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A new approach to study and optimize cooling performance of a Ranque–Hilsch vortex tube
Vortex tube is a simple device usually used to obtain desired hot and cold gas and is widely used for spot cooling in industry. This pipe with its interesting function has been studied using different advanced numerical and experimental methods which are usually complex and expensive. In the current...
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Published in: | International journal of refrigeration 2012-12, Vol.35 (8), p.2339-2348 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Vortex tube is a simple device usually used to obtain desired hot and cold gas and is widely used for spot cooling in industry. This pipe with its interesting function has been studied using different advanced numerical and experimental methods which are usually complex and expensive. In the current study, using a number of CFD simulations to provide interpolation table and define two correlations for the velocity magnitude to the normal velocity, a simple thermodynamic approach is introduced to analyze a vortex tube numerically. The results of the proposed algorithm are verified with the experimental and numerical studies. This approach is a proper method to optimize cooling performance of a vortex tube at different operating conditions. In the current study genetic algorithm is used for optimization. Reasonable results will be obtained if appropriate constraints are applied.
► In the current study a simple thermodynamic approach is introduced to analyze and optimize a vortex tube numerically. ► The investigations show that if only the density at inlet and the two outlets can be estimated then the number of equations and unknown parameters will be equal. ► The densities of flow from more than 30 CFD simulations in several boundary conditions are tabled for each outlet and the inlet. ► Two correlations are also defined for the velocity magnitude to the normal velocity. ► In the current study genetic algorithm is used for optimization. |
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ISSN: | 0140-7007 1879-2081 |
DOI: | 10.1016/j.ijrefrig.2012.08.022 |