Life Prediction Model Research Articles

An optimized multiaxial fatigue life prediction model based on the subcritical plane method

Since a more rigorous requirement is raised for the performance of aero-engine increases, the multiaxial fatigue problem of its components turns out to be increasingly severe. In this study, a multiaxial fatigue life prediction model is developed by using the subcritical plane method, where the effect of non-proportional additional hardening under non-proportional loading is considered by both the deflection angle of the subcritical plane and the combined parameters of strain on the subcritical plane. Moreover, the cyclic strain hardening index in the traditional model is substituted with an additional strengthening material coefficient that is characterized by the static strength of the material, which reduces the difficulty in calibrating the parameters of the multiaxial life model. The effectiveness of the proposed model is validated by comparing the predicted fatigue life with some fatigue test data, and the errors between the predicted and the testing data fall into a factor of two error bands. In general, the proposed multiaxial life prediction model simplifies the calibration of model parameters, and the prediction accuracy is still ensured, which promotes the model to facilitate engineering application.

Entropy‐based method considering nonlinear hardening effect to predict the crack propagation life of superalloy GH4169 at elevated temperature

AbstractThis paper aims to determine the relationship between thermodynamic entropy generation and fatigue crack propagation life of superalloy GH4169 at 300–650°C. The entire specimen was considered as the thermodynamic system. The plastic energy dissipation in the crack tip was obtained by finite element simulation utilizing the Chaboche nonlinear hardening model. Then the cyclic entropy generation rate (CEGR) and the accumulated entropy generation are calculated by combining simulation and experimental methods. Results show that the CEGR is a power function of the stress intensity factor range, and it is almost a constant at fatigue failure. The fatigue fracture entropy (FFE) increases as fatigue cycles at failure increase at constant temperature, but it first decreases and then increases when temperature increases from 300 to 650°C. A fatigue life prediction model based on the thermodynamic damage parameter is established and verified by comparison with experimental results and available data in the literature.

A semi-empirical life-prediction model for multiaxial ratchetting-fatigue interaction of SUS301L stainless steel tubular welded joint

Based on the strain measured in the SUS301L stainless steel tubular welded joint in the asymmetrically stress-controlled multiaxial low-cycle fatigue tests by using the digital image correlation (DIC) method, the dependence of fatigue life on the loading level and loading path is well explained by discussing the multiaxial ratchetting-fatigue interaction in the fatigue failure zone of welded joint. To reflect the contribution of mean stress to the non-proportionality of loading path, a new non-proportionality factor is defined. And then the path-dependent damage parameters of pure fatigue damage and additional ratchetting one are proposed in a strain form and validated. Finally, a multiaxial life-prediction model is constructed through addressing the concurrent efforts of additional ratchetting damage and pure fatigue one to predict the multiaxial fatigue life of welded joint. The results demonstrate that the predicted multiaxial fatigue lives are well expected and all life data fall in the twice error bands regarding to the experimental ones.

Research on lifetime prediction method of FBGs with different reflectance based on thermal decay characterization

Based on the distinct thermal decay traits of high-reflectance FBGs (Reflectance = 98%) and low-reflectance FBGs (Reflectance = 10%), it's proposed that different grating strength characterizations be applied to predict their lifespan. Using isothermal and isochronous annealing methods to track high-temperature strength decay, we establish a master aging curve. This informs a temperature-specific time-dependent life prediction model for FBG strength. Experiments and simulations reveal that over 876,000 h at 37 °C, reflectance reduction was 1.07% for high-reflectance FBGs and 1.896% for low-reflectance FBGs, with NICC decreases of 0.0564 and 0.0995, respectively. Adopting NICC and reflectance as respective indicators for high-reflectance and low-reflectance FBGs refines the detection of minor intensity declines.

Fatigue Behaviour and Life Prediction of YSZ Thermal Barrier Coatings at Elevated Temperature under Cyclic Loads

The concentration of interfacial normal stress at the free edges of thermal barrier coatings (TBCs) can result in coating spallation. Fatigue cracking is one of the main reasons for creating free edges under complex loads. It is crucial to investigate the fatigue cracking of coatings under cyclic loads to assess potential coating failure. To address this issue, a novel model was proposed to predict the fatigue life of the YSZ topcoat under stress parallel to the interface. Firstly, this study conducted uniaxial and tensile-torsional fatigue tests at elevated temperatures on specimens with atmospheric plasma-sprayed TBCs. The test results revealed that fatigue cracks appeared in the topcoat under cyclic loads, but these cracks did not propagate into the bondcoat or substrate immediately. The number of cycles before the topcoat cracked was found to be associated with the magnitude of the cyclic load. Secondly, this study analyzed the test conditions using the finite element method. Simulations indicated that the crack direction in the topcoat under complex loading conditions was aligned with the first principal stress direction. Finally, the fatigue life prediction model of the topcoat was established based on experiments and simulations. The predicted results fell within a fourfold scatter band.

