Fatigue Lifetime Prediction Research Articles

Semantic segmentation of defects based on DCNN and its application on fatigue lifetime prediction for SLM Ti-6Al-4V alloy.

Inevitable defects have an important impact on the fatigue lifetime of additive manufacturing materials. Therefore, it is critical to thoroughly characterize the characteristics of the defects, which requires effective semantic segmentation of the imaged defects. In this paper, a defect dataset for SLM Ti-6Al-4V alloy was obtained by synchrotron radiation computed tomography. Then a semantic segmentation method was developed based on the DeepLabV3 + network to automatically extract defects. Cropping and undersampling were introduced in the dataset pre-processing. A weighted scheme based on the ratio between the number of defect and matrix pixels was applied in the classification layer, and morphological operations were employed in image post-processing to improve the accuracy of identifying small-target defect. Finally, the above method was applied to segment the X-ray computed tomography data for two batches of SLM Ti-6Al-4V materials, and the defect segmentation results were used to predict the fatigue lifetime. The semantic segmentation method performs well with a pixel recognition accuracy of 98.2% for the test dataset, and the error in the predicted fatigue lifetime lies within the scatter band of ±2.2. This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 2)'.

Prediction of fatigue lifetime by the strain energy density for filled polychloroprene during thermo-oxidative ageing

During long-term environmental exposure, polychloroprene undergoes ageing. Throughout the process of thermo-oxidation, chemical degradation leads to crosslinking in the polychloroprene macromolecular network, inducing a significant change in mechanical properties. Among the various consequences of ageing on the properties, the reduction of fatigue lifetime is still poorly understood and needs more accurate prediction methods. This study presents a methodology to relate change in fatigue lifetime loss and network crosslinking during ageing. The material investigated is a carbon black-filled polychloroprene, subjected to more than 25 ageing conditions. Changes in network crosslink density, mechanical strain energy, and fatigue lifetime is experimentally measured. In the present study, a novel prediction strategy is proposed: it relies on the network strain energy density and convincingly describes fatigue loss. As the approach potentially extends to three-dimensional and/or multiaxial problems, it holds promise for addressing ageing-related issues in the analysis of elastomeric parts.

Durability Analysis of CFRP Adhesive Joints: A Study Based on Entropy Damage Modeling Using FEM.

Experimental methodologies for fatigue lifetime prediction are time-intensive and susceptible to environmental variables. Although the cohesive zone model is popular for predicting adhesive fatigue lifetime, entropy-based methods have also displayed potential. This study aims to (1) provide an understanding of the durability characteristics of carbon fiber-reinforced plastic (CFRP) adhesive joints by incorporating an entropy damage model within the context of the finite element method and (2) examine the effects of different adhesive layer thicknesses on single-lap shear models. As the thickness of the adhesive layer increases, damage variables initially increase and then decrease. These peak at 0.3 mm. This observation provides a crucial understanding of the stress behavior at the resin-CFRP interface and the fatigue mechanisms of the resin.

LCF Lifetime Reliability Prediction of Turbine Blisks Using Marine Predators Algorithm-Based Kriging Method

To achieve the low-cycle fatigue (LCF) lifetime prediction and reliability estimation of turbine blisks, a Marine Predators Algorithm (MPA)-based Kriging (MPA-Kriging) method is developed by introducing the MPA into the Kriging model. To obtain the optimum hyperparameters of the Kriging surrogate model, the developed MPA-Kriging method replaces the gradient descent method with MPA and improves the modeling accuracy of Kriging modeling and simulation precision in reliability analysis. With respect to the MPA-Kriging model, the Kriging model is structured by matching the relation between the LCF lifetime and the relevant parameters to implement the reliability-based LCF lifetime prediction of an aeroengine high-pressure turbine blisk by considering the effect of fluid–thermal–structural interaction. According to the forecast, when the allowable value of LCF lifetime is 2957 cycles, allowing for engineering experience, the turbine degree of reliability is 0.9979. Through the comparison of methods, the proposed MPA-Kriging method is demonstrated to have high precision and efficiency in modeling and simulation for LCF lifetime reliability prediction of turbine blisks, which, in addition to the turbine blisk, provides a promising method for reliability evaluation of complicated structures. The work done in this study aims to expand and refine mechanical reliability theory.

