This ONR-funded project seeks to improve hydrogen-based undersea power by controlling granular segregation in aluminum-water reactors. Utilizing combined gas flow and vibration, we seek to control the rate of segregation of granular particles on the basis of particle size and density. We seek to use these insights not only to power sea vehicles but also to improve the sustainability of mining and the efficiency of pharmaceutical production.
This NSF-funded project seeks to study the dynamics of bubbles in fluidized beds and dense suspensions using magnetic resonance imaging (MRI), advancing MRI techniques as needed to image these flows. Ultimately, we seek to produce rapid, fully 3D images of bubbles as well as the velocity of fluid and particles surrounding the bubbles. The insights from these experiments will be used to improve models of complex bubbly flows for ultimate application to geophysics and engineering systems.
This research project covered by the NSF CAREER Award seeks to utilize controlled gas flow and vibration along with the non-Newtonian rheological properties of granular materials and dense suspensions to control bubble dynamics in a structured manner. We seek to use structuring of flow to control heat and mass transport as well as fluid mixing and segregation of particles. Ultimately, we plan to apply these flows to advance chemical reactors for clean energy and particle separation for sustainable mining.