Wear prediction study considering TBM hob slip

Aiming at the problem of serious tool wear and untimely tool change affecting the construction efficiency when TBM is digging in microfractured tuff strata, the hob wear prediction study is carried out based on engineering examples. By analysing the rock-breaking mechanism of hob wear, a linear wear rate model and a life prediction model considering hob slip are derived based on the CSM model and the abrasive wear theory; the wear rate and the wear amount at the tool change point are further calculated by the prediction model in comparison with the measured value, and the furthest digging distance of the hob is calculated by the life prediction model. The results show that: the relative error between the measured average wear rate and the calculated linear wear rate considering the hob slip is 5.3%; the life prediction model predicts that the longest digging distance of the positive hob is 857 rings and the shortest distance is 198 rings. The results of the study are of guiding significance for the prediction of tool wear and the selection of the timing of opening and changing the hob in TBM tunneling.

Prediction of fatigue life of laminated composites by integrating artificial neural network model and non-dominated sorting genetic algorithm

The present study introduces an artificial neural network (ANN) model coupled with the non-dominated sorting genetic algorithm (NSGA-II) to establish an advanced model for fatigue life prediction of laminated composites. The developed model was trained on a comprehensive collection of dependent experimental data of carbon/epoxy composites. This training encompassed 14 distinct cases, covering various stress concentration geometries, loading levels, and stacking sequences to ensure the model’s robustness and generality. A data augmentation technique was employed to generate similar data to enrich the datasets. The best-obtained accuracy from the model, as measured by the coefficient of determination (R2 score), was 88% and 90% for the test and validation datasets, respectively. While using the data augmentation method, these values improved to 97% and 98%, respectively. The results from the model were compared to those of more conventional regression machine learning algorithms, such as decision trees and gradient boosting. To emphasize the superior predictive accuracy of the developed model, it is essential to note that the best R2 score obtained for the test and validation datasets was 68% using conventional models.

Optimization design and performance improvement of ther-mal barrier coating (TBC) system

Thermal Barrier Coatings (TBC) technology has become one of the key technologies to improve the performance and prolong the service life of gas turbine and other high temperature equipment. In this study, the selection of materials, coating methods, the influence of environmental factors on the performance of TBC system and the thermal stress analysis and optimization strategy are discussed, improve the overall performance and stability of TBC system. TBC coatings were efficiently prepared by the use of Nikolay bonding layer and stabilized zirconia as top ceramic materials, combined with electron beam Physical vapor deposition (EB-PVD) and plasma spraying (APS) techniques. In addition, the thermal stress model was established by FEA, and the thermal stress distribution of TBC system under extreme operating conditions was analyzed in detail, to reduce thermal stress concentration and improve the thermal barrier effect of the coating. Finally, through the establishment of TBC system life prediction model and in-depth analysis of the failure mechanism, a series of preventive measures and performance improvement strategies are proposed, it provides theoretical basis and practical guidance for coating design of gas turbine and other high temperature equipment.

Gear contact fatigue prediction under mixed elastohydrodynamic lubrication with ellipsoidal asperity rough surface: Experimental and numerical investigation

A three-dimensional(3D) line-contact mixed lubrication model and contact fatigue life prediction model for gears are established, considering the elastoplastic contact of ellipsoidal asperities and their interactions. The localized lubrication states across the actual 3D rough surfaces are visually depicted. The direct asperity contact pressures calculation exhibits greater accuracy and universality. The proposed mixed lubrication model can be applied accurately and efficiently to heavy-load conditions. The synergistic mechanisms of multi-scale surface integrity parameters, such as surface morphology-lubrication coupling, hardness gradient, and residual stress, on gear contact fatigue has been revealed. The results reveal that surface roughness significantly affects the competitive failure mechanism between surface-initiated micropitting and subsurface-initiated macropitting. The increase in surface compressive residual stress is more sensitive to the enhancement of near-surface and subsurface fatigue lives, compared to the increase of peak residual stress and the depth of peak residual stress. The proposed physics-based gear contact fatigue life prediction model has been validated through gear contact fatigue experiments under various operating conditions. The maximum deviation between the predicted and experimental fatigue lives is within 10%. This paper presents theoretical methodologies and data-driven support for optimizing the design and manufacturing processes of gears, specifically focusing on enhancing anti-fatigue properties.

