Fatigue Indicator Parameters Research Articles

Vibration fatigue of film cooling hole structure of Ni-based single crystal turbine blade: Failure behavior and life prediction

The vibration fatigue failure behavior and fatigue life of the film cooling hole (FCH) structure of Ni-based single crystal superalloy were investigated at high temperature. The vibration fatigue test of the FCH specimens were carried out based on the paired staircase method. The cracks are mostly initiated in the stress concentration area at the edge of the FCH, and may also be initiated in non-stress concentrated areas with large defects. At high temperature, the crack initiation mechanism of the FCH specimens of Ni-based single crystal superalloy is oxidative cracking nucleation in stress concentration area, and the crack propagation mechanism is the competition mechanism of dislocation slip and dislocation climbing. Based on the Fatigue Indicator Parameter (FIP) of the critical plane method, a vibration fatigue life prediction model for FCH structures considering stress concentration and high temperature oxidation damage is proposed. The life prediction model proposed in this paper is applied to the vibration fatigue life prediction of FCH specimens. The deviation between the predicted results and the experimental results is within 2.5 times at 850℃, and the deviation is within 2 times at 980℃. Besides, the life prediction method proposed is compared with other two FIP life prediction methods, and the high accuracy and effectiveness of the proposed life prediction method are verified.

Effect of texture on the fatigue crack initiation of a Dual-Phase Titanium alloy

Fatigue indicator parameters (FIPs) can serve as a measure of fatigue crack initiation (FCI) in metals and alloys. FIPs are volume averaged over grains, bands, and sub bands in crystal plasticity (CP) simulation to investigate the influence of texture on FCI under low cycle fatigue. The equiaxed microstructure of Ti–6Al–4V was generated with three different textures: basal, basal/transverse and transverse. FIPs analysis shows that basal texture has the highest FCI resistance, basal/transverse texture has intermediate resistance, and transverse texture has the lowest resistance when tested along plate direction. All textures exhibit a lower FIP when deformed along rolling direction (RD) than that along transverse direction (TD). The interior of the alloys has a larger FCI resistance than the free surface. Further analysis shows a strong relationship between FIP distribution features and damage nucleation characteristics, with basal texture exhibiting the lowest and wider FIP distributions as a result of high resistance to damage and fatigue cracking; in contrast, the transverse texture exhibits intense and narrow FIP and damage nucleation along the grain boundaries (GBs), basal/transverse texture exhibits FIP and damage nucleation with mixed characteristics. The results can be used as a theatrical reference for the fatigue performance design of Ti alloy.

The influence of substantial intragranular orientation gradients on the micromechanical response of heavily-worked material

In this study, we employ high-energy X-ray characterization to examine the role of relatively large amounts of intragranular lattice misorientation – present after many thermomechanical processes – on the micromechanical response of Al-7085 with a modified T7452 temper. We utilize near-field high energy X-ray diffraction microscopy (HEDM) to measure three-dimensional (3D) spatial orientation fields, facilitated by a novel method that utilizes grain orientation envelopes measured using far-field HEDM to enable reconstruction of grains with intragranular orientation spreads greater than 20°. We then assess the consequences of consideration of intragranular orientation fields on the predicted deformation response of the sample through 3D micromechanical simulations of the forged Al-7085. We construct two virtual polycrystalline specimens for use in simulations: the first a faithful representation of the HEDM reconstruction, the second a microstructure with no intragranular misorientation (i.e., grain-averaged orientations). We find significant differences in the predicted deformation mechanism activation, distribution of stress, and distribution of plastic strain between simulations containing intragranular misorientation and those with grain-averaged orientations, indicating the necessity for consideration of intragranular orientation fields for accurate predictions. Further, the influence of elastic anisotropy is discussed, along with the effects of intragranular misorientation on fatigue life through the calculation and analysis of fatigue indicator parameters.

