In this study, we generated polypropylene fibre mats via melt blowing (average diameter:1.03 µm), and then produced self-reinforced composites using hot compaction and investigated the effect of the processing temperature. Scanning electron microscopy (SEM) revealed that our composites had good consolidation, low void content and besides, the fibres and the matrix were clearly distinguishable. The differential scanning calorimetry (DSC) tests showed that the composites are easy to recycle by re-melting. The tensile tests of the melt-blown nonwovens and the produced composites revealed that increasing the temperature of hot compaction results in embrittlement (from ductile to brittle) of the samples, which means higher specific tensile forces and smaller deformations. Using the Fibre Bundle Cells modelling method, we developed a phenomenological, analytical model to describe the total tensile curve (both the deformation and the failure behaviour) and analyse the tensile properties of these hot compacted composites. The determination coefficients (R 2 ) between the modelled and measured force were larger than 0.99 and the relative mean squared error (RMSE) values (related to the measured maximum force 2 value) were smaller than 3% in every examined case, which indicated good modelling. Hence, the FBC model not only described the tensile behaviour of the nonwovens well, but it was also applicable for the composites.
In this study, we modeled the deformation and failure behavior of different glass woven fabrics under uni-axial tension using the Fibre Bundle Cells-modeling method. The difference between the analytical, phenomenological model curve and the mean curve calculated from the measurement results was classified by the relative mean squared error (RMSE), which is closely related to the coefficient of determination. This value was less than 3.6% in all the examined cases, which indicated good modeling.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.