Investigating the relationship between natural frequency and residual strength and stiffness of cross‐ply laminate under cyclic loading

AbstractPredicting the fatigue life of wind turbine rotor blades is a challenging and crucial engineering task. This study investigates the correlation between modal parameters and the degradation of residual strength and tensile modulus in the cross‐ply glass epoxy laminate [0/90]7 used in wind turbine blades under fatigue loading. The tensile and vibration characteristics were assessed, followed by constant amplitude fatigue tests at 35%, 43% and 55% of the ultimate tensile strength, with R = 0.1 and a frequency of 8 Hz. The modal analysis was performed on the cycled specimens at life fractions from 0.05 to 0.70 and residual modulus and strength were obtained. The results establish a well‐defined correlation between these residual mechanical properties and the natural frequency. Normalized residual strength, tensile modulus and natural frequency demonstrated similar behaviors during the fatigue life. An initial rapid decrease in the first tenth of the life fraction was observed, followed by minimal changes up to a life fraction of 0.7. The strong correlation between the first mode natural frequency and both the residual strength and the tensile E‐modulus provides a promising basis for developing accurate fatigue life prediction models for fiber‐reinforced composite structures. © 2024 Society of Chemical Industry.

Capacity fading knee-point recognition method and life prediction for lithium-ion batteries using segmented capacity degradation model

Aiming at the problem that the cycle life of the battery is hard to be accurately estimated, a segmented capacity degradation model is established based on the trend of capacity degradation rate. By applying a genetic algorithm (GA) to optimize the model parameters, GA-Weibull and GA-SVR (support vector regression) degradation models and their corresponding segmented models are established, and the battery life is calculated. Furthermore, a method taking the RMSE as the target is put forward to calculate the knee-point of capacity degradation. Finally, the life is predicted by segmented models. The results show that compared with unsegmented models, describing the process of capacity degradation by segmented models reduces the error notably, makes the determination coefficient closer to 1, and improves the model accuracy effectively. Later, the proposed method makes the fitting error of the segmented model smaller than that of Bacon-Watts method, thus obtaining a more accurate knee-point. In addition, it is found that there exists linear relationship between the estimated knee-point and the battery life. Finally, the prediction results based on segmented model show that the prediction accuracy of segmented GA-SVR model is higher, and the MAPE is only 4.32%. The relevant results can provide some guidance for the reliability evaluation and product quality management of lithium-ion batteries, which is conducive to establishing more accurate models for battery life prediction.

Low-cycle fatigue behavior of coated and uncoated single crystal Ni-based superalloy at various temperatures

Within this work, the effect of different oxidation-resistant coatings on the low-cycle fatigue (LCF) behavior and damage mechanisms of third-generation single crystal (SC) Ni-based superalloy was investigated. Stress-controlled LCF tests of bare alloy, MCrAlY-coated and PtAl-coated thin-walled specimens were carried out at 760 °C, 850 °C and 980 °C. A unique clamping system was meticulously designed to overcome the clamping challenge in high-temperature furnaces. The cracking behaviors and failure modes were determined by advanced microstructure characterization. The results show that the coatings are detrimental to the LCF lifetime of thin-walled specimens, especially at low-medium temperatures of 760 °C and 850 °C. For bare alloy, the tip cracks nucleate from the surface oxide layer, whereas cracks in the coating-substrate system nucleate prematurely from the coating surface and propagate to the substrate. The oxygen diffusion and the frontward propagation of cracks are synergistically enhanced in the SC substrate, resulting in oxidation-assisted crack propagation and ultimate failure. Finally, A fatigue life prediction model is proposed by introducing coating-induced crack initiation and oxidation effects, where the predictive results fit well with experimental results. This study provides a comprehensive insight into the damage mechanisms and coating-induced LCF life degradation of the coating-substrate system.