Investigation of individual lack-of-fusion defects in the fatigue performance of laser-powder bed fusion Ti6Al4V alloys: A finite element analysis

Laser-Powder Bed Fusion (L-PBF) techniques have revolutionized the production of Ti6Al4V alloys across various industries. However, the widespread adoption of L-PBF Ti6Al4V alloys is impeded by their inadequate fatigue performance, particularly in high cycle regimes. A significant contributing factor to this limitation is the presence of internal defects inherent to the L-PBF process, act as sites for fatigue crack initiation. Previous investigations have focused on the fatigue performance of L-PBF Ti6Al4V alloys with gas porosities, while research on lack-of-fusions (LOFs) which are recognized as the most detrimental defects, remains limited. In order to deepen our understanding of the factors influencing the reduced fatigue performance observed in L-PBF Ti6Al4V alloys associated with inherent LOFs, this study employed three-dimensional (3D) finite element analysis approaches. Such approaches allow to assess fatigue indicator parameters to evaluate fatigue life and predict fatigue crack propagation. A 3D average Smith-Watson-Topper method has been proposed, which is able to rationally estimate the fatigue life of L-PBF Ti6Al4V. In addition, a novel finite element method has been developed to accurately calculate stress intensity factors along irregular shaped crack front of a notch-like feature embedded on a LOF. Additionally, parametric studies were conducted to gain further insights into the influence of LOFs on fatigue performance. The results shown the presence of embedded humps and notch-like features, and their topologies play key roles in the fatigue performance of LOF predominated L-PBF Ti6Al4V alloys.

A Monte-Carlo approach for crack initiation modeling of cast superalloys informed by crystal plasticity

Crystal plasticity simulations of materials to assess the fatigue response on the microscale are becoming increasingly popular in industrial application. However, in the case of parts made from cast Ni-base superalloys, the amount of pores in a part combined with the fine spatial discretization around the pores needed due to strong mechanical gradients quickly leads to a computationally impractical number of mesh elements. In this paper we show an alternative to explicit crystal plasticity modeling of part-scale porosity by introducing a Monte-Carlo submodel that recombines the fatigue response of single pores predicted by crystal plasticity into the fatigue response of the pore agglomerate. The model can be applied in realtime due to the use of precomputed crystal plasticity results. We demonstrate that fatigue indicator parameters predicted by the Monte-Carlo submodel agree well with those predicted by explicit crystal plasticity simulations. Lastly, we apply the proposed model to study the influence of different porosity volume percentages, pore sizes and pore morphologies on the fatigue indicator parameters of a cast MAR-M247 superalloy.

Microstructure-sensitivity of CPFEM models on fretting fatigue crack initiation of AA2024-T351 alloy

The AA2024-T351 alloy is widely used in civil engineering, machinery, and aerospace industries for bolts, rivets, and thin plate components. When in service within these fields, the components are susceptible to performance degradation and fracture failure due to fretting fatigue. In this study, a crystal plastic finite element method (CPFEM) model incorporating microstructure sensitivity is employed to predict the fretting fatigue crack initiation (FFCI) location and lifetime. The submodel method is utilized to simulate various microstructures in the contact region of the specimen under fretting fatigue. This research focuses on two fatigue indicator parameters (FIPs): accumulated plastic slip p and FIPFS, used to determine the hotspots for crack nucleation on the contact surface and subsurface in fretting fatigue. The study explores the impact of different grain size and orientation on crack nucleation and analyzes how various microstructural characteristics influence the crack initiation lifetime. The findings indicate that the influence of grain orientation distribution in fretting fatigue on the initiation location of contact surface cracks is not significant, but it has a notable impact on subsurface cracks. Different grain textures combinations exhibit a more pronounced anisotropy based on the accumulated plastic slip p than FIPFS. Additionally, the effect of grain orientation distribution on the FFCI lifetime is influenced by the average grain size, showing remarkable influence within a specific range of grain sizes.

