Computational Fluid Dynamics

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1 Aerodynamics Computational Fluid Dynamics Industrial Use of High Fidelity Numerical Simulation of Flow about Aircraft Presented by Dr. Klaus Becker / Aerodynamic Strategies

2 Contents Aerodynamic Vision where do we go? Numerical Simulation what is it? CFD typical pictures and examples meshing, modelling, quality of results CFD what is it used for? Some challenges Route to the future Page 2

3 Aerodynamics is a Major Contributor to Overall Community & Company Vision The European aviation community leads the world in sustainable aviation products and services, meeting the needs of global citizens and society.*) Major 2050 Goals **) CO 2 reduced by 75%, NO x by 90% and perceived noise by 65%, relative to typical new aircraft in 2000 Certification cost reduced by 50% through leading new standards Leading edge design, manufacture & integration maintained Jointly defined European research and innovation strategies, from basic research to demonstrators Strategic European aeronautic test, simulation and development facilities identified, maintained and continuously developed Page 3 *) Flightpath 2050 Vision, supported by Airbus **) agreed and presented in Flightpath 2050

4 Aerodynamic Simulation Method Simulation machine Model Experiment Wind tunnel Flying aircraft Real image Theoretical / Numerical Computer Physical / mathematical ti models of nature Both types of simulation do have advantages, drawbacks and limits Both techniques complement each other Both methods are further being needed and developed Page 4

5 Computational Fluid Dynamics the Principle CAD CATIA V5 Geometry, flight conditions Physical model of flow conservation laws of nature 5+2 equations Mesh Generator ICEM/Centaur/SOLAR Discretization Mio. mesh points Flow Solver elsa/tau Numerical Solution Mio. numbers Postprocessing FFDx/ENSIGHT etc. Evaluation Lift: 0.5 Drag: Moment: Flow, Aero Data Problem: Quality Discretizationi i error Size of task Cost/time Page 5

6 CFD Models Refinement of Physical Models Full Aircraft Configurations Flow Properties Problem Size Go ahead Reduced Configurational Complexity Simple Vortex Models Subsonic Flow A300 InviscidFlow Complex Configurations Vortex Flow A310 A320 A330/340 Reduced Configurational Complexity Viscous Flow Turbulent Flow A321 A Complex Configurations Wake Vortex Separation A /600 A318 A A Configuration CFD-Model Potential Equation Euler Equations Navier-Stokes Equations Page 6

7 Expected Improvement Lines for CFD/WTT M Cost CFD WT New model technologies/ rapid prototyping High Re testing/ improved strategies improved WT improvement of algorithms & hardware intelligent meshes improved CFD Number of simulations > Page 7

8 CFD Page 8

9 CFD Industrial Use of High Fidelity Numerical Simulation of Flow about Aircraft CFD Status: mesh generation Page 9

10 CFD Status: Flow physical modelling Significant improvement in flow modelling RSM turbulence model clearly favourable to classical 1- or 2-eqn models Much better prediction of shock-induced separation Page 10 31/01/2012Page 10

11 Use of CFD Page 11

12 CFD Purpose: Predict Unsteady Aerodynamic Effects Unsteady simulation on installed rotor configuration Validation investigation on A400M and IPEKA test models Chimera mesh technique with combined structured & unstructured meshes Page 12

13 CFD Purpose: Support engine integration Stream Lines and x-velocity (CT= -0.2, decelerated flow) Stream Lines and x-velocity (CT= -0.6, reverse flow) Page 13

14 CFD Purpose: Support WT test set-up and analysis Consistent CFD application helps to understand d WT results and create confidence Lessons learnt: best match with WT only via complete simulation of experiment (support, flexibility, walls,...) Page 14

15 CFD Purpose: Predict Aerodynamics on true shapes High Fidelity CFD/CSM applied to aileron/spoiler case Validation of CFD/CSM model on ETW wind tunnel data Mesh deformation and CFD-CSM transfer interfaces independent of specific CFD Page 15

