Search Results (920)

This study evaluated fracture risk associated with varying trochlear groove depth-to-patellar thickness (D/T) ratios in toy and small-breed dogs using finite element analysis and cadaveric mechanical testing. Finite element models derived from computed tomography data of a 4.5-kg toy poodle were adjusted to simulate D/T ratios ranging from 0.5 to 2.0 and analyzed for von Mises stress, principal strain, safety factor, and fatigue life under standing, trotting, and jumping conditions. Increasing D/T ratios led to progressive rises in stress and compressive strain, with the safety factor falling below 1.0 during jumping at ratios of 1.0 or higher. Fatigue life declined sharply beyond a ratio of 1.25 and reached zero-cycle failure at 2.0. Complementary mechanical testing of six distal femurs (6.42–8.7 kg), surgically modified to D/T ratios of 0.5, 1.0, or 1.5, revealed fracture patterns consistent with finite element predictions. These findings suggest that excessive trochlear deepening may compromise femoral integrity and elevate fracture risk, particularly under cyclic loading. Maintaining a D/T ratio between 0.75 and 1.0 may provide an optimal balance between effective patellar tracking and mechanical safety. Full article

Bearings are essential components in mechanical systems, with ceramic ball bearings increasingly adopted in turbine, automotive, and aerospace applications due to their superior strength and durability. Despite these advantages, bearings are subjected to significant cyclic loading, which can accelerate plastic deformation and lead to sudden catastrophic failure. Current approaches for predicting bearing lifespan rely on time-consuming theoretical and experimental methods. This study proposes a more efficient finite element (FE) approach to predict fatigue behaviour in silicon nitride ball bearings operating under lubricated conditions. In this research, a 12.7 mm diameter silicon nitride ball bearing was analysed under a Hertzian contact pressure of 3 GPa using SolidWorks Simulation 2023(SWS). Friction coefficients ranging from 0.00 to 1.00 were investigated to represent different lubrication conditions. The results indicate that the stress amplitude remained below the fatigue limit of 1.02 GPa for friction coefficients up to 0.80, while fatigue failure was predicted at a coefficient of 1.00, corresponding to 1.086 × 10⁴ cycles. Full article

Purpose—The flexspline of a harmonic drive constitutes a thin-walled structure with discontinuous gear rim and cylinder configuration, where cyclic stresses induce stress concentration, followed by crack initiation, propagation, and ultimately fatigue failure. This paper reviews advancements in understanding its mechanical properties and fatigue failure mechanisms, aiming to establish a foundation for enhancing operational longevity and guiding future research. Design/Methodology/Approach—The study integrates meshing theory, tooth shape parameters, cylinder stress influencers, and assembly/meshing stress considerations. Theoretical analysis, finite element simulations, and experimental methods are employed to examine stress patterns and fatigue dynamics. Structural parameters and tooth profiles are systematically analyzed for their impact on stress distribution and fatigue life. Findings—Flexspline fatigue failure arises from tooth root stress concentration and cylinder bending stress accumulation. The double-circular-arc tooth profile boosts load capacity by 35% relative to the involute profile, yet demands high-precision machining to preserve meshing performance. Increasing cylinder length mitigates stress concentration but reduces torsional stiffness, while optimized root fillet radii can lower the stress concentration coefficient by 28%. Assembly interference and meshing contact stress accelerate crack initiation, as validated by transient dynamics simulations. Surface strengthening processes (e.g., shot peening) enhance fatigue life by up to 66% through residual compressive stress regulation. Originality/Value—This paper synthesizes multi-scale research on flexspline design, structural optimization, and fatigue mechanisms, proposing novel approaches such as “manufacturability-oriented optimization” and digital twin-driven monitoring. By linking dynamic loads, material properties, and geometric parameters, it bridges theoretical gaps and provides actionable insights for high-precision harmonic drives in robotics and aerospace, advancing reliability in precision transmission systems. Full article

