Search Results (581)

Flow lines in aluminum alloy forgings are not merely post-deformation metallographic features; they are integrated indicators of material transport, microstructural evolution, defect susceptibility, and service performance. This review critically examines the mechanisms controlling flow-line evolution, with emphasis on constitutive flow behavior, dynamic recovery and recrystallization, second-phase redistribution, friction, thermal gradients, and die/preform design. It then evaluates how abnormal flow paths promote key defects, including folding/laps, flow-through discontinuities, vortex-like instability, and exposed flow lines, and distinguishes well-established mechanisms from topics that still rely on indirect evidence. Particular attention is given to the effects of flow-line morphology on anisotropy, notch sensitivity, corrosion-assisted damage, and fatigue life in forged aluminum alloys. Current control strategies, including preform optimization, FE-based backward tracing, multiphysics defect indices, frictional heat management, and isothermal forging, are also assessed. The available literature shows that stable contour-following flow lines are essential for the simultaneous control of defect formation, microstructural homogeneity, and durability, while major research needs remain in in situ validation, quantitative defect criteria, and digitally closed-loop process control. This review is therefore framed as a critical narrative synthesis rather than a formal systematic review; emphasis is placed on forging-centered studies that directly relate flow-path evolution to defect formation, anisotropy, fatigue, and process optimization, while evidence transferred from adjacent processes is treated as mechanistic support rather than equivalent proof. Full article

Laser-based Powder Bed Fusion (LPBF) enables the fabrication of complex metal components but often results in high porosity and microdefect densities, compromising fatigue performance despite acceptable static properties. Standard fatigue characterisation methods are time-consuming and costly and yield scattered results due to defect-induced brittleness and residual stresses. This study investigates the application of thermographic techniques as a rapid alternative for evaluating the intrinsic fatigue behaviour of tensile coupons fabricated by LPBF employing AISI 316L steel. By monitoring surface temperature during stepwise static monotone and fatigue loading, thermographic methods aim to detect early hints of heat dissipation associated with microdamage initiation. Approaches based on temperature harmonic analysis have been implemented, allowing near-real-time and full-field mapping of stress distribution and damage development. Results show that harmonic metrics correlate with the material state and effectively track the thermoelastic effect-induced temperature changes. Some evidence is found regarding the onset of intrinsic heat dissipation, which needs to be confirmed by more focused and extensive experimental tests. Full article

The structural integrity of bogie frames is a critical factor in the safety and reliability of railway rolling stock, requiring advanced assessment methods to handle complex, multi-axial stress states. This research presents a robust numerical framework for the preliminary fatigue evaluation of a metro bogie frame, integrating high-fidelity Finite Element Analysis (FEA) with the Findley multi-axial fatigue criterion. The methodology overcomes the limitations of traditional uniaxial verification methods by employing a localized critical plane approach, implemented through a proprietary computational code. The investigation simulates a realistic operational scenario by superimposing a static vertical load of 15 tons per side with dynamic components derived from on-track accelerometric data. This integrated loading condition enables a precise reproduction of the “rotating” stress states typically encountered in service. Global structural analysis identified critical transverse welded joints as high-stress concentration zones, which were then subjected to a detailed multi-axial investigation. By correlating the extracted stress tensors with the resistance category included in the reference standard, over a regulatory life of 10 million cycles, a maximum cumulative damage index of 0.4602 was recorded. The results demonstrate that while the frame possesses adequate structural reserves, nearly half of its fatigue life is consumed in localized nodes. This methodology provides a reliable and computationally efficient tool for the structural health monitoring and development of innovative railway geometries, offering a superior predictive capability that remains scarcely utilized by major rolling stock manufacturers. Full article