16 CFD Purpose: Aircraft unsteady aero loads Gust encounter simulation for flexible trimmed aircraft Full MD simulation of standard gust affecting aircraft, incl. flexibility and trim Multiple iterative coupling with automated process control Trim-iteration convergence Page 16

17 The Future logy / Perf formance rodynamic cs Technol Ae Fully 3D optimized integrated wing design A320 A300 A330 Evolut lution Game Changer? Future Aircraft A380 All-new advanced technology wing Advanced Aerodynamics in Wing Design for excellent economics Supercritical airfoil for superior economical performance 1st airliner to use winglets for better cruise performance Time Laminarity Flow Control Multi-disciplinary Optimisation Page 17

18 Future Expectations on Numerical Simulation By the power of the future simulation capability, multidisciplinary simulation and optimisation will be at hand of every Flight Physics engineer Quality of the simulation will be appropriate for product development Turn-around of simulation will be such that the engineer will not be faced with major interruptions of his work process There is a strong tendency and need towards multi-disciplinary simulation and optimisation across Flight Physics MD interaction will be fully implemented in FP simulation capability Numerical optimisation will provide baseline design as well as improvement steps, it will widely assist the design engineer Numerical simulation will be the major source of all FP aircraft data Comprehensiveness as well as quality of data is accepted by related customers/authorities Physical experiments will only back-up/validate numerical data Page 18

19 Flight Envelope Flow Physics Challenges 3g High lift configuration flow is physically very complex due to high loading 2g LOAD FACTOR 1g 0g Maximum lift borders are determined by onset of massive separation causing total t lift loss VF Buffet boundary The colour gradient is intended to show level of confidence in CFD flow solutions Region of highest accuracy and robustness Region of most experience VC Beyond buffet boundary flow tends to become more and more separated from the aircraft surface Unsteady effects start to become dominant Transonic flow effects (shocks) get stronger with increasing Mach number and load Interaction of physical effects (shock flow, boundary layer flow) start to dominate VD EAS (at a given altitude) -1g Local low Mach number / low compressibility flow only weakly coupled to main flow Low g flow tends to separate on the lower side of the aircraft Page 19

20 HPC is a key to future Capacity: # of Overnight Loads cases run 10 2 Unsteady RANS LES Available Computational Capacity [Flop/s] 1 Zeta (10 21 ) RANS High Speed RANS Low Speed 10 5 Smart use of HPC power: Algorithms Data mining i 10 6 Knowledge 1 Exa (10 18 ) 1 Peta (10 15 ) 1 Tera (10 12 ) 1 Giga (10 9 ) x Page 20 HS Design Data Set CFD-based LOADS & HQ Aero Optimisation &CFDCSM CFD-CSM Capability achieved during one night batch Full MDO CFD-based noise simulation Real time CFD based in flight simulation

21 CFD: Request for real-time The factor needed d is 10 7 The factor needed is 10 6 Vorticity Page 21

22 Numerical Simulation Capability 5 Corner Stones High fidelity aerodynamic simulation High Fidelity Flow Simulation CFD capability Full parametric product definition Parametric aircraft - shapes and aero data model Multi-disciplinary product optimisation Integrated product simulation and optimisation Highly efficient numerical simulation & optimisation Platform backbone software system High performance computing Latest processor and hardware architecture Page 22 31/01/2012Page 22

23 Thank you! Page 23

24 This document and all information contained herein is the sole property of AIRBUS Operations GmbH. No intellectual property rights are granted by the delivery of this document or the disclosure of its content. This document shall not be reproduced or disclosed to a third party without the express written consent of AIRBUS Operations GmbH. This document and its content shall not be used for any purpose other than that for which it is supplied. The statements made herein do not constitute an offer. They are based on the mentioned assumptions and are expressed in good faith. Where the supporting grounds for these statements are not shown, AIRBUS Operations GmbH will be pleased to explain the basis thereof. AIRBUS, its logo, A300, A310, A318, A319, A320, A321, A330, A340, A350, A380, A400M are registered trademarks. Page 24

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