2019
DOI: 10.2514/1.c034940
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Overview and Summary of the Third AIAA High Lift Prediction Workshop

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Cited by 135 publications
(31 citation statements)
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“…Strong code-to-code agreement is observed for both the integrated quantities and the flow fields for the entire alpha sweep despite the tendency for steady-state RANS to bifurcate in regions of separated flow. Indeed the differences in CFD solutions become more pronounced post-stall, but the relative error between the codes is well within acceptable bounds as compared to the High Lift Prediction Workshop scatter in the stall regime [21]. These results are especially encouraging due to the fact that entirely different mesh paradigms and CFD solvers have independently predicted pre-stall and post-stall flow characteristics.…”
Section: Applying Lessons Learned To An Aerodynamic Databasementioning
confidence: 68%
“…Strong code-to-code agreement is observed for both the integrated quantities and the flow fields for the entire alpha sweep despite the tendency for steady-state RANS to bifurcate in regions of separated flow. Indeed the differences in CFD solutions become more pronounced post-stall, but the relative error between the codes is well within acceptable bounds as compared to the High Lift Prediction Workshop scatter in the stall regime [21]. These results are especially encouraging due to the fact that entirely different mesh paradigms and CFD solvers have independently predicted pre-stall and post-stall flow characteristics.…”
Section: Applying Lessons Learned To An Aerodynamic Databasementioning
confidence: 68%
“…The gridding guidelines from the third American Institute of Aeronautics and Astronautics (AIAA) CFD High Lift Prediction Workshop are used to generate different grids in four levels: coarse, medium, fine, and extra-fine. 45 A super-fine grid level is added. The chordwise spacing at the leading edge (LE), , and trailing edge (TE), , are varied between 1 and 0.001% .…”
Section: Geometry Definition and Grid Resolution Studymentioning
confidence: 99%
“…Computational fluid dynamics (CFD) technology has made tremendous progress [2][3][4]; it has advantages in that not only can it reduce capital investment and maintenance costs, but it also can acquire physical quantity at any position in a computational domain. However, to realize accurate aerodynamic performance prediction for control devices, CFD is not mature yet; we deepen the perception of knowledge through the American Institute of Aeronautics and Astronautics high-lift prediction workshops [5][6][7]. On the other hand, in the wind tunnel test, we can obtain spatial data through particle image velocimetry (PIV) [8] measurements; we can comprehensively gain surface pressure/temperature through the invention and development of Pressure/Temperature Sensitive Paint (PSP/TSP) [9].…”
Section: Introductionmentioning
confidence: 99%