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Steady and Unsteady CFD Analysis of a Half-Span Delta Wing
Simone CrippaDept. of Aeronautical and Vehicle Engineering
Royal Institute of Technology (KTH)
Symposium on Hybrid RANS-LES MethodsRica City Hotel, Stockholm 14-15 July 2005
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Outline• Constrains / Environment
• Case selection
• Steady-state computations
• DES, “small” time-scales time-step
• DES, “large” time-scales time-step
• Comparison
• Conclusions
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Constrains / Environment• New cluster at KTH, Lenngren
442 Dell PowerEdge 1850 nodes• 2 x 3.4GHz "Nocona" Xeon processors (EM64T)• 8GB main memory • 6TFlop/s peak performance
• First application of• Edge 3.3.1• New postprocessing program, Paraview• Detached Eddy Simulation
... but ...
• Existing knowledge on delta-wing aerodynamics (Prof. Arthur Rizzi, Stefan Görtz, Yann Lemoigne)
• Mesh was given
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Case selection• Extensive database of surface pressure
measurements from NASA's NTF. [Luckring & Chu, NASA-TM-4645, 1996]
• interchangeable LE segments: sharp + 3 bluntness
• Remac= 6E6 – 60E6 (120E6, blunt LE)
• M = 0.4 – 0.85 (0.9)
• AoA = 0º – 25º • Computational mesh available in native
Edge FFA-format• sharp LE, croot = 0.3048 m (12'')• 7.89E6 tetrahedral, prismatic & pyramidal
cells• prismatic layer for Remac= 6E6
• M=0.4; AoA=23º; Remac= 6E6; sharp LE
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Steady-state computations Short comp. of RANS turb. models:
• W&J EARSM + standard k-ω (Edge 3.2)
• W&J EARSM + Hellsten k-ω (Edge 3.3)
• W&J CC-EARSM + Hellsten k-ω
W&J EARSM + Hellsten k-ω most accurate → DES initialization
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DES, “small” time-scales time-step• implicit time-stepping
“appropriate” ?∆t = ∆0/umax or ∆t = l/(u∞ · res) ∆t = 5E-6 s → ∆t* = 2.3E-3
• 7800 it ≅ 0.039 s• 0 – 2300 it @ 50 inner-it
• 2300 – 3600 it @ 70 inner-it
• 3600 it – 7800 it @ 100 inner-it
• mean, 5000 it – 7800 it• video, t = 0.036 s – 0.038 s
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DES, “large” time-scales time-step• implicit time-stepping
“bigger” ?∆t = 10 · ∆tsmall
∆t = 5E-5 s → ∆t* = 2.3E-2
• 860 it ≅ 0.043 s• 0 – 600 it @ 50 inner-it
• 600 it – 860 it @ 100 inner-it
• mean, 700 it – 860 it• video, t = 0.036 s – 0.038 s• video, t = 0.038 s – 0.041 s
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ComparisonVortex Burst LocationCPUh
RANS: 138DES, Dt=5E-5: 357DES, Dt=5E-6: 3360
Vortex burst location moves by ca. 20% c (RANS → DES-6)
O[Dxburst(DES-5-DES-6)]=
O[Dxburst(RANS-DES-5)]
Dxburst(RANS-DES-5
Dxburst(DES-5-DES
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ComparisonSurface pressure• DES predict strong secondary
vortex, RANS predicts weaker secondary vortex
• DES resolve primary vortex strength and burst better than RANS
• DES capture second vortex pair
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Conclusions• Strong secondary vortex predicted by DES might be due to
different free-stream turbulence levels (DES: 0.001%, RANS: 0.1%)
→ Assess turbulence level influence
• Improvement between DES with smaller and bigger time-step is as big as between RANS and DES with big time-step
→ DES with smaller time-step
