上海交通大学：《飞机设计 Aircraft Design》课程教学资源_Aircraft Design - 7-Aerodynamics（b）.pdf_大学文库

2018/3/11 1 © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Wenbin Song School of Aeronautics and Astronautics Shanghai Jiao Tong University swb@sjtu.edu.cn Aircraft Design （飞行器设计） © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Overview of Lectures 0. Overview 1. Introduction 2. Overall configuration (a, b) 3. Preliminary weight estimation 4. Refined weight estimation 5. Fuselage design 6. Aerodynamic design(a, b) 9. Thrust/Weight ratio and wing loading 10.Landing gear and Aircraft systems 11.Power plant 12.Stability and control 13.Loads, materials and structures 14/15 Performance(a, b) 16.Aircraft certification 17.Aviation economics 18.System integration and configuration management 19.Multidisciplinary design optimization 20.Military aircraft design – overview 21.Environmental issues 22.Design skills © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Content • Aerodynamic Design （2） – Airfoil – Wing – Fuselage – Tail Geometry • Aerodynamic Forces and Moments （2） – Lift Estimation – Drag Estimation – Moment Estimation (not included • CFD-based aerodynamic shape design （2） – Geometry Parameterization – CFD Simulation – Reverse Design and Numerical Optimization •3 © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics International Standard Atmosphere (ISA) • An atmospheric model of how pressure, density, temperature, and viscosity relate to altitudes (ISO 2533:1975) • Basic law • Troposphere • Stratosphere (Temperature Constant, about 10-50km) • Sea-level data •4 g dz dp Buoyancy Equation   Gas Law p  RT L dz dT                   1 0 0 RL g T T                  RL g T T p p 0 0   0 0 z z RT g e        0 0 z z RT g e p p    T  T0 t0  15C T0  288.15C 3 0   1.225kg / m a  340.294m/s g0  9.80665 1 1 287.05278   R  J  kg  K © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics ISA Data Chart 0.0000 0.1000 0.2000 0.3000 0.4000 0.5000 0.6000 0.7000 0.8000 0.9000 1.0000 0 5000 10000 15000 20000 25000 30000 T/T0 p/p0 density ratio © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Topics Covered • Lift – Clean configuration – Effect of high lift devices on aero coefficients • Drag – Drag breakdown – according to physical mechanisms • form drag + friction drag + wave drag – Drag breakdown – component based • Use of form factors – Trim drag • Methods and software – DATCOM, ESDU – Coding it yourself

2018/3/11 5 © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Skin Friction Drag: Laminar flow over a smooth flat plate tw   , 2 , 0 0.664 0.664 1 Re 2 f lam x x c Vx V        , 0 , 0 1.328 Re l f lam F lam l l c dx C dx     Local skin friction coefficient Average, or integrated, skin friction coefficient X=0 X=l Re  Vl /  where , is characteristic length, fuselage length or wing mean aerodynamic chord l © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Laminar, Transitional, and Turbulent Flow •26 laminar transitional turbulent 104 105 106 107 Rex 10 4 1 1000cf Turbulent cf=0.74Rex -1/5 Laminar cf=1.328Rex -1/2 Transitional 0 X © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Skin Friction Drag in Turbulent Flow D C S q f turb F turb wet , ,  106<Rel<109 CF is small but the dynamic pressure and wetted area are large    0.65 2.58 2 10 , log 1 0.144 0.455 R M CF turb   106 107 108 109 Rel 0.0045 0.0035 0.0025 CF © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Wave Drag • Drag increases due to compressibility effects for airspeeds higher than critical Mach number Mcr, due to the appearance of shock waves. • This increase has a moderate slope until reaching drag divergence Mach Mdd • Drag divergence Mach is defined as – 20-drag-count increase, or – drag-increase slope of 0.1 Mcr Mdd © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Drag Build-up for the Wing DW,0 = DW,f + DW,p = zero-lift drag DW,0 = CF,turbSwet q + k CF,turbSwet q DW,0 = (1 + k) CF,turbSwet q DW,0 = KWCFSwet q The drag estimate is based on a multiple of the friction drag, KW, the form factor for the wing © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Drag build-Up with Component Form Factors ,0 ,0W W D D C Sq  ,0 , W W wet D W F turb S C K C S  ,0 , 1 i i n wet D i F turb i S C K C  S   Zero-lift drag coefficient for the wing Zero-lift drag coefficient for the airplane

2018/3/11 6 © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Calculation of Form Factors © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Fuselage Drag Breakdown •32 LN LF LC LR DF D D D D D D D       p NC f NC p C f C p TC f TC , , , , , , 0 Base drag © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Fuselage Drag= Friction Drag + Base Drag •33   , , , , . Re, f NC f C f TC p BASE wetted p BASE D f D D D D D D S D c c M qS S qS        , 0.029 D BASE wetted f base c S c S Hoerner suggests  3 0.029 2 wetted base D f wetted f S S c c S S S c S         Then the fuselage drag coefficient becomes Hoerner, S.F.: Fluid Dynamic Drag, published by the author, 1958 © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Fuselage Drag General Equation •34 2 2 2 2 2 2 4 4 4 wetted base S A d L d k dL k A k A F KF S b b d b S k d A k A d K S b b                                                     With span denoted by b and the aspect ratio A=b2 /S we have 0.029 4 D f f c K c F c F         Then the fuselage drag coefficient is given by 0 5 10 F cD © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Fuselage Form Factor: different correlations •35 kfactor in fuselage drag correlation 0 0.2 0.4 0.6 0.8 1 0 5 10 15 20 Fineness Ratio L/d k NAA Datcom Torenbeek Hoerner(Kf=1+k) © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Wing Form Factor •36 k - factor in wing drag correction 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0 0.05 0.1 0.15 0.2 Thickness Ratio t/c k Jenkinson Torenbeek NAA Hoerner DATCOM 2 DATCOM 1 (Kw=1+k)

