Search Results (139)

The study investigates the influence of microstructures on fatigue behavior and failure mechanisms of the α-β titanium alloy Ti6246, fabricated via Powder Bed Fusion-Laser Beam (PBF-LB). In particular, the investigation assesses the effect of two post-processing heat treatments, namely α-β annealing at 875 °C (AN875) and solution treatment at 825 °C followed by aging at 500 °C (STA825), on the alloy’s rotating and bending fatigue behavior. The results indicate that the STA825 condition provides superior fatigue resistance (+25%) compared to AN875, due to the presence of a finer bilamellar microstructure, characterized by thinner primary α lamellae (α_p) and a more homogeneous distribution of secondary α lamellae (α_s) within the β matrix. Additionally, an investigation conducted using the Kitagawa–Takahashi (KT) approach and the El-Haddad model, based on the relationship between the fatigue limit and defect sensitivity, revealed improved crack propagation resistance from pre-existing defects (ΔK_th) for the STA825 condition compared to AN875. Notably, the presence of fine α_s after aging for STA825 is effective in delaying crack nucleation and propagation at early stages, while refined α_p contributes to hindering macrocrack growth. The fatigue behavior of the STA825-treated Ti6246 alloy was even superior to that of the PBF-LB-processed Ti64, representing a viable alternative for the production of high-performance components in the automotive and aerospace sectors. Full article

The fatigue resistance of cement-stabilized macadam (CSM) plays a vital role in ensuring the long-term durability of pavement structures. However, limited cementitious material (CM) content often leads to high packing voids, which significantly compromise fatigue performance. Existing studies have rarely explored the coupled mechanism between pore structure and fatigue behavior, especially in the context of solid-waste-based CMs. In this study, a cost-effective alkali-activated sludge gasification slag (ASS) was proposed as a sustainable CM substitute for ordinary Portland cement (OPC) in CSM. A dual evaluation approach combining cross-sectional image analysis and fatigue loading tests was employed to reveal the effect pathway of void structure optimization on fatigue resistance. The results showed that ASS exhibited excellent cementitious reactivity, forming highly polymerized C-A-S-H/C-S-H gels that contributed to a denser microstructure and superior mechanical performance. At a 6% binder dosage, the void ratio of ASS–CSM was reduced to 30%, 3% lower than that of OPC–CSM. The 28-day unconfined compressive strength and compressive resilient modulus reached 5.7 MPa and 1183 MPa, representing improvements of 35.7% and 4.1% compared to those of OPC. Under cyclic loading, the ASS system achieved higher energy absorption and more uniform stress distribution, effectively suppressing fatigue crack initiation and propagation. Moreover, the production cost and carbon emissions of ASS were 249.52 CNY/t and 174.51 kg CO₂e/t—reductions of 10.9% and 76.2% relative to those of OPC, respectively. These findings demonstrate that ASS not only improves fatigue performance through pore structure refinement but also offers significant economic and environmental advantages, providing a theoretical foundation for the large-scale application of solid-waste-based binders in pavement engineering. 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

This study provides a comprehensive analysis of the fatigue cracking behavior of super martensitic stainless steel in air and water environments, highlighting the critical influence of environmental factors on its mechanical properties. By examining the distribution of fatigue test data, the Weibull three-parameter model was identified as the most accurate descriptor of fatigue life data in both environments. Key findings reveal that, in air, cracks predominantly propagate along the densest crystallographic planes, whereas, in water, corrosive media significantly accelerate crack initiation and propagation, reducing fatigue resistance, creating more tortuous crack paths, and inducing microvoids and secondary cracks at the crack tip. These corrosive effects adversely alter the material’s microstructure, profoundly impacting fatigue life and crack propagation rates. The insights gained from this research are crucial for understanding the performance of super martensitic stainless steel in aqueous environments, offering a reliable basis for its engineering applications and contributing to the development of more effective design and maintenance strategies. Full article

