Analysis of the deformation paths and thermomechanical parameter identification of a shape memory alloy using digital image correlation over heterogeneous tests. (June 2015)

• Record Type: Journal Article
• Authors: Chemisky, Yves; Meraghni, Fodil; Bourgeois, Nadine; Cornell, Stephen; Echchorfi, Rachid; Patoor, Etienne
• Is Part Of: International journal of mechanical sciences. Volume 96/97(2015)
• Page Start: 13
• Page End: 24
• Publication Date: 2015-06
• Subjects: Identification -- Optimization -- Parallelization -- Shape memory alloys -- Heterogeneous tests; Mechanical engineering -- Periodicals; Génie mécanique -- Périodiques; Mechanical engineering; Maschinenbau; Mechanik; Zeitschrift; Periodicals; 621.05
• DOI: 10.1016/j.ijmecsci.2015.03.007
• Languages: English
• ISSNs: 0020-7403

Abstract

Abstract: With the design of new devices with complex geometry and to take advantage of their large recoverable strains, shape memory alloys (SMA) components 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 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 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 are 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. Abstract : Highlights: Analysis of deformation paths has been performed on Shape Memory Alloys specimens. A robust identification methodology for the material parameters of up to date constitutive model for SMAs is proposed. A parallelized coupled genetic/gradient based algorithm has been developed. The identification methodology is validated based on in-plane strain field obtained from digital image correlation.