Numerous sectors,such as education,the IT sector,and corporate organizations,transitioned to virtual meetings after the COVID-19 crisis.Organizations now seek to assess participants’fatigue levels in online meetings ...Numerous sectors,such as education,the IT sector,and corporate organizations,transitioned to virtual meetings after the COVID-19 crisis.Organizations now seek to assess participants’fatigue levels in online meetings to remain competitive.Instructors cannot effectively monitor every individual in a virtual environment,which raises significant concerns about participant fatigue.Our proposed system monitors fatigue,identifying attentive and drowsy individuals throughout the online session.We leverage Dlib’s pre-trained facial landmark detector and focus on the eye landmarks only,offering a more detailed analysis for predicting eye opening and closing of the eyes,rather than focusing on the entire face.We introduce an Eye Polygon Area(EPA)formula,which computes eye activity from Dlib eye landmarks by measuring the polygonal area of the eye opening.Unlike the Eye Aspect Ratio(EAR),which relies on a single distance ratio,EPA adapts to different eye shapes(round,narrow,or wide),providing a more reliable measure for fatigue detection.The VMFD system issues a warning if a participant remains in a fatigued condition for 36 consecutive frames.The proposed technology is tested under multiple scenarios,including low-to high-lighting conditions(50-1400 lux)and both with and without glasses.This study builds an OpenCV application in Python,evaluated using the iBUG 300-W dataset,achieving 97.5%accuracy in detecting active participants.We compare VMFD with conventional methods relying on the EAR and show that the EPA technique performs significantly better.展开更多
Statistical distribution of residual fatigue life(RFL)of railway axles under given loading was computed using the Monte Carlo method by considering random variation of the selected input parameters.Experimental data f...Statistical distribution of residual fatigue life(RFL)of railway axles under given loading was computed using the Monte Carlo method by considering random variation of the selected input parameters.Experimental data for the EA4T railway axle steel,the loading spectrum,the press fit loading and the residual stress induced by surface hardening were considered in the crack propagation simulations.Usually,the material properties measured by tensile tests are considered to be the most informative source of material data.Under fatigue loading,however,the crack growth rates near the threshold are the most critical data.Two important influencing factors on these crack growth rates are presented:first,the air humidity and,second,the near-surface residual stress.The typical variation of these parameters in operation may change the RFL by one or two orders of magnitude.Experimentally obtained crack growth thresholds and residual stress profiles are highly affected by the used methodology.Therefore,the obtained input data may be located anywhere within a large scatter,while the experimenters are completely unaware of it.This can lead to dangerously non-conservative situations,e.g.when the thresholds are measured in a laboratory under humid air conditions and then applied to predictions of RFLs of axles operated in winter in low air humidity.This is significant for the topic of inspection interval optimisation.The results of experiments done on real 1:1 railway axles were close to the most frequent value found in the histogram of the numerically computed RFLs.展开更多
Ultrafine-grained(UFG)pure titanium was produced by equal channel angular pressing for 4 passes,followed by rotatory swaging at room temperature.The strain-controlled low-cycle fatigue tests of UFG and coarse-grained(...Ultrafine-grained(UFG)pure titanium was produced by equal channel angular pressing for 4 passes,followed by rotatory swaging at room temperature.The strain-controlled low-cycle fatigue tests of UFG and coarse-grained(CG)pure titanium were conducted by Instron electro-hydraulic servo fatigue testing machine in the strain amplitude range of 0.5%—1.1%at room temperature.Transmission electron microscope(TEM)and scanning electron microscope were used to investigate the microstructure and fracture surface of UFG pure titanium after fatigue tests.Results show that UFG pure titanium exhibits a longer low-cycle fatigue life,compared with the CG pure titanium.For example,at a total strain amplitude of 0.5%,UFG and CG pure titanium has fatigue life of 10850 and 4820 cycles,respectively.Significant cyclic softening occurs in UFG pure titanium,except in the case of a total strain amplitude of 0.5%.Hysteresis loop area is increased rapidly with the increase in strain amplitude.The fracture surface shows that the fatigue crack is initiated from the specimen surface.A series of fatigue striations and many microcracks exist in the propagation region.With the increase in strain amplitude,the predominant failure mode is transformed from ductile failure into quasi-cleavage failure.Dislocation slip is the main plastic deformation mechanism of UFG pure titanium during low-cycle fatigue deformation.展开更多
The fatigue crack growth rate of a novel Ti-6Al-4V-1Mo titanium alloy,which is developed for laser directed energy deposition technique,was investigated before and after cyclic heat treatment(CHT).Changes in microstru...The fatigue crack growth rate of a novel Ti-6Al-4V-1Mo titanium alloy,which is developed for laser directed energy deposition technique,was investigated before and after cyclic heat treatment(CHT).Changes in microstructure,fracture surfaces,and crack growth paths were analyzed before and after CHT.Results indicate that in the stable crack growth region,the growth rates for the as-deposited and cyclic heat-treated specimens follow the relationships da/dN=1.8651×10^(−8)(ΔK)^(3.2271)and da/dN=1.4112×10^(−8)(ΔK)^(3.1125),respectively.Compared with that at the as-deposited state,the microstructure after CHT is transformed from a uniform basket-weave microstructure to a dual-phase microstructure consisting of near-sphericalαandβ-transformed matrix phases.The cyclic process also disrupts the continuity of the grain boundaryα(αGB)at the primaryβ-phase grain boundary.The coarsening of primaryαand the disruption ofαGB continuity are the primary factors to release stress concentration and promote crack deflection,thereby decreasing the fatigue crack growth rate.Additionally,the increased occurrence of crack branching,secondary cracking,and crack bridging in cyclic heat-treated specimens further reduces the crack driving force and slows the fatigue crack growth rate.展开更多
