Search Results (332)

Background: Radspherin^® is a novel α-emitting radiopharmaceutical administered intraperitoneally following complete cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS-HIPEC) for peritoneal metastases. It delivers short-range radiation aimed at eliminating residual microscopic disease. This qualitative study explored how participants with colorectal cancer experienced participating in an early-phase clinical trial involving CRS-HIPEC followed by Radspherin^®. Materials and Methods: Semi-structured interviews were conducted with ten participants enrolled in a phase 1/2a trial involving CRS-HIPEC and intraperitoneal Radspherin^®. The analysis was guided by a phenomenological and interpretive approach using reflexive thematic analysis. Results: Participants expressed a strong sense of motivation and hope tied specifically to receiving Radspherin^®, which they perceived as an opportunity to improve their prognosis. Many also viewed participation as a contribution to future cancer research. None attributed complications or side effects to Radspherin^®. Clear and supportive verbal communication from healthcare professionals was highly valued, while the written information was described as overwhelming. Despite fears of recurrence, most participants remained optimistic about regaining a meaningful life. While experiences with Radspherin^® were largely positive, participants also described pain, fatigue, and prolonged recovery related to CRS-HIPEC, including ongoing functional and psychosocial challenges. Conclusions: Participants associated Radspherin^® with hope and a therapeutic benefit but did not link it to their adverse events. Their willingness to participate in experimental treatment was shaped by trust in clinicians, clear communication, and a desire for extended survival. However, the burden of CRS-HIPEC-related side effects underscores the importance of tailored follow-up and support. Full article

Metal-composite joints, leveraging the high specific strength/stiffness and superior fatigue resistance of carbon fiber reinforced polymers (CFRP) alongside metallic materials’ excellent toughness and formability, have become prevalent in aerospace structures. Fastener flexibility serves as a critical parameter governing load distribution prediction and fatigue life assessment, where accurate quantification directly impacts structural reliability. Current approaches face limitations: experimental methods require extended testing cycles, numerical simulations exhibit computational inefficiency, and conventional machine learning (ML) models suffer from “black-box” characteristics that obscure mechanical principle alignment, hindering aerospace implementation. This study proposes an integrated framework combining numerical simulation with explainable ML for fastener flexibility analysis. Initially, finite element modeling (FEM) constructs a dataset encompassing geometric features, material properties, and flexibility values. Subsequently, a random forest (RF) prediction model is developed with five-fold cross-validation and residual analysis ensuring accuracy. SHapley Additive exPlanations (SHAP) methodology then quantifies input features’ marginal contributions to flexibility predictions, with results interpreted in conjunction with theoretical flexibility formulas to elucidate key parameter influence mechanisms. The approach achieves 0.99 R2 accuracy and 0.11 s computation time while resolving explainability challenges, identifying fastener diameter-to-plate thickness ratio as the dominant driver with negligible temperature/preload effects, thereby providing a validated efficient solution for aerospace joint optimization. Full article

To overcome the limitation of the Paris law in capturing stress-ratio (R) effects, a modification of the Goodman model is introduced to account for the nonlinear variation of the fatigue limit with mean stress in this study. Based on the modified formulation, an equivalent crack driving force model incorporating R-effects is subsequently derived for fatigue-crack growth (FCG). The model unifies the stress-intensity factor ranges at different values of R into an equivalent value at R = 0 without introducing fitting parameters other than the Paris constants, relying solely on basic material properties (fatigue limit and tensile strength). This feature facilitates practical application and avoids extensive experimental calibration. Validation using FCG test results of Q345qD steel and 23 datasets show that the model outperforms classical models, achieving a goodness of fit up to 0.98 and demonstrating strong robustness and practical value for FCG prediction and residual-life assessment in engineering structures. Full article

