An examination of initial structural degradation in tubular braided composites through region-by-region strain analysis.

The objective of this study was to characterize the early structural degradation behavior of tubular braided composites (TBCs) under quasi-static tension through direct quantification of the surface strains developed in their yarn-reinforced and unreinforced (resin-rich) material regions. Kevlar-epoxy TBCs with varying braid angles and numbers of yarns were analyzed through quasi-static testing and stereo digital image correlation (DIC) analysis to understand how the yarnreinforced and resin-rich regions deformed under tensile loads up to the initiation of structural degradation within the braid structure. Structural weakening was confirmed to initiate in the unreinforced, resin-rich regions of the TBC specimens by way of a normal tensile failure mode, as the strains developed within these regions were the first to deviate from a linear-elastic growth trend and also exceed the expected strain to failure of their constituent material. Through two-way full-factorial ANOVA analysis with a 95% confidence interval, the stress required to initiate degradation within these regions was found to depend significantly upon both the quantity and angular orientation of the preform yarns, the former to a markedly lower extent. The maximum strain accumulated in the resin-rich regions upon their degradation was found to not statistically depend on either of these parameters, affirming that it is purely defined by the strength properties of the constituent neat resin material. To provide conservative and repeatable estimates of the stress to failure in TBC structures, it is recommended that this quantity be estimated from both the global stress-strain data of the entire specimen and the local stress-strain data measured exclusively within its resin-rich regions, with the lower of the two taken. Through these means, the relationship between a TBC's preform geometry and its stress to failure may be optimally modeled using a polynomial regression trend. [ABSTRACT FROM AUTHOR]

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