BACKGROUND Parkinson’s disease(PD)is a common neurodegenerative disorder in the elderly population.Non-motor symptoms such as anxiety and depression are often subtle,hindering early detection and intervention,yet the...BACKGROUND Parkinson’s disease(PD)is a common neurodegenerative disorder in the elderly population.Non-motor symptoms such as anxiety and depression are often subtle,hindering early detection and intervention,yet they markedly affect quality of life and clinical outcomes.AIM To investigate the prevalence of anxiety and depression in elderly PD patients,identify associated risk factors,and assess their relationship with fatigue severity.METHODS A cross-sectional analysis was conducted in 123 elderly PD patients treated at The Second Rehabilitation Hospital of Shanghai between January 2023 and December 2024.Demographic and clinical data were obtained using standardized questionnaires.Anxiety,depression,and fatigue were assessed using the Beck Anxiety Inventory(BAI),Geriatric Depression Scale(GDS),and Fatigue Scale-14(FS-14),respectively.Binary logistic regression identified risk factors for anxiety and depression,whereas Spearman’s correlation assessed associations with fatigue.RESULTS Anxiety and depression prevalence rates were 64.2%(mean BAI score:19.59±10.92)and 56.1%(mean GDS score:12.82±6.37),respectively.The mean FS-14 total score was 9.46±1.89,comprising physical(5.77±1.51)and mental(3.69±1.20)fatigue components.Significant positive correlations were observed between fatigue scores(total,physical,and mental)and both anxiety and depression(all P<0.05).Univariate analysis revealed statistically significant associations between anxiety/depression and monthly income,disease duration,and disease severity(all P<0.05).Multivariate logistic regression indicated higher anxiety risk in patients with lower monthly income,prolonged disease duration,advanced disease severity,or multimorbidity.Depression risk was elevated in patients with lower monthly income and severe disease,whereas longer disease duration unexpectedly served as a protective factor.CONCLUSION Elderly PD patients show high rates of anxiety and depression,both of which are significantly correlated with fatigue severity.These findings highlight the importance of psychological monitoring and targeted mental health interventions in PD management among the elderly.展开更多
The interrupted fatigue test method was utilized to investigate the damage evolution mechanism of the notch high-cycle fatigue(NHCF)in Ti-55531 alloy with a multilevel lamellar microstructure.The results reveal that s...The interrupted fatigue test method was utilized to investigate the damage evolution mechanism of the notch high-cycle fatigue(NHCF)in Ti-55531 alloy with a multilevel lamellar microstructure.The results reveal that significant microvoids and microcracks predominantly initiate at α/β interfaces under various notch root radii(R).Notably,even under larger R(0.75 mm),mutual interactions of stacking faults(SFs)−deformation twins,twins−twins,and SFs−SFs are observed.Furthermore,with decreasing R(0.34 and 0.14 mm),the volume fraction of SFs escalates significantly and twins are almost absent.Moreover,activated prismatic slip system decreases with a decrease in Schmidt factor and with the further decrease in R.Finally,strain localization near α/β interfaces contributes to the initiation of fatigue microcracks.展开更多
Most failures in component operation occur due to cyclic loads.Validation has been performed under quasistatic loads,but the fatigue life of components under dynamic loads should be predicted to prevent failures durin...Most failures in component operation occur due to cyclic loads.Validation has been performed under quasistatic loads,but the fatigue life of components under dynamic loads should be predicted to prevent failures during component service life.Fatigue is a damage accumulation process where loads degrade the material,depending on the characteristics and number of repetitions of the load.Studies on themechanical fatigue of 3D-printedOnyx are limited.In this paper,the strength of 3D-printed Onyx components under dynamic conditions(repetitive loads)is estimated.Fatigue life prediction is influenced bymanufacturing processes,material properties,and applied loads,which can cause scatter in the results due to the interplay of these factors.By utilizing synthetic parameters derived from mechanical properties,the accuracy of fatigue life predictions has been improved significantly,from 23.13%to 98.33%.Additive manufacturing is flexible,but this flexibility generates scatter in the mechanical properties of produced components.This work also proposes the use of synthetic data with a neural network to improve the fatigue life prediction of printedOnyx subjected to tension–tension loads.Experimental uniaxial loads were used to characterize themechanical behaviorofprinted specimens.The experimental datawereused to evaluate thenumerical predictionsobtainedthrough finite element analysis using commercial software and an artificial neural network.The results showed that the use of synthetic data helped improve fatigue life prediction.展开更多
High-performance magnesium alloys are in great demand to meet the lightweight design requirements of aircraft.Grain size has long been recognized as a key factor influencing the mechanical properties of alloys.This st...High-performance magnesium alloys are in great demand to meet the lightweight design requirements of aircraft.Grain size has long been recognized as a key factor influencing the mechanical properties of alloys.This study investigates the effect of grain size,controlled by Zr addition,on the fatigue behavior of a recently developed low-cost Mg-2.6Nd-0.35Zn alloy,through systematic characterization and analysis of stress-life(S-N)curves,fatigue crack propagation,fracture surface morphology,stress intensity factor,and crack propagation threshold.The results show that after heat treatment(solution at 525±5℃ for 8 h and water quenching at 60-80℃,followed by aging at 250±5℃for 14 h and then air cooling),coarse-grained specimens(average grain size approximately 596μm)containing 0.12wt.%Zr exhibit greater resistance to fatigue crack propagation than fine-grained specimens(average grain size approximately 94μm)containing 0.46wt.%Zr.Coarse grains promote intergranular fracture,while fine grains favor transgranular fracture.In addition,coarse grains reduce the sensitivity of the crack tip to stress concentration.Furthermore,fine-grained samples demonstrate a longer total fatigue life,owing to their superior resistance to crack initiation,which significantly prolongs the crack initiation stage.These findings highlight the importance of optimizing grain size to achieve the best possible fatigue resistance in Mg-Nd-Zn-Zr alloys for practical engineering applications.展开更多
With the continuous advancement of aerospace technology,ensuring the reliability of aerospace engines after testing is critical.While various methods exist for assessing fatigue life,non-destructive prediction based o...With the continuous advancement of aerospace technology,ensuring the reliability of aerospace engines after testing is critical.While various methods exist for assessing fatigue life,non-destructive prediction based on insitu X-ray diffraction(XRD)residual stress analysis remains underexplored—particularly for low-cycle fatigue in welded joints.This study proposes a novel approach that uses in-situ XRD to monitor residual stress evolution under fatigue and creep loading in gas tungsten arc welding(GTAW)joints of aerospace-grade austenitic stainless steel SUS321.Through metallographic observation,scanning electron microscopy(SEM),electron backscatter diffraction(EBSD),and in-situ XRD measurements,we demonstrate a strong correlation between longitudinal residual stress at the weld center and fatigue life.Under fatigue loading at 60%of the ultimate tensile strength(UTS),longitudinal residual stress transitions from tensile to compressive with increasing cycles,and fatigue fracture occurs once residual stress approaches base metal levels(∼0 MPa).In contrast,under creep loading,no clear trend in Y-direction residual stress was observed,limiting its utility for creep life prediction.This work establishes a reliable,non-destructive framework for evaluating the service life of welded aerospace components,offering a new methodology beyond conventional practices.展开更多