Post-dialysis fatigue is one of the most frequent and limiting symptoms among patients undergoing hemodialysis (HD), characterized by intense physical exhaustion that may persist beyond the treatment session. Sleep disturbances frequently coexist with fatigue and may contribute to overall symptom burden. Nutritional status has been identified as a potential determinant of fatigue severity. Understanding these relationships may help identify associated factors and guide multidisciplinary interventions. Objectives: To assess the prevalence and intensity of fatigue in patients receiving HD, to describe the burden of sleep disturbances, and to analyze their association with nutritional status and various clinical, dialytic, and sociodemographic variables. Methods: A cross-sectional descriptive study was conducted between November and December 2024 in adults with chronic kidney disease undergoing maintenance HD. Fatigue and sleep disturbances were assessed using brief patient-reported outcome items adapted from PROMIS item bank concepts and analyzed as separate subscales. Nutritional status was evaluated using the Mini Nutritional Assessment–Short Form (MNA-SF). Sociodemographic, clinical, dialytic, and laboratory variables were collected. Statistical analyses were performed using SPSS v29, applying association and correlation tests (p ≤ 0.05). Results: A total of 729 patients were included (67.1% men), with a mean age of 67.7 ± 14.5 years. Clinically relevant fatigue was reported by approximately 50% of participants, with around 20% presenting severe fatigue. Sleep disturbances affected nearly 60% of patients, with severe impairment reported in approximately 30%. Regarding nutritional status, 61.9% had normal nutrition, 33.2% were at risk of malnutrition, and 4.9% were malnourished. Fatigue was significantly associated with female sex (p < 0.001), longer time on hemodialysis (p < 0.001), greater weekly dialysis exposure (p = 0.012), and poorer nutritional status (p = 0.003). The absence of residual urine output showed a borderline association with fatigue (p = 0.059) but was significantly associated with sleep disturbances (p = 0.002). Sleep disturbance scores were also significantly associated with lower levels of albumin, total proteins, and transferrin. No associations were observed between fatigue and age, BMI, comorbidity, ultrafiltration rate, or biochemical parameters. Conclusions: Fatigue is a highly prevalent and clinically relevant symptom in patients undergoing HD and is closely associated with nutritional status and dialysis-related factors. Sleep disturbances are also highly prevalent and may act as an important modulating factor, potentially amplifying fatigue, particularly in patients with greater biological vulnerability or loss of residual kidney function. The systematic use of patient-reported outcome measures (PROMs) to assess fatigue and sleep, together with nutritional evaluation, may facilitate the early identification of vulnerable patients and guide targeted strategies to reduce symptom burden and improve quality of life. Full article

Shot peening is a widely used surface treatment method for improving fatigue life by inducing surface compressive residual stresses. In critical automotive components such as parabolic leaf springs, shot peening under pre-tension (stress shot peening) can further enhance durability. This study presents a finite element model simulating stress peening in high-strength spring steels, incorporating realistic boundary conditions, material degradation due to decarburization, and stochastic shot properties, offering a high-accuracy yet computationally efficient alternative to extensive experimental testing. Results show that both below- and above-yield pre-stressing produce beneficial residual stresses, while the consideration on decarburization effects significantly alters surface stress fields. The model offers a reliable, time-efficient alternative to experiments for process and fatigue life optimization. Full article

This study investigates the effects of multiple laser shock peening (LSP) treatments on the low-cycle fatigue performance and fracture mechanisms of laser-melted, additive-manufactured Ti-6.5Al-1Mo-1V-2Zr (TA15) titanium alloy. The primary objective is to systematically evaluate how different LSP impact numbers (0, 1, and 2 impacts) enhance fatigue life and alter fracture behavior. Low-cycle fatigue life was determined via tensile-compression fatigue testing. Microfracture morphology was examined using scanning electron microscopy (SEM), surface residual stresses were measured by X-ray diffraction (XRD), and microhardness tests were conducted concurrently. Results indicate that LSP significantly enhances fatigue life: fatigue life increased by 2.34 times and 2.56 times after one and two LSP impacts, respectively, compared to the untreated state. As impact cycles increased, the microhardness of the material surface rose by 8.51% and 14.53%, respectively, with residual compressive stresses reaching −145 MPa and −183 MPa. Concurrently, LSP-2 treatment formed a refined microstructure featuring coexisting lamellar α and acicular martensite in the surface layer. This strengthening effect is attributed to LSP-induced surface residual compressive stress, grain refinement, and the resulting migration of fatigue crack initiation from the surface to subsurface regions. These findings provide critical insights for optimizing fatigue-resistant designs of additively manufactured titanium alloy components. Full article

This study presents a fatigue life prediction procedure for high-strength steel suspension components that exhibit surface and depth-graded mechanical properties due to manufacturing processes such as shot peening and heat treatment. A layer-by-layer approach based on local stress and material properties at the examined depth from the surface is implemented, allowing the generation of S-N curves that reflect the local fatigue response at different depths. The methodology is applied to a parabolic monoleaf spring for the axle suspension of commercial vehicles, made of 51CrV4 steel, and validated against experimental fatigue data. Results show strong agreement, demonstrating the effectiveness of incorporating local mechanical characteristics in terms of stress and material properties into fatigue design workflows. Full article