Low-cycle fatigue life assessment of SAC solder alloy through a FEM-data driven machine learning approach

Purpose This paper aims to present the novel stacked machine learning approach (SMLA) to estimate low-cycle fatigue (LCF) life of SAC305 solder across structural parts. Using the finite element simulation (FEM) and continuous damage mechanics (CDM) model, a fatigue life database is built. The stacked machine learning (ML) model's iterative optimization during training enables precise fatigue predictions (2.41% root mean square error [RMSE], R2 = 0.975) for diverse structural components. Outliers are found in regression analysis, indicating potential overestimation for thickness transition specimens with extended lifetimes and underestimation for open-hole specimens. Correlations between fatigue life, stress factors, nominal stress and temperature are unveiled, enriching comprehension of LCF, thus enhancing solder behavior predictions. Design/methodology/approach This paper introduces stacked ML as a novel approach for estimating LCF life of SAC305 solder in various structural parts. It builds a fatigue life database using FEM and CDM model. The stacked ML model iteratively optimizes its structure, yielding accurate fatigue predictions (2.41% RMSE, R2 = 0.975). Outliers are observed: overestimation for thickness transition specimens and underestimation for open-hole ones. Correlations between fatigue life, stress factors, nominal stress and temperature enhance predictions, deepening understanding of solder behavior. Findings The findings of this paper highlight the successful application of the SMLA in accurately estimating the LCF life of SAC305 solder across diverse structural components. The stacked ML model, trained iteratively, demonstrates its effectiveness by producing precise fatigue lifetime predictions with a RMSE of 2.41% and an “R2” value of 0.975. The study also identifies distinct outlier behaviors associated with different structural parts: overestimations for thickness transition specimens with extended fatigue lifetimes and underestimations for open-hole specimens. The research further establishes correlations between fatigue life, stress concentration factors, nominal stress and temperature, enriching the understanding of solder behavior prediction. Originality/value The authors confirm the originality of this paper.

Low cycle fatigue lifetime prediction of superplastic shape memory alloy structures: Application to endodontic instruments

In this paper we propose a methodology for a fast numerical determination of low cycle fatigue lifetime of superelastic shape memory alloy structures. This method is based on the observation that generally, in low cycle fatigue, shape memory alloy (SMA) structures are subject to loadings that lead to a confined non-linear behaviour at stress concentration points, such as notches. Numerical fatigue lifetime prediction requires the computation of the mechanical state at critical points. However, classical computational methods, like the non-linear finite element method, lead to a prohibitive computation time in a non-linear cyclic framework. To overcome this issue, we propose to use fast prediction methods, based on localization laws. Following the determination of the stabilized behaviour, an energetic fatigue criterion is applied. The numerical fatigue life prediction model is validated experimentally on SMA endodontic instruments.

Fatigue lifetime prediction model for leading edge protection coating systems of wind turbine blades

Rain erosion of wind turbine blades causes increased maintenance cost and shortened intervals. Lifetime prediction of coating systems is challenging because of complexities in determining liquid droplet impact pressures, resulting coating stress history and high strain rate fatigue parameters. The current work discusses a novel modeling method for characterizing single point and distributed impact fatigue lifetimes. The effects of changes in material, impact and geometric parameters on the predicted lifetimes were studied. Droplet diameter and coating layer thickness were found to play an important role in the lifetime of the system. Overlap of stress histories led to a difference between single point and distributed impact location lifetimes. The resulting model allows more elaborate analysis of LEP performance.