A comprehensive full-sieve-hole grading correction method was used to adjust aggregate gradings.The fatigue properties of recycled concrete aggregate(RCA)asphalt mixtures were investigated using an improved indirect t...A comprehensive full-sieve-hole grading correction method was used to adjust aggregate gradings.The fatigue properties of recycled concrete aggregate(RCA)asphalt mixtures were investigated using an improved indirect tensile fatigue test under temperature-humidity coupling based on 20-year meteorological data of Beijing,and the degeneration mechanism was further explored by scanning electron microscopy and energy-dispersive spectroscopy.The experimental results indicate that replacing 5-20 mm coarse limestone aggregate(LA)with RCA at a 50% substitution volume can mitigate the impact of RCA variations on the asphalt mixture proportioning design.All RCA asphalt mixtures have lower initial fatigue properties than the LA asphalt mixture.However,under temperature-humidity coupling,the long-term fatigue property of an RCA asphalt mixture with a low proportion of recycled brick exceeds that of the LA asphalt mixture,and the fatigue life decline rate of the RCA asphalt mixture during 10-year service decreases by approximately 25%.This is due to the penetration of the asphalt mortar into the RCA through the pores and cracks on the RCA surface.It forms an interfacial transition zone composed of asphalt mortar and cement mortar and further reduces the mixture damage caused by the water and freeze-thaw conditions.展开更多
Aviation aluminum alloys,primarily from the Al-Cu,Al-Zn-Mg-(Cu),and Al-Li series,have been widely applied over six decades,greatly advancing the aviation industry.However,their Corrosion Fatigue(CF)properties impede f...Aviation aluminum alloys,primarily from the Al-Cu,Al-Zn-Mg-(Cu),and Al-Li series,have been widely applied over six decades,greatly advancing the aviation industry.However,their Corrosion Fatigue(CF)properties impede further advancements,prompting extensive research into their CF behaviors and underlying mechanisms.This review comprehensively evaluates previous studies on their development history,CF mechanisms,and key influencing factors.First,the historical evolution of aerospace aluminum alloys is summarized.Then,the currently recognized four crack initiation mechanisms and three crack propagation mechanisms are concluded,and the effects of external and internal factors on CF performance are discussed.The paper also reviews three methods and CF life prediction models for characterizing the CF behavior of aerospace aluminum alloys.Most existing studies on the CF behavior of aluminum alloys are based on the single corrosive environment,neglecting the fact that aircrafts experience multiple corrosive environments during service.However,the most critical scientific challenge is how to enhance their CF properties under increasingly demanding service conditions.For the purpose,this paper introduces advanced forming techniques based on the microstructural control,such as Equal Channel Angular Pressing(ECAP)and High-Pressure Torsion(HPT),aimed at laying the theoretical foundation for improving CF properties through microstructural regulation.展开更多
Myalgic encephalomyelitis/chronic fatigue syndrome-an insidious disease:The recent COVID-19 pandemic has brought substantial attention to the overlapping symptoms between long COVID and myalgic encephalomyelitis/chron...Myalgic encephalomyelitis/chronic fatigue syndrome-an insidious disease:The recent COVID-19 pandemic has brought substantial attention to the overlapping symptoms between long COVID and myalgic encephalomyelitis/chronic fatigue syndrome(ME/CFS),a chronic and poorly understood neurological disorder(Shankar et al.,2024).展开更多
This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher ope...This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher operational speeds.Fatigue tests were conducted at loading frequencies ranging from 5 to 40 Hz,with a focus on fatigue life,damage evolution,energy dissipation,and residual fatigue strain in the concrete.The results indicate that between 5 and 15 Hz,the fatigue life and energy dissipation remain relatively stable,with minimal damage evolution and small residual strains.As the frequency increases to 15-20 Hz,the fatigue life and energy dissipation gradually decrease,while damage accumulation and residual strain increase.Beyond 20 Hz,both fatigue life and energy dissipation decrease rapidly,damage accumulation becomes more pronounced,and residual strain continues to rise.These phenomena are primarily attributed to the increased strain rate and load change rate at higher frequencies,which affect the microstructure evolution and lead to reduced fatigue performance.展开更多
Accurately predicting fatigue life under multiaxial fatigue damage conditions is essential for ensuring the safety of critical components in service.However,due to the complexity of fatigue failure mechanisms,achievin...Accurately predicting fatigue life under multiaxial fatigue damage conditions is essential for ensuring the safety of critical components in service.However,due to the complexity of fatigue failure mechanisms,achieving accurate multiaxial fatigue life predictions remains challenging.Traditional multiaxial fatigue prediction models are often limited by specific material properties and loading conditions,making it difficult to maintain reliable life prediction results beyond these constraints.This paper presents a study on the impact of seven key feature quantities on multiaxial fatigue life,using Convolutional Neural Networks(CNN),Long Short-Term Memory Networks(LSTM),and Fully Connected Neural Networks(FCNN)within a deep learning framework.Fatigue test results from eight metal specimens were analyzed to identify these feature quantities,which were then extracted as critical time-series features.Using a CNN-LSTM network,these features were combined to form a feature matrix,which was subsequently input into an FCNN to predict metal fatigue life.A comparison of the fatigue life prediction results from the STFAN model with those from traditional prediction models—namely,the equivalent strain method,the maximum shear strain method,and the critical plane method—shows that the majority of predictions for the five metal materials and various loading conditions based on the STFAN model fall within an error band of 1.5 times.Additionally,all data points are within an error band of 2 times.These findings indicate that the STFAN model provides superior prediction accuracy compared to the traditional models,highlighting its broad applicability and high precision.展开更多
This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fati...This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.展开更多
Accurate detection of driver fatigue is essential for improving road safety.This study investigates the effectiveness of using multimodal physiological signals for fatigue detection while incorporating uncertainty qua...Accurate detection of driver fatigue is essential for improving road safety.This study investigates the effectiveness of using multimodal physiological signals for fatigue detection while incorporating uncertainty quantification to enhance the reliability of predictions.Physiological signals,including Electrocardiogram(ECG),Galvanic Skin Response(GSR),and Electroencephalogram(EEG),were transformed into image representations and analyzed using pretrained deep neu-ral networks.The extracted features were classified through a feedforward neural network,and prediction reliability was assessed using uncertainty quantification techniques such as Monte Carlo Dropout(MCD),model ensembles,and combined approaches.Evaluation metrics included standard measures(sensitivity,specificity,precision,and accuracy)along with uncertainty-aware metrics such as uncertainty sensitivity and uncertainty precision.Across all evaluations,ECG-based models consistently demonstrated strong performance.The findings indicate that combining multimodal physi-ological signals,Transfer Learning(TL),and uncertainty quantification can significantly improve both the accuracy and trustworthiness of fatigue detection systems.This approach supports the development of more reliable driver assistance technologies aimed at preventing fatigue-related accidents.展开更多