With a low cement dosage and a well-formed skeleton-dense structure, super-large-particle-size cement-stabilized macadam (CTB-50, maximum particle size of 53 mm) can effectively reduce base course cracking and construction costs. Nevertheless, the existing literature lacks research on the strength design criteria for CTB-50, and the absence of dedicated strength specifications currently limits its practical application. This study investigates the mechanical properties of CTB-50 and the stress levels in the (sub)base course under construction vehicle loading, based on the vertical vibration compaction method (VCM) and Miner’s fatigue cumulative theory. Aiming to prevent ultimate failure under a single load during construction and fatigue failure under repeated loading during both construction and operation, this study proposes strength criteria for CTB-50 to control fatigue damage. The 7-day compressive strength of CTB-50 specimens prepared using the VCM is approximately 90% of that of field core samples, whereas that obtained using the static-pressing method is less than 70% of the field core sample value. The mechanical strengths of CTB-50 specimens prepared via the VCM are highly correlated with those of on-site core samples. Based on the strength criteria for controlling ultimate failure during construction and fatigue failure during service, this paper proposes strength criteria for controlling the fatigue failure of CTB-50. Specifically, the 7-day splitting and compressive strengths of the base course for expressways and first-class highways should exceed 0.77 MPa and 7.6 MPa, respectively, while those of the sub-base course should exceed 0.71 MPa and 7.0 MPa, respectively. Full article

To address the challenge of maintenance decision-making for critical components in electro-hydraulic servo material fatigue testing machine, characterized by weak state observability and difficulty in degradation prediction, a multi-component joint maintenance decision-making method based on multi-head deep reinforcement learning is proposed. Considering the heterogeneity of the degradation mechanisms and observation methods for the four components—bearing beam, fixture, main machine sensors, and hydraulic oil tank—a continuous-discrete hybrid state Markov decision process (HS-MDP) is constructed. To account for differences in maintenance strategies across components, a differentiated discrete action space for each component is designed, and engineering feasibility constraints are explicitly integrated into the policy through action masking. A data-quality loss term, determined by the degradation level of the sensors, is introduced into the reward function to align the optimization objective with the metrological properties of the fatigue testing machine. Based on the Branching Dueling DQN framework, a Q-network structure is constructed, incorporating a shared encoder, an inter-component attention mechanism, and multi-head branched outputs. Taking a 100 kN electro-hydraulic servo fatigue testing machine as a case study, comparisons with baseline strategies such as periodic maintenance, threshold-based condition-based maintenance (CBM), independent DQN, and PPO indicate that the proposed method reduces the average annual total cost by 60.3% compared to periodic maintenance and by 42.6% compared to threshold-based CBM. The number of failures decreases from 9.8 times/year to 1.4 times/year, while data efficiency increases from 82.1% to 96.2%. Ablation experiments and robustness tests further verify the critical contributions of three key design elements: action masking, inter-component attention, and data-quality loss. Full article

The long-term reliability of stay cables is essential to the structural integrity of cable-stayed bridges, particularly under the coupled effects of high stress ratios, progressive corrosion, and local stress concentrations. Conventional fatigue formulations—such as S–N curves or static Weibull models—are inadequate for representing the nonlinear and stochastic nature of corrosion-fatigue deterioration. This study develops a time-dependent reliability model formulated within a four-parameter Weibull framework, where the shape and scale parameters evolve as functions of the corrosion rate and stress ratio. The corrosion evolution is modeled by an exponential function of exposure time, establishing a temporal coupling between mechanical loading and environmental degradation. Analytical derivations yield closed-form expressions for the time-dependent hazard function ℎ(t) and survival function R(t), providing explicit reliability evaluation without iterative computation. At the system level, a series–parallel reliability model is constructed by integrating wire-level degradation with a load redistribution function that captures sequential wire failures. Model parameters are estimated using a maximum-likelihood method based on 99 experimental datasets, and Monte Carlo simulations are performed to assess stochastic reliability evolution under varying corrosion intensities. The findings show that models incorporating corrosion evolution and stress-amplification effects consistently predict earlier fatigue failure than those based on the conventional assumption of constant corrosion, thereby offering a more conservative and realistic representation of structural degradation. The proposed framework is mathematically tractable and broadly applicable, enabling rigorous corrosion–fatigue reliability assessment for cable-stayed structures and other complex multi-component systems. Full article

