With the design of new devices with complex geometry and to take advantage of their large recoverable strains, shape memory alloys components (SMA) are increasingly subjected to multiaxial loadings. The development process of SMA devices requires the prediction of their thermomechanical response, for which the calibration of the material parameters for the numerical model is an important step. In this work, the parameters of a phenomenological model are extracted from tests performed on specimens with non-uniform geometry, which induce heterogeneous strain fields carried out on specimens with the same thermomechanical loading history. The digital image correlation technique is employed to measure the strain fields on the surface of the specimen and to analyze the strain paths of chosen points. Finite element analysis enables the computation of numerical strain fields using a thermodynamicalconstitutive model for shape memory alloys previously implemented in a finite element code. The strain fields computed numerically are compared with experimental ones obtained by DIC to find the model parameters which best match experimental measurements using a newly developed parallelized mixed genetic/gradient-based optimization algorithm. These numerical simulations are carried out in parallel using a supercomputer to reduce the time necessary to identify the set of model parameters. The major features of this new algorithm is its ability to identify the material parameters which describe the thermomechanical behavior of shape memory alloys from full-field measurements for various loading conditions (different temperatures, multiaxial behavior, heterogeneous test configurations). It is demonstrated that model parameters for the simulation of SMA structures are thus obtained based on a reduced number of heterogeneous tests at different temperatures.International audienceWith the design of new devices with complex geometry and to take advantage of their large recoverable strains, shape memory alloys components (SMA) are increasingly subjected to multiaxial loadings. The development process of SMA devices requires the prediction of their thermomechanical response, for which the calibration of the material parameters for the numerical model is an important step. In this work, the parameters of a phenomenological model are extracted from tests performed on specimens with non-uniform geometry, which induce heterogeneous strain fields carried out on specimens with the same thermomechanical loading history. The digital image correlation technique is employed to measure the strain fields on the surface of the specimen and to analyze the strain paths of chosen points. Finite element analysis enables the computation of numerical strain fields using a thermodynamicalconstitutive model for shape memory alloys previously implemented in a finite element code. The strain fields computed numerically are compared with experimental ones obtained by DIC to find the model parameters which best match experimental measurements using a newly devel...

is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. AbstractWith the design of new devices with complex geometry and to take advantage of their large recoverable strains, shape memory alloys components (SMA) are increasingly subjected to multiaxial loadings. The development process of SMA devices requires the prediction of their thermomechanical response, where the calibration of the material parameters for the numerical model is an important step. In this work, the parameters of a phenomenological model are extracted from multiaxial and heterogeneous tests carried out on specimens with the same thermomechanical loading history. Finite element analysis enables the computation of numerical strain fields using a thermodynamical constitutive model for shape memory alloys previously implemented in a finite element code. The strain fields computed numerically are compared with experimental ones obtained by DIC to find the model parameters which best matches experimental measurements using a newly developed parallelized mixed genetic/gradient-based optimization algorithm. These numerical simulations are carried out in parallel in a supercomputer to reduce the time necessary to identify the set of identified parameters. The major features of this new algorithm is its ability to identify material parameters of the thermomechanical behavior of shape memory alloys from full-field measurements for various loading conditions (different temperatures, multiaxial behavior, heterogeneous test configurations).It is demonstrated that model parameters for the simulation of SMA structures are thus obtained based on a reduced number of heterogeneous tests at different temperatures.

A method for detecting fatigue cracks has been explored at NASA Langley Research Center. Microscopic NiTi shape memory alloy (sensory) particles were embedded in a 7050 aluminum alloy matrix to detect the presence of fatigue cracks. Cracks exhibit an elevated stress field near their tip inducing a martensitic phase transformation in nearby sensory particles. Detectable levels of acoustic energy are emitted upon particle phase transformation such that the existence and location of fatigue cracks can be detected. To test this concept, a fatigue crack was grown in a mode-I single-edge notch fatigue crack growth specimen containing sensory particles. As the crack approached the sensory particles, measurements of particle strain, matrix-particle debonding, and phase transformation behavior of the sensory particles were performed. Full-field deformation measurements were performed using a novel multi-scale optical 3D digital image correlation (DIC) system. This information will be used in a finite element-based study to determine optimal sensory material behavior and density.

This work introduces the use of digital image correlation together with infrared thermography to study nonuniform deformations due localized heating of equiatomic NiTi. While this short paper focuses on demonstrating the mechanical response of the material to localized heating, future work will also demonstrate calibration and validation of a 3-D constitutive model of the material using the concepts presented here. A comparison is made between the behavior of the material due to localized heating and the behavior due to uniform heating and cooling. The relevant parameters used for calibration of the constitutive model are quantified using the results of an ambient heating and cooling experiment.

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