To address the insufficient prediction accuracy of multi-state parameters in electro-hydraulic servo material fatigue testing machines under complex loading and nonlinear coupling conditions,this paper proposes a mult...To address the insufficient prediction accuracy of multi-state parameters in electro-hydraulic servo material fatigue testing machines under complex loading and nonlinear coupling conditions,this paper proposes a multivariate sequence-to-sequence prediction model integrating a Long Short-Term Memory(LSTM)encoder,a Gated Recurrent Unit(GRU)decoder,and a multi-head attention mechanism.This approach enhances prediction accuracy and robustness across different control modes and load spectra by leveraging multi-channel inputs and cross-variable feature interactions,thereby capturing both short-term high-frequency dynamics and long-term slow drift characteristics.Experiments using long-term data from real test benches demonstrate that the model achieves a stable MSE below 0.01 on the validation set,with MAE and RMSE of approximately 0.018 and 0.052,respectively,and a coefficient of determination reaching 0.98.This significantly outperforms traditional identification methods and single RNN models.Sensitivity analysis indicates that a prediction stride of 10 achieves an optimal balance between accuracy and computational overhead.Ablation experiments validated the contribution of multi-head attention and decoder architecture to enhancing cross-variable coupling modeling capabilities.This model can be applied to residualdriven early warning in health monitoring,and risk assessment with scheme optimization in test design.It enables near-real-time deployment feasibility,providing a practical data-driven technical pathway for reliability assurance in advanced equipment.展开更多
The paper designs a novel material-level specimen and its dedicated fixture suitable for applying Combined high-and low-Cycle Fatigue(CCF)loads.Unlike full-scale or simulation specimens,the CCF specimen eliminates geo...The paper designs a novel material-level specimen and its dedicated fixture suitable for applying Combined high-and low-Cycle Fatigue(CCF)loads.Unlike full-scale or simulation specimens,the CCF specimen eliminates geometrically induced stress gradients in the test region.Experimental data on CCF life and strain responses of ZSGH4169 alloy are acquired under different CCF loads.The Maximum Strain within Each(MSE)CCF cycle is demonstrated to be independent of the Low-Cycle Fatigue(LCF)loads and High-Cycle Fatigue(HCF)stress amplitudes,but exhibits a correlation with the Cycle Ratio of HCF/LCF(Rf).The growth law of MSE changes from linear to logarithmic as Rfdecreases.Strain amplitudes in the dwell stage,observed unaffected by Rf,are quantified as a function of LCF nominal stresses and HCF stress amplitudes.However,under a defined CCF load,strain amplitudes in the dwell stage remain constant.Strain peaks in the dwell stage in a single CCF cycle decrease in a power function with increasing HCF cycles.展开更多
Current fatigue damage analysis of various components(e.g.aircraft parts)focuses on effects of High-Cycle-Fatigue(HCF)loads while overlooking effects of Very-High-Cycle-Fatigue(VHCF)loads,thereby introducing a substan...Current fatigue damage analysis of various components(e.g.aircraft parts)focuses on effects of High-Cycle-Fatigue(HCF)loads while overlooking effects of Very-High-Cycle-Fatigue(VHCF)loads,thereby introducing a substantial bias.The crux of decreasing this bias lies in how to reasonably consider the threshold effect and nonlinear effect of VHCF loads'fatigue damage evolution.This problem is addressed in this paper from the perspective of Residual Fatigue Quality(RFQ,represent residual S-N^(*)curve and residual fatigue limitσ_(-1)^(*)).Fatigue tests were conducted on AA2024-T4 under various constant/variable-amplitude loads to reveal the evolution characteristics of RFQ and measure the equivalent fatigue damage of VHCF loads block loaded with various number of pre-loading HCF loads.Corresponding mechanisms were analysed in view of evolution of extrusions/intrusions along persistent slip bands.Theoretical analysis was conducted to reveal the relationship between RFQ and fatigue damage of VHCF loads block.Based on the above results,an isodamage curve-based fatigue damage analysis method was proposed,where bilinear-isodamage curves(consist of S-N^(*)curves intersecting at a point and corresponding_(σ-1)^(*))were adopted to consider the RFQ degeneration and its effect.This method reduces analysis bias to 1/3 of previous methods for typical variable-amplitude loads in HCF and HCF-VHCF regime.展开更多
Fatigue analysis of engine turbine blade is an essential issue.Due to various uncertainties during the manufacture and operation,the fatigue damage and life of turbine blade present randomness.In this study,the random...Fatigue analysis of engine turbine blade is an essential issue.Due to various uncertainties during the manufacture and operation,the fatigue damage and life of turbine blade present randomness.In this study,the randomness of structural parameters,working condition and vibration environment are considered for fatigue life predication and reliability assessment.First,the lowcycle fatigue problem is modelled as stochastic static system with random parameters,while the high-cycle fatigue problem is considered as stochastic dynamic system under random excitations.Then,to deal with the two failure modes,the novel Direct Probability Integral Method(DPIM)is proposed,which is efficient and accurate for solving stochastic static and dynamic systems.The probability density functions of accumulated damage and fatigue life of turbine blade for low-cycle and high-cycle fatigue problems are achieved,respectively.Furthermore,the time–frequency hybrid method is advanced to enhance the computational efficiency for governing equation of system.Finally,the results of typical examples demonstrate high accuracy and efficiency of the proposed method by comparison with Monte Carlo simulation and other methods.It is indicated that the DPIM is a unified method for predication of random fatigue life for low-cycle and highcycle fatigue problems.The rotational speed,density,fatigue strength coefficient,and fatigue plasticity index have a high sensitivity to fatigue reliability of engine turbine blade.展开更多
文摘Numerous sectors,such as education,the IT sector,and corporate organizations,transitioned to virtual meetings after the COVID-19 crisis.Organizations now seek to assess participants’fatigue levels in online meetings to remain competitive.Instructors cannot effectively monitor every individual in a virtual environment,which raises significant concerns about participant fatigue.Our proposed system monitors fatigue,identifying attentive and drowsy individuals throughout the online session.We leverage Dlib’s pre-trained facial landmark detector and focus on the eye landmarks only,offering a more detailed analysis for predicting eye opening and closing of the eyes,rather than focusing on the entire face.We introduce an Eye Polygon Area(EPA)formula,which computes eye activity from Dlib eye landmarks by measuring the polygonal area of the eye opening.Unlike the Eye Aspect Ratio(EAR),which relies on a single distance ratio,EPA adapts to different eye shapes(round,narrow,or wide),providing a more reliable measure for fatigue detection.The VMFD system issues a warning if a participant remains in a fatigued condition for 36 consecutive frames.The proposed technology is tested under multiple scenarios,including low-to high-lighting conditions(50-1400 lux)and both with and without glasses.This study builds an OpenCV application in Python,evaluated using the iBUG 300-W dataset,achieving 97.5%accuracy in detecting active participants.We compare VMFD with conventional methods relying on the EAR and show that the EPA technique performs significantly better.
