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The overall objective of this research is to develop models to predict drop-size-distribution evolutions due to droplet collisions and coalescence during processing within the miscibility gap of bimetallic liquid-phase-miscibility-gap materials. The individual and collective action of gravitational and nongravitational mechanisms on the relative motion and coalescence of drops are considered.

In resin transfer molding (RTM), the liquid matrix is pumped into the mold to infiltrate a preform assembled in the mold and under compressive stresses. The matrix tends to flow around the preform periphery, along the path(s) of least resistance and arrive at the vents before the entire preform is impregnated, causing the part to be defective. This phenomenon is known as "race tracking." A preform-mold misfit could waste an entire part since recovery from a non-fill is not possible. The primary goal of this research was to develop and demonstrate a practical quantitative method for evaluating the preform-mold fit with the mold closed before the matrix is injected. The preform-mold fit is determined by probing the ready-to-inject mold assembly with nitrogen and collecting the exhaust gas through a series of flow meters located along the periphery of the mold. Experiments have been developed to test the instrumentation and the methodology for the prediction of the characteristics of the resin flow front with satisfactory results.

Computational modeling and simulations involving STEM (science, technology, engineering and mathematics) disciplines are highly interdisciplinary growing out of complex, challenging, multi-domain, multi-component and data intensive application needs of several disciplines and the need for high end computing hardware and software, algorithms and information driven technologies. The research efforts in this project focused on the synergistic coupling of: Computational material science and mechanics of hybrid and light weight polymeric composite structures. Computational multi-scale deformation behavior in metallic material systems. Computational enabling technologies of multi-scale flow simulation investigations with Lattice-Boltzmann equations and finite volume methods; physics based composite process flow. modeling in GPU systems; and probabilistic methods to understand uncertainties in deterministic composite processing flow models.