TY - JOUR
T1 - Parallel projection—An improved return mapping algorithm for finite element modeling of shape memory alloys
AU - Kang, Ziliang
AU - Tortorelli, Daniel A.
AU - James, Kai A.
N1 - Funding Information:
This research was supported by the National Science Foundation, USA through Grant Number CMMI1663566 .
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2022/2/1
Y1 - 2022/2/1
N2 - We present a novel finite element analysis of inelastic structures containing Shape Memory Alloys (SMAs). Phenomenological constitutive models for SMAs lead to material nonlinearities, that require substantial computational effort to resolve. Finite element analysis methods, which rely on Gauss quadrature integration schemes, must solve two sets of coupled differential equations: one at the global level and the other at the local, i.e. Gauss point level. In contrast to the conventional return mapping algorithm, which solves these two sets of coupled differential equations separately using a nested Newton procedure, we propose a scheme to solve the local and global differential equations simultaneously. In the process we also derive closed-form expressions used to update the internal/constitutive state variables, and unify the popular closest-point and cutting plane methods with our formulas. Numerical testing indicates that our method allows for larger thermomechanical loading steps and provides increased computational efficiency, over the standard return mapping algorithm.
AB - We present a novel finite element analysis of inelastic structures containing Shape Memory Alloys (SMAs). Phenomenological constitutive models for SMAs lead to material nonlinearities, that require substantial computational effort to resolve. Finite element analysis methods, which rely on Gauss quadrature integration schemes, must solve two sets of coupled differential equations: one at the global level and the other at the local, i.e. Gauss point level. In contrast to the conventional return mapping algorithm, which solves these two sets of coupled differential equations separately using a nested Newton procedure, we propose a scheme to solve the local and global differential equations simultaneously. In the process we also derive closed-form expressions used to update the internal/constitutive state variables, and unify the popular closest-point and cutting plane methods with our formulas. Numerical testing indicates that our method allows for larger thermomechanical loading steps and provides increased computational efficiency, over the standard return mapping algorithm.
KW - Computational inelasticity
KW - Finite element analysis
KW - Parallel projection algorithm
KW - Return mapping algorithm
KW - Shape-memory alloys
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U2 - 10.1016/j.cma.2021.114364
DO - 10.1016/j.cma.2021.114364
M3 - Article
AN - SCOPUS:85121467090
SN - 0374-2830
VL - 389
JO - Computer Methods in Applied Mechanics and Engineering
JF - Computer Methods in Applied Mechanics and Engineering
M1 - 114364
ER -