Forces For Fatigue Crack Formation Research Articles

Effect of sample size on the maximum value distribution of fatigue driving forces in metals and alloys

An analytical framework is presented to predict the effects of sample size on the maximum value distribution (MVD) of the driving forces for fatigue crack formation in metals and alloys. The distribution of the maximum driving force for fatigue crack formation over the domain follows the generalized extreme value theory in the limit as the domain size increases to infinity. However, a simulation-based analysis of microstructure influences on fatigue resistance for polycrystalline metals and alloys is very costly, and reaching those limits is intractable. This work models the MVD of Fatigue Indicator Parameters (FIPs), which serve as surrogate measures for the driving force for fatigue crack formation, at finite sample sizes prior to their convergence to a limiting extreme value distribution. Large-scale crystal plasticity finite element (CPFE) simulations of FCC Al 7075-T6 with microstructure realizations of various sizes are incorporated to calibrate and evaluate the developed framework, and a total of ∼6.5 million grains of Al 7075-T6 are examined. The calibrated analytical solution agrees well with the brute force Monte Carlo simulation results extracted from the CPFE simulations. Furthermore, the developed formulation can predict the MVD of FIPs for different sample sizes using a size-dependent parameter, and it is capable of accurately extrapolating the MVD of FIPs for much larger microstructure sample sizes than the size used for its calibration.

Modeling the statistical distribution of fatigue crack formation lifetime in large volumes of polycrystalline microstructures

Microstructure-scale interactions involving crystallographic texture (orientation and disorientation distributions), distributions of grain shape and size, nearest neighbor grains/phases, etc. in polycrystals can be simulated using the Crystal Plasticity Finite Element Method (CPFEM). Digital statistical volume element (SVE) instantiations that comprise a significant number of grains are analyzed by CPFEM to compute fatigue indicator parameters (FIPs) which are used as surrogate measures of the driving force for fatigue crack formation within the first grain or nucleant phase. The computed maximum FIPs usually increase in magnitude with larger numbers of realistic microstructure instantiations or SVEs analyzed. This work predicts the extreme value distribution (EVD) of the maximum FIPs associated with large engineering components comprised of up to 108 SVEs using a recently developed upscaling scheme, based on statistical information identified from simulations involving only hundreds of SVEs, with each SVE containing nominally 264 grains. This scheme is numerically validated by extensive simulations for samples of duplex Ti-6Al-4V microstructure models with sharp transverse texture strained in two characteristic directions. The size of the training dataset for a reliable prediction is determined for different textures and loading directions based on uncertainty analysis. Finally, the statistical distribution of fatigue crack formation lifetime (FCFL) is correlated with the EVD of the maximum FIPs, facilitating quantitative exploration of the effect of crystallographic texture and sample size on the FCFL.

Microstructure-Sensitive modeling of surface roughness and notch effects on extreme value fatigue response

Fatigue life knockdown due to surface roughness induces local stress concentrations. Physical fatigue experiments are crucial to qualify materials for use but are limited in their capability to examine the mechanisms underlying the fatigue crack formation driving force due to these stress concentrations. Microstructure-sensitive computational models can aid in this regard and are employed in this work to examine the effects of surface roughness in Al 7075-T6. Digital microstructure models are subjected to crystal plasticity finite element method (CPFEM) simulations to examine the combined effects of microstructure and grain scale asperities on the driving force for fatigue crack formation. Following elastic–plastic shakedown, mesoscale volume-averaged fatigue indicator parameters (FIPs) are computed within fatigue damage process zones of grains. An increase in the intensity of realistic surface roughness profiles corresponds accordingly to larger FIPs but it is difficult to precisely interpret the mechanisms and effects of this intensification. We thus parametrically investigate surface asperities that couple with microstructure and lack of constraint on slip at the free surface to describe microstructure-sensitive surface roughness knockdown effects on fatigue resistance. The depth of a single valley (i.e., notch) due to surface roughness is found to be more detrimental to fatigue resistance than the radius (i.e., notch width, not to be confused with notch acuity). We also find that different crystallographic textures, grain morphologies, and number of sampled grains have a limited effect on the depth of influence of these notches.

Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response

Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. The present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework [Yaghoobi et al., npj Comput. Mater., 7, 38 (2021)] to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVE of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.

PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys

The PRISMS-Fatigue open-source framework for simulation-based analysis of microstructural influences on fatigue resistance for polycrystalline metals and alloys is presented here. The framework uses the crystal plasticity finite element method as its microstructure analysis tool and provides a highly efficient, scalable, flexible, and easy-to-use ICME community platform. The PRISMS-Fatigue framework is linked to different open-source software to instantiate microstructures, compute the material response, and assess fatigue indicator parameters. The performance of PRISMS-Fatigue is benchmarked against a similar framework implemented using ABAQUS. Results indicate that the multilevel parallelism scheme of PRISMS-Fatigue is more efficient and scalable than ABAQUS for large-scale fatigue simulations. The performance and flexibility of this framework is demonstrated with various examples that assess the driving force for fatigue crack formation of microstructures with different crystallographic textures, grain morphologies, and grain numbers, and under different multiaxial strain states, strain magnitudes, and boundary conditions.

Effects of microstructure on high cycle fatigue properties of dual-phase Ti alloy: combined nonlocal CPFE simulations and extreme value statistics

The nonlocal crystal plasticity finite element (CPFE) simulations and extreme value statistics were combined to study the effects of microstructure on the high cycle fatigue (HCF) behavior of dual-phase Ti alloy. A modified Armstrong-Frederick nonlinear kinematic hardening equation accounting for cyclic softening effect was employed in the crystal plasticity constitutive model. Three-dimensional equiaxed microstructure models and two-dimensional duplex microstructure models with real lamellar structure were generated based on Voronoi method, serving as statistical volume elements (SVEs). The effects of morphological and crystallographic features, including grain size, grain orientation, phase volume fraction and lamellae width, on the fatigue performance were investigated. By simulating multiple SVEs, extreme value distributions of the driving force for fatigue crack formation were predicted using Fatemi-Socie (FS) parameter as a fatigue indicator parameter (FIP). Meanwhile, whether the extreme values of geometrically necessary dislocation (GND) density can be taken as a FIP was discussed with compared to FS FIP. The GND density, related to local stress and strain gradient, has considerable potential as a FIP to estimate the fatigue performance of titanium alloys. Based on simulated results, it is suggested that microstructure with small grain size, low volume fraction of primary α grains, and thinner α lamellae width have the lowest probability of crack formation during HCF.

Prediction of maximum fatigue indicator parameters for duplex Ti–6Al–4V using extreme value theory

Fatigue Indicator Parameters (FIPs) based on the cyclic plastic strain are used as surrogate measures of the driving force for fatigue crack formation. For a given microstructure, the Extreme Value Distribution (EVD) of FIPs can be populated using results of a number of digital Statistical Volume Element (SVE) instantiations analyzed by the crystal plasticity finite element method. The number of microstructure instantiations affects the maximum FIPs computed. To predict the maximum FIPs in a large volume of material using simulation results from a limited number of SVEs, we proposed a statistical approach based on extreme value theory. The predicted maximum FIP values are compared directly to simulation results of 1000 SVEs to validate the proposed method for duplex Ti–6Al–4V. It is shown that simulations of only 100 SVEs suffice to identify the statistical information for a reliable prediction of the maximum FIPs in polycrystalline duplex Ti–6Al–4V with initial random texture.

Microstructure-sensitive computational multiaxial fatigue of Al 7075-T6 and duplex Ti-6Al-4V

Multiaxial fatigue experiments are expensive and typically require specialized equipment and specimens, but they are essential to support fatigue design of components that experience multiaxial stress states. To leverage limited experimental data, we pursue parametric simulations regarding the influence of multiaxial strain state on extreme value distributions (EVDs) of fatigue crack formation driving force in realistic microstructures. Ensembles of Statistical volume elements (SVEs) for both Al 7075-T6 and Ti-6Al-4V polycrystalline microstructures are subjected to multiaxial cyclic straining to compute EVDs of Fatigue Indicator Parameters (FIPs) that serve as computable surrogate measures of the driving force for fatigue crack formation.