This study presents a unique and comprehensive application of ANSYS Mechanical R19.2’s SMART crack growth feature, leveraging its capabilities to conduct an unprecedented parametric investigation into fatigue crack propagation behavior under a wide range of positive and negative stress ratios, and to provide detailed insights into the influence of hole positioning on crack trajectory. By uniquely employing an unstructured mesh method that significantly reduces computational overhead and automates mesh updates, this research overcomes traditional fracture simulation limitations. The investigation breaks new ground by comprehensively examining an unprecedented range of both positive (R = 0.1 to 0.5) and negative (R = −0.1 to −0.5) stress ratios, revealing previously unexplored relationships in fracture mechanics. Through rigorous and extensive numerical simulations on two distinct specimen configurations, i.e., a notched plate with a strategically positioned hole under fatigue loading and a cracked rectangular plate with dual holes under static loading, this work establishes groundbreaking correlations between stress parameters and fatigue behavior. The research reveals a novel inverse relationship between the equivalent stress intensity factor and stress ratio, alongside a previously uncharacterized inverse correlation between stress ratio and von Mises stress. Notably, a direct, accelerating relationship between stress ratio and fatigue life is demonstrated, where higher R-values non-linearly increase fatigue resistance by mitigating stress concentration, challenging conventional linear approximations. This investigation makes a substantial contribution to fracture mechanics by elucidating the fundamental role of hole positioning in controlling crack propagation paths. The research uniquely demonstrates that depending on precise hole location, cracks will either deviate toward the hole or maintain their original trajectory, a phenomenon attributed to the asymmetric stress distribution at the crack tip induced by the hole’s presence. These novel findings, validated against existing literature, represent a significant advancement in predictive modeling for fatigue life assessment, offering critical new insights for engineering design and maintenance strategies in high-stakes industries. Full article

This study investigates the microstructural evolution and mechanical degradation mechanisms of cold-drawn 310S stainless steel subjected to repeated thermal cycling between 900 °C and room temperature. The results reveal that thermal cycling induces significant lattice distortion, dislocation accumulation, and recrystallization, leading to grain refinement and increased tensile strength. However, these microstructural changes also initiate subsurface cracks and reduce ductility. TGA analysis confirms thermal weight loss from decarburization, especially under oxidative atmospheres. EPMA analysis and tensile tests after thermal cycling reveal that surface cracks formed during thermal cycling act as origins for transgranular crack propagation under tensile stress, significantly reducing fracture resistance. Bending fatigue tests further demonstrate that thermally fatigued specimens exhibit inferior fatigue life compared to raw material, confirming the deteriorating mechanical properties of 310S stainless steel after thermal cycling. Overall, the combined effects of thermal and mechanical fatigue degrade the structural integrity of 310S stainless steel, revealing that lattice distortion and subsurface cracking are the key factors in its embrittlement and reduced fatigue performance. Full article

A single batch of AlSi10Mg powder was used to fabricate two groups of round bars via horizontal printing, employing an identical strategy except for one parameter in the process of powder bed fusion-laser beam. The parameter is layer thickness, set at 50 and 80 μm for Group-1 and Group-2, respectively, resulting in laser energy densities of 29.95 and 18.72 J/mm³. Both materials exhibit similar microstructures; Group-1 has fewer and smaller defects than Group-2, leading to higher strength and ductility. Fatigue performance of low-cycle and long-life up to 10⁸ cycles under rotating bending was assessed, and the fracture surfaces were carefully examined under scanning electron microscopy. The S-N data converge to a single slope followed by a horizontal asymptote, indicating the occurrence of very-high-cycle fatigue (VHCF) in both cases. Group-1 shows higher fatigue strength in the range of 10⁴ to 10⁸ cycles, and a greater failure probability in VHCF regime than Group-2. This is attributed to the larger defect size in Group-2, where the smaller control volume in rotating bending greatly increases the likelihood of encountering large defects compared to Group-1. At the defect edge, the microstructure shows distinct resistance to crack propagation under high and low loads. Full article

This study investigated the mechanical, fatigue, and creep properties of polyamide 6 (PA6)/graphene oxide (GO) nanocomposites manufactured by a combination of melt and solvent mixing. Results showed that increasing GO content improved tensile and bending properties and reduced temperature dependence. The tensile modulus and strength of PA6/GO nanocomposite containing 1 wt.% GO (PA6 + 1GO) were measured with an increment of 33% and 37%, respectively, compared with neat PA6. The reduction in tensile strength occurred gradually with the increasing amount of GO. As the temperature increased from 25 °C to 70 °C, the tensile strength of PA6 and PA6 + 1GO decreased by 20% and 4%, respectively. Fatigue tests demonstrated that the rigid GO particles hindered the deformation capability of the matrix and facilitated crack propagation. While the PA6 reached 10⁵ cycles at 60% of its tensile strength, PA6 + 1GO was able to reach 10⁵ cycles at 35% of its tensile strength. Dynamic mechanical analysis (DMA) revealed that GO enhanced both storage modulus and glass transition temperature (T_g). Creep tests demonstrated better deformation resistance under stress in PA6/GO nanocomposites compared to pure PA6. After a 10 h creep test, the decrease in creep strain was observed as 52.4% for PA6 + 1GO. Full article

