A three-dimensional finite-strain phenomenological model for shape-memory polymers: Formulation, numerical simulations, and comparison with experimental data

Boatti, Elisa; Scalet, Giulia; Auricchio, Ferdinando

doi:10.1016/j.ijplas.2016.04.008

Cited by 58 publications

(49 citation statements)

References 54 publications

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“…Particularly, Young's moduli for the glassy and rubbery phases, respectively, E g and E r , were defined from the data presented in Figure 3a, and 3b, respectively; Poisson's coefficients for the glassy and rubbery phases, respectively, ν g and ν r , were taken from ref. [34]; transformation temperature, θ t , was calibrated from values shown in Figure 1b; the parameter defining half-width of the temperature range, ∆θ, and the transformation coefficient, w, were chosen taking into account that both inks are in a fully amorphous phase at 60 • C; the plastic hardening coefficient, h, and the stress limit, R p g , for plastic yielding of the glassy phase were calibrated from the stress-strain relationships below the transition temperature (see Figures S1 and S5) and above the transition temperature ( Figures S7 and S11). No imperfect material behavior was assumed.…”

Section: Resultsmentioning

confidence: 99%

“…The geometry was meshed by using eight-node linear isoparametric hexahedral elements with full integration. The thermo-mechanical response of the pure and mixed inks was captured by using the three-dimensional finite-strain constitutive model for SMPs, as proposed in [34]. Specifically, the model is based on a phase transition approach and formulated within a thermodynamically consistent mathematical framework.…”

Section: Smp Behavior Characterizationmentioning

confidence: 99%

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Multi-Material 3D Printed Shape Memory Polymer with Tunable Melting and Glass Transition Temperature Activated by Heat or Light

et al. 2020

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Shape memory polymers are attractive smart materials that have many practical applications and academic interest. Three-dimensional (3D) printable shape memory polymers are of great importance for the fabrication of soft robotic devices due to their ability to build complex 3D structures with desired shapes. We present a 3D printable shape memory polymer, with controlled melting and transition temperature, composed of methacrylated polycaprolactone monomers and N-Vinylcaprolactam reactive diluent. Tuning the ratio between the monomers and the diluents resulted in changes in melting and transition temperatures by 20, and 6 °C, respectively. The effect of the diluent addition on the shape memory behavior and mechanical properties was studied, showing above 85% recovery ratio, and above 90% fixity, when the concentration of the diluent was up to 40 wt %. Finally, we demonstrated multi-material printing of a 3D structure that can be activated locally, at two different temperatures, by two different stimuli; direct heating and light irradiation. The remote light activation was enabled by utilizing a coating of Carbon Nano Tubes (CNTs) as an absorbing material, onto sections of the printed objects.

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Section: Resultsmentioning

confidence: 99%

Section: Smp Behavior Characterizationmentioning

confidence: 99%

Multi-Material 3D Printed Shape Memory Polymer with Tunable Melting and Glass Transition Temperature Activated by Heat or Light

et al. 2020

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“…In the last example of this paper, we demonstrate the robustness of the proposed SPH algorithm on a complex geometry displayed in Figure 28. As reported in Reference [61], the geometry used in this example is a simplified version of a cardiovascular stent used in biomedical applications. The structure has an initial outer diameter of 20 mm, a thickness of 0.5 mm and a total length of 20 mm.…”

Section: Complex Geometrymentioning

confidence: 99%

A Total Lagrangian upwind Smooth Particle Hydrodynamics algorithm for large strain explicit solid dynamics

Lee

Gil

Ghavamian

et al. 2019

Computer Methods in Applied Mechanics and Engineering

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In previous work [1, 2], Lee et al. introduced a new Smooth Particle Hydrodynamics (SPH) computational framework for large strain explicit solid dynamics with special emphasis on the treatment of near incompressibility. A first order system of hyperbolic equations was presented expressed in terms of the linear momentum and the minors of the deformation, namely the deformation gradient, its co-factor and its Jacobian. Taking advantage of this representation, the suppression of numerical deficiencies (e.g. spurious pressure, long term instability and/or consistency issues) was addressed through well-established stabilisation procedures. In Reference [1], the adaptation of the very efficient Jameson-Schmidt-Turkel algorithm was presented. Reference [2] introduced an adapted variationally consistent Streamline Upwind Petrov Galerkin methodology. In this paper, we now introduce a third alternative stabilisation strategy, extremely competitive, and which does not require the selection of any user-defined artificial stabilisation parameter. Specifically, a characteristic-based Riemann solver in conjunction with a linear reconstruction procedure is used, with the aim to guarantee both consistency and conservation of the overall algorithm. We show that the proposed SPH formulation is very similar in nature to that of the upwind vertex centred Finite Volume Method presented in [3]. In order to extend the application range towards the incompressibility limit, an artificial compressibility algorithm is also developed. Finally, an extensive set of challenging numerical examples is analysed. The new SPH algorithm shows excellent behaviour in compressible, nearly incompressible and truly incompressible scenarios, yielding second order of convergence for velocities, deviatoric and volumetric components of the stress.

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“…Based on the abovementioned meso-mechanical method with a mixture rule, a threedimensional model was proposed for TSMPs [48], which distinguishes between two phases presenting different properties. The model can reproduce both heating-stretching-cooling and cold drawing shape-fixing procedures and was applied in the simulations from simple uniaxial and biaxial tests to complex loadings of biomedical devices.…”

Section: Meso-mechanical Modelmentioning

confidence: 99%

Experiments and Models of Thermo-Induced Shape Memory Polymers

Kan¹,

Li²,

Kang³

et al. 2018

Shape-Memory Materials

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Recent advances in experiments and models of thermo-induced shape memory polymers (TSMPs) were reviewed. Some important visco-elastic and visco-plastic features, such as rate-dependent and temperature-dependent stress-strain curves and nonuniform temperature distribution were experimentally investigated, and the interaction between the mechanical deformation and the internal heat generation was discussed. The influences of loading rate and peak strain on the shape memory effect (SME) and shape memory degeneration of TSMPs were revealed under monotonic and cyclic thermo-mechanical loadings, respectively. Based on experimental observations, the capability of recent developed visco-elastic and visco-plastic models for predicting the SME was evaluated, and the thermo-mechanically coupled models were used to reasonably predict the thermomechanical responses of TSMPs.

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A three-dimensional finite-strain phenomenological model for shape-memory polymers: Formulation, numerical simulations, and comparison with experimental data

Cited by 58 publications

References 54 publications

Multi-Material 3D Printed Shape Memory Polymer with Tunable Melting and Glass Transition Temperature Activated by Heat or Light

Multi-Material 3D Printed Shape Memory Polymer with Tunable Melting and Glass Transition Temperature Activated by Heat or Light

A Total Lagrangian upwind Smooth Particle Hydrodynamics algorithm for large strain explicit solid dynamics

Experiments and Models of Thermo-Induced Shape Memory Polymers

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