基金financially supported by the Czech Science Foundation in the frame of the project No.22-28283Sby the Technology Agency of the Czech Republic through the project No.CK03000060.
文摘Statistical distribution of residual fatigue life(RFL)of railway axles under given loading was computed using the Monte Carlo method by considering random variation of the selected input parameters.Experimental data for the EA4T railway axle steel,the loading spectrum,the press fit loading and the residual stress induced by surface hardening were considered in the crack propagation simulations.Usually,the material properties measured by tensile tests are considered to be the most informative source of material data.Under fatigue loading,however,the crack growth rates near the threshold are the most critical data.Two important influencing factors on these crack growth rates are presented:first,the air humidity and,second,the near-surface residual stress.The typical variation of these parameters in operation may change the RFL by one or two orders of magnitude.Experimentally obtained crack growth thresholds and residual stress profiles are highly affected by the used methodology.Therefore,the obtained input data may be located anywhere within a large scatter,while the experimenters are completely unaware of it.This can lead to dangerously non-conservative situations,e.g.when the thresholds are measured in a laboratory under humid air conditions and then applied to predictions of RFLs of axles operated in winter in low air humidity.This is significant for the topic of inspection interval optimisation.The results of experiments done on real 1:1 railway axles were close to the most frequent value found in the histogram of the numerically computed RFLs.
基金Natural Science Foundation of Shaanxi Province (2023-JC-YB-312)。
文摘Ultrafine-grained(UFG)pure titanium was produced by equal channel angular pressing for 4 passes,followed by rotatory swaging at room temperature.The strain-controlled low-cycle fatigue tests of UFG and coarse-grained(CG)pure titanium were conducted by Instron electro-hydraulic servo fatigue testing machine in the strain amplitude range of 0.5%—1.1%at room temperature.Transmission electron microscope(TEM)and scanning electron microscope were used to investigate the microstructure and fracture surface of UFG pure titanium after fatigue tests.Results show that UFG pure titanium exhibits a longer low-cycle fatigue life,compared with the CG pure titanium.For example,at a total strain amplitude of 0.5%,UFG and CG pure titanium has fatigue life of 10850 and 4820 cycles,respectively.Significant cyclic softening occurs in UFG pure titanium,except in the case of a total strain amplitude of 0.5%.Hysteresis loop area is increased rapidly with the increase in strain amplitude.The fracture surface shows that the fatigue crack is initiated from the specimen surface.A series of fatigue striations and many microcracks exist in the propagation region.With the increase in strain amplitude,the predominant failure mode is transformed from ductile failure into quasi-cleavage failure.Dislocation slip is the main plastic deformation mechanism of UFG pure titanium during low-cycle fatigue deformation.
基金National Key Research and Development Program of China(2024YFB4610803)。
文摘The fatigue crack growth rate of a novel Ti-6Al-4V-1Mo titanium alloy,which is developed for laser directed energy deposition technique,was investigated before and after cyclic heat treatment(CHT).Changes in microstructure,fracture surfaces,and crack growth paths were analyzed before and after CHT.Results indicate that in the stable crack growth region,the growth rates for the as-deposited and cyclic heat-treated specimens follow the relationships da/dN=1.8651×10^(−8)(ΔK)^(3.2271)and da/dN=1.4112×10^(−8)(ΔK)^(3.1125),respectively.Compared with that at the as-deposited state,the microstructure after CHT is transformed from a uniform basket-weave microstructure to a dual-phase microstructure consisting of near-sphericalαandβ-transformed matrix phases.The cyclic process also disrupts the continuity of the grain boundaryα(αGB)at the primaryβ-phase grain boundary.The coarsening of primaryαand the disruption ofαGB continuity are the primary factors to release stress concentration and promote crack deflection,thereby decreasing the fatigue crack growth rate.Additionally,the increased occurrence of crack branching,secondary cracking,and crack bridging in cyclic heat-treated specimens further reduces the crack driving force and slows the fatigue crack growth rate.
基金Supported by Foundation of Shanghai Baoshan Science and Technology Commission,No.2024-E-66Shanghai Nursing Association Scientific Research Project,No.2024MS-B02.