Prediction of Maximum Fatigue Indicator Parameters for Duplex Ti-6Al-4V Using Extreme Value Theory

Fatigue Indicator Parameters (FIPs) based on the cyclic plastic strain are used as surrogate measures of the driving force for fatigue crack formation. For a given microstructure, the Extreme Value Distribution (EVD) of FIPs can be populated using results of a number of digital Statistical Volume Element (SVE) instantiations analyzed by the crystal plasticity finite element method. The number of microstructure instantiations affects the maximum FIPs computed. To predict the maximum FIPs in a large volume of material using simulation results from a limited number of SVEs, we proposed a statistical approach based on extreme value theory. The predicted maximum FIP values are compared directly to simulation results of 1000 SVEs to validate the proposed method for duplex Ti-6Al-4V. It is shown that simulations of only 100 SVEs suffice to identify the statistical information for a reliable prediction of the maximum FIPs in polycrystalline duplex Ti-6Al-4V with initial random texture.

Microstructure-Sensitive Computational Estimates of Driving Forces for Surface Versus Subsurface Fatigue Crack Formation in Duplex Ti-6Al-4V and Al 7075-T6

Statistical realizations of three-dimensional digital microstructures with different crystallographic orientation distributions, grain shapes, and grain size distributions are subjected to uniaxial cyclic straining to compare the cases of bulk and free surface on driving forces for fatigue crack formation. Crystal plasticity finite element simulations are conducted using both fully periodic (more representative of the bulk) and traction-free (i.e., free surface) boundary conditions for duplex Ti-6Al-4V and rolled Al 7075-T6. Following elastic–plastic shakedown, mesoscale volume-averaged fatigue indicator parameters (FIPs) are computed within fatigue damage process zones of grains and are fit to known extreme value distributions (EVDs). Owing to differences in crystallographic slip symmetry, FIPs for fcc Al 7075-T6 statistically occur much closer to the traction-free surface than for hcp Ti-6Al-4V. Additionally, surface versus bulk EVDs of FIPs vary differently for the two material systems, indicating a coupled role of microstructure and surface proximity that had not been previously elucidated.

Fatigue hot spot simulation for two Widmanstätten titanium microstructures

A simulated microstructure-sensitive fatigue study has been performed for two titanium alloy microstructures. The investigated materials exhibit a Widmanstätten structure and include the α–β alloy Ti–6Al–4V and the near β alloy Ti-18 in a β-annealed, slow-cooled, and aged condition (BASCA). In other work [1], crystal plasticity models implemented into ABAQUS (2011) [2] UserMATerial subroutines have been calibrated to experimental cyclic deformation data for both materials. The current study utilizes calibrated crystal plasticity models to simulate fatigue loading of varying microstructures for each material to study the influence of key morphological and crystallographic aspects on the fatigue performance, e.g., the mean colony size, phase volume fraction, and crystallographic texture. Localized stress and plastic strain are studied via computation of fatigue indicator parameters (FIPs), which represent the driving force for fatigue crack formation and early propagation in the microstructure. The maximum FIP values are sampled over several stochastic simulations and are utilized to determine extreme value statistical distributions which demonstrate the trends in the microstructural influence on fatigue performance. Marked radial correlation functions developed by Przybyla and McDowell [3] have also been employed to study the correlation between favorably oriented slip systems and the extreme value FIP locations within the instantiated microstructures. The simulation results suggest that reduced lamellar colony sizes, reduced α-phase, and a transverse texture within a reference plane normal to the applied uniaxial loading direction can enhance resistance to formation and early growth of fatigue cracks.

