With applications in the automotive, packaging, and construction industries, natural-fiber composites have gained in relevance over the past few decades as sustainable alternatives to synthetic-fiber composite materials. However, widespread application of natural-fiber composites remains limited due to concerns regarding their durability in high-humidity and wet environments. Previous moisture-related durability research has been empirical in nature. This award will support fundamental research to model the environmentally assisted degradation of natural-fiber composites. The mechanics-based modeling approaches will be used to elucidate relationships between composite composition, hygrothermal exposure, mechanical degradation, and environmental sustainability. The research activities will advance the science and engineering of materials that are fully biorenewable and economically viable on a global scale. The complementary education and outreach efforts will help foster a more inclusive generation of female engineers who will become technical leaders in engineering mechanics and materials sustainability.
The primary objective of this research is to use micromechanics to predict moisture- and frost-induced damage in both short- and continuous-fiber natural-fiber composites that are exposed to fluctuating hygrothermal conditions. In addition to composite synthesis, the experimental work includes meso- and nano-scale mechanical testing to correlate moisture content and temperature with reductions in mechanical properties of fibers, matrices, and composites thereof. The computational work includes formulation of diffusion-based moisture transport models; formulation of micromechanical damage models to account for internal strains from fiber softening and expansion; and model validation using data obtained from the accelerated weathering of composite samples. Once calibrated with experimental data, the mechanics-based service-life models will be used to predict in-situ degradation and to estimate functional obsolescence (end of life) in several applications in a variety of geographic locations. These service-life estimates will be integrated into a probabilistic lifecycle assessment modeling framework to calculate true environmental impacts across variable spatial and temporal domains.
