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

Abstract

A B S T R A C TA 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. = Plastic rate of deformation tensors in intermediate and current configurations, respectively d 2 , d 3 = Secondary and tertiary γ precipitate sizes, respectively d gr = Mean grain size F, F e , F p = Total, elastic and plastic deformation gradient tensors, respectively FIP = Fatigue indicator parameter (e.g. P FS , P mps , P cyc ) FIP ,av = Average value of the FIP over all elements in the grain (e.g. P FS,av ) FIP ,max = Maximum value of the FIP over all elements in the grain (e.g. P FS,max ) f p2 , f p3 = Secondary and tertiary γ precipitate volume fractions, respectivelŷ L p = Plastic velocity gradient tensor in the intermediate configuration M = Taylor factor (3.06 for fcc polycrystals with random texture) max FIP ,max = Maximum value of the FIP ,max over all grains in the SVE m α o = Unit normal vector in the reference configuration on slip system α N f = Number of cycles for specimen failure N inc = Crack incubation life N I = Crack initiation life, defined as the number of cycles for a crack to incubate and grow to 3d gr

On the mechanistic basis of fatigue crack nucleation in Ni superalloy containing inclusions using high resolution electron backscatter diffraction

“…In connection with the former, independent experimental and crystal plasticity computational studies in ferritic steel samples have indicated the importance of stored energy density (is Jm -2 ) in determining both the location of crack nucleation, and in predicting cycles to nucleation [14]. The stored energy, it is argued, accrues by virtue of the establishment of sessile dislocation structures of both geometrically necessary and statistically stored types, both of which have been incorporated in determination of stored energy in dislocation-based crystal plasticity models.…”

“…These reviews highlight the need to deliver new experimental insight into deformation processes and failure in fatigue to drive modelling that can accurately capture microstructurally-sensitive effects and use geometrically faithful models. These modelling efforts have focused at a range of length and timescales, using approaches such as molecular dynamic simulations [8,9] up to the grain level using crystal plasticity finite element techniques [10][11][12][13][14][15]. This range of approaches necessitates ever increasing fidelity of experimental studies that span length and timescales, such as X-ray synchrotron [16] [17,18] and high energy neutron diffraction [19]; as well as electron microscopy [20,21] microstructurally-sensitive and physically based modelling approaches necessitate local measurements of defect content and residual stresses to improve the prediction of fatigue crack nucleation and short crack growth.…”

Microstructure-dependent fatigue damage process zone and notch sensitivity index

“…The threshold FIP, th , can be associated with the microscopic critical resolved shear stress threshold for yielding, τ y . The critical resolved shear stress may be estimated from the macroscopic yield via the Taylor relation σ y /M, where M = 3.06 is the Taylor factor for a randomly textured face-centered cubic (fcc) polycrystalline aggregate (Shenoy et al 2007). To estimate th , τ y is used in the modified form of the microstructurally small crack growth law given by Shenoy et al (2007) as…”

“…For the OFHC Cu, the magnitude of the burger vector b = 2.55 × 10 −10 m, η = 1, τ y = 13 MPa (McGinty 2001). A F S is calibrated such that the number of cycles for formation of a small crack is equal to the number of cycle for the growth of microstructurally small crack (MSC) at an applied strain level that is equal to the yield strain, ε y (Shenoy et al 2007). In Shenoy et al (2007), the MSC life is defined as the number of cycles for the crack to form and grow to 3 times the average grain size.…”

Low Cycle Fatigue Behaviour of DP Steels: Micromechanical Modelling vs. Validation

“…Furthermore, the mechanism of fatigue on a microscopic scale has been extensively investigated in many research studies by Mughrabi et al [21,22]. Furthermore, Shenoy et al [23,24] conducted a hierarchical model that provides the systematic linkage of the macroscale model to the microstructure. Steglich et al [25] investigated the micromechanical modelling of cyclic plasticity incorporating damage.…”