A two-scale approach for assessing the role of defects in fatigue crack nucleation in metallic structures

Metal structures often exhibit macroscopic defects from which cracks can nucleate during cyclic loading. The current work presents a two-scale approach to enable the prediction of crack nucleation from such defects by taking into account local microstructure features. The geometrical description of the defect and associated non-homogeneous strain fields are modeled using a macroscale model which employs a continuum elastoplastic material model for cyclic deformation. The cyclic deformation of the microstructure near the defect is modeled using a mesoscale model which employs a crystal plasticity material model and uses multiple realizations to address the statistical microstructure variability. The boundary conditions of the mesoscale model are extracted from the macroscale model. By simulating the deformation of the microstructure using the strain fields near the defect and by introducing a fatigue indicator parameter for crack nucleation, along with the weakest-link based upscaling methodology, the developed approach enables the prediction of the distribution of crack nucleation life. The approach is used for analyzing different defects for crack nucleation by considering local grain orientations. The predictions are shown to not only capture phenomena such as scatter, size effects, etc. qualitatively, but also agree with a classical engineering approach and experimentally reported data sets quantitatively.

Analysis of rolling contact and tooth root bending fatigue in a new high-strength steel: Experiments and micromechanical modelling

To find materials that meet the future requirements of increasing load density in wind turbine gear structures, the commonly used reference material, 18CrNiMo7-6, and another high-strength steel were analysed. Their fatigue properties were studied through rolling contact fatigue (RCF) and gear tooth root bending fatigue (TRBF) tests. The reference steel exhibited better fatigue performance under RCF conditions compared to the new steel; however, it was outperformed by the new steel under TRBF conditions. This study aims to understand gear contact fatigue at the microscopic level, moving beyond the macroscopic focus that dominates current research literature. To establish the causal link between the varied fatigue performance observed in these materials, we proposed a multiscale modelling workflow based on crystal plasticity. This crystal plasticity framework is combined with the fatigue indicator parameter (FIP) to explore the fatigue resistance of materials subjected to RCF and TRBF conditions. Emphasis has been placed on the role of retained austenite (RA) in fatigue performance. Utilizing representative elementary volumes (REVs) generated based on statistically representative crystallographic features and measured size distribution of RA, we examined the effects of various RA levels on fatigue resistance. Our findings reveals that the fatigue damage accumulation is significantly influenced by the level of RA. Different fatigue damage accumulation behaviours were observed under RCF and TRBF conditions. These insights offer new perspectives on RA’s role in fatigue resistance and highlight its complex influence under varied loading conditions.

Effect of grain orientation distribution on the mechanical properties of Al-7.02Mg-1.78Zn alloys

PurposeDuring the forming process, aluminum alloy sheets develop various types of textures and are subjected to cyclic loading as structural components, resulting in fatigue damage. This study aims to develop polycrystalline models with different orientation distributions and incorporate suitable fatigue indicator parameters to investigate the effect of orientation distribution on the mechanical properties of Al-7.02Mg-1.78Zn alloys under cyclic loading.Design/methodology/approachIn this study, a two-dimensional polycrystalline model with 150 equiaxed grains was constructed based on optical microscope images. Subsequently, six different orientation distributions were assigned to this model. The fatigue indicator parameter of strain energy dissipation is utilized to analyze the stress response and fatigue crack driving force in polycrystalline models with different orientation distributions subjected to cyclic loading.FindingsThe study found that orientation distribution significantly influences fatigue crack initiation. Orientation distributions with a larger average Schmid factor exhibit reduced stress response and lower fatigue indicator parameters. Locations with a larger average Schmid factor experience greater plastic deformation and present a higher risk for fatigue crack initiation. RVE with a single orientation undergoes more rotation to reach cyclic steady state under cyclic loading due to the ease of deformation transfer.Originality/valueCurrently, there are no reports in the literature on the calculation of fatigue crack initiation for Al-Mg-Zn alloys using the crystal plasticity finite element method. This study presents a novel strategy for simulating the response of Al-7.02Mg-1.78Zn materials with different orientation distributions under symmetric strain cyclic loading, providing valuable references for future research.