Laser additive manufacturing shows great promise for repairing high-value carburized gears, but the underlying relationships among thermal history, microstructure, and properties remain insufficiently quantified. This study uniquely integrates finite-element modeling with microstructural mapping to decipher thermo-mechanical coupling during gear repair. A thermal simulation model that combines a double-ellipsoidal heat source with phase-transformation kinetics achieves 91.1% accuracy in predicting melt pool depth and hardened-layer depth. The cladding process induces a substantial increase in subsurface hardness, primarily due to phase-transformation-induced refinement and regeneration of martensite during rapid thermal cycling. This results in a peak hardness of 64 HRC and a tensile strength of 2856 MPa in the secondary-hardened layer, both exceeding those of the original carburized substrate. The presence of beneficial compressive residual stresses further improves fatigue resistance. Spatial gradients in elastic modulus, strength, and hardness, measured by flat indentation and microhardness testing, are quantitatively correlated with simulated peak temperatures and predicted phase distributions. These correlations establish a causal link from the thermal history to phase transformations, microstructural evolution, and the resulting local hardness and strength. These findings provide a mechanistic foundation for precision repair and service-life prediction of high-carbon gear steels using laser additive manufacturing. Full article

Predicting the fatigue lifespan of Twisted String Actuators (TSAs) is essential for improving the reliability of robotic and mechanical systems that rely on flexible transmission mechanisms. Traditional empirical approaches based on regression or Weibull distribution analysis have provided useful approximations, yet they often struggle to capture nonlinear dependencies and stochastic influences inherent to real-world fatigue behavior. This study introduces and compares four machine learning (ML) models—Linear Regression, Random Forest, XGBoost, and Gaussian Process Regression (GPR)—for predicting TSA lifespan under varying weight (W), number of strings (N), and diameter (D) conditions. Building upon this comparison, a hybrid physics-guided model is proposed by integrating an empirical fatigue life equation with an XGBoost residual-correction model. Experimental data collected from repetitive actuation tests (144 valid samples) served as the basis for training and validation. The hybrid model achieved an R² = 0.9856, RMSE = 5299.47 cycles, and MAE = 3329.67 cycles, outperforming standalone ML models in cross-validation consistency (CV R² = 0.9752). The results demonstrate that physics-informed learning yields superior interpretability and generalization even in limited-data regimes. These findings highlight the potential of hybrid empirical–ML modeling for component life prediction in robotic actuation systems, where experimental fatigue data are scarce and operating conditions vary. Full article

In the design and manufacturing of pressure vessels, the quality of welded joints and their operational safety are critical considerations. Weld quality classification is closely linked to its impact on fatigue performance. In this study, aluminum alloy welds with varying levels of porosity were produced by adjusting welding parameters, and X-ray inspection was used to assess porosity levels. Representative welds corresponding to different quality grades were selected to fabricate fatigue specimens, and their fatigue lives were determined. The influence of quality grades on the residual fatigue life of aluminum alloy welded sheets was systematically analyzed. The results indicate that, under identical loading conditions, the fatigue life of specimens with defects is significantly reduced compared to defect-free specimens. This reduction becomes more pronounced as the quality grade decreases—corresponding to an increase in circular hole defects. Specifically, for 5083 aluminum alloy, transitioning from Grade I to Grade III results in fatigue life reductions of approximately 25%, 35%, and 50%, respectively. Full article

DH36 high-strength steel is widely used in shipbuilding and other fields due to its excellent strength, low-temperature toughness, wear resistance, and corrosion resistance. However, the harsh deep-sea environment seriously reduces the service life of welds. In this study we subjected DH36 welded joints to laser shock peening at three different energy levels (5 J, 7 J, 9 J) to investigate its effects on microhardness, microstructure, high-cycle fatigue, and residual stress of the DH36 welded joints. Results indicate that LSP can significantly enhance the surface microhardness of welded joints. Notably, the 7 J energy treatment increased the weld zone microhardness from 195 HV_0.2 to 231 HV_0.2 (18.5% improvement) and the heat-affected zone microhardness from 194 HV_0.2 to 234 HV_0.2 (20.6% improvement). Residual tensile stress on the specimen surface was offset and replaced by residual compressive stress after LSP. Concurrently, the high-cycle fatigue limit of the specimens was significantly improved, with the most pronounced improvement observed in specimens subjected to 5 J energy—increasing from 258 MPa to 295 MPa, representing an increase of 14.34%. Full article