COMPUTATIONAL STUDY ON MICROSTRUCTURE-SENSITIVE HIGH CYCLE FATIGUE DISPERSIVITY

Empirical approaches to characterize the variability of high cycle fatigue have been widely used. However, little is understood about the intrinsic relationship of randomness of microstructure attributes on the overall variability in high cycle fatigue. The ability of quantifying the dispersivity of high cycle fatigue with physics based computational methods has great potential in design of minimum life and can aid in the improvement of fatigue resistance. To investigate the effects between microstructure attributes and high cycle fatigue dispersivity, the microstructure-sensitive extreme value probabilistic framework is introduced. First, the Voronoi algorithm is used to construct random polycrystalline microstructure representative volume elements. Different kinds of periodic boundary conditions are proposed to simulate the interior and surface constraints in polycrystalline microstructure representative volume elements. Then mechanical responses of both interior and surface microstructure representative volume elements under different strain amplitudes are simulated by internal state variable based crystal plasticity. The fatigue indicator parameter is introduced to characterize the driving force for fatigue crack formation dominated by maximum shear plastic strain amplitude. By computing a limited number of random polycrystalline microstructure representative volume elements, the distributions of fatigue indicator parameter under different strain amplitudes are obtained and analyzed with extreme value probability theory. The study with a kind of titanium alloy with material grade TC4 supports that the high cycle fatigue dispersivity increases with the decrease of the strain *国家重点基础研究发展计划资助项目2015CB057400 收到初稿日期: 2015-06-23,收到修改稿日期: 2015-12-01 作者简介:韩世伟,男, 1987年生,博士生 DOI: 10.11900/0412.1961.2015.00322 第289-297页 pp.289-297

A mesoscale approach for growth of 3D microstructurally small fatigue cracks in polycrystals

In the high cycle fatigue regime, microstructure attributes such as grain size, shape, and crystallographic orientation usually affect fatigue crack formation and early growth. However, most computational strategies and theoretical models for assessing the influence of the microstructure on early stages of fatigue crack formation and growth rely on simple constitutive models and 2D microstructures, which limit their applicability in design of microstructure of engineering materials. This work employs finite element simulations that explicitly render the 3D microstructure of an Face-centered cubic (FCC) alloy to evaluate the change of the driving force for fatigue crack formation and early stages of transgranular growth, including consideration of growth within individual grains and stress redistribution as the crack extends. The methodology is implemented using a crystal plasticity algorithm in ABAQUS and used to study the effect of microstructure on early fatigue life of a powder processed Ni-base RR1000 superalloy at 650℃ subjected to constant amplitude loading. The effects of the microstructure in extending a fatigue crack over the first few grains are analyzed.

Microstructure-sensitive extreme-value probabilities of high-cycle fatigue for surface vs. subsurface crack formation in duplex Ti–6Al–4V

The distributions of the extreme-value driving force(s) for surface vs. subsurface fatigue crack formation (nucleation and early growth) in high-cycle fatigue are evaluated for a microstructure variant of duplex Ti–6Al–4V. In polycrystalline metals, previous work has explored estimation of the driving force(s) for fatigue crack formation at the scale of the grains by computing non-local fatigue indicator parameters (FIPs) based on the cyclic plastic strain averaged over domains on the length scale of the grains. Instantiated statistical volume elements (SVEs), which sample the distributed microstructure attributes of interest for a given material system, can be simulated via the finite element method with embedded polycrystalline plasticity models to estimate the distributed plasticity and resulting FIPs. This strategy of simulating multiple SVEs is in contrast to the simulation of a single representative volume element which is typically untenably large for extreme-value distributions of microstructure attributes or response variables. In this work, multiple SVEs are instantiated with both traction-free (i.e. surface) boundary conditions and fully periodic (i.e. subsurface) boundary conditions. In addition to estimating the extreme-value distributions of the FIPs, newly introduced extreme-value marked correlation functions are applied to characterize the coupled crystallographic microstructure attributes (e.g. grain size, grain orientation, grain misorientation) that most influence the extreme-value distributions of the FIPs. It is shown that there is overlap in the distributions of the driving forces for surface vs. subsurface crack formation in the low to moderate range of failure probability based on FIPs; however, at higher failure probability levels, the driving forces are highest for surface crack formation. The overlap in the distributions of the driving forces for fatigue crack formation in the low to moderate probability range may assist in describing the competing surface vs. subsurface failure modes that are observed experimentally.