A physics‐informed neural network framework based on fatigue indicator parameters for very high cycle fatigue life prediction of an additively manufactured titanium alloy

AbstractThe exploitation of fatigue life prediction methods based on fatigue indicator parameters revealed the influence of the defect size, position, and morphology on the fatigue life and fatigue behavior of additively manufactured metals. Meanwhile, Data‐driven life prediction methods are time‐efficient but inexplainable. Current machine learning‐based fatigue life prediction methods call for not only the accuracy but also the interpretability and stability of prediction results. Thus, the fusion of physical methods and machine learning methods has been a prevailing research topic in fatigue life prediction. In this study, a novel physics‐informed neural network framework is proposed by integrating a fatigue indicator parameter based on defects into the physical constraints term of a loss function. This method outperforms conventional machine learning methods in high‐cycle and very high‐cycle regimes, exhibiting superior prediction performance and generalization ability. Furthermore, the prediction results can be explained from a physical standpoint, correlating with the applicability range of the introduced physical equation describing defect positions.

Crystal plasticity quantification of anisotropic tensile and fatigue properties in laser powder bed fused Inconel 718 superalloy

The high thermal gradients during the laser powder bed fusion (LPBF) process induce an inhomogeneous microstructure with anisotropic mechanical properties. This study developed a dislocation-based strain-gradient crystal plasticity finite element (CPFE) model to reveal the microstructure-based deformation mechanisms and quantify their strengthening contributions to the mechanical property anisotropy of LPBF-ed Inconel 718 (IN718) superalloy. The analyzed microstructural attributes included 1- crystallographic orientations/misorientations, 2- solid solutions (SS), 3- grain size and morphologies, and 4- dislocation dynamics, such as statistically stored dislocations (SSDs) and geometrically necessary dislocations (GNDs). The investigated mechanical properties contained tensile strength, fatigue resistance, fracture mechanisms, and their anisotropy under loading towards building (BD) and transverse (TD) directions. The experimentally obtained microstructural features of the as-LPBF-ed IN718 were synthesized into the crystal plasticity representative volume elements (CPRVE) to model the deformation behavior using a user-defined material subroutine (UMAT) in the ABAQUS solver. The energy-based fatigue indicator parameter (FIP) captured the fatigue properties and failure mechanisms. The main slip-strengthening contributions stemmed from SSDs, grain size, SS, and GNDs. in TD. The corresponding order in BD was SSDs, SS, GNDs, and grain size because the grain dimensions were larger in BD than in TD. The grain-size effect had the highest contribution to the tensile property anisotropy, followed by SSDs, GNDs, and SS. Aside from their strengthening effects, crystal texture and grain size induced mechanical property heterogeneity and fatigue sensitivity at grain boundaries, reducing their contributions to fatigue strength relative to tensile. In contrast to the previous findings, local accumulations of SSDs and GNDs at softer sides of grain boundaries during cyclic loading reduced the strength heterogeneity in these areas, improving fatigue properties. The highest slip-strengthening effect for fatigue resistance and anisotropy was under SSDs, followed by GNDs, SS, and grain size.

Interpretation of Frequency Effect for High-Strength Steels with Three Different Strength Levels via Crystal Plasticity Finite Element Method.

The fatigue behavior of a high-strength bearing steel tempered under three different temperatures was investigated with ultrasonic frequency and conventional frequency loading. Three kinds of specimens with various yield strengths exhibited obvious higher fatigue strengths under ultrasonic frequency loading. Then, a 2D crystal plasticity finite element method was adopted to simulate the local stress distribution under different applied loads and loading frequencies. Simulations showed that the maximum residual local stress was much smaller under ultrasonic frequency loading in contrast to that under conventional frequency at the same applied load. It was also revealed that the maximum local stress increases with the applied load under both loading frequencies. The accumulated plastic strain was adopted as a fatigue indicator parameter to characterize the frequency effect, which was several orders smaller than that obtained under conventional loading frequencies when the applied load was fixed. The increment of accumulated plastic strain and the load stress amplitude exhibited a linear relationship in the double logarithmic coordinate system, and an improved fatigue life prediction model was established.