文摘BACKGROUND Parkinson’s disease(PD)is a common neurodegenerative disorder in the elderly population.Non-motor symptoms such as anxiety and depression are often subtle,hindering early detection and intervention,yet they markedly affect quality of life and clinical outcomes.AIM To investigate the prevalence of anxiety and depression in elderly PD patients,identify associated risk factors,and assess their relationship with fatigue severity.METHODS A cross-sectional analysis was conducted in 123 elderly PD patients treated at The Second Rehabilitation Hospital of Shanghai between January 2023 and December 2024.Demographic and clinical data were obtained using standardized questionnaires.Anxiety,depression,and fatigue were assessed using the Beck Anxiety Inventory(BAI),Geriatric Depression Scale(GDS),and Fatigue Scale-14(FS-14),respectively.Binary logistic regression identified risk factors for anxiety and depression,whereas Spearman’s correlation assessed associations with fatigue.RESULTS Anxiety and depression prevalence rates were 64.2%(mean BAI score:19.59±10.92)and 56.1%(mean GDS score:12.82±6.37),respectively.The mean FS-14 total score was 9.46±1.89,comprising physical(5.77±1.51)and mental(3.69±1.20)fatigue components.Significant positive correlations were observed between fatigue scores(total,physical,and mental)and both anxiety and depression(all P<0.05).Univariate analysis revealed statistically significant associations between anxiety/depression and monthly income,disease duration,and disease severity(all P<0.05).Multivariate logistic regression indicated higher anxiety risk in patients with lower monthly income,prolonged disease duration,advanced disease severity,or multimorbidity.Depression risk was elevated in patients with lower monthly income and severe disease,whereas longer disease duration unexpectedly served as a protective factor.CONCLUSION Elderly PD patients show high rates of anxiety and depression,both of which are significantly correlated with fatigue severity.These findings highlight the importance of psychological monitoring and targeted mental health interventions in PD management among the elderly.
基金supported by the National Natural Science Foundation of China(Nos.52061005,52261025)the Science and Technology Programs of Guizhou Province,China(Nos.YQK[2023]009,CXTD[2023]009)the Technology Innovation Leading Program of Shaanxi Province,China(No.2024ZCYYDP92)。
文摘The interrupted fatigue test method was utilized to investigate the damage evolution mechanism of the notch high-cycle fatigue(NHCF)in Ti-55531 alloy with a multilevel lamellar microstructure.The results reveal that significant microvoids and microcracks predominantly initiate at α/β interfaces under various notch root radii(R).Notably,even under larger R(0.75 mm),mutual interactions of stacking faults(SFs)−deformation twins,twins−twins,and SFs−SFs are observed.Furthermore,with decreasing R(0.34 and 0.14 mm),the volume fraction of SFs escalates significantly and twins are almost absent.Moreover,activated prismatic slip system decreases with a decrease in Schmidt factor and with the further decrease in R.Finally,strain localization near α/β interfaces contributes to the initiation of fatigue microcracks.
文摘Most failures in component operation occur due to cyclic loads.Validation has been performed under quasistatic loads,but the fatigue life of components under dynamic loads should be predicted to prevent failures during component service life.Fatigue is a damage accumulation process where loads degrade the material,depending on the characteristics and number of repetitions of the load.Studies on themechanical fatigue of 3D-printedOnyx are limited.In this paper,the strength of 3D-printed Onyx components under dynamic conditions(repetitive loads)is estimated.Fatigue life prediction is influenced bymanufacturing processes,material properties,and applied loads,which can cause scatter in the results due to the interplay of these factors.By utilizing synthetic parameters derived from mechanical properties,the accuracy of fatigue life predictions has been improved significantly,from 23.13%to 98.33%.Additive manufacturing is flexible,but this flexibility generates scatter in the mechanical properties of produced components.This work also proposes the use of synthetic data with a neural network to improve the fatigue life prediction of printedOnyx subjected to tension–tension loads.Experimental uniaxial loads were used to characterize themechanical behaviorofprinted specimens.The experimental datawereused to evaluate thenumerical predictionsobtainedthrough finite element analysis using commercial software and an artificial neural network.The results showed that the use of synthetic data helped improve fatigue life prediction.
文摘High-performance magnesium alloys are in great demand to meet the lightweight design requirements of aircraft.Grain size has long been recognized as a key factor influencing the mechanical properties of alloys.This study investigates the effect of grain size,controlled by Zr addition,on the fatigue behavior of a recently developed low-cost Mg-2.6Nd-0.35Zn alloy,through systematic characterization and analysis of stress-life(S-N)curves,fatigue crack propagation,fracture surface morphology,stress intensity factor,and crack propagation threshold.The results show that after heat treatment(solution at 525±5℃ for 8 h and water quenching at 60-80℃,followed by aging at 250±5℃for 14 h and then air cooling),coarse-grained specimens(average grain size approximately 596μm)containing 0.12wt.%Zr exhibit greater resistance to fatigue crack propagation than fine-grained specimens(average grain size approximately 94μm)containing 0.46wt.%Zr.Coarse grains promote intergranular fracture,while fine grains favor transgranular fracture.In addition,coarse grains reduce the sensitivity of the crack tip to stress concentration.Furthermore,fine-grained samples demonstrate a longer total fatigue life,owing to their superior resistance to crack initiation,which significantly prolongs the crack initiation stage.These findings highlight the importance of optimizing grain size to achieve the best possible fatigue resistance in Mg-Nd-Zn-Zr alloys for practical engineering applications.
基金supported by the Fundamental Research Funds for the Central Universities,the Institute of Marine Equipment,the Shanghai Rising-Star Program of Science and Technology Commission of Shanghai Municipality(Grant No.23QA1404700)National Natural Science Foundation of China(Grant Nos.52475384,52505409)China Postdoctoral Science Foundation(Grant No.2024M761963).
文摘With the continuous advancement of aerospace technology,ensuring the reliability of aerospace engines after testing is critical.While various methods exist for assessing fatigue life,non-destructive prediction based on insitu X-ray diffraction(XRD)residual stress analysis remains underexplored—particularly for low-cycle fatigue in welded joints.This study proposes a novel approach that uses in-situ XRD to monitor residual stress evolution under fatigue and creep loading in gas tungsten arc welding(GTAW)joints of aerospace-grade austenitic stainless steel SUS321.Through metallographic observation,scanning electron microscopy(SEM),electron backscatter diffraction(EBSD),and in-situ XRD measurements,we demonstrate a strong correlation between longitudinal residual stress at the weld center and fatigue life.Under fatigue loading at 60%of the ultimate tensile strength(UTS),longitudinal residual stress transitions from tensile to compressive with increasing cycles,and fatigue fracture occurs once residual stress approaches base metal levels(∼0 MPa).In contrast,under creep loading,no clear trend in Y-direction residual stress was observed,limiting its utility for creep life prediction.This work establishes a reliable,non-destructive framework for evaluating the service life of welded aerospace components,offering a new methodology beyond conventional practices.
