Slat noise prediction with Fast Multipole BEM based on anisotropic synthetic turbulence sources

Transcription

1 DLR.de Chart 1 Slat noise prediction with Fast Multipole BEM based on anisotropic synthetic turbulence sources Nils Reiche, Markus Lummer, Roland Ewert, Jan W. Delfs Institute of Aerodynamics and Flow Technology Technical Acoustics German Aerospace Center (DLR)

2 DLR.de Chart 2 Contents Introduction high-lift noise, numerical methods Numerical Approach novel hybrid noise prediction approach Fast Multipole-BEM anisotropic synthetic vorticity slat noise for small wing section with 2-D turbulence slat noise for full scale 3-D wing with 3-D turbulence Summary and Outlook

3 DLR.de Chart 3 Introduction High-lift noise: problem & simulation Turbulence related noise prediction Broadband noise prediction fast & efficient accurate (first principle based) Acoustic assement of full scale aircrafts trend analysis of modifications Scale resolving simulation DNS /LES Stochastic sound sources hybrid RANS/CAA surface based: BEM Semi empirical models Guo resolved physics modeled physics

4 DLR.de Chart 4 Contents Introduction high-lift noise, numerical methods Numerical Approach novel hybrid noise prediction approach Fast Multipole-BEM anisotropic synthetic vorticity slat noise for small wing section with 2-D turbulence slat noise for full scale 3-D wing with 3-D turbulence Summary and Outlook

5 DLR.de Chart 5 Numerical Approach Fast Multipole Boundary Element Method Boundary Element Method: N surface elements 2 resolution: N A f rrrrrrrr problem order: O N 2 avoiding interior resonances (Burton Miller) B ii p j = q i p j = B ii 1 q i Fast Multipole Method (FMM): iterative solution of BEM equation acceleration of matrix-vector product from O N 2 to O N log N Example: 2.17 mio. triangles f rrrrrrrr = 3410HH, A = 582m iterations in 8.3h 32 CPUs (Opteron 2.7GHz) FMM surface pressure source: monopole above left wing 3410 Hz Lummer

6 DLR.de Chart 6 Numerical Approach Fast Multipole BEM: surface sources BEM source term: incident turbulent velocity BEM surface φ n = u vv splitting theorem, Goldstein Kinematic boundary condition (Howe): wall normal acoustic velocity and induced incompressible upwash velocity annihilate Biot-Savart induction formula u v x = x V s Ω y 4π x y d 3 y

7 DLR.de Chart 7 Numerical Approach Vorticity modeling Synthetic turbulence generation: geometry Fast Random Particle Mesh (FRPM) Method based on RANS statistics convecting particles as vortex cores turbulence scaling filtering with Gaussian kernel on cartesian background mesh P Ω i x = ε iii G x x x p, l a kk x p δ j ρ 0 x p p=1 n r pp Anisotropic, solenoidal vorticity (ASV): 3D vorticity divergence free (solenoidal) anisotropic scaling, LES validated scaling model FRPM domain / turbulence region

8 DLR.de Chart 8 Numerical Approach Broadband Noise Prediction k t CFD RANS mean flow & turbulence ρ 0, u 0, p 0 k t, ω, r, ζ 4-D synthetic turbulence, FRPM u vv FFF u vn Spectral stochastic sound sources, FRPM interface Sound Propagation, FM-BEM SSS f i Acoustic Evaluation

9 DLR.de Chart 9 Contents Introduction high-lift noise, numerical methods Numerical Approach novel hybrid noise prediction approach Fast Multipole-BEM anisotropic synthetic vorticity slat noise for small wing section with 2-D turbulence slat noise for full scale 3-D wing with 3-D turbulence Summary and Outlook

10 DLR.de Chart 10 2-D turbulence & FM-BEM DLR F15LS airfoil Geometry: l rrr = 1.2m, s = 2.0m Flow: α = 5, MM = , RANS-RSM FRPM patch: 2-D, 256x128 points, particles Surface: triangles, 6 PPW, f mmm = 7640HH Test cases: isotropic Source B (2D) anisotropic Source ASV (2D & 3D) source patch triangulated surface

11 DLR.de Chart 11 2-D turbulence & FM-BEM time steps t rrrr = s 129 discrete frequencies f mmm = 7640HH smoothed velocity spectrum Computational time: up to 1 hour Δ=10 Δ=10 Δ=10 Highest level at impingement point

12 DLR.de Chart 12 2-D turbulence & FM-BEM CAA-Methods vs. WTT FM-BEM/FRPM vs. WTT Microphone position on cylinder: r = 2.4l rrr φ = 284 (α WW = 14 ) Trend and maximum are predicted Decrease : Isotropic model better

13 DLR.de Chart 13 2-D turbulence analysis and improvement DISCO vs. WTT FM-BEM/FRPM vs. WTT CAA study (DISCO) : confirms low performance at high frequencies for src ASV Parameter modification resolving larger structures leads to better agreement

14 DLR.de Chart 14 3-D turbulence & FM-BEM time steps t rrrr = 0.227s Computational time: up to 35 hours Geometry: FNG wing, l rrr = 0.332m Flow: α = 5.9, MM = , RANS Menter SST FRPM patch: 3-D, 256x128x128 points, 10.2 mio. particles Surface: 2 mio. triangles, 6 PPW, f mmm = 18kkk

15 DLR.de Chart 15 3-D turbulence & FM-BEM y1 y2 y3 Slat noise characteristics: Semi analytical model by Guo, regression analysis Fitting coeffitients are order of 1 parameters

16 DLR.de Chart 16 Contents Introduction high-lift noise, numerical methods Numerical Approach novel hybrid noise prediction approach Fast Multipole-BEM anisotropic synthetic vorticity slat noise for small wing section with 2-D turbulence slat noise for full scale 3-D wing with 3-D turbulence Summary and Outlook

17 DLR.de Chart 17 Summary & Outlook Novel approach for slat noise prediction FRPM/FM-BEM Slat noise simulation 2-D wing section (2-D turbulence) 3-D full scale wing (3-D turbulence) within 2 days Comparison slat noise of 3-D full scale wing FM-BEM/FRPM vs. Measurements Improvement of turbulence modeling Pott-Pollenske

18 DLR.de Chart 18 Slat noise prediction with Fast Multipole BEM anisotropic synthetic turbulence sources based on Questions? contact Dipl.-Ing. Nils Reiche