A dual-time-scale finite element model is developed in this paper for simulating cyclic deformation in polycrystalline alloys. The material is characterized by crystal plasticity constitutive relations. The finite element formulation of the initial boundary-value problems with cyclic loading involves decoupling the governing equations into two sets of problems corresponding to two different time-scales. One is a long-time-scale (low-frequency) problem characterizing a cycle-averaged solution, while the other is a short-time-scale (high-frequency) problem for a remaining oscillatory portion. Cyclic averaging together with asymptotic expansion of the variables in the time domain forms the basis of the multitime-scaling. The crystal plasticity equations at the two scales are used to study cyclic deformation of a titanium alloy Ti-6Al. This model is intended to study the fatigue response of a material by simulating a large number of cycles to initiation.
A recent microstructure-based FEM model that couples crystal-based plasticity, the B2 M B19 0 phase transformation and anisotropic elasticity at the grain scale is calibrated to recent data for polycrystalline NiTi (49.9 at.% Ni). Inputs include anisotropic elastic properties, texture and differential scanning calorimetry data, as well as a subset of recent isothermal deformation and load-biased thermal cycling data. The model is assessed against additional experimental data. Several experimental trends are captured -in particular, the transformation strain during thermal cycling monotonically increases and reaches a peak with increasing bias stress. This is achieved, in part, by modifying the martensite hardening matrix proposed by Patoor et al. [Patoor E, Eberhardt A, Berveiller M. J Phys IV 1996;6:277]. Some experimental trends are underestimated -in particular, the ratcheting of macrostrain during thermal cycling. This may reflect a model limitation that transformation-plasticity coupling is captured on a coarse (grain) scale but not on a fine (martensitic plate) scale.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.