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Parameter Identification and Validation of Shape-Memory Polymers within the Framework of Finite Strain Viscoelasticity

Shape-Memory Polymers (SMPs) can be stretched to large deformations and recover induced strains when exposed to an appropriate stimulus, such as heat. This emerging class of functional polymers has attracted much interest and found applications in medicine and engineering. Nevertheless, prior to any...

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Detalles Bibliográficos
Autores principales: Ghobadi, Ehsan, Shutov, Alexey, Steeb, Holger
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8073646/
https://www.ncbi.nlm.nih.gov/pubmed/33921751
http://dx.doi.org/10.3390/ma14082049
Descripción
Sumario:Shape-Memory Polymers (SMPs) can be stretched to large deformations and recover induced strains when exposed to an appropriate stimulus, such as heat. This emerging class of functional polymers has attracted much interest and found applications in medicine and engineering. Nevertheless, prior to any application, their physical and mechanical properties must be thoroughly studied and understood in order to make predictions or to design structures thereof. In this contribution, the viscoelastic behavior of a polyether-based polyurethane (Estane) and its rate- and temperature-dependent behavior have been studied experimentally and by the mean of simulations. The model-inherent material parameters are identified with the assumption of the thermo-rheological complexity. Here, the numerical results of uni-axial stress relaxations were compared with the associated experiments in conjucation with the Levenberg-Marquard optimization method to determine the parameters of the Prony equation. The ability of the model to simulate the thermo-mechanical properties of Estane was evaluated by data-rich experimental observations on tension and torsion in various temperature ranges. Heterogeneous tests are included into the experimental program to cover a broader spectrum of loading scenarios.