Optimization of the Composition of a Gas Mixture in a Joule-Thomson Cycle

Mixed gas working fluids can be used within Joule-Thomson devices to achieve a greater refrigeration effect than is possible with a pure substance. Lower temperatures and higher cooling powers can be obtained with appropriate mixtures, resulting in lower operating pressures and mass flow rates. This...

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Published inHVAC&R research Vol. 10; no. 2; pp. 213 - 230
Main Authors Keppler, Florian, Nellis, Gregory, Klein, Sanford A.
Format Journal Article
LanguageEnglish
Published Atlanta Taylor & Francis Group 01.04.2004
Taylor & Francis Ltd
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ISSN1078-9669
2374-4731
1938-5587
2374-474X
DOI10.1080/10789669.2004.10391100

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Abstract Mixed gas working fluids can be used within Joule-Thomson devices to achieve a greater refrigeration effect than is possible with a pure substance. Lower temperatures and higher cooling powers can be obtained with appropriate mixtures, resulting in lower operating pressures and mass flow rates. This paper describes a computational tool that allows the composition of gas mixtures to be optimized for a particular operating condition. Automated optimization algorithms are described, evaluated, and validated for two- and three-component mixtures consisting of nitrogen and various hydrocarbons. A genetic optimization algorithm was found to be the most robust and reliable technique and was adapted to this application. Subsequently, the optimization space was extended to a larger number of components for a range of load temperatures and operating pressures. The performance of optimized hydrocarbon gas mixtures is compared with that of nonflammable hydrofluorocarbon mixtures for a range of load temperatures and supply pressures.
AbstractList Mixed gas working fluids can be used within Joule-Thomson devices to achieve a greater refrigeration effect than is possible with a pure substance. Lower temperatures and higher cooling powers can be obtained with appropriate mixtures, resulting in lower operating pressures and mass flow rates. This paper describes a computational tool that allows the composition of gas mixtures to be optimized for a particular operating condition. Automated optimization algorithms are described, evaluated, and validated for two- and three-component mixtures consisting of nitrogen and various hydrocarbons. A genetic optimization algorithm was found to be the most robust and reliable technique and was adapted to this application. Subsequently, the optimization space was extended to a larger number of components for a range of load temperatures and operating pressures. The performance of optimized hydrocarbon gas mixtures is compared with that of nonflammable hydrofluorocarbon mixtures for a range of load temperatures and supply pressures.
Author Keppler, Florian
Klein, Sanford A.
Nellis, Gregory
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  organization: Solar Energy Lab , University of Wisconsin
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Cites_doi 10.1007/978-1-4757-9047-4_112
10.1007/978-1-4757-9047-4_114
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