Abstract: Gas and liquid converging at a microchannel cross junction results in the formation of periodic, dispersed microslugs. This microslug-formation phenomenon has been proposed as the basis for a fuel-injection system in a novel, discrete monopropellant microthruster design for use in next-generation miniaturized satellites. Experimental work by McCabe et al. (“A Micro-Scale Monopropellant Fuel Injection Scheme Using Two-Phase Slug Formation,” Journal of Propulsion and Power, Vol. 27, No. 6, 2012, pp. 1295–1302) demonstrated the ability to generate fuel slugs with characteristics commensurate with the intended application. In this work, numerical modeling and simulation is used to further study this problem and identify the sensitivity of the slug characteristics to key material properties including surface tension, contact angle, and fuel viscosity. These concerns are of practical concern for this application due to the potential for thermal variations and/or fluid contamination during typical operation. For each of these properties, highly stable regions exist where the slug characteristics are essentially insensitive to property variations. Next, a series of three-dimensional simulations were performed to study the effects of channel depth on the slug-formation process. These simulations show that the relative slug volume and the detachment location increase with channel depth. Over the range of depths studied, the relative slug volume increased by up to 20% and the detachment location increased by 10 channel widths. The results demonstrate the impact of three-dimensional effects on the ability of the system to throttle the fuel flow rate to a level necessary for low thrust applications, which will have ramifications on the design and manufacture of the microthruster system.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).