Topology optimization for energy dissipation structures based on shape memory alloys

Jie Hou, Chang Wei, Jie Wang, Xiaojun Gu, Jihong Zhu, Weihong Zhang

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Shape memory alloys (SMA) are an ideal class of metallic materials for reusable energy dissipation structures because of pseudo-elasticity. This paper presents a density-based topology optimization framework for the design of SMA structures utilizing pseudo-elastic behaviors to dissipate large amounts of energy under prescribed design constraints. A phenomenological constitutive model is adopted to accurately simulate the mechanical behaviors of SMA, and the corresponding material interpolation scheme is developed via SIMP method. Numerical instability caused by excessive distortion of low-density elements is alleviated by super element method. The degree of phase transformation, which is related to the energy dissipation, is characterized by strain energy and end compliance. Sensitivities are derived via adjoint method. A number of optimized simple-supported beam structures and 2D lattice structures with different energy dissipation performance and stiffness capacity are tailored. In addition, the load dependency and initial design dependency for the optimization of SMA energy dissipation structures are discussed.

Original languageEnglish
Article number55
JournalStructural and Multidisciplinary Optimization
Volume66
Issue number3
DOIs
StatePublished - Mar 2023

Keywords

  • Energy dissipation
  • Lattice structures
  • Material and geometric nonlinearity
  • Shape memory alloys
  • Topology optimization

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