Experimental study on creep-fatigue damage of hot central plant recycling asphalt mixture containing high RAP

The objective of this study is to delve into the nonlinear damage evolution mechanism of hot central plant recycling asphalt mixture under the influence of creep-fatigue interaction. A predictive model for lifespan, considering the interaction of temperature and load, was developed. Dynamic creep tests were conducted at different temperatures to assess the creep effect of the asphalt mixture under actual road temperature conditions. The investigation began by acknowledging the material's viscoelastic properties, thereby deriving the loss compliance value - a key indicator of temperature effects - using an equivalent conversion factor and a viscoelastic mechanics model. This allowed for the incorporation of creep behavior into the load system. Furthermore, to analyze the nonlinear damage mechanism and fatigue prediction mechanism, direct tensile fatigue tests were performed at different temperatures and different stress levels. The fatigue damage evolution law of hot central plant recycling asphalt mixture containing high RAP considering the creep effect was revealed, and the fatigue life evaluation method under the combined action of temperature and stress level was proposed. The results show that the fitting degree of the time-temperature conversion equation and the viscoelastic mechanics model to the test data is more than 0.9, and the derived loss compliance value better captures the creep effect. Based on the nonlinear creep-fatigue damage model, the damage law of high-RAP hot central plant recycling asphalt mixture was identified. The optimized fatigue life prediction model fully considers the combined effect of temperature and stress level and analyzes the influence parameters of the real state of pavement fatigue. The prediction accuracy is within the requirements of engineering applications. The model's predictive accuracy meets the criteria for engineering applications, enhancing the multifaceted damage coupling analysis approach for hot central plant recycling asphalt mixture and predict the service life of recycled pavements under complex conditions, establishing a groundwork for the prediction and assessment of long-lasting recycled pavements.

Fatigue Assessment of Inclined Film Cooling Holes in Nickel-Based Single-Crystal Superalloy

Fatigue tests of nickel-based single-crystal superalloys with inclined film cooling holes (FCHs) at 1000°C were conducted to investigate the effects of crystal orientation and to quantify the fatigue performance of the high-temperature structures. Fractographic analysis and computations of stress concentrations revealed competitive failure mechanisms between mode I crack nucleation and fatigue crack growth in crystallographic plastic slip systems, whereas crack nucleation around inclined FCHs can be characterized by the known fatigue criteria derived for smooth specimens. A life prediction model based on the crystal slip mechanism and the theory of critical distance was introduced to predict the fatigue life of FCH structures and provided reasonable accuracy for different FCH specimens.

Fretting fatigue in dovetail assembly and bridge-flat model: Verification of a life prediction model based on stress gradient

The dovetail assembly and the bridge-flat model are two typical fretting fatigue tests. This article concentrates on the fretting fatigue of the dovetail assembly, utilizing a sub-scaled specimen tested under cyclic loading. Simultaneously, fretting tests on the bridge-flat and combined high and low cycle fatigue tests on the dovetail assembly were conducted. These tests were analyzed in conjunction with the dovetail assembly to understand the stress state characteristics in the contact region. The results from both tests and finite element analysis highlight that fretting leads to a significant reduction in fatigue life, primarily attributed to stress concentration at the edges of the contact area. Building upon the method of stress gradient correction, a life prediction model for fretting fatigue is proposed, demonstrating good accuracy in predicting fretting fatigue life.

Experimental investigation on surface integrity and fatigue performance of Ti60 alloy under ultrasonic impact treatment

The surface integrity and fatigue properties of Ti60 alloy under different ultrasonic impact processes were investigated. Ultrasonic impact treatment (UIT) with various parameters enhanced the surface integrity of the turned specimen. The Ra values of the UIT specimens were all less than 0.380 μm, with the surface stress concentration factor (Kst) values ranging from 1.075 to 1.120. The compressive residual stress values of the UIT specimens were enhanced, leading to the localization of the maximum residual stress (σrsm) in the subsurface. Increases in surface residual stress (σs) values exceeded 21.9 % and σrsm values were improved by more than 74.4 % compared to the turned specimen. The microhardness values showed improvement after UIT, with surface microhardness (HVs) values ranging from 408.5 HV0.025 to 461.6 HV0.025. The orientation of the grains was deflected in UIT specimens, and the depths of the plastic deformation layer (hp) values experienced increases of more than 17 times. The fatigue life (Nf) value of the Comb. U2 with the best surface integrity was approximately 9328.4 % higher than that of turned and about 4362.1 % higher than that of Comb. U1 with the worst surface integrity among the UIT specimens. Observing the fatigue fractures, the crack initiation locations of the UIT specimens were relocated to the subsurface at a distance of more than 150 μm from the surface. A higher fatigue life of the specimen was achieved when there was better surface integrity and when the fatigue crack source was located further away from the surface. The crack source in the UIT specimen exhibited a large and irregular shape, and there were numerous small, evenly distributed dimples and a limited number of cleavage planes in fatigue instantaneous fracture region. Additionally, it was found that the subsurface fatigue life prediction model demonstrates superior accuracy for shorter fatigue life.