Mean stress correction and fatigue failure criteria for hyperelastic adhesive joints

ABSTRACT The work investigates failure criteria and mean stress correction approaches for the fatigue lifetime prediction of two hyperelastic adhesives (a polyurethane, PU, and a silicon-modified polymer, SMP). Fatigue experiments are carried under constant amplitude cyclic loading at RT and 40°C/60% r.h with butt- and the thick-adherend-shear-test-joints at three stress ratios R = −1, 0.1 and 0.5. Three mean stress correction approaches are evaluated: Goodman (static strength based), Schütz (mean stress sensitivity based) and Kujawski & Ellyin (parameter optimisation based). Fatigue failure criteria considered are: Drucker-Prager (linear-relation with the hydrostatic stress), Beltrami (quadratic relationship with the hydrostatic stress), and a multivariable nominal shear and tensile stresses criterion (data-based). The comparison is based on prediction accuracy (R-squared of master SN curves) and complexity of parameter determination. The highest values of R-squared were obtained by the Kujawski and Ellyin correction, followed by Schütz and then Goodman. However, the complexity of parameter determination follows an opposite trend with Goodman being the lightest approach. Failure criteria yielded comparable results with the multivariable criterion having the advantage of not dealing with FEA, but being limited to joints with nearly uniform stress distribution. Finally, compared to Drucker-Prager, the Beltrami criterion had a more robust parameter determination.

Optimization Design and Fatigue Lifetime Analysis for Elastic Wheel of Low-floor Trams Using in Urban Rail Transit

Elastic wheel is an important component of the low floor tram using in urban rail transit, so it is of significance to optimize its structure and predict its service lifetime. Firstly, the fatigue characteristics of rubber material are studied based on the crack energy theory, and a finite element model of an elastic wheel for fatigue lifetime prediction is constructed. The numerical simulation results show that the fatigue lifetime of such a elastic wheel does not match with the expected one. Secondly, based on the orthogonal numerical test and the Sobol model, an improved sensitivity analysis method is proposed. Taking the minimum strain as an optimization objective, and selecting the structural parameters determined by the sensitivity analysis method as the design variables, the second-order response surface model is established, and the multi-island genetic algorithm is used to carry out the single objective and multi-factor optimization design of the rubber bodies of elastic wheel under the condition of stiffness constraint. The simulation results of the elastic wheel show that the fatigue lifetime of the optimized structure is 30% higher than that of the original one. Finally, the optimized elastic wheel is tested, and the results show that the stiffness coefficient, and the fatigue lifetime as well, are all satisfy with the design requirements.

Data-Driven, Physics-Based, or Both: Fatigue Prediction of Structural Adhesive Joints by Artificial Intelligence

Here, a comparative investigation of data-driven, physics-based, and hybrid models for the fatigue lifetime prediction of structural adhesive joints in terms of complexity of implementation, sensitivity to data size, and prediction accuracy is presented. Four data-driven models (DDM) are constructed using extremely randomized trees (ERT), eXtreme gradient boosting (XGB), LightGBM (LGBM) and histogram-based gradient boosting (HGB). The physics-based model (PBM) relies on the Findley’s critical plane approach. Two hybrid models (HM) were developed by combining data-driven and physics-based approaches obtained from invariant stresses (HM-I) and Findley’s stress (HM-F). A fatigue dataset of 979 data points of four structural adhesives is employed. To assess the sensitivity to data size, the dataset is split into three train/test ratios, namely 70%/30%, 50%/50%, and 30%/70%. Results revealed that DDMs are more accurate, but more sensitive to dataset size compared to the PBM. Among different regressors, the LGBM presented the best performance in terms of accuracy and generalization power. HMs increased the accuracy of predictions, whilst reducing the sensitivity to data size. The HM-I demonstrated that datasets from different sources can be utilized to improve predictions (especially with small datasets). Finally, the HM-I showed the highest accuracy with an improved sensitivity to data size.

