Auto-cascade systems is a widely employed in ultra-low refrigeration applications, particularly for preserving medical and biological samples. This cycle works with a mixture composed of refrigerants with distant normal boiling points which are fractionated inside the cycle and create two different currents. One with highest proportion of most volatile component, the one that produces cooling effect, is condensed by using the other in the cascade heat exchanger. This study focuses on the experimental optimization of an auto-cascade plant employing the mixture R-600a/R-1150 [70/30%] for maintaining a set temperature of -80°C in the refrigerated space. Optimization consists of an experimental pressure adjustment by modifying capillary lengths within the system. A theoretic-experimental calculation method is employed for calculating COP, cooling capacity, and uncertainties. These results, along with parameters like plant power consumption, compressor duty cycle, and mass flow, are key factors in the selection of the best-found capillary combination.

Pressure optimization of an R600a-R1150 auto-cascade cycle for ultra-low temperature applications

Giovanni CORTELLA;
2024-01-01

Abstract

Auto-cascade systems is a widely employed in ultra-low refrigeration applications, particularly for preserving medical and biological samples. This cycle works with a mixture composed of refrigerants with distant normal boiling points which are fractionated inside the cycle and create two different currents. One with highest proportion of most volatile component, the one that produces cooling effect, is condensed by using the other in the cascade heat exchanger. This study focuses on the experimental optimization of an auto-cascade plant employing the mixture R-600a/R-1150 [70/30%] for maintaining a set temperature of -80°C in the refrigerated space. Optimization consists of an experimental pressure adjustment by modifying capillary lengths within the system. A theoretic-experimental calculation method is employed for calculating COP, cooling capacity, and uncertainties. These results, along with parameters like plant power consumption, compressor duty cycle, and mass flow, are key factors in the selection of the best-found capillary combination.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1293004
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