Theses and Dissertations from UMD
Permanent URI for this communityhttp://hdl.handle.net/1903/2
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item Modeling Approaches for Treatment Wetlands(2009) Carleton, James N.; Montas, Hubert J; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Although treatment wetlands can reduce pollutant loads, reliably predicting their performance remains a challenge because removal processes are often complex, spatially heterogeneous, and incompletely understood. Although initially popular for characterizing wetland performance, plug flow reactor models are problematic because their parameters exhibit correlation with hydraulic loading. One-dimensional advective-dispersive-reactive (ADE) models are also inadequate because longitudinal dispersion in wetlands is often non-Fickian as a result of steep velocity gradients. Models that make use of residence time distributions have shown promise in improving performance characterization, particularly when interdependencies of stream-tube scale velocities and reaction rate coefficients are considered (the "DND" approach). However this approach is limited to steady-state conditions, and to an assumption that transverse mixing is nil. This dissertation investigates three aspects of wetland modeling and is organized in a journal paper format. The first paper describes development of a DND model which accommodates non-steady-state conditions. The model processes flow and inlet concentration time series, and calculates as output effluent concentration time series. A version of the code allows optimization of model parameters by minimization of summed squared deviations between predicted and measured effluent concentrations. In example comparisons, model results compare favorably with measured data. The second paper develops an analytical solution to a two-dimensional advective-dispersive-reactive equation, in which all flux terms are expressed as power functions of the transverse dimension. For uniform inlet concentration this idealized heterogeneity model is similar to a DND model, but with the inclusion of transverse diffusion. An example is used to illustrate the beneficial impact that transverse mixing has on reactor performance. The third paper describes development of a model based upon a stochastic interpretation of the ADE. The solution technique that is employed results in a bicontinuum model that for steady-state conditions becomes a weighted sum of two exponential decline functions. For low and intermediate degrees of mixing, model results nicely match those of the corresponding idealized heterogeneity model, and for high mixing they match results of the corresponding one-dimensional ADE. Comparisons against data suggest the bicontinuum model may represent wetland performance better than the DND model in some but not all cases.Item Testing for Differentially Functioning Indicators Using Mixtures of Confirmatory Factor Analysis Models(2009) Mann, Heather Marie; Hancock, Gregory R; Measurement, Statistics and Evaluation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Heterogeneity in measurement model parameters across known groups can be modeled and tested using multigroup confirmatory factor analysis (CFA). When it is not reasonable to assume that parameters are homogeneous for all observations in a manifest group, mixture CFA models are appropriate. Mixture CFA models can add theoretically important unmeasured characteristics to capture heterogeneity and have the potential to be used to test measurement invariance. The current study investigated the ability of mixture CFA models to identify differences in factor loadings across latent classes when there is no mean separation in both the latent and measured variables. Using simulated data from models with known parameters, parameter recovery, classification accuracy, and the power of the likelihood-ratio test were evaluated as impacted by model complexity, sample size, latent class proportions, magnitude of factor loading differences, percentage of noninvariant factor loadings, and pattern of noninvariant factor loadings. Results suggested that mixture CFA models may be a viable option for testing the invariance of measurement model parameters, but without impact and differences in measurement intercepts, larger sample sizes, more noninvariant factor loadings, and larger amounts of heterogeneity are needed to distinguish different latent classes and successfully estimate their parameters.Item Keep it the same: Need for closure and the allure of homogeneous groups with impermeable boundaries(2007-07-17) Schultz, Jeremy Michael; Kruglanski, Arie W.; Psychology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The Need for (cognitive) Closure has been found to predict a "syndrome" of group-centric behaviors in numerous experiments (Kruglanski et al., 2006). This is theorized to be due to a strong desire for social reality, which groups can provide. The present research investigates the requisite conditions in which groups can fulfill this desire for a firm social reality, specifically group boundary impermeability and group homogeneity. It was found that Need for Closure predicted greater liking for the group only when the group was both homogeneous in composition and had impermeable boundaries, but not when only one of these conditions was met. These findings are explained using lay epistemic theory (Kruglanski, 1989).