The mechanical response of 7xxx aluminum alloys is strongly influenced by both alloy chemistry and the resulting microstructure. In this study, the effect of precipitate characteristics on the fatigue behavior of three 7xxx aluminum alloys with different total amounts of main alloy elements was systematically investigated. Quantitative microstructural characterization was performed under T6 and T74 heat-treatment conditions by combining scanning electron microscopy, transmission electron microscopy, and electron backscatter diffraction. Meanwhile, hardness measurements, room-temperature tensile tests, and fatigue crack growth experiments were carried out to evaluate the mechanical behavior. The results show that, within the present alloy set, the over-aged condition and the alloys with higher overall alloying levels exhibited lower fatigue crack growth rates, which correlated with the coarsening of intragranular precipitates. Such microstructural evolution is suggested to facilitate dislocation motion and thereby reduce fatigue damage associated with dislocation pile-up in the present alloy set. In this work, three typical 7xxx aluminum alloys with different alloying levels were systematically investigated under T6 and T74 conditions. A statistical criterion was established to distinguish GPII zones from η′ precipitates, and a model linking precipitate characteristics to fatigue crack growth behavior was further developed. The present study aims to provide a quantitative framework for understanding and predicting the fatigue behavior of 7xxx aluminum alloys with different total amounts of main alloy elements. Full article

Titanium alloys exhibit exceptional strength-to-density ratios, high hardness, and outstanding resistance to elevated temperatures, making them indispensable structural materials in aerospace engineering, marine construction, and biomedical applications. In aerospace systems specifically, fatigue failure represents the predominant failure mode for titanium alloy components. This review systematically examines prevalent surface treatment techniques for titanium alloys—including shot peening, ultrasonic rolling treatment, hot isostatic pressing (HIP), physical vapor deposition (PVD), micro-arc oxidation (MAO), and thermal spray processes—and critically evaluates their respective effects on fatigue performance. The underlying mechanisms of each technique are concisely outlined, with emphasis on stress state evolution, near-surface microstructural refinement, and interfacial integrity. Building upon the characteristic surface-dominated fatigue fracture behavior of titanium alloys, this work focuses on how coating composition, architecture (e.g., graded, multilayer, or nanocomposite designs), and interfacial bonding strength govern fatigue resistance. A unified analysis is presented on the distinct yet complementary roles of substrate deformation strengthening (e.g., residual compression, grain refinement) and coating-mediated protection (e.g., barrier function, crack deflection, stress redistribution) during fatigue crack initiation and propagation. Key determinants of fatigue performance, including residual stress distribution, coating/substrate adhesion, thermal mismatch, and environmental degradation susceptibility, are rigorously assessed. Finally, emerging research frontiers are identified, including intelligent process–structure–property mapping, in situ monitoring of fatigue damage at coated interfaces, and design of multifunctional gradient coatings that synergistically enhance strength, wear resistance, and fatigue endurance of titanium alloy components. Full article

Additive manufacturing (AM) enables a level of design flexibility that is difficult to achieve with conventional techniques, yet it inherently yields materials marked by significant variability, anisotropy, and sensitivity to defects that challenge classical mechanics-of-materials assumptions. Process-driven microstructural heterogeneity, stochastic defect populations, and residual stresses strongly influence deformation, fatigue, and fracture behavior, often outweighing nominal material properties and constraining the predictive capability of traditional constitutive and fracture mechanics models. Machine learning (ML) has emerged as a powerful means of handling the complexity of AM data; however, many current approaches depend on black-box models that lack physical transparency, extrapolate poorly, and treat uncertainty inadequately. This review contends that ML should augment—rather than replace—mechanics-based modeling, and that dependable prediction of AM material behavior requires mechanics-informed ML frameworks. We critically analyze the central mechanics challenges in AM and evaluate established modeling strategies alongside emerging ML methods relevant to deformation, damage, fatigue, and fracture. Particular emphasis is given to physics-informed and hybrid ML approaches that explicitly incorporate anisotropy, defect sensitivity, residual stress effects, and uncertainty quantification within learning architectures. Recent progress in ML-assisted constitutive modeling, fatigue and fracture prediction, and digital twin development is synthesized, and the implications for qualification, certification, and structural deployment of AM components are discussed. Full article