Towards minimal empirical uncertainty bounds of damping estimates of an offshore wind turbine in idling conditions

Structural damping is a critical quantity for condition assessment and fatigue lifetime prediction in wind energy. Its estimation from operational vibration data comes with a considerable amount of uncertainty, derived from environmental and operational variability and from the quality of the estimation process itself. In this paper, we aim to determine experimentally the damping values and their least possible uncertainty bounds for the first two modes of an idling offshore wind turbine. For this purpose, we use field measurements from a 3.6 MW offshore wind turbine located at the DanTysk wind farm. We select a subset of cases from the wind turbine on idling conditions for a confined interval of environmental and operational conditions, in an attempt to minimize operational variability in the damping estimates. In addition, we make a study on the adjustment parameters of the automated operational modal analysis method, aiming at obtaining the most consistent damping estimates. As a result of the proposed methodology, it is possible to confine the 90% confidence intervals of the damping ratio estimates of the first two tower modes within 0.8 and 1.1 percentual points in the fore-aft and the side-to-side direction, respectively.

Ratchetting-fatigue behavior of a 42CrMo steel under near-yield mean stress

42CrMo high-strength structural steel is widely used to manufacture the bolt fasteners of engineering machinery, which are subjected to cyclic loading with a near-yield pre-stress in service. In this contribution, we focused on the intrinsic correlation between macroscopic ratchetting-fatigue behavior and microscopic mechanisms in a quenching & tempering 42CrMo HSS steel under near-yield mean stress (σm) conditions. The results indicate that fatigue strength obviously decreases as σm increases from low level (51.9% of yield strength, σy) to near-yield range (80–95% of σy), which is followed by a slight decrease with σm increasing in near-yield σm range. Two distinct fracture patterns were found: (i) high-cycle fatigue failure under low σm and (ii) ratchetting-fatigue failure with plastic strain due to obvious ratchetting effect under near-yield σm. Compared to low σm, near-yield σm leads to the disappearance of fatigue striations, but emerging of some plastic micro-strains, sub-grains and high-density dislocation cells. Fatigue crack-path analysis demonstrates that the decreases in secondary crack size and crack deflection degree are favorable to fatigue crack propagation at a higher rate. Furthermore, fatigue crack tends to propagate along the high Schmid factor regions with the specific slip system of {110}<111> under near-yield σm, corresponding to quicken fatigue cracking behavior. However, it did not occur under low σm. Therefore, it can be concluded that near-yield σm and the resulting ratchetting effect play significant roles in fatigue cracking behavior of 42CrMo steel, which should be carefully taken into account for predicting fatigue lifetime of actual bolt fasteners.

Low cycle fatigue lifetime and deformation behaviour prediction of nickel-based single crystal superalloy considering thickness debit effect

Through stress-controlled low cycle fatigue (LCF) experiments, LCF performances for thickness debit effect of nickel-based single crystal superalloy DD6 with [001] orientation are investigated. Based on scanning electron microscope (SEM) observation, the formation mechanism of thickness debit effect and the damage mechanism under LCF loads are revealed. Then, considering the thickness debit effect of nickel-based single crystal superalloy DD6, an improved slip-based damage model is developed. Predicted LCF lifetimes are mainly within a scatter band of factor 2, and the predicted laws between LCF lifetimes and wall-thicknesses are in good agreement with the experimental data, which verifies the rationality and accuracy of the thickness-sensitive LCF damage model established in this paper. Furthermore, a damage-coupled crystallographic constitutive model reflecting thickness debit effect is developed. For DD6 specimens with different wall-thicknesses, the predicted results of the stress-controlled LCF deformation behaviours including the whole-lifetime ratcheting behaviours show good agreement with the experimental data.

