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TTS package: Computational tools for the application of the Time Temperature Superposition principle

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http://hdl.handle.net/2183/34346
Atribución-NoComercial-SinDerivadas 3.0 España
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Title
TTS package: Computational tools for the application of the Time Temperature Superposition principle
Author(s)
Meneses Freire, Antonio
Naya, Salvador
Francisco-Fernández, Mario
López-Beceiro, Jorge
Gracia-Fernández, Carlos
Tarrío-Saavedra, Javier
Date
2023
Citation
Meneses, A. et al. (2023) ‘TTS package: Computational tools for the application of the time temperature superposition principle’, Heliyon, 9(5). doi:10.1016/j.heliyon.2023.e15816.
Abstract
[Abstract]: The TTS package has been developed in R software to predict the mechanical properties of viscoelastic materials, at short and long observation times/frequencies by applying the Time Temperature Superposition (TTS) principle. TTS is a physical principle used in material science to estimate mechanical properties beyond the experimental range of observed times/frequencies by shifting data curves obtained at other temperatures relative to a reference temperature in the dataset. It is a methodology related to accelerated life-tests and reliability, whereas the TTS library is one of the first open source computational tool to apply the TTS principle. This R package provides free computational tools to obtain master curves that characterize materials from a thermal-mechanical approach. The TTS package also proposes, implements and explains our own method to obtain the shift factors and the master curve in a TTS analysis, based on horizontal shifting of the first derivative function of viscoelastic properties. This procedure provides shift factors estimates and smooth master curve estimates using B-spline fitting, in a fully automatic way, without assuming any parametric expression. Williams-Landel-Ferry (WLF) and Arrhenius TTS parametric models are also implemented in the TTS package. They can be fitted from shifts obtained by the our first derivative based method.
Keywords
Time Temperature Superposition
Thermal analysis
Statistical modeling
R software
 
Editor version
https://doi.org/10.1016/j.heliyon.2023.e15816
Rights
Atribución-NoComercial-SinDerivadas 3.0 España
 
https://creativecommons.org/licenses/by-nc-nd/4.0/
 
ISSN
2405-8440

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