A prediction method for high speed turbulent separated flows with experimental verification

Lindblad, I.; Wallin, Stefan; Johansson, A.; Friedrich, Rainer; Lechner, Richard; Krogmann, P.; Schuelein, Erich; Courty, Jean-Claude; Ravachol, M.; Giordano, D.

doi:10.2514/6.1998-2547

Cited by 12 publications

(5 citation statements)

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“…Lenahan 23 used NASA's Wind-US solver with both the Spalart-Allmaras and SST turbulence models. Lindblad et al 24 used an Explicit Algebraic Reynolds Stress Model (EARSM) and Fedorova and Fedorchenko 13 extended the work by investigating the effects of external turbulence and the separated shock unsteadiness for the G14 case. Brown 11 used NASA's DPLR production solver with Spalart-Allmaras, k-ω, and SST turbulence models.…”

Section: A 2-d Impinging Swtblimentioning

confidence: 98%

Computational Analysis of Shock Wave Turbulent Boundary Layer Interaction

Leger

Poggie

2014

52nd Aerospace Sciences Meeting

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An investigation was conducted to evaluate the error involved in predicting aerothermodynamic loads (surface pressure, skin friction, and heat transfer) using a Reynolds Averaged Navier Stokes (RANS) solver. Numerical simulations of Shock Wave / Turbulent Boundary Layer Interaction (SWTBLI) at Mach 5 are performed and compared with vetted experimental data. These simulations include three 2-D impinging shock, and two 3-D swept shock cases. The impinging shock cases involve different levels of interaction intensity, which result in attached, incipiently separated, and fully separated flows. Comparisons between the numerical results and experimental data for each case are used to evaluate the error in predicting the associated SWTBLI aero-thermodynamic loads. The result shows that while wall pressure is accurately predicted, skin friction is under predicted, and heat transfer is over predicted. However, the trends in skin friction and heat transfer are captured by the RANS simulations. Nomenclature β = Shock generator or fin deflection angle x = Streamwise distance from flat plate or fin leading edge y = Normal distance from the flat plate z = Spanwise distance from fin leading edge M = Mach number δ = Boundary layer height δ * = Boundary layer displacement thickness θ = Boundary layer momentum thickness H = Boundary layer shape factor or intersection point of separation and incident shocks γ = Angle of reattachment ε = Shock angle φ = Angle of separation ψ = Angle of upstream influence S = Line of separation R = Line of reattachment UI = Line of upstream influence P = Pressure T = Temperature M = Mach number Re/m = Unit Reynolds number U = Streamwise Velocity H o = Enthalpy ρ = Density μ = Dynamic viscosity = Dynamic viscosity from Sutherlands' law = Dynamic viscosity from Keyes' law f = Viscosity blending function ν ̃ = Eddy viscosity 1 Research Scientist, Ohio Aerospace Institute, Member AIAA. 2 Senior Aerospace Engineer, AFRL/RQHF, Associate Fellow AIAA. Downloaded by KUNGLIGA TEKNISKA HOGSKOLEN KTH on July 30, 2015 | http://arc.aiaa.org |

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Section: A 2-d Impinging Swtblimentioning

confidence: 98%

Computational Analysis of Shock Wave Turbulent Boundary Layer Interaction

Leger

Poggie

2014

52nd Aerospace Sciences Meeting

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“…These investigations were mainly confined within the context of linear EVMs, and some of them do help to overcome some weaknesses seen in certain models when predicting flow separation or wall heat flux. However, in many cases these methods have not been widely tested, and may cause other issues, such as having a negative impact on incompressible flows or leading to worse predictions of other "simple" flows that the original model did predict reasonably well [6,7]. Furthermore, the studies of Huang et al [8], and Duan et al [9] on compressible turbulent boundary layer flows by the use of direct numerical simulation (DNS) suggest that the failure to correctly predict the wall heat flux in the interaction region may be due to the use of constant turbulent Prandtl number.…”

Section: Introductionmentioning

confidence: 99%

Application of Linear and Nonlinear Two-Equation Turbulence Models in Hypersonic Flows

