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Cited 2 time in webofscience Cited 2 time in scopus
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All-polymer syntactic foams: Linking large strain cyclic experiments to Quasilinear Viscoelastic modelling for materials characterisationopen access

Authors
Nguyen, Sy-NgocDe Pascalis, RiccardoYousaf, ZeshanParnell, William J.
Issue Date
Jan-2025
Publisher
ELSEVIER SCI LTD
Keywords
Particle-reinforcement; Polymer-matrix composites (PMCs); Stress relaxation; Computational modelling; Mechanical testing
Citation
Composites Part B: Engineering, v.288, pp 1 - 15
Pages
15
Indexed
SCIE
SCOPUS
Journal Title
Composites Part B: Engineering
Volume
288
Start Page
1
End Page
15
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/57807
DOI
10.1016/j.compositesb.2024.111866
ISSN
1359-8368
1879-1069
Abstract
The time-dependent behaviour of polymeric composites is critical in abroad range of applications, including those in marine, aerospace, and automotive environments. In the present study, we assess the validity of the quasi-linear viscoelastic (QLV) model to fit the stress-strain behaviour of all-polymer syntactic foams under large cyclic compressional strain in a novel experimental configuration. These syntactic foams were manufactured by adding hollow polymer microspheres of various sizes and wall thicknesses into a polyurethane matrix. These materials are known for their relatively large initial stiffness, and strong recoverability after large strains. In the QLV model, several strain energy functions (SEFs) were employed, including neoHookean, Ogden type I, and type II. The bulk and shear moduli are presented in the form of a Prony series. By estimating these experimental data using optimisation, the natural viscoelastic material properties and coefficients associated with the SEF were determined. The influence of the microsphere filling fraction was also explored. We show that at the strain rate considered hereof 0.013 s-1, the compressible QLV model coupled with the Ogden-I SEF is capable of providing an excellent fit to experimental data. Critically, this fit can be achieved over a range of cycles via model optimisation to the first cyclic response only.
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