The cleaning and dewatering of ultrafine (minus 44 micron) coal slurries is one of the biggest challenges faced by coal industry. Existing commercial technologies cannot produce sellable products from these ultrafine streams; therefore, the industry is forced to discard this potential energy resource to waste impoundments. This practice also has the potential to create an environmental hazard associated with blackwater pollution. To address these issues, researchers at Virginia Tech have worked over the past decade to develop a novel separation process that simultaneously removes both mineral matter and surface moisture from fine coal particles. The first stage of the process uses immiscible non-polar liquids, such as straight chain hydrocarbons, to selectively agglomerate fine coal particles in an aqueous medium. The agglomerates are then passed second stage of processing where mild agitation is used to disperse and fully engulf hydrophobic coal particles into the non-polar liquid and to simultaneously reject any residual water and associated hydrophillic minerals entrapped in the agglomerates. The non-polar liquid, which has a low heat of evaporation, is then recovered by evaporation/condensation and recycled back through the process. The research work described in this document focused on the engineering development of this innovative process using batch laboratory and continuous bench-scale systems. The resulting data was used to design a proof-of-concept (POC) pilot-scale plant that was constructed and successfully demonstrated using a variety of fine coal feedstocks. / Ph. D.

Electoral geographers are mostly concerned with mapping the responses of voters to different political candidates, while they also work to explain the factors that influence those responses. Yet most studies do not consider how different geographic contexts can affect the political perceptions of voters. In particular, people who live in close proximity to one another may come to embrace similar beliefs and values, while broader social and economic processes may divide these individuals into separate camps. Thus, electoral studies performed at the local level may produce different results than those done at the regional or national level. In exploring how different scales of analysis can give different interpretations of voting patterns, this research gathered data from a series of elections that took place in Virginia. These elections, which occurred between 2003 and 2006, span a variety of federal and state offices, with each presiding over a certain geographic jurisdiction. The study proceeded to map the results of each election in terms of three different types of geographic areas: precincts, counties, and legislative districts. The maps displayed the majority winners within each of these areas, giving a rough indication of the bases of support for each of the different candidates. The study then determined the number of instances where two neighboring areas both favored the same candidate, as well as the number of cases where they voted for opposing candidates. These data helped to shed light on the autocorrelation structure of voting patterns in Virginia, revealing how people in the same general vicinity tend to vote together. Overall, the results of this study demonstrate that smaller geographic units (e.g., precincts) exhibit greater autocorrelation in voting than do larger areas. This observation agrees with the concept of sectionalism, which asserts that location and culture are key influences on voting behavior. However, the data also suggest that class differences are a major source of electoral cleavage, as people from different social and economic backgrounds tend to settle in different areas. The use of multiple scales of analysis thus presents multiple explanations for the voting trend of a given location. / Master of Science

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Depression is a common, debilitating disorder that is often treated using behavioral activation (BA), which includes identification and scheduling of pleasant activities. Owning a pet appears to be a viable source of pleasant activities, though current BA tools do not extensively consider these activities. The present study aimed to develop the Pet-Related Events and Tasks Scale (PETS) to determine what activities of pet ownership are pleasant and may be used in BA. Various methods were used to generate items (i.e., focus groups, surveys, and adaptation of existing event schedule items) and revise the developing PETS (i.e., cognitive interviews and expert review). Initial data collection on the developing PETS resulted in a small, homogeneous sample that concluded prematurely due to changes in engagement in pet-related activities due to the COVID-19 pandemic stay-at-home orders. Despite limited data collection, various future directions exist for the developing PETS.