Machine learning-based fatigue life prediction of lamellar titanium alloys: A microstructural perspective

Fatigue life prediction based on the traditional empirical formulation in large fatigue regimes is limited and prone to over-fitting. In this regard, we propose an integrated approach for fatigue life prediction of lamellar titanium alloys incorporating crystal plasticity simulations and a variety of machine learning methods from a microstructural perspective. Firstly, various defect shapes and distinct lamellar distributions are employed to characterize fatigue performance under different microstructural features. By utilizing fatigue indicator parameters (FIPs) to get an expanded dataset, this work employs algorithms including artificial neural networks (ANN), random forests regression (RFR), support vector regression (SVR), and particularly convolutional neural networks (CNN) to predict fatigue life. The results indicate that CNN outperforms the previously mentioned algorithms in prediction accuracy, due to its ability to directly extract microstructural features from images. Our proposed approach provides a microstructural perspective for fatigue life prediction of lamellar titanium alloys, broadening the way for life assessment of materials with diverse microstructures.

Crystal plasticity modeling fatigue behavior in bimodal Ti–6Al–4V: Effects of microdefect and lamellar orientation

AbstractInvestigating fatigue failure in titanium alloys is crucial for material design and engineering. Fatigue behavior in dual‐phase titanium alloys is strongly correlated with microstructural features and microdefects. This work formulates an improved modeling method to investigate fatigue behavior of bimodal Ti–6Al–4V, emphasizing the effects of lamellar orientation and microdefects. Using an improved Voronoi tessellation method, we establish representative volume element (RVE) models with various grain size distributions. Crystal plasticity finite element modeling (CPFEM) is used to analyze fatigue deformation in bimodal Ti–6Al–4V, considering microdefects and lamellar orientation. Fatigue indicator parameters are then incorporated into CPFEM to predict fatigue life and verified with experimental data. Numerical results highlight the significant influence of lamellar orientation and microdefects on fatigue behavior, with predicted life within the 3‐error band. This method efficiently overcomes challenges in quantitatively characterizing microstructural lamellae that experiments are short of, paving the way for designing fatigue‐resistant alloy materials with similar microstructures.

Prediction of the fatigue life in a textured AZ31 Mg alloy as a function of orientation using fatigue indicator parameters

Computational homogenization was used to simulate the mechanical response of a textured AZ31Mg alloy subjected to fully-reversed cyclic deformation. The behavior of each grain in the polycrystal followed a phenomenological crystal plasticity model that considered different deformation mechanisms, namely pyramidal, basal, and prismatic slip, as well as twinning and detwinning. It also accounted for both kinematic and isotropic hardening effects. The crystal plasticity model's parameters were adjusted to replicate the cyclic stress-strain curves along three different orientations (rolling direction, normal direction and at 45° between the rolling and normal directions) at different cyclic strain semi-amplitudes. Three different fatigue indicator parameters were calculated from the simulations, based on the accumulated plastic shear strain in one stabilized fatigue cycle from basal slip and pyramidal slip, and from the shear strain accommodated by twinning/de-twinning during one fatigue cycle. The predictions of the fatigue life based on the fatigue indicator parameters were compared with the experimental results for the three orientations. It was found that the most accurate prediction was obtained by using the fatigue indicator parameter associated with twinning/de-twinning. Thus, it is concluded that fatigue cracks nucleated at twin boundaries control the fatigue life of textured Mg alloys.

Crystal plasticity based modelling and high cycle fatigue life prediction for bi-lamellar Ti-6Al-4V

Microstructural defects and inhomogeneity of titanium alloys fabricated by additive manufacturing technology make their fatigue performance much more complicated, especially reflected in the dispersion of fatigue life. This work employs crystal plasticity finite element method (CPFEM) to predict high cycle fatigue (HCF) life of bi-lamellar Ti-6Al-4V alloy. We first propose a modified VT technique to build representative volume element (RVE) models highlighting lamellar microstructure and micro-defects. Subsequently, fatigue indicator parameter (FIP) is adopted to analyse fatigue deformation under cyclic loading. Finally, HCF life determined by critical fatigue indicator parameter is compared with experimental data collected from published literatures. The results demonstrate that our approach is able to reflect the dispersion of fatigue life and to predict HCF life of bi-lamellar Ti-6Al-4V in a satisfactory manner.

