Fiber reinforced composites are used widely for their high strength and low weight advantages in various aerospace and automotive applications. While their use may be sought after, modeling of these material requires increasing fidelity at the lower scales to capture accurate material behavior under loading. The first steps in creating statistically equivalent models to real life cases is developing a method of rapid evaluation and artificial microstructure generation. The outlined work is capable of tracking microscale fiber positions and determining regions of localized volume fraction extrema (high and low end). Groupings of high and low volume fraction regions are called clusters and their geometry is used to characterize the microstructure. These cluster features can be evaluated for both artificial models and actual scans, allowing correlation to be established which can ultimately be used to regenerate statistically equivalent models. The results of this work show that if one feature is to be correlated, a model can be generated which matches almost exactly. But once more features are equally taken into account, the regeneration loses accuracy.
Micromechanical models of fiber reinforced composites are becoming a main area of research because damage and failure often initiates at small scales. Microscale features such as fiber clusters and matrix pockets are thought to impact failure because they introduce localized stress concentrations and low stiffness regions where cracks propagate easily. The challenge in modelling these features is due to the fidelity required to capture local fiber to fiber interactions. In this study, a generator was used which can tailor microstructures to create fiber clusters and matrix pockets, while still maintaining a degree of randomness. Fiber clusters and matrix pockets were identified by using an algorithm which sorted and filtered neighboring fiber triads. Descriptors were calculated for each microstructure based on the area and number of clusters, as well as local volume fraction distribution. Microstructures were loaded using a reducedorder model which calculated strength and stiffness. Results show the relationship between generator inputs and descriptor outputs, as well as strength and stiffness.
Adhesively bonded composite joints can help reduce weight in structures and avoid material damage from fastener holes, but stress concentrations formed at the edges of the adhesive bond line are a main cause of failure. Stress concentrations within the adhesive can be reduced by lowering the stiffness at these edges and increasing the stiffness in the center of the joint. This may be achieved using a dual-cure adhesive system, where conventional curing is first used to bond a lap joint, after which high energy radiation is applied to the joint to induce additional crosslinking in specific regions. Anhydride-cured epoxy resins have been formulated to include a radiation sensitizer enabling the desired cure behavior. Tensile testing was performed on cured systems containing varying levels of radiation sensitizer in order to evaluate its effects on young’s modulus as a function of radiation dose.
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.