Simulated microstructure-sensitive extreme value probabilities for high cycle fatigue of duplex Ti–6Al–4V

A newly developed microstructure-sensitive extreme value probabilistic framework to characterize the performance/variability for damage evolution processes is exercised to compare the driving forces for fatigue crack formation (nucleation and early growth) at room temperature for four different microstructure variants of a duplex Ti–6Al–4V alloy. The aforementioned probabilistic framework links certain extreme value fatigue response parameters with microstructure attributes at fatigue critical sites through the use of marked correlation functions. By applying this framework to study the driving forces for fatigue crack formation in these microstructure variants of Ti–6Al–4V, these microstructures can be ranked in terms of relative high cycle fatigue (HCF) performance and the correlated microstructure attributes that have the most influence on the predicted fatigue response can be identified. Nonlocal fatigue indicator parameters (FIPs) based on the cyclic plastic strain averaged over domains on the length scale of the microstructure attributes (e.g., grains, phases) are used to estimate the driving force(s) for fatigue crack formation at the grain scale. By simulating multiple statistical volume elements (SVEs) using crystal plasticity constitutive relations, extreme value distributions of the predicted driving forces for fatigue crack formation are estimated using these FIPs. This strategy of using multiple SVEs contrasts with simulation based on a single representative volume element (RVE), which is often untenably large when considering extreme value responses. The simulations demonstrate that microstructures with smaller relative primary α grain sizes and lower volume fractions of the primary α grains tend to exhibit less variability and smaller magnitudes of the driving forces for fatigue crack formation. The extreme value FIPs are predicted to most likely occur at clusters of primary α grains oriented for easy basal slip. Additionally, surrounding grains/phases with soft orientation shed load to less favorably oriented primary α grains, producing extreme value FIPs.

Simulated extreme value fatigue sensitivity to inclusions and pores in martensitic gear steels

The objective of this work is to model the sensitivity of high cycle fatigue resistance of secondary hardening martensitic gear steels to variability in extrinsic inhomogeneities such as primary inclusions, and pores, coupled with intrinsic microstructure variability. A simplified approach is presented to quantify the variability in the driving force for fatigue crack formation in the matrix at non-metallic inclusions and pores in lath martensitic gear steels using a three-dimensional crystal plasticity constitutive model. The utility of a simulation-based strategy for exploring sensitivity of minimum fatigue lifetime (low probability of failure) to microstructure lies in its inherent capability to consider parametric simulations of hundreds of inclusions and microstructures in contrast to limited numbers of physical experiments. Experiments are used to calibrate the polycrystalline cyclic stress–strain response and mean (50% probability) fatigue crack formation life. Several remote loading conditions are considered in the high cycle fatigue (HCF) regime relevant to typical gear applications. Idealized inhomogenieties (spherical) in the form of hard (Al 2O 3), soft inclusions (La 2O 2S), and pores are systematically investigated in this parametric computational study. Relations between remote loading conditions and local plasticity are discussed as a function of stress amplitude and microstructure. The maximum plastic shear strain range is used in the modified form of Fatemi–Socie parameter evaluated at the grain scale as a measure of the driving force for fatigue crack formation (nucleation and early growth to lengths on the order of several times the average grain size). Multiple realizations of the polycrystal microstructure are considered to obtain a statistical distribution of this fatigue indicator parameter (FIP). The results are used to construct an extreme value Gumbel distribution of the FIPs for the selected microstructures. Subsequently, a computational micromechanics based minimum life estimate that corresponds to 1% fatigue crack formation probability is calculated.

Simulation-based extreme value marked correlations in fatigue of advanced engineering alloys

The objective of this research is to estimate the microstructure dependence of the extreme value probabilities of fatigue crack formation at the scale of the grains in polycrystalline and polyphase microstructures to facilitate preliminary parametric design exploration and property assessment. A simulation-based methodology is introduced for computing correlation functions of microstructure attributes marked by the extreme value microstructure-scale fatigue indicator parameters. Multiple statistically representative microstructure volumes simulated using a crystal plasticity constitutive model coupled with the FEM are used to characterize these extreme value marked correlation functions. By comparing these marked correlation functions to traditional correlation functions sampled from the bulk material, the interacting microstructure attributes important to the extreme value response are identified. This methodology is applied to identify dominant crystallographic relationships relative to fatigue crack formation in the polycrystalline P/M Ni-base superalloy IN100 and duplex Ti-6Al-4V. It is demonstrated that certain high contrast orientation relationships in both IN100 and Ti-6Al-4V (where grains oriented for hard slip are near grains oriented for easier slip) can significantly increase the driving forces for fatigue crack formation.

