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Civil-Comp Conferences
ISSN 2753-3239 CCC: 9
PROCEEDINGS OF THE FIFTEENTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY Edited by: P. Iványi, J. Kruis and B.H.V. Topping
Paper 10.8
Fractional Calculus in Describing the Viscoelastic Response of PVB foil M. Ĺ ejnoha
Department of Mechanics, Faculty of Civil Engineering, Czech Technical University in Prague, Czechia M. Šejnoha, "Fractional Calculus in Describing the
Viscoelastic Response of PVB foil", in P. Iványi, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fifteenth International Conference on
Computational Structures Technology", Civil-Comp Press, Edinburgh, UK,
Online volume: CCC 9, Paper 10.8, 2024, doi:10.4203/ccc.9.10.8
Keywords: viscoelasticity, fractional viscoelasticity, Maxwell chain model, laminated
glass, polymer interlayer, PVB foil, rheometer experiment.
Abstract
This paper is concerned with a theoretical description of a polyvinyl butyral (PVB)
foil, which is commonly used as an interlayer of laminated-glass composites. This
polymer exhibits a significant time and temperature-dependent behaviour and can be
effectively described employing the theory of viscoelasticity. The present study concentrated
on the ability of both standard and fractional Maxwell chain models to represent
the polymer behavior observed experimentally. Both models were calibrated
adopting the same set of laboratory data derived with the help of a dynamic shear
rheometer for the selected range of frequencies and temperatures. The time temperatures
superposition principal was exploited to extend the data beyond the allowable
frequency range. The optimal model parameters were then obtained by matching the
measured and theoretically predicted response of the polymer in the framework of
least squares method. We have seen that the model based on fractional calculus not
only requires less number of model parameters but it also provides predictions which
are closer to a real behavior of the examined polymer. This promotes its application
in smoothing the measured data and consequently allows us to extend the measured
domain with a relatively low number of model parameters.
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