Modelling of Synthetic Fibre Rope Mooring for Floating Offshore Wind Turbines

Fibre ropes offer beneficial properties for mooring of floating offshore wind turbines (FOWTs). However, the mooring line’s stiffness is both load-history and load-rate dependent. A quasi-static stiffness is observed for slow loading, with a higher stiffness related to rapid, cyclic loading (dynamic stiffness). Design standards provide different guidelines for how to combine these in the mooring analysis. This paper describes procedures for adapting laboratory test stiffness results to the Syrope and a bi-linear model and investigates the consequence of using the models for load calculations. The Syrope model accounts for the quasi-static and permanent rope elongation, while performing the analyses with the dynamic stiffness. The bi-linear model applies both the quasi-static and dynamic stiffness in the dynamic analyses. Based on fibre rope tests performed by Bridon-Bekaert, a Syrope model and two bi-linear models are adapted to the same fibre rope. Fatigue damage and ultimate loads on the mooring lines of Saitec’s SATH FOWT are calculated. The bi-linear model artificially reduces the tension ranges, particularly if there is a large difference between the quasi-static and dynamic stiffness of the fibre rope. This leads to a longer predicted fatigue lifetime. Differences in the extreme loads are caused by the permanent elongation of the Syrope model. This may be countered if the elongation is known and included in the bi-linear model. Finally, the bi-linear model introduces an amplitude-dependency in the horizontal natural periods.

Prediction of the fatigue life of notched specimens: The influence of the surface quality produced by machining

The article introduces a method for fatigue lifetime predictions of notched specimens. The method uses fracture stresses of smooth and notched specimens with notch radius r = 0.2 mm. These two sets of experimental data are evaluated with the knowledge of axial stress distributions of the notched specimens using average stress over a length parameter l. This parameter l is considered to be a material characteristic (depending on the number of cycles to failure) and can be used for lifetime predictions of notched specimens with various notch radii. The predictions are compared to experimental data and analyzed. There is a strong influence of the process of machining of notches, which can lead to fatigue failure earlier than predicted. The data are evaluated in the area of high cycle fatigue and gigacycle fatigue.

Fatigue life enhancement mechanism and lifetime prediction of AA6061-T6 open-holed sheet treated by electromagnetic driving dynamic cold expansion

In this study, mechanisms of fatigue life enhancements of electromagnetic driving dynamic cold expansion (DCE) open holed sheets were investigated by testing fatigue life and obtaining residual stress fields experimentally and numerically. Furthermore, a fatigue life prediction method based on three-dimensional stress distributions was proposed. Results showed that DCE method extended higher fatigue life and produced more uniform residual stress along hole axial direction than static cold expansion (SCE) method. The differences in stress distribution led to different fatigue crack initiation and propagation modes of DCE and SCE specimens. Moreover, the predicted fatigue life results were in accordance with experimental data. • Dynamic cold expansion extended larger fatigue life for holed-sheets. • More uniform residual stress was induced by dynamic cold expansion. • Fatigue cracks propagated horizontally in dynamic cold expanded specimens. • Proposed method to predict fatigue life had good agreement with experiments.

Atomistic measurement and modeling of intrinsic fracture toughness of two-dimensional materials

Quantifying the intrinsic mechanical properties of two-dimensional (2D) materials is essential to predict the long-term reliability of materials and systems in emerging applications ranging from energy to health to next-generation sensors and electronics. Currently, measurements of fracture toughness and identification of associated atomistic mechanisms remain challenging. Herein, we report an integrated experimental-computational framework in which in-situ high-resolution transmission electron microscopy (HRTEM) measurements of the intrinsic fracture energy of monolayer MoS2 and MoSe2 are in good agreement with atomistic model predictions based on an accurately parameterized interatomic potential. Changes in crystalline structures at the crack tip and crack edges, as observed in in-situ HRTEM crack extension tests, are properly predicted. Such a good agreement is the result of including large deformation pathways and phase transitions in the parameterization of the inter-atomic potential. The established framework emerges as a robust approach to determine the predictive capabilities of molecular dynamics models employed in the screening of 2D materials, in the spirit of the materials genome initiative. Moreover, it enables device-level predictions with superior accuracy (e.g., fatigue lifetime predictions of electro- and opto-electronic nanodevices).

