AERODYNAMIC ANALYSIS Research Assistant Prof. Paolo MAGGIORE FOR - PowerPoint PPT Presentation

VARIABLE-FIDELITY Ing. Laura MAININI Ph.D. Candidate – Research Assistant Ing. Marco TOSETTI AERODYNAMIC ANALYSIS Research Assistant Prof. Paolo MAGGIORE FOR MULTIDISCIPLINARY Associate Professor Department Of Mechanical WING DESIGN and Aerospace Engineering (DIMEAS) STAR Global Conference 2012 19-21 March 2012, Amsterdam, NL

Outline 2  Introduction  The design problem  The design environment  Multidisciplinarity & Interdisciplinarity  Time and cost containment  Approximated model for aerodynamic coefficients  Methodology  Conclusions STAR Global Conference - Amsterdam, March 19-21, 2012

Introduction 3 Aerospace engineering project is Necessity to develop an characterized by: Optimal Design since  need to manage complexity preliminary stages i.o.t.  need to maintain competitiveness reduce changes in further  design quality design phases  reduction of time to market  development & production costs containment Multidisciplinary Analysis and Concurrent Engineering (CE) & Optimization (MAO) Addressing: Need to integrate Complexity management design phases Competitiveness requirements STAR Global Conference - Amsterdam, March 19-21, 2012

The design problem 4 Design of wing eventually able to assume optimized shape for different mission legs Multidisciplinary Integrated Design Environment Able to address the three main key issues: Multidisciplinarity Interdisciplinarity Cost & time containment STAR Global Conference - Amsterdam, March 19-21, 2012

The design environment 5 Multidisciplinarity & Interdisciplinarity STAR Global Conference - Amsterdam, March 19-21, 2012

The design environment 6 Multidisciplinarity Interdisciplinarity Multilevel distributed Wing design framework that analyses architecture that integrates different manages variables and disciplines models distributing the process across three levels STAR Global Conference - Amsterdam, March 19-21, 2012

The design environment 7 Multilevel Analysis architecture  The most external loop deals with geometric configuration and mission variables  A first inner loop manages performance and structural layout variables  The most internal loop performs structural sizing STAR Global Conference - Amsterdam, March 19-21, 2012

The design environment 8 Geometry management Level 1 Geometry layout Flight conditions & Structural Aerodynamic analysis mission leg layout pressure field management management Level 2 Structural Structural sizing Aerodynamic Performance Flight management layout analysis analysis conditions Level 3 CL & CD Flight mechanics Approximation Structural Manufacturing Structural static costs analysis sizing & dynamic analysis Material model STAR Global Conference - Amsterdam, March 19-21, 2012

The design environment 9 Cost & time containment STAR Global Conference - Amsterdam, March 19-21, 2012

The design environment 10 Geometry management Level 1 Geometry layout Flight conditions & Structural Aerodynamic analysis mission leg layout pressure field management management Level 2 Structural Structural sizing Aerodynamic Performance Flight management layout analysis analysis conditions Level 3 CL & CD Flight mechanics Approximation Structural Manufacturing Structural static costs analysis sizing & dynamic analysis Material model STAR Global Conference - Amsterdam, March 19-21, 2012

The design environment 11  Focusing attention on the most expansive HF analysis involved in the design process  Aerodynamic analysis of the wing i.o.t. evaluate lift and drag coefficients  The use of a finite volume CFD model to solve the Navier-Stokes equations at each cycle is definitely too much expensive.  However a good accuracy in the results is necessary and what comes from other cheaper models is not enough Variable fidelity strategies and surrogate modeling techniques to obtain a fast and agile model for aerodynamic analysis Ad hoc methodology STAR Global Conference - Amsterdam, March 19-21, 2012

Aerodynamic Coefficients Approx 12 The methodology • Complete design space exploration 1 • Screening and reduction of space dimensionality 2 • Reduced design space exploration 3 • Surrogate models construction and comparison 4 • Correction for low fidelity model 5 STAR Global Conference - Amsterdam, March 19-21, 2012

