Effect of Turbulence Model Uncertainty on Scramjet Isolator Flowfield Analysis

Stefano, Martin A. Di; Hosder, Serhat; Baurle, Robert A.

doi:10.2514/1.b37597

Cited by 14 publications

(3 citation statements)

References 24 publications

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“…It is a well-known fact that the choice of turbulence model in a RANS computation can have a significant impact on the computed flowfield, especially in high-speed applications where shock/ boundary-layer interactions and the induced flow separations are present [24][25][26]. A major goal of the current work was to assess the performance of several of the popular turbulence models for use in computing the flowfield through a high-speed inlet.…”

Section: A Results From Quasi-steady Model 1 Turbulence Model Assessmentmentioning

confidence: 99%

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Computational Analysis of Unstart in Variable-Geometry Inlet

Reardon

Schetz

Lowe

2021

Journal of Propulsion and Power

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Computational fluid dynamics was used to study the flow through a scaled, mixed-compression, high-speed inlet with a rotating cowl at Mach 4.0 conditions. First, steady Reynolds-averaged Navier-Stokes computations were undertaken with a range of popular turbulence models including the Spalart-Allmaras model, the realizable k-ε model, the cubic k-ε model, and the Menter shear stress transport (SST) model to assess the impact on the inlet operating state. It was found that two models, the Spalart-Allmaras model and the Menter SST model, predicted the inlet to become unstarted at a cowl angle where the experimental data indicated the inlet remained started. Next, steady-state flow structures were studied at three discrete cowl positions, identifying highly three-dimensional flow features including regions of separated flow and spanwise gradients that became stronger as the cowl opened. Finally, the study culminated with the development of the new transient model, which allowed for time-accurate investigation into the unstart, restart, and hysteresis. The evolution of the separation bubbles was shown to be a major factor in the hysteresis, causing the inlet to restart at an angle different from where it unstarted. The utility of unsteady Reynolds-averaged Navier-Stokes computations to capture the complex time-dependent details of such flows was demonstrated.

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Section: A Results From Quasi-steady Model 1 Turbulence Model Assessmentmentioning

confidence: 99%

“…[24], which found that the order of accuracy in an isolator flow solution was first order despite the use of a second-order scheme. The cause of this was stated to be due to the use of the TVD flux limiter [24].…”

Section: A Spatial Discretization Errormentioning

confidence: 99%

Computational Analysis of Unstart in Variable-Geometry Inlet

Reardon

Schetz

Lowe

2021

Journal of Propulsion and Power

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“…In recent years, several related studies have been conducted. Hosder et al [22][23][24] performed a series of works for different turbulence models in various flows, including transonic wallbounded flows, compression ramp flows, and relatively complex engineering problems. They quantified the effects of uncertainties in the model's parameters for different QoIs and identified the key parameters through sensitivity analysis.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Analysis of Parameters in SST Turbulence Model for Shock Wave-Boundary Layer Interaction

Zhang

Zeng

et al. 2022

Aerospace

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Shock wave-boundary layer interactions (SWBLIs) have a tremendous influence on the performance of hypersonic vehicles. For the numerical simulation of such engineering flows, Reynolds averaged Navier-Stokes (RANS) still occupies an irreplaceable role. However, parameters of turbulence models in RANS have substantial uncertainties, which impact the reliability of simulation results. Thus, the aim of the present study is to conduct an uncertainty analysis on parameters in the shear-stress transport (SST) turbulence model for the simulation of SWBLIs. In the current work, uncertainty quantification was performed first. A surrogate model was constructed by the non-intrusive polynomial chaos (NIPC) method to propagate uncertainties from model parameters to the quantities of interests (QoIs) and quantify them. In the subsequent sensitivity analysis, the key parameters were identified for such flow by calculating the Sobol index of each parameter for various QoIs. The results indicate that uncertainties of model parameters led to non-negligible uncertainties in those QoIs, particularly in skin friction and wall heat flux. The parameters α1, σω1, β1 were identified as primary contributors through the sensitivity analysis. Moreover, the specific effects of the three parameters on the flow prediction were analyzed by changing the parameters’ values separately.

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Parametric uncertainty quantification of SST turbulence model for a shock train and pseudo-shock phenomenon

Zeng

Wang

et al. 2022

Acta Astronautica

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Effect of Turbulence Model Uncertainty on Scramjet Isolator Flowfield Analysis

Cited by 14 publications

References 24 publications

Computational Analysis of Unstart in Variable-Geometry Inlet

Computational Analysis of Unstart in Variable-Geometry Inlet

Uncertainty Analysis of Parameters in SST Turbulence Model for Shock Wave-Boundary Layer Interaction

Parametric uncertainty quantification of SST turbulence model for a shock train and pseudo-shock phenomenon

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