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Modeling evolutions of plastic strain, maximum transformation strain and transformation temperatures in SMA under superelastic cycling AITranslate

Tsinghua University; Beihang University; Tsinghua University; Beihang University
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Publisher: Elsevier
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Abstract AITranslate

Highlights • The behaviors of SMA under superelastic cycling are simulated. • The evolution of various strains are considered simultaneously. • The cumulated martensites in forward and reverse transformations are simulated. • The plastic strain are assumed to evolve only in the forward transformation. Experimental investigations on shape memory alloy (SMA) wires subjected to superelastic cycling show significant performance degradations, including the accumulation of the plastic strain, the evolutions of the maximum transformation strain and transformation temperatures. The cyclic degradation of SMAs must be carefully studied and understood when the alloys are used in SMA based actuators and vibration isolators. Motivated by these issues, the present work aims to develop a comprehensive approach for the cyclic behaviors of SMAs taking into account degradations caused by superelastic cycling. The new cyclic constitutive model is constructed in the thermodynamic framework based on the Helmholtz free energy. To account for the evolutions of the plastic strain, the maximum transformation strain and transformation temperatures separately in the forward and reverse transformations, the total cumulated martensite volume fraction is split into two parts: the cumulated martensite volume fraction created in the forward as well as in the reverse transformations. Based on the decomposing, corresponding evolution laws for the plastic strain, maximum transformation strain and transformation temperatures are also constructed. Finally, numerical simulations based on the proposed constitutive model are also performed in our work, and good correlations are observed.

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DOI:https://doi.org/10.1016/j.commatsci.2013.07.022

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Citation Information:

Highlights • The behaviors of SMA under superelastic cycling are simulated. • The evolution of various strains are considered simultaneously. • The cumulated martensites in forward and reverse transformations are simulated. • The plastic strain are assumed to evolve only in the forward transformation. Experimental investigations on shape memory alloy (SMA) wires subjected to superelastic cycling show significant performance degradations, including the accumulation of the plastic strain, the evolutions of the maximum transformation strain and transformation temperatures. The cyclic degradation of SMAs must be carefully studied and understood when the alloys are used in SMA based actuators and vibration isolators. Motivated by these issues, the present work aims to develop a comprehensive approach for the cyclic behaviors of SMAs taking into account degradations caused by superelastic cycling. The new cyclic constitutive model is constructed in the thermodynamic framework based on the Helmholtz free energy. To account for the evolutions of the plastic strain, the maximum transformation strain and transformation temperatures separately in the forward and reverse transformations, the total cumulated martensite volume fraction is split into two parts: the cumulated martensite volume fraction created in the forward as well as in the reverse transformations. Based on the decomposing, corresponding evolution laws for the plastic strain, maximum transformation strain and transformation temperatures are also constructed. Finally, numerical simulations based on the proposed constitutive model are also performed in our work, and good correlations are observed.

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GB/T 7714-2015 [1] Xiaoyong Zhang, Xiaojun Yan, Huimin Xie, et al. Computational Materials Science, 2014(81). DOI:10.1016/j.commatsci.2013.07.022.
MLA [1] Xiaoyong Zhang, et al., Computational Materials Science, no. 81, 2014, https://doi.org/10.1016/j.commatsci.2013.07.022.
APA [1] Xiaoyong Zhang, Xiaojun Yan, Huimin Xie, & Ruijie Sun. (2014). Computational Materials Science(81). https://doi.org/10.1016/j.commatsci.2013.07.022
IEEE [1] Xiaoyong Zhang, Xiaojun Yan, Huimin Xie, and Ruijie Sun, Computational Materials Science, no. 81, 2014, doi: 10.1016/j.commatsci.2013.07.022.