Force and multiple-shape-recovery in shape-memory-polymers under finite deformation torsion-extension

Abstract

This paper presents a general semi-analytic solution for the thermomechanical behavior of shape memory polymer (SMP) in large deformation, based on a thermo-viscoelastic constitutive model. The formulation presented in this paper is suitable for describing shape memory behaviors such as fixed-strain, stress-recovery and stress-free, strain-recovery, as well as for multiple shape memory effect in uniaxial and combined extension-torsion problems. To verify the results, a comparison has been carried out among the proposed formulation results and those of experiments and 3D finite element analysis outcomes. Compared to the finite element analysis, semi-analytical solutions are interesting due to their very low computational cost. It was observed that the solution time for the proposed method is much lower than the computational time needed for the FE analyses (around 1%). Therefore, the presented solution can be employed as an efficient tool for examining the effects of changing any of the material or geometrical parameters on smart structures consisting of SMP components under torsion-extension for their design and optimization, which involves a large number of simulations. Additionally, the proposed solution is suitable for calibrating material parameters in both uni-axial and 3D benchmark problem of torsion-extension.

Constitutive Modeling of multi-stimuli-responsive shape memory polymers with multi-functional capabilities

“…In this way, the reduced time, 𝑡 𝑟 , is defined and the thermal effect is considered by replacing the real time, t, by the reduced time. The relationship between t and 𝑡 𝑟 is usually expressed through shift factor parameter 𝑎 𝑇 as follows [39,40]:…”

“…( 7), the influence of thermal effect is considered. It is noted that the thermo-visco-hyperelastic contribution of the proposed model has been adopted by Westbrook et al [42] and Diani and Arrieta [41,43] and recently solved semi-analytically by Baniasadi et al [39].…”

A comprehensive review on thermomechanical constitutive models for shape memory polymers

“…They used Arrieta et al’s (2014b) model and numerically investigated large deformation of coiled CNT-reinforced SMPs. In addition, recently, a semi-analytical solution for Arrieta et al, model (2014b) was proposed by Baniasadi et al, (2020). In that study, they formulated a thermo-visco-hyperelastoc model similar Arrieta et al, work, and then, time discretized the model and eventually solved a SMP-based cylinder under torsion-extension.…”

“…Thereafter, as mentioned before, Arrieta et al (2014b) proposed a thermo-viscohyperelastic model in large deformation regime which calibrated the model for an acrylate-based SMP as a conventional SMP and for a PFSA as a triple-SMP. Meanwhile, Baniasadi et al, (2020) by means of a semi-analytical solution, investigated a multi-SMP though a thermo-visco-hyperelastic model similar Arrieta et al,’s model. To examine the model capability, similar to Yu et al (2012), they made use of the test results from Xie (2010).…”

Numerical investigation of smart auxetic three-dimensional meta-structures based on shape memory polymers via topology optimization

“…Shape memory polymers (SMPs) are a type of smart materials capable of recovering their original shape from a temporary shape under application of external stimuli, for example, heat, magnetic, electricity, pH, light, and moisture (Baniasadi et al, 2020; Hager et al, 2015; Meng and Li, 2013; Momeni et al, 2017; Xie et al, 2016). Low weight, low cost, high deformability, controllable recovery, biocompatibility, and biodegradability are advantages of SMPs over metallic shape memory materials (Ansari et al, 2019; Li and Wang, 2011; Liu et al, 2007; Roudbarian et al, 2019).…”