2018
DOI: 10.1016/j.ijsolstr.2017.12.002
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Computationally-efficient modeling of inelastic single crystal responses via anisotropic yield surfaces: Applications to shape memory alloys

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Cited by 11 publications
(4 citation statements)
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“…Specifically, J 2 based models cannot capture tensioncompression asymmetry; J 2 − I 1 based models can capture tension-compression asymmetry or pressure dependence, and J 2 − J 3 − I 1 based models capture volumetric transformation strain, asymmetry, and pressure dependence. 28,29 Due to the inherent complexity of the model formulations, the authors advise the interested readers to reference the available publications 29,30 for more details regarding the model derivations and implementations. In the following simulation work, a three-dimensional finite element analysis model was developed to match the beam bending boundary value problems.…”
Section: Simulation Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Specifically, J 2 based models cannot capture tensioncompression asymmetry; J 2 − I 1 based models can capture tension-compression asymmetry or pressure dependence, and J 2 − J 3 − I 1 based models capture volumetric transformation strain, asymmetry, and pressure dependence. 28,29 Due to the inherent complexity of the model formulations, the authors advise the interested readers to reference the available publications 29,30 for more details regarding the model derivations and implementations. In the following simulation work, a three-dimensional finite element analysis model was developed to match the beam bending boundary value problems.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…The finite element model consists of 1/4 th of the total structure to represent symmetry along the length and width to reduce computational effort. A combination constitutive model based on the work of Xu et al 18 and Hartl et al 29 is used in this simulation.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…The need to craft an appropriate cost function for optimization is noted as being critical to producing effective results and is emphasized in their work. Other work aimed at creating materials science modeling capabilities suitable for design needs includes the work of Hartl et al [38], who have created an efficient modeling capability aimed at capturing microscale single crystalline shape memory alloy responses needed for design and property optimization. This capability is expected to provide significant efficiency improvements for the analysis of these materials while maintaining robustness in the analysis results.…”
Section: Methodsmentioning
confidence: 99%
“…Many researchers have tried to model the hysteresis behavior. 13–16 Hysteresis as a kind of internal loss of the material behavior emerges between the input and output of smart materials such as piezoelectric, 17 magnetic shape memory alloys (MSMAs), 18 magnetostrictive 19 , and magneto-rheological (MR) dampers. 20 SMAs hysteresis has a particular complexity because of its wide saturation curve and asymmetry in the heating and cooling paths.…”
Section: Introductionmentioning
confidence: 99%