基金Funded by"Green Construction and Maintenance of Road Engineering"the Belt and Road Joint Laboratory,International(Hong Kong,Macao and Taiwan)Science and Technology Cooperation Project(No.Z251100007125040)the National Key R&D Program of China(No.2022YFC3803403)+3 种基金the Project of Construction and Support for High-level Innovative Teams of Beijing Municipal Institutions(No.BPHR20220109)the Cultivation Project Funds for Beijing University of Civil Engineering and Architecture(No.X24013)the BUCEA Doctor Graduate Scientific Research Ability Improvement Project(No.DG2024016)the China Scholarship Council(No.202408110091)。
文摘A comprehensive full-sieve-hole grading correction method was used to adjust aggregate gradings.The fatigue properties of recycled concrete aggregate(RCA)asphalt mixtures were investigated using an improved indirect tensile fatigue test under temperature-humidity coupling based on 20-year meteorological data of Beijing,and the degeneration mechanism was further explored by scanning electron microscopy and energy-dispersive spectroscopy.The experimental results indicate that replacing 5-20 mm coarse limestone aggregate(LA)with RCA at a 50% substitution volume can mitigate the impact of RCA variations on the asphalt mixture proportioning design.All RCA asphalt mixtures have lower initial fatigue properties than the LA asphalt mixture.However,under temperature-humidity coupling,the long-term fatigue property of an RCA asphalt mixture with a low proportion of recycled brick exceeds that of the LA asphalt mixture,and the fatigue life decline rate of the RCA asphalt mixture during 10-year service decreases by approximately 25%.This is due to the penetration of the asphalt mortar into the RCA through the pores and cracks on the RCA surface.It forms an interfacial transition zone composed of asphalt mortar and cement mortar and further reduces the mixture damage caused by the water and freeze-thaw conditions.
基金co-supported by the National Natural Science Foundation of China(Nos 52475346 and U21A20130)the Natural Science Foundation of Hunan Province,China(No.2023JJ10019)+1 种基金China Postdoctoral Science Foundation(No.2022M712642)Hunan Science and Technology Innovation Plan,China(2023RC1068)。
文摘Aviation aluminum alloys,primarily from the Al-Cu,Al-Zn-Mg-(Cu),and Al-Li series,have been widely applied over six decades,greatly advancing the aviation industry.However,their Corrosion Fatigue(CF)properties impede further advancements,prompting extensive research into their CF behaviors and underlying mechanisms.This review comprehensively evaluates previous studies on their development history,CF mechanisms,and key influencing factors.First,the historical evolution of aerospace aluminum alloys is summarized.Then,the currently recognized four crack initiation mechanisms and three crack propagation mechanisms are concluded,and the effects of external and internal factors on CF performance are discussed.The paper also reviews three methods and CF life prediction models for characterizing the CF behavior of aerospace aluminum alloys.Most existing studies on the CF behavior of aluminum alloys are based on the single corrosive environment,neglecting the fact that aircrafts experience multiple corrosive environments during service.However,the most critical scientific challenge is how to enhance their CF properties under increasingly demanding service conditions.For the purpose,this paper introduces advanced forming techniques based on the microstructural control,such as Equal Channel Angular Pressing(ECAP)and High-Pressure Torsion(HPT),aimed at laying the theoretical foundation for improving CF properties through microstructural regulation.
基金supported by the Judith Jane Mason and Harold Stannett Williams Memorial Foundation National Medical Program(#Mason2210)to JX。
文摘Myalgic encephalomyelitis/chronic fatigue syndrome-an insidious disease:The recent COVID-19 pandemic has brought substantial attention to the overlapping symptoms between long COVID and myalgic encephalomyelitis/chronic fatigue syndrome(ME/CFS),a chronic and poorly understood neurological disorder(Shankar et al.,2024).
基金sponsored by the National Natural Science Foundation of China(Grant No.52438002)the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher operational speeds.Fatigue tests were conducted at loading frequencies ranging from 5 to 40 Hz,with a focus on fatigue life,damage evolution,energy dissipation,and residual fatigue strain in the concrete.The results indicate that between 5 and 15 Hz,the fatigue life and energy dissipation remain relatively stable,with minimal damage evolution and small residual strains.As the frequency increases to 15-20 Hz,the fatigue life and energy dissipation gradually decrease,while damage accumulation and residual strain increase.Beyond 20 Hz,both fatigue life and energy dissipation decrease rapidly,damage accumulation becomes more pronounced,and residual strain continues to rise.These phenomena are primarily attributed to the increased strain rate and load change rate at higher frequencies,which affect the microstructure evolution and lead to reduced fatigue performance.
基金supported by Key Program of National Natural Science Foundation of China(U2368215)the Science and Technology Research and Development Program Project of China Railway Group Co.,Ltd.(N2023J056).
文摘Accurately predicting fatigue life under multiaxial fatigue damage conditions is essential for ensuring the safety of critical components in service.However,due to the complexity of fatigue failure mechanisms,achieving accurate multiaxial fatigue life predictions remains challenging.Traditional multiaxial fatigue prediction models are often limited by specific material properties and loading conditions,making it difficult to maintain reliable life prediction results beyond these constraints.This paper presents a study on the impact of seven key feature quantities on multiaxial fatigue life,using Convolutional Neural Networks(CNN),Long Short-Term Memory Networks(LSTM),and Fully Connected Neural Networks(FCNN)within a deep learning framework.Fatigue test results from eight metal specimens were analyzed to identify these feature quantities,which were then extracted as critical time-series features.Using a CNN-LSTM network,these features were combined to form a feature matrix,which was subsequently input into an FCNN to predict metal fatigue life.A comparison of the fatigue life prediction results from the STFAN model with those from traditional prediction models—namely,the equivalent strain method,the maximum shear strain method,and the critical plane method—shows that the majority of predictions for the five metal materials and various loading conditions based on the STFAN model fall within an error band of 1.5 times.Additionally,all data points are within an error band of 2 times.These findings indicate that the STFAN model provides superior prediction accuracy compared to the traditional models,highlighting its broad applicability and high precision.
基金supported by National Natural Science Foundation of China[NO.11932013].
文摘This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.
基金the Australian Research Council Discovery Projects funding scheme(DP190102181,DP210101465).
