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A Numerical Method to Model Non-linear Damping Behaviour of Martensitic Shape Memory Alloys

This article investigates the efficiency of hybridizing composites with thin layers of martensitic shape memory alloys for improvement of damping. The non-linear damping behaviour of martensitic shape memory alloys is simulated using a modified version of Masing’s rules. The model was implemented in...

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Detalles Bibliográficos
Autores principales: Haghdoust, Pouya, Lo Conte, Antonietta, Cinquemani, Simone, Lecis, Nora
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6266486/
https://www.ncbi.nlm.nih.gov/pubmed/30400293
http://dx.doi.org/10.3390/ma11112178
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author Haghdoust, Pouya
Lo Conte, Antonietta
Cinquemani, Simone
Lecis, Nora
author_facet Haghdoust, Pouya
Lo Conte, Antonietta
Cinquemani, Simone
Lecis, Nora
author_sort Haghdoust, Pouya
collection PubMed
description This article investigates the efficiency of hybridizing composites with thin layers of martensitic shape memory alloys for improvement of damping. The non-linear damping behaviour of martensitic shape memory alloys is simulated using a modified version of Masing’s rules. The model was implemented in a user subroutine of a finite element code, and validated by a numerical simulation of experimental hysteresis loops at different maximum strain amplitudes. The experimental free decay of hybridized glass fiber reinforced polymer beams was simulated using the finite element model, including the validated model of the investigated materials. The amplitude-dependent damping of the hybrid beams in free decay was reproduced successfully in the numerical analysis and it was proven that the hybridization technique is efficient for improvement of damping.
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spelling pubmed-62664862018-12-17 A Numerical Method to Model Non-linear Damping Behaviour of Martensitic Shape Memory Alloys Haghdoust, Pouya Lo Conte, Antonietta Cinquemani, Simone Lecis, Nora Materials (Basel) Article This article investigates the efficiency of hybridizing composites with thin layers of martensitic shape memory alloys for improvement of damping. The non-linear damping behaviour of martensitic shape memory alloys is simulated using a modified version of Masing’s rules. The model was implemented in a user subroutine of a finite element code, and validated by a numerical simulation of experimental hysteresis loops at different maximum strain amplitudes. The experimental free decay of hybridized glass fiber reinforced polymer beams was simulated using the finite element model, including the validated model of the investigated materials. The amplitude-dependent damping of the hybrid beams in free decay was reproduced successfully in the numerical analysis and it was proven that the hybridization technique is efficient for improvement of damping. MDPI 2018-11-03 /pmc/articles/PMC6266486/ /pubmed/30400293 http://dx.doi.org/10.3390/ma11112178 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Haghdoust, Pouya
Lo Conte, Antonietta
Cinquemani, Simone
Lecis, Nora
A Numerical Method to Model Non-linear Damping Behaviour of Martensitic Shape Memory Alloys
title A Numerical Method to Model Non-linear Damping Behaviour of Martensitic Shape Memory Alloys
title_full A Numerical Method to Model Non-linear Damping Behaviour of Martensitic Shape Memory Alloys
title_fullStr A Numerical Method to Model Non-linear Damping Behaviour of Martensitic Shape Memory Alloys
title_full_unstemmed A Numerical Method to Model Non-linear Damping Behaviour of Martensitic Shape Memory Alloys
title_short A Numerical Method to Model Non-linear Damping Behaviour of Martensitic Shape Memory Alloys
title_sort numerical method to model non-linear damping behaviour of martensitic shape memory alloys
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6266486/
https://www.ncbi.nlm.nih.gov/pubmed/30400293
http://dx.doi.org/10.3390/ma11112178
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