Effect of the turbulence modeling in the prediction of heat transfer in suction mufflers.
Number: pap. 1182
Author(s) : RODRIGUES T. T., LINK R.
Summary
The well-grounded knowledge of the available numerical methods is of fundamental importance to get advantage of computational aided design. Concerning compressor development, the employment of Computational Fluid Dynamics is nowadays a must, however, very little attention has been given to the importance of the turbulence modeling in the prediction of flow behavior and, moreover, the heat transfer. The present paper reports an investigation of the turbulence models influence in the heat transfer prediction of the compressor suction system, specifically the suction muffler. The importance of the correct heat transfer modeling in the suction muffler represents great importance for the computation of the volumetric efficiency, additionally, influences significantly the thermal profile and suction valve behavior. In order to present such influence, the turbulent flow and heat transfer is modeled in the suction muffler of a hermetic refrigeration compressor. Several turbulence models are employed, including standard engineering models as the k-e and SST. The results are treated to observe the gas superheating during the flow through the suction muffler, which is performed through the heat flux mapping, outlet suction muffler temperature variations and heat transfer coefficient on muffler walls. Standard care is taken in consideration with a mesh refinement study to reduce numerical uncertainties and with the near wall treatment suitable for each model used in the investigation.
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Details
- Original title: Effect of the turbulence modeling in the prediction of heat transfer in suction mufflers.
- Record ID : 30007591
- Languages: English
- Source: 2012 Purdue Conferences. 21st International Compressor Engineering Conference at Purdue.
- Publication date: 2012/07/16
Links
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Indexing
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Themes:
Compressors;
Heat transfer - Keywords: CFD; Turbulence; Heat transfer; Model; Compressor
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