1. Complete design space exploration 13  All design variables are considered, 23 variables:  20 geometry variables  3 flight condition variables  Exploration technique: 2-level fractional factorial  It allows broad but intensive investigation of design space  It provides useful information about the edges of the space  64 sample points are evaluated using high fidelity aerodynamic analysis model:  Finite volume CFD commercial code STAR-CCM+ is used STAR Global Conference - Amsterdam, March 19-21, 2012

High fidelity model 14  Fully parametric models  Finite Volume model implemented using STAR-CCM+ by CD-adapco.  Java macros have been recorded and parameterized. STAR Global Conference - Amsterdam, March 19-21, 2012

High fidelity model 15  The model for this CFD analysis is based onto the solution of Navier-Stokes governing equations for three dimensional, turbulent flow.  It represents the high fidelity (HF) aerodynamic analysis option. STAR Global Conference - Amsterdam, March 19-21, 2012

2. Screening and reduction of space dimensionality 16  Determination of which variables predominantly contribute to the output  A variance based technique was chosen  It is very fast  It exploits the 2-level DOE  Variables whose total effects contribute up to 85% of the results are considered STAR Global Conference - Amsterdam, March 19-21, 2012

2. Screening and reduction of space dimensionality 17 Complete Reduced Variables Range Initial value Activation Activation Dihedral Angle [deg] X X 2 : 6 5 Root chord [m] X - 6 : 9 7 Semi Wing Span [m] X - 15 : 20 16 Sweep Angle [deg] X X 10 : 40 30 Taper Ratio X - 0.15 : 0.5 0.3 Twist Angle [deg] X - 0 : 5 5 Airfoil Camber a [X X X X] [ - - - - ] 0 : 4 0 Airfoil Camber Position a [X X X X] [ - - - - ] 0 : 4 0 Airfoil Thickness % a [X X X X] [ - X - -] 10 : 40 12 25 : 50 – 60 : 75 Aifoil Position (spanwide) % b [ - X X - ] [ - - - - ] 0 - 30 - 60 - 100 Airspeed [m/s] X X 100 : 200 180 Altitude [m] X - 6000 : 12000 10000 Angle of attack [deg] X X -2 : 12 5 a Each value of the vector refers to a different naca4digit generative airfoil spanwise; the first one is the root airfoil, the last one is the tip airfoil so that their position is fixed b Because the root and tip airfoil are fixed, the only two airfoils which position can change are the mid-ones STAR Global Conference - Amsterdam, March 19-21, 2012

3. Reduced design space exploration 18  Only 5 screened variables are considered, 18 are blocked to initial values  Exploration technique: 5-level Central Composite Design (CCD) space inscribed  It allows a denser exploration that enable the construction of more reliable approximated models  Inscribed because mid-points are more interesting than outer points  27 sample points are evaluated using different fidelity aerodynamic analysis models:  High fidelity model HF – finite volume CFD  Low fidelity model LF – Vortex Lattice Method STAR Global Conference - Amsterdam, March 19-21, 2012

Low fidelity model 19  Fully parametric panel model  Vortex Lattice Method code: AVL – Athena Vortex Lattice 3.27  Computational Fluid Dynamic (CFD) numerical method based on the theory of ideal and potential flow.  The flow field is considered inviscid, incompressible and irrotational (compressible flow can be considered by the use of the Prandtl-Glauert transformation)  The thickness of the modeled surfaces is neglected  The small angle of approximation is applied.

4. Surrogate models construction and comparison 20 High fidelity Low fidelity  27 sample points  27 sample points  21 for models construction  21 for models construction  6 for models validation  6 for models validation  HF data-fit surrogates  LF data-fit surrogates  Response surfaces  Response surface  Kriging models  Kriging models STAR Global Conference - Amsterdam, March 19-21, 2012

4. Surrogate models construction and comparison 21  The response surface with interaction terms (RSi) seems to be the best approximation for both C L and C D coefficients such as for both low and high fidelity evaluations p p      RSi x ( ) a a x a x x 0 i i ij i j   i 1 i j  It is the basic model to which the implemented corrections are applied and tested STAR Global Conference - Amsterdam, March 19-21, 2012