Probabilistic framework for a microstructure-sensitive fatigue notch factor

To advance fatigue life prediction algorithms, more comprehensive knowledge of the intensity and distribution of slip within microstructure at the notch root is desired to quantify notch size effects. This study utilizes 3D computational crystal plasticity to assess the degree of heterogeneity of cyclic plastic deformation as a function of notch size and notch root acuity for notch root strain amplitudes near and below the macroscopic yield strain (high cycle fatigue) and for several realizations of aggregates of grains with random orientation distribution at the notch root for polycrystalline OFHC Cu. By using different notch root radii and microstructure realizations of aggregates of grains, statistical information regarding the distributions of stress/strain gradients and fatigue indicator parameters provides useful insight into the microstructure dependence of driving forces for fatigue crack formation at the scale of mean grain size. Results from simulations within a quantitatively defined notch root damage process zone are used along with a probabilistic mesomechanics approach to quantify notch size effects by defining a new microstructure-sensitive fatigue notch factor that considers the probability distribution of the high cycle fatigue strength.

Microstructure-sensitive computational modeling of fatigue crack formation

Recent trends towards simulation of the cyclic slip behavior of polycrystalline and polyphase microstructures of advanced engineering alloys subjected to cyclic loading are facilitating understanding of the relative roles of intrinsic and extrinsic attributes of microstructure in fatigue crack formation, comprised of nucleation and growth of cracks at the scale of individual grains or phases. Modeling of processes of early stages of fatigue crack nucleation and growth at these microstructure scales is an important emerging frontier in several respects. First, it facilitates analysis of the influence of local microstructure attributes on the distribution of driving forces for fatigue crack formation as a function of the applied stress state. This can support microstructure-sensitive estimates of minimum life, as well as characterization of competing failure modes. Second, it can inform modification of process route and its manifestations (e.g., residual stress, texture) to alter microstructure in ways that promote enhanced resistance to formation of fatigue cracks. Third, microstructure-sensitive modeling, even conducted at the mesocopic scale of individual grains/phases, can facilitate parametric design exploration in searching for microstructure morphologies and/or compositions that modify fatigue resistance. Fourth, such technologies offer promise for integration with advanced nondestructive evaluation methods for prognosis and structural health monitoring. Finally, as a longer term prospect in view of uncertainties in modeling mechanisms of cyclic slip, crack nucleation and growth, such modeling can serve to support more quantitative predictions of fatigue lifetime as a function of microstructure. We first discuss computationally based microstructure-sensitive fatigue modeling in the context of recent initiatives in accelerated insertion of materials and integration of computational mechanics, materials science, and systems engineering in design of materials and structures. We then highlight recent application of such strategies to Ni-base superalloys, gear steels, and α–β Ti alloys, with focus on the individual grain scale as the minimum length scale of heterogeneity. Finally, we close by outlining opportunities to advance microstructure-sensitive fatigue modeling in the next decade.

Estimating fatigue sensitivity to polycrystalline Ni‐base superalloy microstructures using a computational approach

ABSTRACTA computational study is conducted to determine the influence of microstructure attributes and properties on driving forces for fatigue crack formation and microstructurally small crack growth in a polycrystalline Ni‐base superalloy, IN100, a turbine disk alloy. A principal objective is to obtain quantitative estimates of the effect of variability of microstructure features on scatter in fatigue life or fatigue strength for a given life. Understanding is sought regarding sensitivity of driving forces to various microstructure attributes that may guide selection of the process route to tailor microstructure to achieve fatigue resistance. A microstructure‐sensitive crystal plasticity model is used to explicitly model individual grains and polycrystals, which is then used to explore effects of: (a) grain size distribution and (b) secondary and tertiary coherent γ′ precipitate size distributions and volume fractions on the cyclic inelastic strain distribution. Multiple statistical volume elements (SVEs) are subjected to random periodic boundary conditions to build up statistically significant measures of distributions of cyclic microplasticity. Multiaxial fatigue criteria with critical plane approaches are used to estimate the crack initiation life. Methods are developed for assessing crack formation and microstructurally small crack growth as a function of microstructure attributes.