The steady-state modeling and optimization of a refrigeration system for high heat flux removal

• Published in: Applied thermal engineering 2010-11, Vol.30 (16), p.2347-2356
• Main Authors: Zhou, Rongliang, Zhang, Tiejun, Catano, Juan, Wen, John T., Michna, Gregory J., Peles, Yoav, Jensen, Michael K.
• Format: Article
• Language: English
• Subjects: Accumulators; Applied sciences; CHF; COP; Energy; Energy. Thermal use of fuels; Engines and turbines; Equipments for energy generation and conversion: thermal, electrical, mechanical energy, etc; Exact sciences and technology; Heat flux; Heat transfer; High heat flux; Liquids; Mathematical analysis; Mathematical models; Optimization; Pareto optimization; Refrigerating engineering; Refrigerating engineering. Cryogenics. Food conservation; Refrigeration; Techniques. Materials; Theoretical studies. Data and constants. Metering; Vapor compression cycle
• ISSN: 1359-4311
• DOI: 10.1016/j.applthermaleng.2010.05.023

Steady-state modeling and optimization of a refrigeration system for high heat flux removal, such as electronics cooling, is studied. The refrigeration cycle proposed consists of multiple evaporators, liquid accumulator, compressor, condenser and expansion valves. To obtain more efficient heat transfer and higher critical heat flux (CHF), the evaporators operate with two-phase flow only. This unique operating condition necessitates the inclusion of a liquid accumulator with integrated heater for the safe operation of the compressor. Due to the projected incorporation of microchannels into the system to enhance the heat transfer in heat sinks, the momentum balance equation, rarely seen in previous vapor compression cycle heat exchangers modeling efforts, is utilized in addition to the mass and energy balance equations to capture the expected significant microchannel pressure drop witnessed in previous experimental investigations. Using the steady-state model developed, a parametric study is performed to study the effect of various external inputs on the system performance. The Pareto optimization is applied to find the optimal system operating conditions for given heat loads such that the system coefficient of performance (COP) is optimized while satisfying the CHF and other system operation constraints. Initial validation efforts show the good agreement between the experimental data and model predictions.