To investigate the influence of repeated loading on the bond behavior between steel bars and reactive powder concrete (RPC), this study conducted repeated loading tests on eight beam specimens and one static loading test as a control. The effects of stress levels and the number of repeated loading cycles on the bond behavior between steel bars and RPC were examined. The results indicate that the static failure mode was characterized by steel bar pull-out accompanied by significant plastic deformation, with no propagation of cracks in the RPC after their initiation, demonstrating the excellent crack control capability of RPC. After 10,000 cycles of repeated loading at a high stress level (Z = 0.9), the ultimate bond strength decreased by only 3.68%, indicating the superior fatigue resistance of the steel–RPC interface. Based on the analysis of slip accumulation effects, a constitutive model considering stress levels and the number of repeated loading cycles was established. This model can serve as a basis for the design of steel anchorage in RPC structures subjected to cyclic loading. Full article

Fatigue-induced crack initiation and propagation are a major concern in pearlitic railway rails and wheels. Rails and wheels undergo significant plastic deformation on their near-surface layers during service, leading to the initiation and propagation of cracks within the deformed region. Existing models typically use finite element models (FEMs) to describe these kinds of fatigue phenomena. However, they fail to establish a strong connection between the microstructure of the undeformed and the deformed materials and their corresponding fatigue properties. Therefore, a model based on the soft-contact discrete element method (DEM) was developed that considers microstructural details such as prior austenite grains (PAGs), pearlite blocks, pearlite colonies, and lamellar orientation of the ferrite–cementite structure of the pearlite. The Voronoi Tessellation method was used to generate a hierarchical mesh to represent these microstructural details, considering the distribution of microstructural details. Crack propagation is simulated by applying damage laws on the microstructural interface level that degrade the stiffness of the fibers connecting the mesh elements. The model’s crack growth predictions are compared with experimental results from the literature to validate its accuracy for different deformation degrees. The developed model can be used in the designing and material selection phase in the railway industry to help select the material with optimum microstructural features. Also, it can be used for the selection of the optimum heat treatment process considering materials resistance to the fatigue crack growth. Full article

Circular hollow sections (CHSs) are widely used in offshore jacket structures due to their excellent compressive strength, torsional resistance, and direction-independent stiffness. However, CHS joints are prone to fatigue-induced cracking caused by complex geometries, environmental loading, and aging. Fatigue crack propagation, governed by the stress intensity factor (SIF), threatens structural integrity if the SIF exceeds fracture toughness. Composite reinforcement has emerged as a promising solution for mitigating crack propagation and enhancing joint performance. This study presents a numerical parametric investigation of fatigue-cracked tubular T-joints, focusing on the effects of crack size, crack location, and composite reinforcement on the SIF under various loading conditions. The highest SIF was consistently observed at the saddle point in T-joints under axial and out-of-plane bending (OPB) loads. However, in T-joints subjected to in-plane bending (IPB) loads, the highest SIF was found between the crown and saddle points. The SIF increased with the size and diameter of the cracks. The application of CFRP wrapping was found to reduce the SIF by more than 50% across all loading conditions, with the most significant reductions observed when the reinforcement was oriented along the chord axis. Full article

Reflection cracks significantly compromise the service life of half-rigid asphalt pavements in cold regions. This study introduces SAKIII warm-mixed rubber–asphalt mixture (SAKIII WMRA Mix) as a stress absorption layer to address this issue. Through orthogonal tests, regression analysis, and performance comparisons with SBS-modified asphalt, the material composition, low-temperature cracking resistance, and fatigue performance of WMRAM were systematically evaluated. The results show that SAKIII WMRA Mix maintains superior road performance with 30 °C lower mixing/compaction temperatures compared to traditional hot-mix asphalt mixture. At −10 °C, its low-temperature cracking resistance improves by 40% and fatigue life extends by 35% over the SBS-modified asphalt mixture. Mechanistically, SAKIII WMRA Mix reduces reflection crack propagation by 30% and prolongs pavement service life by over 25% under equivalent traffic/climate conditions. Additionally, it decreases energy consumption by 15–20% and provides a sustainable solution for cold-region road construction. This research establishes optimized mix design methods and performance criteria for WMRAM, offering theoretical support and practical guidance for reflective crack mitigation in cold climates. The proposed technology effectively balances mechanical properties, energy efficiency, and environmental benefits, making it especially suitable for cold areas where thermal stress dominates road damage. Full article

