Heat transfer inside microscale geometries is a complex and a challenging phenomenon. As supercritical fluids display large variations in their properties in the vicinity of the critical point, their usage could be more beneficial than traditional coolants. This numerical study, in two parts, primarily focuses on the physics that drives the enhanced heat transfer characteristics of carbon dioxide (CO2) near its critical state and in its supercritical state. In the first part of the study, the flow of supercritical Carbon Dioxide (sCO2) over a heated surface inside a microchannel of hydraulic diameter 0.3 mm was studied using three-dimensional computational fluid dynamics (CFD) model. The temperature of the heated surface was then compared and validated with available experimental results. Also, the heat transfer coefficients were predicted and compared with experiments. Additionally, the acceleration and pressure drop of the fluid were estimated and it was found that the available correlations for conventional fluids failed to predict the flow characteristics of the CO2 due to its supercritical nature. In the second part of the analysis, a relatively new phenomenon known as the Piston Effect (PE), also known as the fourth mode of heat transfer, was studied numerically inside a microchannel of depth 0.1 mm using a two-dimensional CFD model, and it was found that the adiabatic thermalization caused by PE was significant in microgravity and terrestrial conditions and that the time scales associated with the PE are faster than the diffusion time scales by a factor of 5 to 6400. In addition, this study revealed the presence of PE in laminar forced convective conditions. A new correlation was developed to predict the temperature raise of the bulk fluid that is farthest from the heated surface.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2250 |
| Date | 01 January 2022 |
| Creators | Manda, Uday |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
Page generated in 0.0019 seconds