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Journal of Materials Science

, Volume 44, Issue 13, pp 3578–3588 | Cite as

Long-term water immersion ageing characteristics of GFRP composites

  • K. BerketisEmail author
  • D. Tzetzis
Article

Abstract

This paper evaluates the water absorption characteristics of glass fibre reinforced polymers after long-term exposure to a hygrothermal environment. In particular, three types of laminates, fabricated using woven and non-crimp triaxial glass fabric with a polyester matrix, were immersed in deionised water baths for 2.5 years (30 months) at temperatures of 43, 65 and 93 °C. In order to assess the effects of through-thickness delaminations on the water absorption characteristics, a series of specimens were impacted prior water immersion with low-velocity impact using three energy levels of 2.5, 5 and 10 J. The changes in the thermo-mechanical properties of laminates after water immersion were examined using the dynamic mechanical thermal analysis (DMTA) technique. The results revealed that the long-term water uptake profiles had no similarities to the classical Fickian absorption behaviour and they were markedly different for each water immersion temperature. At higher temperatures a multi-stage diffusion was observed, which was attributed to the microporosity of the laminates as well as to the osmotically enhanced uptake through the interfaces, with the peak values showing dependency on the type of material system. The impact damage on laminates immersed in water did not cause any marked change in the maximum water absorption level or at the absorption rate compared to the undamaged specimens. DMTA have shown matrix plasticizing effects at 43 °C and some post-curing effects at 65 and 93 °C while the effect of the time of immersion at all temperatures tested resulted in a decrease of the value of storage modulus.

Keywords

Water Absorption Storage Modulus Dynamic Mechanical Thermal Analysis Water Immersion Impact Damage 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Spectrum Labs SAPiraeusGreece
  2. 2.Department of Materials, Queen Mary CollegeUniversity of LondonLondonUK

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