Integrating machine learning into additive manufacturing offers transformative opportunities to optimize material properties and design high-performance, fatigue-resistant structures for critical applications in aerospace, biomedical, and structural engineering. This study explores mechanistic machine learning techniques to tailor microstructural features, leveraging data from ultrasonic fatigue tests where very high cycle fatigue properties were assessed up to $1\times {10}^{10}$ cycles. Machine learning models predicted critical fatigue thresholds, optimized process parameters, and reduced design iteration cycles by over 50%, leading to faster production of safer, more durable components. By refining grain orientation and phase uniformity, fatigue crack propagation resistance improved by 20–30%, significantly enhancing fatigue life and reliability for mission-critical aerospace components, such as turbine blades and structural airframe parts, in an industry where failure is not an option. Additionally, the machine learning-driven design of metamaterials enabled structures with a 15% weight reduction and improved yield strength, demonstrating the feasibility of bioinspired geometries for lightweight applications in space exploration, medical implants, and high-performance automotive components. In the area of titanium and aluminum alloys, machine learning identified key process parameters such as temperature gradients and cooling rates, which govern microstructural evolution and enable fatigue-resistant designs tailored for high-stress environments in aircraft, biomedical prosthetics, and high-speed transportation. Combining theoretical insights and experimental validations, this research highlights the potential of machine learning to refine microstructural properties and establish intelligent, adaptive manufacturing systems, ensuring enhanced reliability, performance, and efficiency in cutting-edge engineering applications. Full article

The rapid development of 3D printing technology has enabled its application in many fields, including dentistry. One of the key applications is temporary prosthetic restorations on dental implants, used during the osteointegration process. These restorations provide functionality and aesthetics, but their durability under oral conditions exposed to dynamic loads remains a challenge. This pilot study evaluated the thermal expansion and fatigue resistance of three commercially available photopolymer materials used in 3D printing: NextDent Denture 3D, NextDent C&B MFH Bleach, and Graphy TC-80DP. Thermal expansion and dimensional stability analyses were performed on samples subjected to cyclic heating and cooling. Fatigue tests were designed to evaluate the behaviour of the materials under repetitive mechanical loads mimicking chewing. Microscopic analyses (SEM) made it possible to identify the internal structure of the materials and their damage mechanisms. The results showed that the tested materials have a low coefficient of thermal expansion and high dimensional stability after cyclic heating and cooling. However, significant differences were observed in their mechanical properties and fatigue resistance. The best results were obtained for the Graphy TC-80DP material, while NextDent Denture 3D showed the least resistance to cyclic loading. NextDent Denture 3D exhibited the highest thermal expansion coefficient (123.6 × 10⁻⁶/K), while Graphy TC-80DP showed the lowest (83.9 × 10⁻⁶/K), ensuring better dimensional stability. Fatigue tests revealed that Graphy TC-80DP withstood up to 675,221 cycles at 51 MPa, while NextDent Denture 3D failed after 420 cycles. SEM analysis confirmed that Graphy TC-80DP maintained structural integrity longer, while NextDent Denture 3D exhibited early crack propagation. This study fills a gap in the knowledge of the behaviour of dental materials produced with 3D printing technology under real-world conditions and provides a basis for further, more advanced research to improve their properties and patient comfort. Full article

Mechanical gears are essential in power transmission systems across various industrial applications. Their performance is critically influenced by residual stresses from manufacturing processes like induction hardening, case hardening, and shot peening. Surface compressive residual stresses enhance resistance to pitting fatigue, bending fatigue and crack propagation, improving overall hardness. In the present work, a Non-Destructive Thermographic method (Active thermography), based on measurement of the thermal diffusivity parameter, is presented to characterize the surface treatments applied to gears. Surface hardness was measured using a micro-hardness tester, and residual stresses were determined with an X-Ray diffractometer, showing variations due to surface treatments. The variation in the thermal diffusivity parameter, obtained using the Slope Method, was found to be an indicator of the surface treatments’ effectiveness. Full article