Drift-free magnetic geometries in adiabatic

A class of two-dimensional drift-free fields, somewhat resembling the configuration found in the geomagnetic tail, is described; several proofs of the drift-free property are given, including some that suggest that the property of vanishing net drift might extend to nonadiabatic orbits. A general criterion for identifying drift-free fields was developed, and a case of motion in a nearly drift-free field was also investigated. The theory was applied to the plasma sheet in the earth's magnetotail, and observational evidence is presented suggesting that the magnetic field there does approach a drift-free configuration

Simulation of electrostatic ion instabilities in the presence of parallel currents and transverse electric fields

A spatially two-dimensional electrostatic PIC simulation code was used to study the stability of a plasma equilibrium characterized by a localized transverse dc electric field and a field-aligned drift for L is much less than Lx, where Lx is the simulation length in the x direction and L is the scale length associated with the dc electric field. It is found that the dc electric field and the field-aligned current can together play a synergistic role to enable the excitation of electrostatic waves even when the threshold values of the field aligned drift and the E x B drift are individually subcritical. The simulation results show that the growing ion waves are associated with small vortices in the linear stage, which evolve to the nonlinear stage dominated by larger vortices with lower frequencies

Properties of the spokes in coaxial and parallel - Plate plasma accelerator

Photographic, magnetic, and spectroscopic study of vortex spokes in coaxial and parallel-plate plasma accelerator

WATERFRONT REGENERATION: Mediating Boundaries of Abandonment Along the Hudson River

The edge between city + water has become a divide. This thesis addresses this edge that has been thickened by abandoned industry and challenges the way we design for our changing waterfronts through a design approach relying on specificity of place. The design proposal shows how the water/city divide can become a connective threshold, how industrial landscapes can be reclaimed, and how this place-specific investigation can be an example to learn from through Westchester County’s Hudson River Waterfront, the City of Yonkers, and the abandoned Glenwood Power Plant. This method has resulted with the integration of building into landscape so that it acts as part of a new infrastructure which cleans water, supports urban agriculture, and provides recreational and training opportunities for the surrounding community. Flows have been re-purposed to knit connections in all axes, and begin to heal water’s edge

Reconnecting Neighborhoods: Carroll Creek & The Communities of Frederick, MD

Final project for ARCH700: Graduate Urban Design Studio (Fall 2014). School of Architecture, Planning and Preservation, University of Maryland, College Park.Frederick, Maryland is a unique and beautiful city, rich in history and steeped in historic architecture. Situated at the foothills of the Catoctin Mountains, the City is a robust employment center. Its location within forty miles of Baltimore and Washington D.C., allows Frederick residents to commute to jobs in these cities and their outer suburbs. Founded in 1745, Frederick possesses a rich texture of historic residential, commercial and civic architecture. The city is principally defined by Market Street, the main commercial spine of the city, and by Carroll Creek. Carroll Creek crosses Market Street at a low point, passes through Baker Park and residential neighborhoods on the City’s west side, and terminates in the light industrial areas on the east. In the 1970’s, Carroll Creek flooded twice, devastating the commercial enterprises in the downtown and causing great hardship to the regional economy. In an effort to reduce the risk to downtown Frederick and restore economic vitality to the historic commercial district, the City built Carroll Creek Park. This project provides flood control and protects the downtown while offering new public outdoor space and civic amenities. Today, more than $150 million in private investments are underway or planned in new construction, infill development or historic renovation in the park area. The first phase of the park improvements total nearly$11 million in construction. New elements to the park include brick pedestrian paths, water features, shade trees and plantings, pedestrian bridges, and a 350-seat amphitheater for outdoor performances. The Carroll Creek project has been a tremendous success for the City as a rebirth of the downtown is underway.The City of Frederic

Dynamic Attractors and Basin Class Capacity in Binary Neural Networks

The wide repertoire of attractors and basins of attraction that appear in dynamic neural networks not only serve as models of brain activity patterns but create possibilities for new computational paradigms that use attractors and their basins. To develop such computational paradigms, it is first critical to assess neural network capacity for attractors and for differing basins of attraction, depending on the number of neurons and the weights. In this paper we analyze the attractors and basins of attraction for recurrent, fully-connected single layer binary networks. We utilize the network transition graph - a graph that shows all transitions from one state to another for a given neural network - to show all oscillations and fixed-point attractors, along with the basins of attraction. Conditions are shown whereby pairs of transitions are possible from the same neural network. We derive a lower bound for the number of transition graphs possible 2n2- n , for an n-neuron network. Simulation results show a wide variety of transition graphs and basins of attraction and sometimes networks have more attractors than neurons. We count thousands of basin classes - networks with differing basins of attraction - in networks with as few as five neurons. Dynamic networks show promise for overcoming the limitations of static neural networks, by use of dynamic attractors and their basins. We show that dynamic networks have high capacity for basin classes, can have more attractors than neurons, and have more stable basin boundaries than in the Hopfield associative memory