Abstract: Data from a pilot study, in which renewable energy was used for low-temperature subsurface heating in a northern climate, suggests that such an approach may be useful for remediating low permeable soils. Low-temperature soil heating is expected to enhance remediation effectiveness by increasing contaminant volatility, diffusion, desorption, and microbiological activity. Direct and indirect solar energy was harvested with a hybrid photovoltaic/wind electric system. The electrical energy generated by the hybrid renewable energy system was distributed to the subsurface using a control system and wire, then converted to heat energy using a resistive element emplaced in an unsaturated silty layer 2.3m below grade. Renewable energy system performance, soil temperature, and environmental data were collected. Ambient soil temperatures fluctuated seasonally within the silt layer from 4 to 15°C. The small renewable energy system performed as predicted and injected 441 kWh of energy into the soil over the eight-month study. This energy input translated to increased soil temperatures ranging from 7.7 to 19.4°C and from 3.3 to 4.3°C above ambient at distances 0.3 and 0.9m from the heating well, respectively. The system supplied sufficient heat to maintain soil temperatures above ambient even in winter in Vermont, where low direct solar energy was available and sustained low ambient temperatures prevail.
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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).