Exploring the role of Type-II residual stresses in a laser powder bed fusion nickel-based superalloy using measurement and modeling

Far-field high-energy X-ray diffraction microscopy (ff-HEDM) and the crystal plasticity finite element method (CPFEM) are used to investigate the role of grain-scale (Type-II) residual stresses on the fatigue life of additively manufactured (AM) Inconel alloy 625 (IN-625). Grain-averaged orientations, centroids, and residual elastic strain tensors from ff-HEDM data are used to instantiate a crystal plasticity model to simulate the effect of residual stresses at the grain scale. Simulation results indicate that the presence of tensile residual strains increase stress localization and heterogeneity within grains, triggering an earlier onset of plasticity. A microscale fatigue indicator parameter (FIP) is computed to model the impact of these residual strains on the cycles to fatigue crack nucleation. The crack nucleation model, based on the computed FIPs, predicts a significant reduction in the number of cycles for fatigue crack nucleation for mid- and high-cycle fatigue due to the residual strain induced localization, while the residual strains have minimal impact on low-cycle fatigue life.

Interpretable machine learning for microstructure-dependent models of fatigue indicator parameters

Fatigue indicator parameters (FIPs) are typically computed using crystal plasticity finite element modeling (CPFEM) and used to predict microscale crack initiation. While informative, computing FIPs in this manner can limit their application in engineering use cases due to the computational demand of CPFEM. To address this limitation, an interpretable machine learning approach is developed and used to model FIPs in additive manufactured IN625 single-phase microstructures. Genetic programming based symbolic regression is used to evolve inherently interpretable expressions of FIPs from microstructure features. Once developed, these FIP models act as an efficient surrogate for CPFEM and, due to their symbolic representation, can be readily combined with engineering workflows.

A crystal plasticity based methodology for crack initiation lifetime prediction of fretting fatigue in AA2024-T351 alloy

AA2024-T351 alloy finds extensive use as a component material in the fields of civil engineering, machinery and aerospace, which are prone to long-term contact loading during service that may cause catastrophic failure such as fretting fatigue. In this work, a crystal plasticity finite element (CPFE) model has been established to predict the fretting fatigue crack initiation (FFCI) lifetime of AA2024-T351 alloy. Submodel methods for frictional contact parts are adopted, and crystal plasticity theory is utilized to obtain more accurate simulation results. The hotspots for fretting fatigue crack nucleation are determined by the difference of maximum value of maximum principal strain. The accumulated plastic slip and accumulated energy dissipation are utilized as fatigue indicator parameters (FIPs) to accurately predict FFCI lifetime. The results show that both FIPs predicted crack initiation lifetime are within twice the scatter band. Furthermore, the submodel is employed to generate diverse grain orientation sets while maintaining a constant total of 800 grains. The results indicate that different sets have little effect on the prediction of FFCI lifetime, but has a significant impact on the cumulative shear strain distribution between each individual grain at the mesoscale.

Fatigue behaviour analysis of thermal cyclic loading for through-silicon via structures based on backstress stored energy density

Through-silicon via (TSV) structures are widely used in microelectronic due to the ease of chip interconnection. Few research has focused on investigating the fatigue properties of TSV structures using crystal plasticity finite element (CPFE) simulations. As the process of TSV structures approaches the micron scale, the effects of anisotropic microstructure and grain size on their fatigue behaviours will become necessary. The present work aims to use CPFE simulations to investigate the fatigue properties of TSVs at the microscale. Finite element models with realistic EBSD morphology and orientation are established for four TSV structures with different grain sizes, and CPFE simulations with thermal cyclic loading from −55℃ to 125℃ are performed. From the energy point of view, the stored energy density based on backstress and strain gradient is proposed as a fatigue indicator parameter (FIP). CPFE simulation results show that low-angle grain boundaries (LAGBs) and high-angle grain boundaries (HAGBs) dominate crack initiation at the top, bottom or edges of the TSV structure, which is still mainly due to the thermal mismatch effect caused by the difference in the coefficients of thermal expansion of the materials. The crack initiation in the internal structure is mainly caused by symmetric grains containing twin boundaries (TBs), or trigrain boundaries, and this is different from the macroscopic simulations. Combined with the local FIPs concentration distribution, the backstress stored energy density is able to capture more details than the cumulative plastic strain because of its direct correlation with the strain gradient, and validates its effectiveness as a FIP.