To model and examine the thermal fluid phenomena involved in high-pressure, multi-nozzle spray cooling, a testbed is developed which includes a heating subsystem and an accumulator to pressurize common rail based piezoelectric injectors. Compared to conventional platforms, the implemented testbed allows for an abundance of layout arrangements and settings that provide a greater range of functionality. The volumetric flow rate of the testbed is modeled by a recurrent neural network trained from time-sequential obtained through experiments. The fidelity of the model, as well as the testbed's hardware, software, functionalities, and shortcomings are discussed.
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Master of Science in Aerospace Engineering (M.S.A.E.)
College of Engineering and Computer Science
Mechanical and Aerospace Engineering
Aerospace Engineering; Space System Design and Engineering
Length of Campus-only Access
Masters Thesis (Campus-only Access)
Fordon, Andrew, "Recurrent Neural Network Modeling of a Developed Multi-Nozzle, Piezoelectric-Based, Spray Cooling Testbed" (2023). Electronic Theses and Dissertations, 2020-. 1829.
Restricted to the UCF community until August 2028; it will then be open access.