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University of Arkansas, Fayetteville

Mechanical Engineering

Heat Transfer

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Deep Learning Strategies For Pool Boiling Heat Flux Prediction Using Image Sequences, Connor Heo Dec 2021

Deep Learning Strategies For Pool Boiling Heat Flux Prediction Using Image Sequences, Connor Heo

Graduate Theses and Dissertations

The understanding of bubble dynamics during boiling is critical to the design of advanced heater surfaces to improve the boiling heat transfer. The stochastic bubble nucleation, growth, and coalescence processes have made it challenging to obtain mechanistic models that can predict boiling heat flux based on the bubble dynamics. Traditional boiling image analysis relies on the extraction of the dominant physical quantities from the images and is thus limited to the existing knowledge of these quantities. Recently, machine-learning-aided analysis has shown success in boiling crisis detection, heat flux prediction, real-time image analysis, etc., whereas most of the existing studies are …