Airbus, ONERA, and DLR Results from the 2nd AIAA Drag Prediction Workshop

Brodersen, Olaf; Rakowitz, M.; Amant, Stephane; Larrieu, Pascal; Destarac, Daniel; Sutcliffe, Mark

doi:10.2514/6.2004-391

Cited by 17 publications

(18 citation statements)

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“…Similar excessive flow separations around the lower surface of the wing near the pylon are observed with the fine grid, while the solutions obtained using the medium grid correlate well with the experimental data [12,13]. The lift matching results also show similar discrepancies in the separation bubble [14][15][16]. compares the pressure distributions of previous studies and the present results.…”

Section: Dlr-f6 Configurationssupporting

confidence: 78%

See 1 more Smart Citation

Performance Evaluation of Two-Equation Turbulence Models for 3D Wing-Body Configuration

Kwak¹,

Lee²,

Lee

et al. 2012

International Journal of Aeronautical and Space Sciences

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Section: Dlr-f6 Configurationssupporting

confidence: 78%

“…The k-ω SST model predicts an excessive flow separation in comparison with the q-ω model and the experimental data. Such a tendency has been reported in other investigations [12][13][14][15][16]. Computational results containing AOA matching using the fine grid system show similar discrepancies in the pressure distribution.…”

Section: Dlr-f6 Configurationssupporting

confidence: 66%

Performance Evaluation of Two-Equation Turbulence Models for 3D Wing-Body Configuration

Kwak¹,

Lee²,

Lee

et al. 2012

International Journal of Aeronautical and Space Sciences

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“…Although the F6 geometry is similar to that of the F4, its pockets of flow separation at the design condition are more severe; these occur predominantly at the wing/body and wing/pylon juncture regions. Again, this workshop was documented with a summary paper, 15, 16 a statistical analysis, 17 an invited reflections paper 18 on the workshop series, and numerous participant papers [19][20][21][22][23][24][25][26][27][28][29][30][31][32] in two special sessions of the 2004 AIAA Aerospace Sciences Meeting in Reno, NV. A conclusion of DPW-II was that the separated flow regions made it difficult to draw meaningful conclusions with respect to grid convergence and drag prediction.…”

Section: Introductionmentioning

confidence: 99%

Summary of the Fourth AIAA CFD Drag Prediction Workshop

Vassberg

Tinoco

Mani

et al. 2010

28th AIAA Applied Aerodynamics Conference

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184

111

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Results from the Fourth AIAA Drag Prediction Workshop (DPW-IV) are summarized. The workshop focused on the prediction of both absolute and differential drag levels for wing-body and wing-body-horizontal-tail configurations that are representative of transonic transport aircraft. Numerical calculations are performed using industry-relevant test cases that include liftspecific flight conditions, trimmed drag polars, downwash variations, dragrises and Reynoldsnumber effects. Drag, lift and pitching moment predictions from numerous Reynolds-Averaged Navier-Stokes computational fluid dynamics methods are presented. Solutions are performed on structured, unstructured and hybrid grid systems. The structured-grid sets include pointmatched multi-block meshes and over-set grid systems. The unstructured and hybrid grid sets are comprised of tetrahedral, pyramid, prismatic, and hexahedral elements. Effort is made to provide a high-quality and parametrically consistent family of grids for each grid type about each configuration under study. The wing-body-horizontal families are comprised of a coarse, medium and fine grid; an optional extra-fine grid augments several of the grid families. These mesh sequences are utilized to determine asymptotic grid-convergence characteristics of the solution sets, and to estimate grid-converged absolute drag levels of the wing-body-horizontal configuration using Richardson extrapolation.

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“…As a follow-up to the DPW-II workshop, many of the participants reported individual code results at a special session of the AIAA 42nd Aerospace Sciences Meeting and Exhibit. [37][38][39][40][41] In Ref. 41, an in-depth comparison was made between three distinctly different unstructured Navier-Stokes flow solvers exercised on a similar family of tetrahedral meshes created for the workshop.…”

Section: Introductionmentioning

confidence: 99%

Application of Parallel Adjoint-Based Error Estimation and Anisotropic Grid Adaptation for Three-Dimensional Aerospace Configurations

Lee-Rausch

Park

Jones

et al. 2005

23rd AIAA Applied Aerodynamics Conference

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I. AbstractThis paper demonstrates the extension of error estimation and adaptation methods to parallel computations enabling larger, more realistic aerospace applications and the quantification of discretization errors for complex 3-D solutions. Results were shown for an inviscid sonic-boom prediction about a double-cone configuration and a wing/body segmented leading edge (SLE) configuration where the output function of the adjoint was pressure integrated over a part of the cylinder in the near field. After multiple cycles of error estimation and surface/field adaptation, a significant improvement in the inviscid solution for the sonic boom signature of the double cone was observed. Although the double-cone adaptation was initiated from a very coarse mesh, the near-field pressure signature from the finaladapted mesh compared very well with the wind-tunnel data which illustrates that the adjoint-based error estimation and adaptation process requires no a priori refinement of the mesh. Similarly, the near-field pressure signature for the SLE wing/body sonic boom configuration showed a significant improvement from the initial coarse mesh to the final adapted mesh in comparison with the wind tunnel results. Error estimation and field adaptation results were also presented for the viscous transonic drag prediction of the DLR-F6 wing/body configuration, and results were compared to a series of globally refined meshes. Two of these globally refined meshes were used as a starting point for the error estimation and field-adaptation process where the output function for the adjoint was the total drag. The field-adapted results showed an improvement in the prediction of the drag in comparison with the finest globally refined mesh and a reduction in the estimate of the remaining drag error. The adjoint-based adaptation parameter showed a need for increased resolution in the surface of the wing/body as well as a need for wake resolution downstream of the fuselage and wing trailing edge in order to achieve the requested drag tolerance. Although further adaptation was required to meet the requested tolerance, no further cycles were computed in order to avoid large discrepancies between the surface mesh spacing and the refined field spacing. II. IntroductionAs advanced computational fluid dynamics (CFD) codes have been developed to capture increasingly more complex flow features, assuring that the computational meshes are adequate to resolve these flow features has become a challenge. In aerospace applications, this can be especially difficult due to the wide range of speeds and conditions that must be simulated. A primary goal of CFD simulation is to accurately predict and understand wind tunnel and full-scale tests. Validation efforts have been applied to two-dimensional (2-D) and three-dimensional (3-D) problems to quantify current capabilities and expose deficiencies in current CFD simulation and wind tunnel testing practices. Both 2-D and 3-D validation efforts have been hampered by a number of factors including adequate...

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Airbus, ONERA, and DLR Results from the 2nd AIAA Drag Prediction Workshop

Cited by 17 publications

References 0 publications

Performance Evaluation of Two-Equation Turbulence Models for 3D Wing-Body Configuration

Performance Evaluation of Two-Equation Turbulence Models for 3D Wing-Body Configuration

Summary of the Fourth AIAA CFD Drag Prediction Workshop

Application of Parallel Adjoint-Based Error Estimation and Anisotropic Grid Adaptation for Three-Dimensional Aerospace Configurations

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