Steadily increasing heat dissipation in electronic devices has generated renewed interest in direct immersion cooling. The ideal heat transfer fluid for direct immersion cooling applications should be chemically and thermally stable, and compatible with the electronic components. These constraints have led to the use of Novec fluids and fluroinerts as coolants. Although these fluids are chemically stable and have low dielectric constants, they are plagued by poor thermal properties. These factors necessitate the development of new heat transfer fluids with improved heat transfer properties and applicability. Computer Aided Molecular Design (CAMD) approach was used in this work to systematically design novel heat transfer fluids that exhibit significantly better properties than those of current high performance electronic coolants. The candidate fluids generated by CAMD were constrained by limiting their boiling points, latent heat of vaporization and thermal conductivity. The selected candidates were further screened using a figure of merit (FOM) analysis. Some of the fluids/additives that have been identified after the FOM analysis include C₄H₅F₃O, C₄H₄F₆O, C₆H₁₁F₃, C₄ H₁₂O₂Si, methanol, and ethoxybutane. The heat transfer performance of these new fluids/fluid mixtures was analyzed through pool boiling and flow boiling experiments. All the fluid mixtures tested showed an improvement in the critical heat flux (CHF) when compared to the base fluid (HFE 7200). A pool boiling model was developed using the phase field method available in COMSOL. Although these simulations are computationally expensive, they provide an alternate solution to evaluate several candidate fluids generated using the CAMD approach.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/50299 |
| Date | 13 January 2014 |
| Creators | Sathyanarayana, Aravind |
| Contributors | Joshi, Yogendra |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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