2018
DOI: 10.3390/ma11091746
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A Multiscale Analysis on the Superelasticity Behavior of Architected Shape Memory Alloy Materials

Abstract: In this paper, the superelasticity effects of architected shape memory alloys (SMAs) are focused on by using a multiscale approach. Firstly, a parametric analysis at the cellular level with a series of representative volume elements (RVEs) is carried out to predict the relations between the void fraction, the total stiffness, the hysteresis effect and the mass of the SMAs. The superelasticity effects of the architected SMAs are modeled by the thermomechanical constitutive model proposed by Chemisky et al. 2011… Show more

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Cited by 13 publications
(1 citation statement)
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“…Modern heterogeneous materials like fiber-reinforced [ 2 ] or multimetallic composites [ 3 ] are gaining more and more popularity in engineering structures due to their application-specific tailored properties. To accurately describe their microstructural behavior, numerical methods such as the multiscale finite element method [ 4 , 5 , 6 , 7 ], asymptotic homogenization method [ 8 , 9 , 10 ], coarse-graining technique [ 11 ], and finite element and Fast Fourier Transforms method [ 12 ] have been developed. High-fidelity microstructure material modeling is essential for macroscale structural analysis prediction.…”
Section: Introductionmentioning
confidence: 99%
“…Modern heterogeneous materials like fiber-reinforced [ 2 ] or multimetallic composites [ 3 ] are gaining more and more popularity in engineering structures due to their application-specific tailored properties. To accurately describe their microstructural behavior, numerical methods such as the multiscale finite element method [ 4 , 5 , 6 , 7 ], asymptotic homogenization method [ 8 , 9 , 10 ], coarse-graining technique [ 11 ], and finite element and Fast Fourier Transforms method [ 12 ] have been developed. High-fidelity microstructure material modeling is essential for macroscale structural analysis prediction.…”
Section: Introductionmentioning
confidence: 99%