The objective of this study was to investigate electron beam hardening (EBH) technology and compare its performance with laser beam hardening (LBH) in the context of manufacturing components such as gears, which increasingly employ submicron bainitic steels. Given the stringent demands for durability and fatigue resistance of gear teeth, identifying an optimal surface hardening method is essential for extending service life. Comprehensive analyses, including light and electron microscopy, hardness testing, tribocorrosion testing, and X-ray diffraction for phase composition, were conducted. The EBH-treated layer exhibited a slightly higher hardness (by 26 HV) compared to the LBH-treated layer (average 654 HV), while the base material measured 393 HV. The EBH process produced a uniform hardness distribution with a subsurface zone of reduced hardness. In contrast, LBH resulted in a surface oxide layer absent in EBH due to its vacuum environment. Both techniques reduced the residual austenite content in the surface layer from 22.5% to approximately 1.3%–1.4%. Notably, EBH achieved comparable hardening effects with nearly half the energy input of LBH, demonstrating superior energy efficiency and industrial feasibility. Application of the developed EBH process to an actual gear component confirmed its practical potential for modern gear manufacturing. Full article

The bogie serves as a critical structural component in high-speed trains, subjected to dynamic loads throughout its operational lifecycle. Enhancing the fatigue life of the bogie necessitates not only ensuring welding quality but also effectively managing welding residual stresses during the manufacturing process. In this study, an efficient and simplified thermal–elastoplastic finite element method was developed based on the ABAQUS software platform, and its reliability and applicability were validated through comparison with measured data. The computational approach was employed to investigate the distribution characteristics of welding residual stresses in a weathering steel bogie beam, with particular emphasis on the influence of different welding sequences on residual stress distribution. Simulated results demonstrate that the welding sequence significantly influences the residual stress distribution and magnitude within the beam. The numerical simulation methodology developed in this study offers a powerful tool for optimizing welding sequences to regulate residual stresses during the fabrication of bogie structures. Full article

The high-cycle fatigue (HCF) strength of titanium alloy blades, particularly Ti-6Al-4V, is critical for the reliability and performance of aviation engine components. Foreign object damage (FOD), which introduces notches, microstructural alterations, and residual stresses, significantly degrades the fatigue performance of these blades. Of particular concern are tensile residual stresses, which, caused by factors such as FOD, notches, or non-uniform plastic deformation, lead to increased local tensile loads, promote crack initiation, and accelerate crack growth. This study investigates the effects of external damage, including the impact angle and the resultant residual stresses, on the high-cycle fatigue strength of Ti-6Al-4V titanium alloy blades. Blade simulation specimens with impact-induced damage were tested under high-cycle fatigue conditions to assess the influence of various impact angles and the resulting tensile residual stresses. A modified fatigue strength prediction model was developed, incorporating shear factors and tensile residual stresses, to improve the accuracy of fatigue life predictions. Compared with the Neuber model and Peterson model, the modified model increases the proportion of predictions falling within the 10% scatter band by 30%, resulting in a significant improvement in prediction accuracy. The experimental results demonstrated that the modified model more accurately predicted the high-cycle fatigue strength, particularly in the presence of external damage and tensile residual stresses. Full article

Gas nitriding was implemented in the current work at a constant nitrogen potential (K_N) of 2.0 for 8 h to enhance the fatigue properties of SCM 440 steel, and the results were compared with those of the substrate tempered at the nitriding temperature (475 °C). Fine particle peening (FPP) prior to nitriding imposed a refined structure and induced compressive residual stress (CRS) in the near-surface peened zone. The fine-grained structure provided numerous paths to enhance nitrogen diffusion inwards during nitriding. The compound layer formed on the nitrided SCM 440 steel primarily comprised a mixture of Fe₃N and Fe₄N; however, the pre-peened and nitrided (SPN) specimens exhibited a higher proportion of Fe₃N and a thicker compound layer than the non-peened and nitrided (NPN) counterparts. In addition, FPP prior to nitriding increased both the case depth and the magnitude of the CRS field compared with nitriding alone. The fatigue limits of the substrate (SB), NPN, and SPN samples were approximately 750, 1050, and 1400 MPa, respectively. Gas-nitriding at 475 °C significantly improved the fatigue performance of SCM 440 steel. Moreover, pre-peening prior to nitriding further enhanced fatigue strength and life of the treated SCM 440 steel by introducing a deeper case depth and higher CRS field. Multiple cracks initiation at the outer surface of the SB sample accounted for its lowest fatigue limit among the tested samples. Surface microcracks and pits on the surface of the NPN specimen would be crack initiation sites and harmful to its fatigue resistance. These surface dents were considered to be responsible for fatigue crack initiation in the SPN specimens. Therefore, polishing after nitriding to reduce surface roughness and/or microcracks was expected to further increase the fatigue resistance and the reliability of nitrided SCM 440 steel. Full article