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Precomputed Panel Solver for Aerodynamics Simulation Haoran Xie The University of Tokyo / JAIST H.XIE@JAIST 0 Aerodynamics Simulation for Graphics and Fabrication T . Martin, et al., SIGGRAPH15 J. Wejchert. SIGGRAPH91 E. Ju, et al.,


  1. Precomputed Panel Solver for Aerodynamics Simulation Haoran Xie The University of Tokyo / JAIST H.XIE@JAIST 0

  2. Aerodynamics Simulation for Graphics and Fabrication T . Martin, et al., SIGGRAPH15 J. Wejchert. SIGGRAPH91 E. Ju, et al., SIGGRAPH14 H.XIE@JAIST 1

  3. Aerodynamics in Graphics Data- Heuristic Coupling Driven Method Based @N.Umetani, et al, TOG2014 @P.Yang, et al, SCA2014 @X.Wei, et al, SCA2013 @T.Martin, et al, TOG2015 @E.Ju, et al, TOG2013 @J.Tan, et al, TOG2011 Low Accuracy Simplified Model Heavy Computation H.XIE@JAIST 2

  4. Aerodynamics in Engineering Grid-Based Singularity-Based @Chen et al., Sci. China-Phys. Mech. Astron., 2013. @D. Willis, Journal of Aircraft, 2014 Heavy Computation Low Cost and Good Accuracy H.XIE@JAIST 3

  5. Aerodynamics in Engineering Grid-Based Singularity-Based We extend panel method ! @Chen et al., Sci. China-Phys. Mech. Astron., 2013. @D. Willis, Journal of Aircraft, 2014 Heavy Computation Low Cost and Good Accuracy H.XIE@JAIST 4

  6. Motivation Our goal is to create a fast aerodynamic simulation algorithm, enabling designers to design gliders with interactive feedbacks. @ANSYS Fluent CFD Tutorial our work CFD tools H.XIE@JAIST 5

  7. Computational Framework Aerodynamics Simulation Algorithm  Precomputed panel method (x10,000~)  Interactive simulation pipeline Interactive Glider Design System  Assembly-based user interface  Glider design and fabrication H.XIE@JAIST 6

  8. Computational Framework Aerodynamics Simulation Algorithm  Precomputed panel method (x10,000~)  Interactive simulation pipeline Interactive Glider Design System  Assembly-based user interface  Glider design and fabrication H.XIE@JAIST 7

  9. Flow Assumption airflow Real Flow: turbulent, unsteady leading edge Potential Flow: inviscid, incompressible trailing edge wake panels H.XIE@JAIST 8 @Marine Hydrodynamics, MIT Lectures

  10. Flow Elements Uniform Source Sink Basic Elements H.XIE@JAIST 9

  11. Flow Elements Streamline Doublet Uniform stagnation point Source flow around cylinder Sink Superposition Basic Elements H.XIE@JAIST 10

  12. Flow Elements Streamline Doublet Uniform stagnation point Source flow around cylinder Sink Superposition Basic Elements @cfd2012.com/aircraft-design H.XIE@JAIST 11

  13. Panel Method [Hess and Smith, 1967] 𝑗 : element index 𝑗 Doublet Body Panel Wake Panel doublet strength H.XIE@JAIST 12

  14. Panel Method [Hess and Smith, 1967] 𝑗 : element index 𝑗 Doublet Body Panel Wake Panel doublet strength Green’s Identity: velocity potential fixed (~ doublet strengths U) (~ body state) H.XIE@JAIST 13

  15. Panel Method  Why we still need panel solver nowadays  Fast, Robust, Accurate in aircraft design  Suitable for many applications [AIAA conference, 2010] [Journal of Aircraft, 2014] [AIAA conference, 2013] [AIAA Journal, 2013] H.XIE@JAIST 14

  16. Computation Issue for each frame: 6,000 ? ※ mesh size: N= 6000 6 Matrix 6,000 6 Operation Interactive design: 0.01 seconds Standard Panel Method: 400 seconds H.XIE@JAIST 15

  17. Body State  Doublet N 6 1 1 N 𝒀 6 N U 𝑻 × 𝑬 𝓞 × × Precomputed Precomputed Doublets Body ※ N: mesh size State Linear !! (6D velocities) 16 H.XIE@JAIST

  18. Doublet  Force doublet body state 6 force x = f ( U , X ) = 6 1 𝑫 𝒚 𝒀 6 𝒀 6 Precomputed ( ※ we compute torque in similar way) H.XIE@JAIST 17

  19. Precomputed Process Precomputation:480.0s Precomputation: 120.0s Runtime: 360.0s Runtime:0.007s Surface Surface Compute D,S O(N) O(N 2 ) Discretization Discretization matrices O(N) O(N 2 ) Compute D,S Compute O(N 3 ) matrices Strength Compute Compute O(N 3 ) O(N 2 ) Local Strength Velocity Compute O(1) Compute O(N 2 ) Compute Local O(N 2 ) force&moment force&moment Velocity O(1) Compute C Compute Compute O(N 2 ) matrices Body State Body State O(1) Precomputed Panel Method O(1) Standard Panel Method O(N 3 ) (N = mesh size) H.XIE@JAIST 18

  20. Computation Cost Panel Method Ours 600 500 400 300 200 100 (seconds) 0 (x2,160) (x50,252) (x27,205) (x41,809) (x68,053) H.XIE@JAIST 19

