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Influence of thermal deconsolidation on the anisotropic thermal conductivity of glass fiber reinforced, pre‐consolidated polypropylene sheets used for thermoforming applications
Author(s) -
Längauer Manuel,
Zitzenbacher Gernot,
Heupl Sarah,
Plank Bernhard,
Burgstaller Christoph,
Hochenauer Christoph
Publication year - 2022
Publication title -
polymer composites
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.577
H-Index - 82
eISSN - 1548-0569
pISSN - 0272-8397
DOI - 10.1002/pc.26538
Subject(s) - thermoforming , materials science , composite material , thermal conductivity , composite number , thermoplastic , glass fiber , polypropylene , thermal , thermoplastic composites , anisotropy , physics , quantum mechanics , meteorology
Modeling how thermoplastic composites are processed using thermoforming is a challenging task, and not only due to the heterogenic nature of the material. During the thermoforming processes, the polymeric matrix has to be heated above the softening temperature, enabling the composite to be formed into three‐dimensional parts. As the system mobility increases, thermal deconsolidation takes place, and voids are created or expand within the composite sheet. These voids alter the sheet's material properties and aesthetic characteristics. The formation of gas‐filled voids in the material hinders the heat transport, resulting in longer heating times and inefficient processes. Moreover, such voids invalidate models widely used for processing thermoplastic composites. This study resulted in a novel analytical model that can be applied to calculate the anisotropic thermal conductivity of thermoplastic composites depending on the deconsolidation temperature and the fiber orientation. The model was validated by running hot disk tests on polypropylene reinforced with glass fibers (PP/GF) and applying X‐ray computed tomography to the composite samples. The samples are first consolidated in a hot‐plate press and consecutively deconsolidated in a pressure‐free process. The study findings show that the model is highly accurate within the temperature range relevant to composite processing and will be a useful asset in process modeling.