2018
DOI: 10.1007/s10494-018-9938-y
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A Priori Tests of RANS Models for Turbulent Channel Flows of a Dense Gas

Abstract: Dense gas effects, encountered in many engineering applications, lead to unconventional variations of the thermodynamic and transport properties in the supersonic flow regime, which in turn are responsible for considerable modifications of turbulent flow behavior with respect to perfect gases. The most striking differences for wall-bounded turbulence are the decoupling of dynamic and thermal effects for gases with high specific heats, the liquid-like behavior of the viscosity and thermal conductivity, which te… Show more

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Cited by 6 publications
(2 citation statements)
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“…Density fluctuations are correlated with pressure ones, unlike the perfect gas, where the near-wall streaks correspond directly to high- and low-density fluid. A priori analyses of several RANS models based on these DNS databases was conducted by Sciacovelli, Cinnella & Gloerfelt (2018). If the modelled eddy viscosity behaves in the same manner as for air flows at similar conditions, the agreement with turbulent Prandtl number models is less conclusive due to the reduced thermal boundary layer.…”
Section: Introductionmentioning
confidence: 99%
“…Density fluctuations are correlated with pressure ones, unlike the perfect gas, where the near-wall streaks correspond directly to high- and low-density fluid. A priori analyses of several RANS models based on these DNS databases was conducted by Sciacovelli, Cinnella & Gloerfelt (2018). If the modelled eddy viscosity behaves in the same manner as for air flows at similar conditions, the agreement with turbulent Prandtl number models is less conclusive due to the reduced thermal boundary layer.…”
Section: Introductionmentioning
confidence: 99%
“…Nevertheless, reliable experimental measurements are still difficult to obtain. To this purpose, high-fidelity datasets, as those provided by DNS, represent an effective tool for getting insight into the physics of turbulent dense-gas flows and for the assessment of lower-fidelity models [8].…”
Section: Introductionmentioning
confidence: 99%