Shock-unsteadiness model applied to oblique shock wave/turbulent boundary-layer interaction

Pasha, Amjad Ali; Sinha, Krishnendu

doi:10.1080/10618560802290284

Cited by 49 publications

(47 citation statements)

References 11 publications

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“…The mean flow Mach number and the local shock inclination angle can be obtained from a RANS solution. The shock-normal Mach number and its variation across the boundary layer can thus be computed; see previous work by Sinha et al (2005) and Pasha & Sinha (2008, 2012. On the other hand, the level of temperature fluctuations in a boundary layer and its correlation with the velocity fluctuations is not readily available in a RANS computation.…”

Section: Application To Shock-boundary Layer Interactionsmentioning

confidence: 99%

“…been validated for several supersonic and hypersonic applications (Sinha, Mahesh & Candler 2005;Pasha & Sinha 2008, 2012. The mean flow variables are initialized to a hyperbolic tangent profile centred at the DNS shock location.…”

Section: Effect Of Entropy Fluctuationsmentioning

confidence: 99%

“…It directly influences the extent of flow separation, and therefore determines the topology of shocks and expansion waves generated by the separation bubble. See, for example, the simulation of an oblique shock impinging on a turbulent boundary layer by Pasha & Sinha (2008) and hypersonic cone-flare configurations by Pasha & Sinha (2012). Accurate prediction of the flow topology is essential to obtain the correct variation of surface properties.…”

Section: Introductionmentioning

confidence: 99%

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Evolution of enstrophy in shock/homogeneous turbulence interaction

Sinha

2012

J. Fluid Mech.

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Interaction of turbulent fluctuations with a shock wave plays an important role in many high-speed flow applications. This paper studies the amplification of enstrophy, defined as mean-square fluctuating vorticity, in homogeneous isotropic turbulence passing through a normal shock. Linearized Navier-Stokes equations written in a frame of reference attached to the unsteady shock wave are used to derive transport equations for the vorticity components. These are combined to obtain an equation that describes the evolution of enstrophy across a time-averaged shock wave. A budget of the enstrophy equation computed using results from linear interaction analysis and data from direct numerical simulations identifies the dominant physical mechanisms in the flow. Production due to mean flow compression and baroclinic torques are found to be the major contributors to the enstrophy amplification. Closure approximations are proposed for the unclosed correlations in the production and baroclinic source terms. The resulting model equation is integrated to obtain the enstrophy jump across a shock for a range of upstream Mach numbers. The model predictions are compared with linear theory results for varying levels of vortical and entropic fluctuations in the upstream flow. The enstrophy model is then cast in the form of k-equations and used to compute the interaction of homogeneous isotropic turbulence with normal shocks. The results are compared with available data from direct numerical simulations. The equations are further used to propose a model for the amplification of turbulent viscosity across a shock, which is then applied to a canonical shock-boundary layer interaction. It is shown that the current model is a significant improvement over existing models, both for homogeneous isotropic turbulence and in the case of complex high-speed flows with shock waves.

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Section: Application To Shock-boundary Layer Interactionsmentioning

confidence: 99%

Section: Effect Of Entropy Fluctuationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evolution of enstrophy in shock/homogeneous turbulence interaction

Sinha

2012

J. Fluid Mech.

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“…A wide range of predictions by different turbulence models is available in the literature, including some variants like compressibility corrections, which yield reasonable agreement with experimental data for shock/boundary-layer interaction flows (Brown, 2013;Guohua & Xiaogang, 2012;Marvin et al, 2013;Roy & Blottner, 2006). However, the standard one-equation SA and two-equation turbulence models do not account for the effect of unsteady shock motion, thus performing poorly in the prediction of shock-wave/turbulent boundary-layer interactions (Pasha & Sinha, 2008;Pasha and Sinha, 2012;Sinha, Mahesh, & Candler, 2005). Results obtained using the standard one-equation SA model deviate from experimental data in predicting the extent of the shock induced separated boundary layer and the accompanying peak wall pressure (Marvin et al, 2013;Roy & Blottner, 2006).…”

Section: Introductionmentioning

confidence: 89%

“…DPLR provides enhanced stability over many other types of algorithms because of the strong implicit coupling of the large wall-normal gradients of the boundary layer into the Jacobian matrices. The code has been validated on several supersonic and hypersonic shock/boundary-layer interaction flows (Druguet et al, 2005;Pasha & Sinha, 2008, 2012Sinha et al, 2005;Wright et al, 2000).…”

Section: Simulation Methodologymentioning

confidence: 99%

Numerical prediction of shock/boundary-layer interactions at high Mach numbers using a modified Spalart–Allmaras model

Pasha

Juhany

Khalid

2018

Engineering Applications of Computational Fluid Mechanics

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The Reynolds-averaged Navier-Stokes equations with one-equation turbulence models are used to simulate the flow field past a cone-flare geometry in the Mach number range from 5 to 8 with emphasis on the interaction region of the flare shock with the upstream boundary layer. A model based on the physics of shock unsteadiness is used to correct the standard Spalart-Allmaras turbulence model to improve the prediction of the extent of the separation bubble arising from the shock/turbulent boundary-layer interaction and its accompanying peak pressure and aerothermal loads on the surface. The computed results are validated against the experimental data. The limitations of the shock-unsteadiness model and the extent of the improvement in predicting the heat flux are discussed. ARTICLE HISTORY

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Research on grid‐dependence of neural network turbulence model

Song

Zhang

Sun

et al. 2022

Numerical Methods in Fluids

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Turbulence machine learning based on deep neural network has become a research hotspot in turbulence modeling. Although most turbulence models have strict requirements on grid dependence, there are few analyses on grid dependence on the coupling of models and equations. In this article, a neural network turbulence model is constructed for the flow around airfoil with high Reynolds number, and the effects of wall‐normal grid spacing on the calculation accuracy are studied. The results show that compared with the traditional differential equation turbulence model, the neural network turbulence model can break through the limitation of y+ < 1 and relax the requirement of the normal density of the boundary layer grid while ensuring the accuracy.

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Shock-unsteadiness model applied to oblique shock wave/turbulent boundary-layer interaction

Cited by 49 publications

References 11 publications

Evolution of enstrophy in shock/homogeneous turbulence interaction

Evolution of enstrophy in shock/homogeneous turbulence interaction

Numerical prediction of shock/boundary-layer interactions at high Mach numbers using a modified Spalart–Allmaras model

Research on grid‐dependence of neural network turbulence model

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