Lactate was traditionally considered a metabolic by-product of anaerobic glycolysis, mainly associated with tissue hypoxia and muscle fatigue. However, increasing evidence has redefined lactate as a multifunctional metabolic intermediate and signaling molecule involved in exercise-induced systemic adaptations. During physical activity, circulating lactate levels rise markedly when skeletal muscle production exceeds systemic clearance, allowing lactate to act as an exercise-responsive metabolite, or exerkine, and as a mediator of cardiometabolic adaptation. In the cardiovascular system, lactate serves not only as an efficient substrate for myocardial energy production but also as a regulator of vascular tone, endothelial function, angiogenesis, inflammation, and cardiac remodeling. These effects occur through receptor-dependent and receptor-independent mechanisms, including activation of hydroxycarboxylic acid receptor 1 (HCAR1/GPR81), modulation of intracellular redox balance, and histone or non-histone protein lactylation. This review summarizes current evidence on lactate in cardiovascular physiology and disease, focusing on myocardial lactate metabolism, HCAR1/GPR81 signaling, protein lactylation, extracellular vesicle communication, gut microbiota interactions, and therapeutic implications in heart failure, atherosclerosis, and diabetic cardiomyopathy. Although lactate is also produced under resting, postprandial, and pathological conditions, exercise is characterized by the amplitude and kinetics of lactatemia, coordinated hormonal and hemodynamic responses, and transient high-concentration signaling. These features support exercise-derived lactate as a context-dependent cardiovascular exerkine. Full article

Shoulder injuries due to labor-related lifting tasks are widespread in manufacturing and logistics companies. Prolonged shifts and repetitive motions lead to muscle fatigue, significantly elevating the risk of both acute accidents and chronic musculoskeletal disorders. Many passive exoskeletons which use springs to provide lifting assistance have been commercialized, and many active exoskeletons have been researched. The drawback to passive exoskeletons is the larger the lifting force that they produce, the larger the force required to lower the arms. This contributes to tiring the user. Conversely, active exoskeletons require substantial energy to provide meaningful torque. Furthermore, they pose a safety risk; a sudden power failure could result in an instantaneous loss of support, potentially causing the user to drop a heavy load and sustain injury. This research project proposes a hybrid exoskeleton with a parallel elastic actuator that uses a motorized helical actuator which can be tuned to improve lifting performance. This paper evaluates the kinematics and statics of the proposed exoskeleton, details the design and implementation of the electrical control system, shows mechanism optimization of the mechanical advantage profile, and validates the concept through the construction and experimental testing of a functional prototype. Full article

Wind turbines are increasingly deployed at larger scales and in harsher operating environments, leading to greater structural complexity, stronger load variability, and higher maintenance demands across both drivetrain and structural components. Reported field data indicate that gearboxes and bearings account for approximately 30–40% of total turbine downtime, while blade-related failures contribute roughly 20–25% of reported failure events, primarily through fatigue, delamination, leading-edge erosion, and lightning-induced defects. In parallel, large-scale and offshore turbines show increasing susceptibility to tower fatigue cracking, corrosion-assisted degradation, and flange joint bolt-preload loss under cyclic and environmental loading. This review provides a comprehensive applied-engineering synthesis of failure mechanisms, reliability challenges, and monitoring strategies for major wind turbine components, including gearboxes, bearings, blades, towers, and flange joints. A wide range of condition monitoring, structural health monitoring (SHM), and prognostics and health management (PHM) approaches is critically examined, including vibration analysis, acoustic emission, ultrasonic inspection, infrared thermography, impedance-based sensing, electromagnetic methods, machine vision, SCADA-based diagnostics, and artificial-intelligence-assisted fault classification. The review compares these techniques in terms of detectable damage types, spatial coverage, sensitivity, deployment practicality, and limitations under real operating conditions. In addition, statistical reliability methods and data-driven models are discussed to interpret failure trends and uncertainty. Recent AI-based studies have reported fault classification accuracies exceeding 90% under controlled or semi-controlled conditions; however, their field reliability remains constrained by data imbalance, domain shift, limited labeled failure datasets, model interpretability, and insufficient validation under realistic turbine operating environments. The main contribution of this review is an integrated applied synthesis that connects drivetrain and structural failure mechanisms with measurable monitoring indicators, diagnostic technologies, AI-enabled PHM limitations, and predictive-maintenance decision needs. The paper provides practical guidance for monitoring design, early fault detection, predictive maintenance, and long-term reliability improvement in next-generation wind turbine systems. Full article