Crumb rubber-modified asphalt concrete (CMAC) has gained increasing attention as a sustainable pavement material capable of improving mechanical performance while utilizing waste tire resources. This study investigates the rutting resistance and fatigue behavior of CMAC using a combined experimental and mechanistic–empirical modeling approach. Asphalt mixtures containing 0–25% crumb rubber by binder weight were prepared and evaluated through Marshall stability and indirect tensile fatigue tests, whereas Fourier-transform infrared spectroscopy (FTIR) was used to examine binder–rubber interactions. The results indicate that crumb rubber significantly influences both the volumetric and mechanical properties of asphalt mixtures. Mixtures containing 10–15% crumb rubber exhibited optimal performances, achieving up to 36% higher Marshall stability and improved fatigue life compared with conventional asphalt mixtures. FTIR analysis revealed that rubber particle swelling and limited chemical interactions enhanced binder elasticity and improved binder–aggregate compatibility. However, excessive rubber content (≥20%) resulted in reduced stability owing to increased binder absorption and decreased effective binder film thickness. A mechanistic–empirical model incorporating viscoelastic, viscoplastic, and fatigue damage parameters successfully reproduced the experimental trends and identified the same optimal rubber content range. The findings demonstrate that CMAC with a moderate rubber content can enhance pavement durability and structural performance while promoting environmentally sustainable road construction through the reuse of waste tires. Full article

This paper deals with a time-domain methodology for nominal stress-based, screening-level fatigue assessment of semi-submersible FWT hulls, using a 10-MW semi-submersible FWT as a case study. A comprehensive procedure is outlined for both short- and long-term fatigue analysis, emphasizing the influence of wind and wave loads, as well as the probability distributions of environmental conditions. A fully coupled dynamic analysis of the FWT, employing a multibody floater, is conducted to compute internal global loads and time-domain nominal stresses on the hull structure. Short-term fatigue damage is evaluated across various wind-wave directions, environmental conditions, and random wind and wave samples, identifying critical loading scenarios. For long-term assessment, 10,182 one-hour time-domain simulations are conducted across three wind-wave directions for five offshore sites in the North Sea and one site in the China Sea. Fatigue damage at different locations of the hull structure is estimated for each offshore site, with results discussed in the context of screening-level nominal fatigue assessment and identification of fatigue-critical regions. The insights gained from this study form a basis for validating simplified and computationally efficient fatigue analysis procedures in an accompanying paper. Additionally, the findings support the design optimization of hull structures. Limitations of the present study are identified, pointing to future research directions aimed at mitigating fatigue risks. Full article

A nonlinear ultrasonic time-domain identification method based on chaos sensitivity was proposed in this study. The Duffing chaotic system was introduced into the weak second harmonic identification to realize early detection and quantitative evaluation of fatigue damage in U71Mn steel. First, to ensure the reliability of nonlinear ultrasonic testing, a probe-pressure monitoring device was designed. Through pressure-stability experiments, 16 N was determined as the optimal pressure, which effectively suppresses contact nonlinearity interference and ensures coupling stability. Subsequently, the Duffing chaos detection system was established. The signal-system frequency-matching problem was resolved through time-scale transformation. Simultaneously, the issue of unknown initial phases was resolved using phase traversal compensation. Based on the chaotic system’s sensitivity to specific frequency signals and immunity to noise, the amplitudes of the fundamental wave and second harmonics in the target signals were quantified to calculate the nonlinear coefficient. Experimental results demonstrate that the proposed method can extract these amplitudes directly in the time domain, thereby effectively overcoming the spectral leakage inherent in traditional frequency-domain methods. The nonlinear coefficient of U71Mn steel exhibits a “double-peak” characteristic as fatigue damage increases. Specifically, the first peak appears at approximately 50% of fatigue life, while the second occurs at approximately 80%. This phenomenon is closely correlated with the distinct stages of internal fatigue crack propagation, reflecting a complex damage-evolution mechanism. This study not only provides a novel method for the precise extraction of weak nonlinear signals but also establishes a critical theoretical and experimental foundation for accurate fatigue life prediction for U71Mn rail steel. Full article

