4 research outputs found

    Phase field-finite element approach to study the effects of plasticity on thermal- and stress-induced martensite in shape memory alloys

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    Numerous experimental studies have shown that evolution of the martensite microstructure in shape memory alloys can lead to plastic deformation. This results in poor functional fatigue in many commercial applications, whereby strain incrementally advances with repeated thermal cycling under stress. This can also affect structural fatigue, whereby repeated cycling initiates and grows fatigue cracks. Conventional strategies to improve fatigue life include increasing flow strength as to decrease plastic zone size, but binary Ni–Ti alloys do not always follow this trend and there is evidence that a stress-induced phase transformation may not improve fatigue life. Thus, functional and structural fatigue performances are coupled to the underlying interaction between phase transformation and plasticity. This interaction is studied using a unique phase field-finite element approach that incorporates finite deformation. It models the austenite-to-martensite phase transformation at the finest (nm) scale and includes the kinetics of nucleation and growth of correspondence variants. Like spectral methods, it includes the driving forces from chemical, mechanical, and interfacial energies. However, the finite deformation approach also captures the rotation and deformation of material elements during transformation and plasticity. The latter is modeled using a rate-dependent crystal plasticity flow law in the austenite phase. The formalism also includes anisotropic elasticity and thermal expansion, thus capturing texture development and local internal stress during arbitrary thermo-mechanical histories. We examine three hypotheses associated with transformation and plasticity. The first is that plasticity can affect the microstructure of thermally induced martensite and the critical temperature at which it forms. This is explored by varying the rate of cooling, which is expected to moderate the amount of rate-dependent plasticity during transformation. We also study cases where the cooling rate is the same but the plastic yield strength is varied. The second hypothesis is that plasticity can affect the microstructure of stress-induced martensite and the critical applied stress at which it forms. This is explored by simulating uniaxial compression tests of single austenite crystals of varying orientation. The change in orientation moderates the relative Schmid factors for transformation vs. plasticity and the large deformation simulations highlight the complex bending and macrostress state during the test. The third hypothesis is that plasticity can affect the microstructure of stress-induced martensite at crack tips. This is explored through Mode I loading in cracked austenite single crystals. Different crack orientations are considered, thus moderating the relative Schmid factors for transformation and plasticity. The crack tip fields can be contrasted with those from conventional elasticity and crystal-plasticity solutions. The effects of plasticity on microstructure in shape memory alloys connect to transmission electron microscope observations of defect and texture evolution during thermal and stress cycling. These microstructural changes affect the performance and ratcheting measured in macroscopic tests. The phase field-finite element approach presented here can explore such microstructure-property-performance relationships in shape memory alloys

    Thermal Cycling and Isothermal Deformation Response of Polycrystalline NiTi: Simulations vs. Experiment

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    A recent microstructure-based FEM model that couples crystal-based plasticity, the B2 MB190 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

    Simulating Thermal Cycling and Isothermal Deformation Response of Polycrystalline NiTi

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    A microstructure-based FEM model that couples crystal plasticity, crystallographic descriptions of the B2-B19' martensitic phase transformation, and anisotropic elasticity is used to simulate thermal cycling and isothermal deformation in polycrystalline NiTi (49.9at% Ni). The model inputs include anisotropic elastic properties, polycrystalline texture, DSC data, and a subset of isothermal deformation and load-biased thermal cycling data. A key experimental trend is captured.namely, the transformation strain during thermal cycling is predicted to reach a peak with increasing bias stress, due to the onset of plasticity at larger bias stress. Plasticity induces internal stress that affects both thermal cycling and isothermal deformation responses. Affected thermal cycling features include hysteretic width, two-way shape memory effect, and evolution of texture with increasing bias stress. Affected isothermal deformation features include increased hardening during loading and retained martensite after unloading. These trends are not captured by microstructural models that lack plasticity, nor are they all captured in a robust manner by phenomenological approaches. Despite this advance in microstructural modeling, quantitative differences exist, such as underprediction of open loop strain during thermal cycling
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