文摘Accurate detection of driver fatigue is essential for improving road safety.This study investigates the effectiveness of using multimodal physiological signals for fatigue detection while incorporating uncertainty quantification to enhance the reliability of predictions.Physiological signals,including Electrocardiogram(ECG),Galvanic Skin Response(GSR),and Electroencephalogram(EEG),were transformed into image representations and analyzed using pretrained deep neu-ral networks.The extracted features were classified through a feedforward neural network,and prediction reliability was assessed using uncertainty quantification techniques such as Monte Carlo Dropout(MCD),model ensembles,and combined approaches.Evaluation metrics included standard measures(sensitivity,specificity,precision,and accuracy)along with uncertainty-aware metrics such as uncertainty sensitivity and uncertainty precision.Across all evaluations,ECG-based models consistently demonstrated strong performance.The findings indicate that combining multimodal physi-ological signals,Transfer Learning(TL),and uncertainty quantification can significantly improve both the accuracy and trustworthiness of fatigue detection systems.This approach supports the development of more reliable driver assistance technologies aimed at preventing fatigue-related accidents.
基金supported by Natural Science Foundation of China(NSFC),Grant number 5247052693.
文摘To address the insufficient prediction accuracy of multi-state parameters in electro-hydraulic servo material fatigue testing machines under complex loading and nonlinear coupling conditions,this paper proposes a multivariate sequence-to-sequence prediction model integrating a Long Short-Term Memory(LSTM)encoder,a Gated Recurrent Unit(GRU)decoder,and a multi-head attention mechanism.This approach enhances prediction accuracy and robustness across different control modes and load spectra by leveraging multi-channel inputs and cross-variable feature interactions,thereby capturing both short-term high-frequency dynamics and long-term slow drift characteristics.Experiments using long-term data from real test benches demonstrate that the model achieves a stable MSE below 0.01 on the validation set,with MAE and RMSE of approximately 0.018 and 0.052,respectively,and a coefficient of determination reaching 0.98.This significantly outperforms traditional identification methods and single RNN models.Sensitivity analysis indicates that a prediction stride of 10 achieves an optimal balance between accuracy and computational overhead.Ablation experiments validated the contribution of multi-head attention and decoder architecture to enhancing cross-variable coupling modeling capabilities.This model can be applied to residualdriven early warning in health monitoring,and risk assessment with scheme optimization in test design.It enables near-real-time deployment feasibility,providing a practical data-driven technical pathway for reliability assurance in advanced equipment.
基金co-supported by the National Natural Science Foundation of China(51805017)National Science and Technology Project(J2017-IV-0012-0049)+1 种基金National Science and Technology Project,China(J2019-IV-0007-0075)the Fundamental Research Funds for the Central Universities,China(JKF-20240036).
文摘The paper designs a novel material-level specimen and its dedicated fixture suitable for applying Combined high-and low-Cycle Fatigue(CCF)loads.Unlike full-scale or simulation specimens,the CCF specimen eliminates geometrically induced stress gradients in the test region.Experimental data on CCF life and strain responses of ZSGH4169 alloy are acquired under different CCF loads.The Maximum Strain within Each(MSE)CCF cycle is demonstrated to be independent of the Low-Cycle Fatigue(LCF)loads and High-Cycle Fatigue(HCF)stress amplitudes,but exhibits a correlation with the Cycle Ratio of HCF/LCF(Rf).The growth law of MSE changes from linear to logarithmic as Rfdecreases.Strain amplitudes in the dwell stage,observed unaffected by Rf,are quantified as a function of LCF nominal stresses and HCF stress amplitudes.However,under a defined CCF load,strain amplitudes in the dwell stage remain constant.Strain peaks in the dwell stage in a single CCF cycle decrease in a power function with increasing HCF cycles.
基金the support from National Key Laboratory of Strength and Structural Integrity independent research project“Failure law and fatigue life prediction method of Metal Materials based on Material property degradation”。
文摘Current fatigue damage analysis of various components(e.g.aircraft parts)focuses on effects of High-Cycle-Fatigue(HCF)loads while overlooking effects of Very-High-Cycle-Fatigue(VHCF)loads,thereby introducing a substantial bias.The crux of decreasing this bias lies in how to reasonably consider the threshold effect and nonlinear effect of VHCF loads'fatigue damage evolution.This problem is addressed in this paper from the perspective of Residual Fatigue Quality(RFQ,represent residual S-N^(*)curve and residual fatigue limitσ_(-1)^(*)).Fatigue tests were conducted on AA2024-T4 under various constant/variable-amplitude loads to reveal the evolution characteristics of RFQ and measure the equivalent fatigue damage of VHCF loads block loaded with various number of pre-loading HCF loads.Corresponding mechanisms were analysed in view of evolution of extrusions/intrusions along persistent slip bands.Theoretical analysis was conducted to reveal the relationship between RFQ and fatigue damage of VHCF loads block.Based on the above results,an isodamage curve-based fatigue damage analysis method was proposed,where bilinear-isodamage curves(consist of S-N^(*)curves intersecting at a point and corresponding_(σ-1)^(*))were adopted to consider the RFQ degeneration and its effect.This method reduces analysis bias to 1/3 of previous methods for typical variable-amplitude loads in HCF and HCF-VHCF regime.
基金supports of the National Natural Science Foundation of China(Nos.12032008,12102080)the Fundamental Research Funds for the Central Universities,China(No.DUT23RC(3)038)are much appreciated。
文摘Fatigue analysis of engine turbine blade is an essential issue.Due to various uncertainties during the manufacture and operation,the fatigue damage and life of turbine blade present randomness.In this study,the randomness of structural parameters,working condition and vibration environment are considered for fatigue life predication and reliability assessment.First,the lowcycle fatigue problem is modelled as stochastic static system with random parameters,while the high-cycle fatigue problem is considered as stochastic dynamic system under random excitations.Then,to deal with the two failure modes,the novel Direct Probability Integral Method(DPIM)is proposed,which is efficient and accurate for solving stochastic static and dynamic systems.The probability density functions of accumulated damage and fatigue life of turbine blade for low-cycle and high-cycle fatigue problems are achieved,respectively.Furthermore,the time–frequency hybrid method is advanced to enhance the computational efficiency for governing equation of system.Finally,the results of typical examples demonstrate high accuracy and efficiency of the proposed method by comparison with Monte Carlo simulation and other methods.It is indicated that the DPIM is a unified method for predication of random fatigue life for low-cycle and highcycle fatigue problems.The rotational speed,density,fatigue strength coefficient,and fatigue plasticity index have a high sensitivity to fatigue reliability of engine turbine blade.