  21. Computational Framework Aerodynamics Simulation Algorithm  Precomputed panel method (x10,000~)  Interactive simulation pipeline Interactive Glider Design System  Assembly-based user interface  Glider design and fabrication H.XIE@JAIST 20

  22. Full Simulation pipeline Geometry Preprocessing Aerodynamics Precomputation pre-computation runtime H.XIE@JAIST 21

  23. Geometry Preprocessing mesh wing wake-panel input segmentation recognition generation H.XIE@JAIST 22

  24. Wing Recognition Mesh Segmentation: → convex shape decomposition Oriented Bounding Box [O. Kaick et al, TOG2014] Extracting wing parts: → bottom-up clustering process 0.18 0.21 0.05 0.04 ? 0.47 0.29 0.46 H.XIE@JAIST 23

  25. Wake Panel positive surface trailing edge negative surface trailing edge wake panels H.XIE@JAIST 24

  26. Full Simulation Pipeline Geometry Preprocessing Aerodynamics Precomputation pre-computation runtime H.XIE@JAIST 25

  27. Aerodynamics Precomputation precomputed precomputed body state doublet strength body state force + torque precomputed H.XIE@JAIST 26

  28. Full Simulation Pipeline Geometry Preprocessing Aerodynamics Precomputation pre-computation runtime H.XIE@JAIST 27

  29. RIGD BODY Simulation [Kobilarov et al, TOG2009] Kinematic Equations: Quadratic to body state! Dynamics Equations: H.XIE@JAIST 28

  30. Computational Framework Aerodynamics Simulation Algorithm  Precomputed panel method (x10,000~)  Interactive simulation pipeline Interactive Glider Design System  Assembly-based user interface  Glider design and fabrication H.XIE@JAIST 29

  31. H.XIE@JAIST 30

  32. Computational Framework Aerodynamics Simulation Algorithm  Precomputed panel method (x10,000~)  Interactive simulation pipeline Interactive Glider Design System  Assembly-based user interface  Glider design and fabrication H.XIE@JAIST 31

  33. Glider Design scaling translation rotation 𝑉 = 𝑸 𝟐 𝑆 𝑙𝑸 𝟑 𝑆 + 𝑸 𝟐 ෠ 𝑈 𝑌 Doublet Matrix Body State Precomputed assembling&editing H.XIE@JAIST 32

  34. Glider Fabrication added mass launching device Fabricated Gliders launching hook H.XIE@JAIST 33

  35. launching H.XIE@JAIST 34

  36. Results Aerodynamics validation and glider design. 35 H.XIE@JAIST

  37. Results Aerodynamics Simulation Algorithm  Aerodynamics validation  Simulation comparison Interactive Glider Design System  Glider design (stable & unstable)  Bird glider design H.XIE@JAIST 36

  38. Validation: Sphere Pressure Distribution: Flow around a sphere theoretical value 956 1m meshes 440 meshes 105 meshes H.XIE@JAIST 37

  39. Validation: Airfoil Pressure Distribution: Flow around an airfoil wind tunnel data section A A 4m B section B section C C 1m NACA0012 Airfoil Location H.XIE@JAIST 38

  40. Validation: Glider Pressure Distribution: 1 Lift Force Flow around a glider Coefficients wind tunnel data Coefficients our model 0.5 137.0 cm 0 77.6 cm Drag Force Coefficients -5 0 5 10 15 Angle of Attack (degree) H.XIE@JAIST 39

  41. Influence of AoA Wind Tunnel Visualization Boundary layer separation @UAF Physics 211 H.XIE@JAIST 40

  42. Validation: Glider Pressure Distribution: 1 Lift Force Flow around a glider Coefficients wind tunnel data Coefficients our model 0.5 137.0 cm 0 77.6 cm Drag Force Coefficients -5 0 5 10 15 Angle of Attack (degree) H.XIE@JAIST 41

  43. Validation: Comparison Saqqara Bird: about 2,200 years old, excavated in 1898 from a tomb in Saqqara, Egypt . Source distribution | Pressure Distribution | Fabrication Results not stable, tumbling a lot no tail design not stable, tumbling few small tail design @wikipedia stable, no tumbling big tail design H.XIE@JAIST 42

  44. Comparison H.XIE@JAIST 43

  45. Results Aerodynamics Simulation Algorithm  Aerodynamics validation  Simulation comparison Interactive Glider Design System  Glider design (stable & unstable)  Bird glider design H.XIE@JAIST 44

  46. Glider Design Single-wing gliders Tandem-wing gliders ✔ ✔ H.XIE@JAIST 45

  47. Glider Design unstable our simulation captured trajectory 45 ° 30 ° 0 ° H.XIE@JAIST 46

  48. experiments unstable H.XIE@JAIST 47

  49. Glider Design stable our simulation captured trajectory 45 ° 30 ° 0 ° H.XIE@JAIST 48

  50. experiments stable H.XIE@JAIST 49

  51. H.XIE@JAIST 50

  52. Bird Glider A normal glider fuselage with bird wings assembly parts H.XIE@JAIST 51

  53. H.XIE@JAIST 52

  54. Conclusion Precomputed Panel Solver Interactive Glider Design H.XIE@JAIST 53

  55. Limitations We assume potential flow, so cannot handle unstable turbulences Mesh segmentation can be wrong, leading to inaccurate simulation. We assume forward flight. It cannot handle flying in other directions. H.XIE@JAIST 54

  56. Future Work H.XIE@JAIST 55

  57. Thank You! Q&A H.XIE@JAIST 56

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