SUBJECT: Ph.D. Dissertation Defense
   
BY: Maxwell Pawlick
   
TIME: Wednesday, July 24, 2024, 9:00 a.m.
   
PLACE: Instructional Center, 115
   
TITLE: An Analytical Model for Oscillating Heat Pipe Performance and Experimental Testing of a Novel Helix-Shaped Design
   
COMMITTEE: Dr. G.P. Peterson, Chair (ME)
Dr. Satish Kumar (ME)
Dr. Srinivas Garimella (ME)
Dr. S. Mostafa Ghiaasiaan (ME)
Dr. Joseph Oefelein (AE)
 

SUMMARY

The research presented focuses on the development and assessment of a novel mechanistic model for oscillating heat pipes (OHPs), also known as pulsating heat pipes (PHPs) and the development of a novel helix-shaped OHP design inspired by insights gained from the model developed. OHPs are passive heat transfer devices with potential applications in fields such as electronics cooling, heat recovery systems, and hypersonic vehicles. Despite their potential, their adoption in industry has been slow due to the lack of reliable design tools. The complex physics governing OHP performance and the need for accurate modeling techniques have hindered the development of such tools. Traditional OHP modeling approaches, ranging from experimental correlations to complex 3D computational models, have had limited success in providing rapid and reliable performance predictions without experimental data. This research aims to develop a mechanistic model capable of predicting the performance of a basic closed-loop OHP design without experimental input. The model is intended to predict temperature profiles and performance trends, allowing designers to narrow down potential OHP designs for further analysis. Insights gained from the model were used to design a novel helix-shaped OHP, which was designed to leverage buoyancy-driven circulation flow for improved performance. The research establishes that analytical modeling methods can significantly enhance the understanding and prediction of OHP performance. The contributions of this study include a comprehensive evaluation of OHP literature, identifying various operating modes that influence performance, developing an analytical framework for understanding some of these modes, and using this framework to develop and test a novel OHP design.