2018/3/11 7 © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics DATCOM Method – Appendix F of the Design Handbook Wing, Horizontal Tail, and Vertical Tail in Subsonic Flight 4 ,0 . . max max 1 100 wet D L S F t t S C L R C c c S                                L= 1.2 for (t/c)max located at x > 0.3c 2.0 for (t/c)max located at x 1 (Fig. 4.1.5.1-28a) http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19930090976_1993090976.pdf New link for NACA Technical Report 824. © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics DATCOM Method – Appendix G of the Design Handbook Fuselage in Subsonic Flight 3 ,0 , 1 60 0.0025 B B S D F D b B l l S C C C d d S                        Note that this drag coefficient is referenced to the maximum cross-sectional area of the body. To use this for the airplane this CD,0 must be multiplied by SB /S to correct the reference area Body with blunt base Closed body (CD,b=0) d © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Drag Coefficients for Landing Gear and Flaps DCD, landing gear =3.30x10-3WTO 0.785 /S (zero flap deflection) DCD, landing gear =1.79x10-3WTO 0.785 /S (full flap deflection) DCD,flaps = 0.9 (cf /c)1.38 (Sf /S) sin2 d (slotted flaps) Landing Gear Flaps © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Drag-Due-to-Lift (Induced Drag) • Two methods to estimate K – Based on the concept of leading edge suction (better for high-speed designs) – Based on Oswald efficiency factor 2 CD  CD0  KCL Drag-due-to-lift factor © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Oswald Efficiency Factor in Conceptual Design Samoylovitch, O. and Strelets D., “Determination of the Oswald efficiency factor at the aeroplane design preliminary stage”, Aircraft Design 3(2000) Where is the Oswald efficiency factor, relating to overall aerodynamic efficiency, for parabolic drag polar Reflects the lift deterioration caused by the distortion of an elliptical lift distribution, affected by • wing planform parameters (taper and aspect ratio, LE sweep) • presence of other components such as nacelle, fuselage e Empirical equations can be used to estimate e 1.781 0.045  0.46 0.68 e   A  4.611 0.045 cos  3.1 0.68 0.15 e   A LE  Unsweep wing sweep wing A more detailed method can be found: © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Influence of fuselage on Oswald efficiency factor Oswald efficiency factor wing only Actual Oswald efficiency factor

2018/3/11 10 © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Where are we going 55 • CFD has become a major design tool, shape optimization is becoming more affordable • CFD needs to be developed in collaboration between Universities and Industry into a system of tools of various fidelity • MDA and MDO in industry settings will be one the key enablers for further improvements • Supercomputing continues to be an enabling factor © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics CFD Simulation Models Navier-Stokes Equations Cannot be analytically solved so far Lifting-line theory Panel code Euler codes Various N- S models Direct Numerical Simulation (DNS) Large Eddy Simulation Viscous terms dropped Various turbulence models, RANS Used on simplified geometries Also known as boundary element methods, fast, 2D/3D Largely research topic CFD simulation is usually a trade off among model fidelity, numerical accuracy and setup/computing time. Book to read “Computational Fluid Dynamics” by Anderson Full Potential code Rotational terms dropped © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Aerodynamic Design Methods • Inverse design – Different flow models can be used • Incompressible inviscid flow • Transonic potential flow • Euler and Navier-Stokes Model – Features: • Matching prescribed pressure distribution given by experienced engineers • Depends on the pressure distribution • More efficient compared to optimization methods • Optimization design – Two categories of methods • Gradient based approach: quasi-newton, etc – Control theory approach (Jameson) – Gradient computed using finite difference • Evolutionary Methods: genetic algorithms, etc – Features • Aerodynamic performances set as objectives and constraints • Optimized by shape modification based on different shape representations 57 © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics Inverse design methods • In inverse design methods, many designers prescribe the airfoil pressure distribution cp on the airfoil and define the objective function to be minimized as • A baseline airfoil is selected as the starting point – some expertise is necessary to choose a good starting point • An iteration process is required to achieve convergence OBJ  (cpdesigni i1 N   cpactuali ) 2 © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics CFD-based Shape Optimization CAD Geometry Parameterization Mesh Generation (Discretization) Flow Solvers Input parameters (length, width, etc) Objective function and Constraints (lift, drag) Updated parameters (length, width, etc) Overall procedure used in CFD-based aerodynamic optimization Optimizers © Shanghai Jiao Tong University – Dr. Wenbin Song School of Aeronautics and Astronautics How aircraft geometry was modelled Source: D.G. Clark and A. Gibson, Concord, Phoebus Publishing Company, 1976/77