The in‐service fatigue fracture mechanisms for the I‐stage low‐pressure compressor disk of the aircraft engine D30KU‐154

AbstractThis paper contains the in‐service fatigue fracture analysis for the first stage low‐pressure compressor disk of the aircraft engines D30KU‐154. Based on the results of the fractographic investigation on collapsed compressor disks the fatigue crack initiation and propagation principles were established. It is shown that the crack initiation in the rim part of the compressor disk is due to a high frequency loading that leads to very high cycle fatigue fracture. The total fatigue lifetime of the compressor disk is determined by simultaneous action of low amplitude loading due to blades vibration, and high amplitude loading due to flight cycle (centrifugal forces). Study of in‐service fracture of the compressor disk was based on the evaluation of numerical simulations of the stress state in the damaged zone under corresponding loading conditions. The estimation of fatigue lifetime and crack path predictions were performed based on the multiregime fatigue fracture model developed by the authors.

Low cycle fatigue properties of refractory high-entropy HfNbTiZr alloy

Considerable effort has been applied toward developing refractory high-entropy alloys (RHEAs) with both high strength and good ductility. However, the deformation and fatigue failure mechanisms of these alloys under cyclic loading remain poorly understood. The present work addresses this issue by investigating the low-cycle deformation behavior and microstructural evolution of an HfNbTiZr RHEA with a nominal composition of 25 mol% each of Hf, Nb, and Ti, and Zr forming the balance under symmetric tension-compression conditions at room temperature. Analysis of the cyclic stress responses of the alloy reveals a variety of internal stress trends at different strain amplitudes (Δεa), which implies the operations of a variety of cyclic deformation mechanisms. Further analysis demonstrates that cyclic softening is mainly caused by a rapid decrease in frictional stress during the initial cycles representing roughly 10% of the total number of cycles to failure. In general, the microstructural characteristics of the alloy observed with an increasing number of cycles under various values of Δεa demonstrate that softening occurs due to the formation of slip bands (SBs) caused by high-density dislocations arising in conjunction with increasing plastic strain accumulation. Specifically, dislocation structures forming at a low value of Δεa = 0.8% mainly consist of planar SBs (PSBs), while low-density cross SBs (CSBs) form at Δεa = 1.1%, and the density of the CSBs increases with further increasing Δεa. In addition, a fatigue lifetime prediction model was presented that obtained good prediction accuracy for the HfNbTiZr RHEA investigated herein. Accordingly, the present study can be expected to provide a fundamental basis for understanding the deformation mechanisms of other RHEAs.

Effect of severe thermo-oxidative aging on the mechanical behavior and fatigue durability of short glass fiber reinforced PA6/6.6

The work deals with the fatigue lifetime estimation of Short Fiber Reinforced Thermoplastics (SFRP), with a focus on conjugated effects of thermal aging. Two materials containing 35% (V35) and 50% (V50) weight ratio of short glass fibers were aged for 500 h at 200°C in air and compared to the same materials in a Dry-As-Molded (DAM) state. Monotonic and fatigue tests were performed in samples machined out of injected plates and cut along three different orientations to the injection one (0°, 45°, 90°) in order to capture the anisotropy of the skin-core microstructure, classical in injected SFRP.Monotonic tensile tests evidenced the stiffening and embrittlement of the Polyamide matrix reported in the literature, nevertheless with an acuity depending on the matrix ratio and fiber orientation. Stress-controlled fatigue tests were performed at constant amplitude, frequency (10 Hz), temperature (200°C) and stress ratio R = 0.1. The fatigue curves of V35 are more affected by aging than those of the V50 material. The combined results from the mean strain evolutions and SEM observations confirmed that the initiation approach for fatigue lifetime estimation was still valid in aged composites. Several fatigue criteria, among the most recently reported in the literature, were evaluated from this database. The effect of aging on the cyclic evolution of the different Fatigue Indicator Parameters (FIP) involved in the criteria was analyzed preliminarily. For the present fatigue conditions, the best criteria for unaged materials (i.e cyclic creep energy-based ones) were shown to still be the best for aged materials. Finally, the ability to predict fatigue lifetime for aged composites from the identification of the fatigue criterion in the unaged state was evaluated.