Creep-fatigue interaction of soft adhesive under shear loading: Damage diagram and life prediction model

Soft adhesives used in cutting-edge technological fields are susceptible to shear fatigue failure under complex in-plane loadings. Although the interaction or coupling effect between creep and fatigue damage have been studied, the effect of the equivalent creep damage during typical fatigue loading on the fatigue life of soft adhesives, as well as the interaction between the equivalent creep damage and fatigue damage of soft adhesives have never been characterized. This study systematically investigates the creep-fatigue interaction of the soft adhesive under various loading conditions. It was found that significant equivalent creep damage occurs and accumulates under typical cyclic loading, which seriously accelerates the shear fatigue failure of soft adhesives. Furthermore, the contribution of the equivalent creep damage to the final shear fatigue failure is even more pronounced than the fatigue damage. The quantitative construction of creep-fatigue damage diagrams has led to the determination of strong creep-fatigue interaction, which could be understood by the interactive mechanism between the stretching, friction, pulling-out, and rupture of molecular chains. In light of the distinctive creep-fatigue interaction mechanism, a modified Chaboche damage model has been developed, which could accurately predict the shear fatigue life of soft adhesives under a wide range of loading conditions.

Probabilistic fatigue life prediction of notched specimens based on modified stress field intensity method under multiaxial loading

In practical engineering components, due to the existence of non-uniform stress and strain field near the notch, it brings severe challenges to fatigue life prediction when evaluating the integrity of notched components. In this study, a probabilistic fatigue life prediction model for notched specimens was established by coupling the stress field intensity (SFI) method and Weibull distribution. Firstly, the position of the dangerous point is determined by finite element calculation, and the maximum strain energy density plane through the dangerous point is defined as the critical plane. Secondly, from the perspective of 2D features, the traditional SFI method is modified based on the stress distribution on the critical plane, and a new concept of effective stress is proposed to predict the fatigue life of notched specimens by the experimental data of smooth specimens. Finally, a new non-proportional additional hardening factor is established to characterize the influence of material properties and loading path on fatigue life. The experimental data of Q345 low alloy steel and GH4169 nickel base alloy are used to compare and analyze the proposed model. The results show that the predicted life of the proposed model is in good agreement with the experimental life.

Experimental and numerical investigations on fretting fatigue in a bridge‐flat component using a stress life prediction model

AbstractThe study investigated the fretting fatigue behavior of a bridge‐flat component, utilizing a flat specimen with two bridge‐type pads tested under cyclic loading. Numerical simulations were also carried out using the finite element method. Firstly, precise calculations of contact stress were performed with the material's elastoplastic model. Secondly, the stress distribution on the maximum stress cross‐section was extracted, and the stress gradient was computed. Finally, a stress fatigue life prediction model considering the stress gradient was proposed, and the predicted life was compared with the test life. The results of the study revealed that the specimens exhibited high stress gradients at the edges of the contact region during the bridge‐flat tests. In comparison with plain fatigue, fretting fatigue life was significantly reduced. The life prediction model proposed in this paper demonstrated good accuracy for predicting fretting fatigue.

Remaining useful life prediction method of rolling bearings based on improved 3σ and DBO-HKELM

Abstract An improved 3σ method and dung beetle algorithm optimization hybrid kernel extreme learning machine-based (DBO-HKELM) approach for predicting the remaining useful life (RUL) of rolling bearings was suggested in order to increase prediction accuracy. Firstly, multi-dimensional degradation feature data is extracted from bearing vibration data. Considering the influence of noise signal on the prediction accuracy, an improved kernel principal component analysis method is proposed to reduce the noise of degraded features. Then, an improved 3σ method is proposed to determine the starting point of bearing degradation by combining bearing vibration signal data. Lastly, a DBO-HKELM life prediction model was put forth. The parameters of hybrid kernel extreme learning machine were optimized by dung beetle algorithm, and appropriate kernel parameters and regularization coefficient were selected. The feature set of degradation indicators is input into the trained model to output the bearing RUL prediction results starting from the determined degradation starting point. Multiple data sets were used to verify that the new RUL prediction method significantly improves the prediction accuracy.