At present, most of the research methods for vibration fatigue of welded structures mainly focus on uniaxial stress, ignoring the influence of shear stress. To this end, by combining the ASME structural stress method with the random and vibration analysis theory outlined in the IEC 61373 standard, a new method for evaluating the fatigue life of multi-axis random vibration problems in the frequency domain has been proposed. This method extends the structural stress method to multi-axis scenarios to accurately extract the local multi-axis structural stress state at the weld toe. Its advantage lies in the fact that it not only accounts for the influence of load frequency distribution and structural modal vibrations on fatigue life, but also incorporates the effect of local multiaxial stress conditions in the weld on fatigue life. Additionally, it includes corrections for non-proportional multiaxial stress conditions, resulting in fatigue assessment results that more closely reflect actual conditions. It was validated by comparing the local multiaxial stress, phase difference between shear and normal stress, and equivalent structural stress power spectrum of 0° and 30° fillet welded specimens with test results. Subsequently, it was applied to a multiaxial random vibration fatigue assessment of a vehicle-mounted electrical cabinet with experimental verification. The results indicate that fatigue life estimates based on a multi-axis stress state are lower than those obtained using a uniaxial method. Compared to traditional uniaxial methods, the multi-axis fatigue life estimates show a significant reduction ranging from 4.20% to 88.35%, effectively accounting for damage caused by shear stress. The fatigue assessment results are more closely aligned with experimental data, thereby validating the effectiveness of the proposed new method. The frequency-domain multiaxial random vibration fatigue assessment method proposed in this article provides a new technology for the design and evaluation of welded structures of vehicle-mounted equipment in rail vehicles. This method reduces costs during the design phase of rail vehicles, offering positive economic implications. Full article

Fatigue damage is a critical factor for the long-term service performance degradation of concrete structures. Nevertheless, the mesoscopic fatigue process is still debatable due to material heterogeneity and the complex internal damage progression. To further investigate the internal damage mechanism of concrete under fatigue loading, this study quantitatively monitors the dynamic internal strain evolution of concrete prismatic specimens during uniaxial compression high-cycle fatigue by designing and embedding aggregate sensors (EAS). The results indicated that EAS may effectively reflect concrete cracking, and the approach can properly capture the internal strain field redistribution features of concrete. Significant internal strain localization was observed during fatigue damage. The turning points in strain evolution, which correlate with the stages of stable propagation and microcrack initiation, were identified. Furthermore, the evolution of internal strain effectively characterized the alteration of stress transfer routes induced by crack propagation. Based on failure modes and mechanical analysis, the synergistic driving mechanism of fatigue damage involving crack growth, interfacial friction and stress field evolution was investigated. The difference in concrete damage under fatigue and monotonic loading due to changing mesoscopic crack propagation was defined, establishing a mechanical foundation for exploring concrete fatigue damage processes. The EAS monitoring method used in this study not only gives a viable approach for the fatigue damage analysis of concrete structures, but it also offers a new viewpoint and data support for comprehending the mesoscopic fatigue mechanism of concrete. Full article

To elucidate the degradation behavior of elastic modulus in normal-strength ordinary concrete under flexural fatigue loading, this study systematically examines its evolution in C50 concrete, which is widely used in engineering applications. Based on four-point bending fatigue test data of plain concrete (PC) and reinforced concrete (RC) beams, degradation curves of the relative residual elastic modulus as a function of the cycle ratio were established. To quantitatively characterize the fatigue degradation process, two integrated indicators—the area under the curve (AUC) and the stable-stage degradation slope (|$K_{mid}$|)—were introduced to represent the degree of cumulative damage and the degradation rate of elastic modulus, respectively. These indicators were subsequently employed to evaluate the effects of maximum stress level, stress ratio, and reinforcement on elastic modulus degradation. The results show that failed PC specimens exhibited a typical three-stage S-shaped degradation pattern, whereas RC specimens primarily exhibited a two-stage degradation behavior. However, the elastic modulus of runout PC specimens remained above 93% of its initial value throughout the entire loading process. For PC specimens, under the same maximum stress level, increasing the minimum stress level from 0.10 to 0.25 resulted in a 24% decrease in |$K_{mid}$| from 0.2505 to 0.1912. At the same minimum stress level, increasing the maximum stress level from 0.75 to 0.90 led to a 94% increase in |$K_{mid}$| from 0.1912 to 0.3705. The presence of reinforcement increased AUC by 3~15% and reduced |$K_{mid}$| by 54~74%, indicating that reinforcement not only mitigated overall damage accumulation but also significantly slowed the degradation rate of the elastic modulus during the stable fatigue stage. The degradation characterization approach proposed in this study provides a simplified and practical framework for fatigue analysis of concrete components based on damage mechanics. Full article

