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Proceedings Paper

Iterative calibration of a shape memory alloy constitutive model from 1D and 2D data using optimization methods
Author(s): Daniel Whitten; Darren Hartl
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Paper Abstract

Shape memory alloy constitutive models have been shown to accurately predict 1-D and 3-D material response under general thermomechanical loading. As with any constitutive model, however, the degree to which simulation results match experimental data is dependent on the accurate calibration of model parameters. This work presents a general framework for the identi cation of SMA material parameters using numerical optimization methods and experimental results that include both 1-D data (i.e., stress-strain and strain-temperature line plots) as well as 2-D digital image correlation (DIC) strain eld data. The optimization framework is verified using 1-D and 3-D nite-element-based simulated results as pseudo-experimental data. The study shows that the proposed optimization methods can identify SMA parameters in an automated fashion using data taken from multiple types of experiment, identifying parameters that t very closely to the pseudo-experimental data.

Paper Details

Date Published: 9 March 2014
PDF: 11 pages
Proc. SPIE 9058, Behavior and Mechanics of Multifunctional Materials and Composites 2014, 905804 (9 March 2014); doi: 10.1117/12.2046666
Show Author Affiliations
Daniel Whitten, Texas A&M Univ. (United States)
Darren Hartl, Texas A&M Univ. (United States)

Published in SPIE Proceedings Vol. 9058:
Behavior and Mechanics of Multifunctional Materials and Composites 2014
Nakhiah C. Goulbourne; Hani E. Naguib, Editor(s)

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