2022

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A non-linear two-equation k-ε model has been implemented in the OpenFOAM framework and has been assessed for the computation of hypersonic flows with shock boundary layer interactions (SWBLI), together with two other linear, low-Reynolds number models, namely the Launder-Sharma k-ε model and the k-ω SST model. Supersonic and hypersonic flow computations resulting from the use of these three models have been compared with experimental benchmark cases over a range of conditions. The three original models tested do generally return reasonable predictions of wall pressure in most cases, with the non-linear model resulting in the best capability among the three in predicting flow separation. The wall heat flux in the interaction region, however, is overpredicted, in most cases by all three models (sometimes showing quite a dramatic overprediction). While the overall wall heat flux predictions of the non-linear model, are closer to the measured values, it is nevertheless evident that there is a need for further improvement. To address this need, the inclusion of a new source term in the dissipation rate equation is proposed, which aims to restrict the turbulent length scales in the shock wave boundary layer interaction region. This is inactive

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“…A large deviation in agreement is observed within the interaction zone, where a severe spike in the Stanton number suggests an over-prediction of the heat-transfer in the interaction zone. This has been observed by others who have employed two-equation turbulence models [165,166,169]. Droske [169] cites Dolling [170] when attributing this behaviour as a common issue in simulating these flows, suggesting that it is most likely a deficiency of the two-equation turbulence models.…”

Section: Resultsmentioning

confidence: 71%

“…This suggests that a poor estimation of the freestream turbulence intensity alone is not sufficient to explain the discrepancy. It is interesting to note that some inconsistency is observed when comparing the skin friction distribution of several authors who have computed this experiment using the k − ω model [165][166][167][168][169]. Finally, it is observed that the Stanton number agrees well upstream of the interaction and downstream of the interaction zone.…”

Section: Resultsmentioning

confidence: 80%

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Adjoint-based aerodynamic design optimisation in hypersonic flow

Damm¹

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The drive for improved flexibility and reusability in satellite launch systems has brought a resurgence in the popularity of scramjet-powered access-to-space launch vehicle concepts. A challenge in scramjet-powered accelerator vehicles is achieving positive thrust margins at the high-speed end of their flight envelopes. As a consequence, scramjet-powered vehicles typically rely on highly integrated airframe-engine configurations. However, due to the tight integration, the geometries and the flow physics are complex. An automated optimisation method seems an excellent candidate approach to explore the complex design space of hypersonic vehicles. This thesis focuses on the development and application of a particular optimisation method, adjoint-based optimisation, to aid in efficient aerodynamic design in hypersonic flows. Shape optimisation of scramjet-powered vehicles requires many design parameters to capture the geometric detail, and, since the flow physics is complex, the fidelity of Reynolds-Averaged Navier-Stokes (RANS) analyses is desirable. The combination of many design parameters and an expensive objective function evaluation drives the need for gradient evaluation methods that scale well with the number of design variables. An advantage of the adjoint method is that all shape sensitivities for an objective function are evaluated at the cost of only one flow solution and one adjoint solution. As a result of its efficiency, the adjoint method has become widely used for aircraft design, evolving to the design optimisation of full configurations. Despite the wide use of adjoint methods in aircraft optimisation, there has been very little application to hypersonic vehicle design. Several high-speed adjoint solvers have been reported in the literature, however, a majority of these works have only verified the adjoint sensitivities, few have followed on to demonstrate the method for use in design optimisation. The contribution of this work is the description and application of a discrete adjoint solver in high-speed compressible flow optimisation. What is unique in this work is a demonstration that complex-step differentiation works well to linearise a second-order spatially accurate unstructured RANS solver. In particular, the approach presented in this work utilises the k − ω turbulence model in high-speed ducted flow configurations. As part of this work, to provide flow analysis with a rapid turnaround , an unstructured steadystate RANS solver driven by a Jacobian-Free Newton-Krylov method was developed. Turbulence is modelled using the two-equation k − ω turbulence model. The Newton method is globalised by using the pseudo-transient approach. A restarted GMRES method is used to solve the system of linear equations arising when solving for the Newton steps. Evaluation of the matrix-vector products required in the GMRES algorithm is accomplished by Fréchet derivatives using imaginary perturbations in the complex plane. This is necessary to achieve robust convergence of the types of turbulent hypersonic flows...

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A prediction method for high speed turbulent separated flows with experimental verification

Cited by 12 publications

References 1 publication

Computational Analysis of Shock Wave Turbulent Boundary Layer Interaction

Computational Analysis of Shock Wave Turbulent Boundary Layer Interaction

Application of Linear and Nonlinear Two-Equation Turbulence Models in Hypersonic Flows

Adjoint-based aerodynamic design optimisation in hypersonic flow

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