The fatigue behaviour of a 90° long radius elbow, which is adjacent to the feedwater nozzle in a BWR, was analyzed. The start-up and shutdown transients were considered. A thermo-mechanical finite element analysis was carried out to determine the stresses induced by thermal transients, considering the environmental conditions in the reactor feedwater pipe. In addition, the Palmgren–Miner methodology and the ASME B&PVC code fatigue curve were applied to evaluate the accumulated damage and service life of the component. Environmental correction factors were considered to estimate environmentally assisted fatigue. Reductions in fatigue life were observed. In the second part of this paper, a part-through thickness semielliptical crack was also postulated in the internal surface of the elbow. It was aligned along the axial direction at the crown zone. Its growth was modelled using the Paris equation, evaluating the risk of failure using fracture parameters. It was found that the vulnerable area is located on the inner surface of the elbow, due to the concentration of stress caused by the curved geometry. Failure assessment diagrams (FADs) were plotted. It was found that the crack depth is the main factor governing crack behaviour under the conditions studied. The results provide a methodology for assessing the integrity of pipes subjected to specific environmental and operating conditions. Full article

Rolling contact fatigue cracks at the contact surface between a wheel and rail are evaluated based on the results of an external inspection (visual inspection). We developed a rail damage assessment technique using a fast regional convolutional neural network deep learning-based image analysis framework. We collected rail specimens from in-service tracks and performed scanning electron microscopy to correlate surface damage with subsurface crack formation, including crack depth, length, and angle. This data was input into an artificial neural network (ANN) to assess internal crack conditions using visual information obtained from rail surface damage. The resulting model achieved an average accuracy of 94.9%, outperforming other algorithms. We integrated this model into a developed rail damage diagnosis app with deep learning that links field photographs with cloud-based big data to learn, quantitatively diagnose, and present the type and scale of rail damage. We examined the field applicability of the application at a rail damage site. The standard deviation of the rail damage diagnosis results was 0.2–1.5% between different users. Appropriateness of the rail damage assessment technique using the proposed ANN image analysis technique was verified experimentally. Consistent diagnosis results could be derived regardless of the inspector, minimizing human error. Full article

Waste sweet potato vine fiber (WSVF) effectively extends asphalt service life by enhancing cracking resistance in gel-like base asphalt matrices, yet its crack-resistant mechanism lacks mechanical characterization. This study proposes an analytical method for evaluating WSVF-modified asphalt’s crack-resistant behavior based on the principle of mechanical energy balance. First, alkali-treated WSVF with a mass fraction of 1% was added into 70# gel-like base asphalt to prepare WSVF-modified asphalt. Lignin fiber (LF)-modified asphalt and 70# gel-like base asphalt were selected as control groups, and three types of time sweep and scanning electron microscopy tests were conducted. Then, the three-dimensional cracking volume model and damage kinetics model were established for analyzing the cracking response behavior, defining the asphalt damage variable and determining the cracking damage activation energy (E_acd). Finally, the E_acd was used to quantify the difficulty of the cracking damage process for the WSVF-modified asphalt. The reinforcement and cracking resistance mechanisms of WSVF in asphalt were analyzed by the E_acd and asphalt microstructure. The results show that the cracking volume response of WSVF-modified asphalt under cyclic loading presents three-stage nonlinear behaviors. The established fatigue damage kinetics model can accurately describe the fatigue damage evolution process of alkali-treated WSVF-modified asphalt. The E_acd values of WSVF-modified asphalt, LF-modified asphalt, and 70# gel-like base asphalt are 10.60 kJ·mol⁻¹, 21.83 kJ·mol⁻¹, and 29.74 kJ·mol⁻¹, respectively. After alkali treatment, the WSVF surface exhibits grooves, demonstrating superior adsorption and storage capacity for asphalt. The WSVF can cross link through the bonding effect of asphalt and form a three-dimensional network framework structure, which can significantly increase the E_acd and provide strengthening and toughening effects on gel-like base asphalt. In summary, E_acd values are used as a mechanical indicator to quantitatively evaluate the fatigue cracking resistance of WSVF-modified asphalt. Full article