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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2013 - 20152

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    Dynamic Modeling of Vapor Compression Systems for Residential Heat Pump Applications with Alternative Low-GWP Refrigerants
    (2015) Bhanot, Viren; Hwang, Yunho; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    With the increased focus on reducing greenhouse gas emissions, low-GWP refrigerants, R32 and D2Y60, have been proposed as drop-in replacements for R410A in residential heat pumps. This thesis presents the development of a modeling framework in Simulink® for the dynamic simulations of such residential heat pumps. The framework is component-based, allowing arbitrary cycle configurations, and includes most of the relevant components. Finite-volume method has been applied to the heat exchanger. Compression and expansion processes are treated as quasi-steady state. The framework has been used to study the performance of the system using the baseline refrigerant and charge-optimized alternatives at ASHRAE test conditions, and the results have been compared against experimental data. Steady-state COP values fall within ±8% of experimental data. For the cyclic tests, the pressure and temperature behaviors compare well and accumulated capacity and power consumption errors are found to be within ±9%. Relative differences between the refrigerants are consistent between simulations and measurements. The framework shows potential for being used to simulate the operation of residential heat pumps under dynamic conditions.
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    Scalable Fast Multipole Methods on Heterogeneous Architecture
    (2013) Hu, Qi; Duraiswami, Ramani; Gumerov, Nail A.; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The N-body problem appears in many computational physics simulations. At each time step the computation involves an all-pairs sum whose complexity is quadratic, followed by an update of particle positions. This cost means that it is not practical to solve such dynamic N-body problems on large scale. To improve this situation, we use both algorithmic and hardware approaches. Our algorithmic approach is to use the Fast Multipole Method (FMM), which is a divide-and-conquer algorithm that performs a fast N-body sum using a spatial decomposition and is often used in a time-stepping or iterative loop, to reduce such quadratic complexity to linear with guaranteed accuracy. Our hardware approach is to use heterogeneous clusters, which comprised of nodes that contain multi-core CPUs tightly coupled with accelerators, such as graphics processors unit (GPU) as our underline parallel processing hardware, on which efficient implementations require highly non-trivial re-designed algorithms. In this dissertation, we fundamentally reconsider the FMM algorithms on heterogeneous architectures to achieve a significant improvement over recent/previous implementations in literature and to make the algorithm ready for use as a workhorse simulation tool for both time-dependent vortex flow problems and for boundary element methods. Our major contributions include: 1. Novel FMM data structures using parallel construction algorithms for dynamic problems. 2. A fast hetegenenous FMM algorithm for both single and multiple computing nodes. 3. An efficient inter-node communication management using fast parallel data structures. 4. A scalable FMM algorithm using novel Helmholz decomposition for Vortex Methods (VM). The proposed algorithms can handle non-uniform distributions with irregular partition shapes to achieve workload balance and their MPI-CUDA implementations are highly tuned up and demonstrate the state of the art performances.