A Phenomenological Model for Turbulent Heat Flux in High-Speed Flows With Shock-Induced Flow Separation

Pathak, Utkarsh; Roy, Sumantra Dutta; Sinha, Krishnendu

doi:10.1115/1.4038760

Cited by 8 publications

(3 citation statements)

References 31 publications

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“…The value of σ, as shown in Equation 4, for the PSP direction at the centerline with respect to the measurem Pathak et al [19] indicated that the constant value of r is questionable for a flow with SIBLS; i.e., the value of r is lower in a strong adverse pressure gradient; the opposite trend may be true in the presence of a favorable pressure gradient. An example (M = 0.83 and λ = 10 • ) of the difference between the PSP and Kulite measurements, ∆(p w /p o ) p-k (= p psp − p kulite /p o ), is shown in Figure 13.…”

Section: Error Analysismentioning

confidence: 99%

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Global Visualization of Compressible Swept Convex-Corner Flow Using Pressure-Sensitive Paint

Chung

Huang

2021

Aerospace

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This study used pressure-sensitive paint (PSP) and determined the surface pressure distributions for a compressible swept convex-corner flow. The freestream Mach numbers were 0.64 and 0.83. The convex-corner angle and swept angle were, respectively, 10–17° and 5–15°. Expansion and compression near the corner apex were clearly visualized. For the test case of shock-induced boundary layer separation, there were greater spanwise pressure gradient and curved shocks. The acquired PSP data agree with the experimental data measured using the Kulite pressure transducers for a subsonic expansion flow. For a transonic expansion flow, the discrepancy was significant. The assumption of a constant recovery factor is not valid in the separation region, and temperature correction for PSP measurements is required.

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Section: Error Analysismentioning

confidence: 99%

“…where T a and M a are, respectively, the temperature and Mach number in the external flow. Note that r depends on the local flow characteristics (subsonic/transonic flow, favorable/adverse pressure gradient) [19]. The error, σ, for all PSP data points with respect to Kulite sensors is calculated by:…”

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confidence: 99%

Global Visualization of Compressible Swept Convex-Corner Flow Using Pressure-Sensitive Paint

Chung

Huang

2021

Aerospace

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“…A similar trend is reported by Pirozzoli et al 35 for a turbulent boundary-layer at Mach 2.25 and Gaviglio 36 for a turbulent boundary-layer at Mach 9.4. Based on our previous work 37 we highlighted that the log-region (0.05< y/δ <0.25) of boundary-layer is most important to model wall heat flux and we take an average value of R uT = −0.7 in our current simulations. We follow the procedure laid out earlier and start with Eq.…”

Section: Effect Of Upstream Velocity Fluctuationmentioning

confidence: 99%

Variable turbulent Prandtl number model applied to hypersonic shock/boundary-layer interactions

Roy

Sinha

2018

2018 Fluid Dynamics Conference

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Interaction of shock waves with turbulent boundary-layers can enhance the surface heat flux dramatically. Reynolds-averaged Navier-Stokes simulations based on constant turbulent Prandtl number often give grossly erroneous heat transfer predictions in SBLI flows. This is due to the fact that the underlying Morkovin's hypothesis breaks down in the presence of shock waves; thus, the turbulent Prandtl number can not be assumed to be a constant. In our recent work (Roy, Pathak and Sinha,AIAA 2017), we developed a new variable turbulent Prandtl number model based on linearized Rankine-Hugoniot conditions applied to shock-turbulence interaction. The turbulent Prandtl number is a function of the shock strength and we proposed a shock function to identify the location and strength of shock waves. The shock function also simulates the post-shock ralaxation of the turbulent heat flux, akin to that observed in canonical shock-turbulence interaction. In this work, we extend the variable turbulent Prandtl number model for hypersonic flows by considering the influence of upstream total temperature fluctuation on turbulent heat flux. The model is combined with the well-validated shock-unsteadiness k-ω model and is used to study eight test cases involving shock/boundary-layer interactions at Mach numbers ranging from 5 to 11. Comparison with experimental data shows significant improvement in the surface heat transfer rate in the interaction region. The shock function is also used to propose a robust form of the existing shock-unsteadiness k-ω model that simplifies the numerical implementation enormously. NomenclatureP r T Turbulent Prandtl number P k Production term of turbulent kinetic energy S ij Symmetric part of mean strain rate tensor S ii Mean dilatation b 1 Shock-unsteadiness damping parameter A uT Correlation between temperature and velocity fluctuations r Density ratio c f Skin friction co-efficient q w Wall heat flux, W/cm 2 δ 0 Boundary-layer thickness upstream of interaction, m k Turbulent kinetic energy, m 2 /s 2 ω Specific dissipation rate of turbulent kinetic energy, s -1 ξ t Instantaneous shock speed, m/s ψ Shock function Subscript ∞ Free-stream condition

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Turbulence modeling of 3D high-speed flows with upstream-informed corrections

Prasad

Gaitonde

2023

Shock Waves

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A Phenomenological Model for Turbulent Heat Flux in High-Speed Flows With Shock-Induced Flow Separation

Cited by 8 publications

References 31 publications

Global Visualization of Compressible Swept Convex-Corner Flow Using Pressure-Sensitive Paint

Global Visualization of Compressible Swept Convex-Corner Flow Using Pressure-Sensitive Paint

Variable turbulent Prandtl number model applied to hypersonic shock/boundary-layer interactions

Turbulence modeling of 3D high-speed flows with upstream-informed corrections

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