Fatigue cracking remains a critical challenge in asphalt pavement design, yet conventional prediction methods fail to capture the fundamental damage mechanisms governing failure evolution. This study proposes an innovative residual strain-based approach to predict the fatigue life of crumb rubber modified asphalt (CRMA) mixtures. Through semi-circular bending (SCB) tests under varying aging conditions and stress ratios, a modified Burgers model was employed to decompose residual strain into residual viscoelastic strain (RVES) and residual viscous-flow strain (RVFS) components. The key innovation lies in establishing the residual strain ratio (RSR) as a damage evaluation parameter, with its plateau value (PV) serving as the independent variable in a novel fatigue prediction equation. Results demonstrate that while RVES stabilizes after initial loading, RVFS accumulation drives fatigue damage progression. The RSR-defined damage factor exhibits a distinct three-stage evolution accurately characterized by the ExpAssoc model (R² > 0.97). The proposed PV-based fatigue equation achieves prediction errors below 15% when validated against field core samples, offering a mechanistically sound and practically viable alternative to conventional phenomenological approaches. Full article

This study presents a combined numerical–statistical framework based on the Extended Finite Element Method (XFEM) and the Taguchi optimization method to assess the fracture behavior of pressurized pipelines containing external longitudinal cracks. XFEM is employed to evaluate the local fracture response without remeshing, while the Taguchi method is used to quantify the influence of key parameters and identify an optimal configuration with a limited number of simulations. The control parameters considered are internal pressure, initial crack length, and wall thickness, and the evaluated mechanical responses include circumferential stress, the J-integral, and the stress intensity factor. The optimization follows the “smaller-the-better” criterion to minimize stress concentration, fracture-driving forces, and the risk of structural failure. Results indicate that internal pressure predominantly affects circumferential stress and the stress intensity factor, whereas wall thickness has the greatest influence on the J-integral. The optimal parameter combination is determined through signal-to-noise ratio analysis and validated using the delta method, confirming the robustness of the selected configuration. A confirmation simulation performed with XFEM demonstrates a consistent reduction in all fracture-related mechanical responses, highlighting the effectiveness of the proposed approach. It should be noted that the present study is limited to the static fracture assessment of external cracks and does not address fatigue crack growth or fatigue life prediction. Overall, the proposed methodology provides a decision-support tool for pipeline integrity management by integrating numerical fracture mechanics analysis with robust design optimization, thereby contributing to safer operation and improved structural reliability. Full article

Water damage under the coupled effects of traffic load and pore water pressure (PWP) is a primary cause of early failure in asphalt pavements. Although dense-graded pavements generally have low void ratios, excess PWP poses a severe threat to durability under extreme conditions. These conditions include heavy rainfall, water accumulation in wheel tracks, and upward capillary water rise. In this study, a mesoscopic model considering fluid–solid coupling effects was established using the Particle Flow Code in the 2 Dimensions (PFC2D) platform, which is based on the discrete element method (DEM). A parallel-bonded stress corrosion model was introduced to describe damage evolution. The results show that the maximum positive PWP increased monotonically with load, reaching a distinct peak value at a critical loading frequency under specific load amplitudes. At this critical frequency, the fatigue life was significantly shortened compared to lower-frequency conditions. The PWP response exhibited a clear phase lag relative to the applied load, with the lag angle increasing alongside frequency. Furthermore, the absolute value of the minimum PWP continued to increase with fatigue damage accumulation. This indicates that regions with a vacuum suction effect were continuously expanding, which is a key reason for asphalt film stripping from the aggregate surface. These findings provide a theoretical basis for understanding mesoscopic water damage mechanisms in asphalt pavements and offer a reference for durability design. Full article

