations. Downhole axial vibration impact tools can provide a stable impact load, but they also increase the complexity of the Bottom Hole Assembly (BHA) motion. Addressing the problem of vibration fatigue in the lower BHA when subjected to high-frequency impact stresses during impact drilling, this study utilizes finite-element impact modules and Design-Life fatigue analysis software to establish a nonlinear dynamic model of the drill string assembly under axial excitation. It investigates the influence patterns of control parameters, such as the impact energy and impact frequency, on BHA vibration damage and rock-breaking efficiency. The results show that the vibration characteristics of the BHA are significantly affected by the impact tool’s control parameters. Increasing the input impact energy intensifies the amplitude of alternating stress in the drill string system. Meanwhile, the equivalent stress fluctuation of the drill string tends to stabilize at high frequencies above 100 Hz, indicating that high-frequency impacts are beneficial for mitigating vibration damage and prolonging the service life of the BHA. This study provides a theoretical basis for reducing the drill string fatigue damage and optimizing the drilling parameters for an improved performance. Full article

Marine risers are essential for offshore resource extraction, yet traditional metal risers encounter limitations in deep-sea applications due to their substantial weight. Fiber-reinforced polymer (FRP) composites offer a promising alternative with advantages including low density and enhanced corrosion/fatigue resistance. However, FRP risers remain susceptible to fatigue damage from vortex-induced vibration (VIV). Therefore, this study investigated VIV behavior of FRP composite risers considering the coupled effect of tensile-flexural moduli, top tensions, slenderness ratios, and flow velocities. Through an orthogonal experimental design, eighteen cases were analyzed using multivariate nonlinear fitting. Results indicated that FRP composite risers exhibited larger vibration amplitudes than metal counterparts, with amplitudes increasing to both riser length and flow velocity. It was also found that the optimized FRP configuration demonstrated enhanced fiber strength utilization. Parameter coupling analysis revealed that the multivariate nonlinear fitting model achieved sufficient accuracy when incorporating two coupled parameters, with the most significant interaction occurring between flexural modulus and top tension. Full article

At present, the research on bridge structure health monitoring mainly focuses on discovering existing structural damage and less on predicting when the damage will occur in the future. This paper proposes a fatigue damage prognosis method for the main girders of cable-stayed bridges based on wavelet neural networks (WNNs). This method integrates WNN with multi-scale finite element modeling to predict fatigue damage progression. First, the theoretical foundation and implementation algorithms of the WNN are elaborated on and applied to forecast the future load environments of cable-stayed bridges. Subsequently, multi-scale finite element models are employed to derive stress influence lines for critical fatigue-prone regions in the main girder of the cable-stayed bridge. Finally, fatigue reliability methods are utilized to predict the fatigue reliability indices, service life, and failure probabilities of critical fatigue details. The proposed prognosis method in this paper can accurately predict the future operation conditions and remaining service life of bridge structures so as to provide a more reasonable maintenance strategy for bridge structures. Full article