Theses and Dissertations from UMD
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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 NEXT GENERATION HEAT PUMP SYSTEM EVALUATION METHODOLOGIES(2021) Wan, Hanlong; Radermacher, Reinhard K.; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Energy consumption of heat pump (HP) systems plays a significant role in the global residential building energy sector. The conventional HP system evaluation method focused on the energy efficiency during a given time scale (e.g., hourly, seasonally, or annually). Nevertheless, these evaluation methods or test metrics are unable to fully reflect the thermodynamic characteristics of the system (e.g., the start-up process). In addition, previous researchers typically conducted HP field tests no longer than one year period. Only limited studies conducted the system performance tests over multiple years. Furthermore, the climate is changing faster than previously predicted beyond the irreversible and catastrophic tipping point. HP systems are the main contributor to global warming due to the increased demands but also can be a part of the solution by replacing fossil fuel burning heating systems. A holistic evaluation of the HP system’s global warming impact during its life cycle needs to account for the direct greenhouse gas (GHG) emissions from the refrigerant leakage, indirect GHG emissions from the power consumption and embodied equipment emissions. This dissertation leverages machine learning, deep learning, data digging, and Life Cycle Climate Performance (LCCP) approaches to develop next generation HP system evaluation methodologies with three thrusts: 1) field test data analysis, 2) data-driven modeling, and 3) enhanced life cycle climate performance (En-LCCP) analysis. This study made following observations: First, time-average performance metrics can save time in extensive data calculation, while quasi-steady-state performance metrics can elucidate some details of the studied system. Second, deep-learning-based algorithms have higher accuracy than conventional modeling approaches and can be used to analyze the system's dynamic performance. However, the complicated structure of the networks, numerous parameters needing optimization, and longer training time are the main challenges for these methods. Third, this dissertation improved current environmental impact evaluation method considering ambient conditions variation, local grid source structure, and next-generation low-GWP refrigerants, which led the LCCP results closer to reality and provided alternative methods for determining LCCP input parameters with limited-data cases. Future work could be studying the uncertainty within the deep learning networks and finding a general process for modeling settings. People may also develop a multi-objective optimization model for HP system design while considering both the LCCP and cost.Item THE CREATION, EVOLUTION , AND DEGRADATION OF THERAPEUTIC LANDSCAPE DURING THE 19TH AND 20TH CENTURIES IN THE UNITED STATES(2017) Mabadi, Reza; Cook, Kelly Dianne; Plant Science and Landscape Architecture (PSLA); Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)During the 18th and 19th centuries, planners, and medical reformists emphasized the restorative effects of natural settings in healthcare facilities. Then, in the 19th and 20th centuries, many hospitals campuses across the United States extensively applied therapeutic landscapes in their designs. While the architectural history of hospitals has been studied thoroughly, the gardens of healthcare institutions have not been independently investigated. In the 20th century, socio-cultural changes and modern technologies caused a degradation of therapeutic landscapes in hospitals. Today, new approaches to medicine and health necessitate a reexamination and reinvention of hospital landscapes in order to better align hospital atmospheres with modern healthcare goals. The goal of this dissertation research is to understand the transformation of hospital landscapes, their evolution and degradation within their socio-cultural context during the 19th and 20th centuries in the United States. This study will also addresses the broad concept of therapeutic landscapes and holistic approaches to using hospital gardens for restorative purposes. Therefore, this research aims to redefine the therapeutic landscape in healthcare facilities by proposing ideas to expand their socio – cultural capacities and extend their therapeutic properties beyond conventional practice. This research hypothesizes that throughout the 19th and 20th centuries in the United States, the therapeutic landscape in hospitals was degraded, and that the reemergence of conventional landscape practices is insufficient to address the whole healing properties of hospital sites. To achieve the stated goal, this research applied a qualitative approach through a case study method. Data collection was conducted via a triangulation strategy, and included semi- structural interviews, content analysis, and an extensive literature review. In analyzing the collected data, I used thick description, spatial-comparative analysis, and content analysis integrated into a holistic framework, in order to examine both historical and modern practices. Analysis of results concluded that throughout the 19th and 20th centuries, the therapeutic hospital landscapes in the United States became degraded due to the introduction of new technologies. In addition, the reemergence of conventional landscape practices, such as small healing gardens, does not fully address the restorative potential of hospital sites. Therefore, many new possibilities need to be explored and implemented.