(1) Aluminum bonding wires are mostly used for electrical contact and transmission of electrical signals in power electronic modules. Combined cyclical mechanical and thermal loads acting on the wires can lead to premature failure of the whole module. For this purpose, based on extensive fatigue tests on a 300 µm Al-Pure wire, the authors developed, calibrated and applied a fatigue life model for a cycle range of $R=0.1$ to $R=0.7$ to other comparable aluminum wires in two previous publications. (2) Since the model is supposed to be used in an FEM post-processor for predicting the lifetime of wire bridges, the existing model was expanded in the following work. (3) Temperature dependence is included in the fatigue model, and it is made more robust in the whole possible R-range to be able to cope with the highly variable load cases in real components. In addition, a creep rupture model was developed and combined with the fatigue model by linear damage accumulation. (4) The applicability of the lifetime consumption model is demonstrated for several combined load cases. It is shown that it is necessary to consider both fatigue and creep in a combined model for a reliable lifetime prediction. Otherwise, the lifetime could be underestimated by several orders of magnitude, depending on the load case. Full article

To meet the increasing demands of aircraft engines for high thrust-to-weight ratios and elevated turbine inlet temperatures, turbine blades have been progressively designed with thin-walled structures. It has been demonstrated that the mechanical properties of Ni₃Al-based single-crystal alloys (SXs) are highly sensitive to specimen thickness. In this study, the high-cycle fatigue behavior of [111]-oriented Ni₃Al-based SXs with wall thicknesses of 0.3, 0.5, and 0.8 mm was systematically investigated under tensile–tensile loading conditions at 1000 °C. The results revealed that, as the wall thickness decreased, the fatigue life of the alloy significantly deteriorated, while the crack initiation site gradually shifted from the specimen interior toward the surface and near-surface regions. Furthermore, the fatigue failure mode transitioned from being dominated by internal defects to being controlled primarily by near-surface damage. Near-surface damage induced by high-temperature oxidation and geometric constraints was identified as the primary factor responsible for the degradation of the high-cycle fatigue performance of the SXs. In addition, the cyclic deformation behavior at 1000 °C was governed by the synergistic effects of dislocation climb, cross-slip, and γ′-phase shearing. This study provides both theoretical guidance and experimental evidence for the structural optimization of next-generation single-crystal turbine blades for advanced aircraft engines. Full article

Rock–concrete composites are critical load-bearing elements in geotechnical engineering applications such as slope support. Their mechanical response and damage evolution after fatigue disturbances, such as blasting and mechanical operations, govern the long-term stability and safety of engineered structures. To fully capture these complex behaviors, this study presents a novel multi-scale approach by integrating uniaxial compression tests with three-dimensional digital image correlation and discrete element modeling. This combined experimental–numerical framework is employed to systematically examine the macro- and meso-scale mechanical behavior, crack evolution, and energy response of composites with varying interface angles after quasi-static cyclic loading. The results reveal that as the interface angle increases, the peak strength declines markedly while the brittleness index increases, reflecting a distinct transition in the failure mode from plastic-dissipation-dominated to elastic-energy-storage-dominated. Consequently, the dominant failure mechanism shifts from tensile to shear-slip control. Furthermore, fatigue disturbances exacerbate material degradation, inducing a composite “interface shear–end tension” failure in specimens with higher interface angles and significantly raising the proportion of shear cracks. Energy analysis indicates that cyclic loading enhances the elastic energy storage capacity, and the energy conversion threshold rises continuously with the interface angle. These findings clarify the multi-scale control mechanisms of interface geometry on fatigue-induced failure, providing a theoretical foundation for predicting fatigue life and enabling early pre-warning of failures in rock–concrete engineering structures. Full article