Flow Boiling of Dielectric Fluids at High Quality in Enhanced Microgaps
Abstract
Ultra-compact two-phase heat exchangers (HXs) are of significant interest in many thermal management applications.Understanding and accurately predicting thermal transport in microgaps#i.e., geometries with hydraulic diameters of 0.1mm to 1 mm#is of great importance because this is the fundamental model of thermal transport in these devices.Fully realizing the benefits of ultra-compact HXs requires two-phase operation at high (at least 50%) qualities. A robust physically based framework formodeling flow boiling in microgaps that can accurately predict dryout and critical heat flux (CHF) would enable the operation of these HXs and other two-phase systems at such high vapor qualities in the slug and annular flow boiling regimes, and enable thermal performance near the inherent limits of two-phase heat transfer.Enhancement features such as micropin or micropillar arrays (with overall dimensions of tens of#m to a few hundred #m) can be incorporated within microgaps to provide additional heat transfer surface area; in three-dimensional chip stacking, such micropins can also provide electrical interconnections between different levels. With only a few recent studies, we have little fundamental understanding of how enhancement features affect flow regimes and boiling in microgaps. Moreover, there is, to our knowledge, no physically based and experimentally validated framework for the prediction of dryout conditions for two-phase flows at high vapor quality in microgaps. Such a framework requires development and evaluation of phase-change models.The objectives of this experimental and numerical research collaboration are therefore to:1) develop a numerical framework to predict critical heat flux (CHF) and boiling flow regimes at high quality in dielectric fluids for enhanced microgaps based upon semi-analytical approaches2) develop and use novel optical measurement techniques to resolvea thin slice of the liquid- vapor interface to quantify film thickness and estimate void fraction in the slug and annular flow boiling regimes. These measurements will validate the numerical framework at high quality.3) evaluate machine learning (ML) approaches for predicting flow regimes and CHF for enhanced surfaces4) delineate the capabilities of structured-illumination fluorescence thermometry (SIFT) to resolve liquid-phase temperature fields and novel optical flow and ML approaches toaccurately identify liquid-vapor interfaces and estimate liquid-phase velocities. Approved for Public Release.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 12, 2023
- Source ID
- N000142312196
Entities
People
- Minami Yoda
Organizations
- Georgia Tech Research Corporation
- Office of Naval Research
- United States Navy