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Recurrent Neural Network Modeling of a Developed Multi-Nozzle, Piezoelectric-Based, Spray Cooling Testbed

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.

Identiferoai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2828
Date15 August 2023
CreatorsFordon, Andrew
PublisherSTARS
Source SetsUniversity of Central Florida
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceElectronic Theses and Dissertations, 2020-

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