A Framework for Fast CFD-based Aero-Servo-Thermo-Elastic Analysis

Politecnico di Milano 

Dipartimento di Ingegneria Aerospaziale 

Dottorato di Ricerca di Ingegneria Aerospaziale (XXVI ciclo) 

A Framework for Fast CFD-based 

Aero-Servo-Thermo-Elastic Analysis 

PhD student: Matteo Ripepi 

Advisor: Prof. Paolo Mantegazza 

March 2, 2011

PhD research proposal PhD work planning 

Outline 

1 PhD research proposal 

Introduction 

Research project 

2 PhD work planning 

Courses 

Software 

Work planning 

Matteo Ripepi Fast high-fidelity aero-servo-thermo-elastic analysis

PhD research proposal PhD work planning Intro Multimodel ROM Mesh Implicit Thermo 

Outline 


Introduction 



Courses 

Software 

Work planning 



Computational aeroservoelasticity 

Load factor 

3 

2 

1 

0 

Loads database prediction 

Flaps Down 

is fundamental in the overall aircraft design and development 

involves a large amount of aeroelastic analyses 

Flaps Up 

CFD mostly done 

near cruise point 

VEAS 

High-fidelity computational aeroservoelasticity 

still too computationally expensive for the preliminary design stage, 

and therefore used for a limited number of cases (e.g. flutter). 

high potential for the prediction of critical flight loads 

necessary to address new challenges in aircraft design 




Purpose of the research 

Accelerate and improve the efficiency and accuracy of high-fidelity 

computational aeroservoelastic analysis 

Developments towards a faster CAE based loads analysis process: 

Variable fidelity multimodel multidomain coupling approach 

New reduced order modelling techniques 

Mesh motion enhancements 

Implicit solver for CFD 

Thermal solver for aerothermoelasticity 

Accuracy/fidelity 

Area of 

interest 

Potential 

Methods 

Euler 

Methods 

Navier-Stokes 

Methods 

Computational resources (cost/time) 























FSI based on a partitioned approach, coupling solvers with 

different levels of fidelity to speed-up full order aeroelastic analysis. 

Coupling in time ⇒ hierarchical approach 

Coupling in space ⇒ hybrid approach 









Switch during the simulation between full/low order model and 

multigrid to accelerate the convergence of high fidelity subiterations. 

Adaptive ROM by basis enrichment 

During the RANS simulation ⇒ extract low-order subspace 

ROM used to continue the simulation while the solution error 

is sufficiently small. 

If error rises ⇒ return to a full order model initialised by ROM 

RANS simulation will continue and will update the subspace 

until the ROM can be used again. 









Switch during the simulation between full/low order model and 

multigrid to accelerate the convergence of high fidelity subiterations. 

Low-fidelity on coarse mesh 

prolongation 

⇄ 

restriction 

High-fidelity on fine mesh 









Low/full order domain decomposition 

Criterion for the distance between interface and wall boundary 

Interface operator (conservative, stability, robustness, . . . ) 

Numerical scheme to solve the low-full order coupled model 

Far field 

POTENTIAL/ROM 

Ω 

out Γ 

Ω 

in 

Near field 

RANS 

ROM used locally where the 

solution error is sufficiently small. 





Variable fidelity multimodel coupling approach 


















ROM requires a set of instantaneous flow solutions (snapshots) 

Projection of onto a reduced subspace 

Direct identification of a system of the required form 

Hilbert-Huang Transform decomposition of aeroelastic system 

adaptive data analysis for nonlinear and nonstationary processes. 

Subspace-based identification methods 

identify a state-space model directly from input-output data 

Global aeroelastic ROM 

parametric input space 

interpolation of flight data 

(full/low order simulations) 

Polinomial response surface 

Kriging/Co-Kriging 























Robust dynamic mesh handling for aeroservoelastic simulation 

purposes, trough the use of a mesh motion solver and topological 

optimization (e.g smoothing, refinement, edge/face swapping). 

Mesquite library 

[Menon et al.,2010] 

Large structural deformations/motions keeping mesh quality 

Control surfaces motion 

Dual-mesh: cell-centered (CC) ⇄ cell-vertex (CV) discretization 

accuracy in the computation of derivatives 

direct computation of the pressure on the wall 

problem: may create non-convex cells near the boundary 























Numerical scalability is required to take full advantage of parallel 

computing techniques. 

Newton-Krylov methods 

standard for solvers of implicit, large-scale, nonlinear systems 

fast convergence 

ability to effectively use scalable preconditioners. 

Preconditioner 

multigrid techniques 

approximate factorization of Jacobian (Jacobian-Free method) 























Thermal solver for CFD-based aerodynamic heating 

aero-thermo-elasticity 

hypersonic aeroelastic stability problems 

aeroelastic analysis that accounts for the effect of thermal 

stresses and material degradation. 

Aerothermoelasticity will also take advantage of ROM tecniques. 

q aero 

q strd 

q cond 

q rad 

wing 

structure 

Exposed 

surface/TPS 

Heat 

transfer 

Aerodynamic 

forces 

Structural 

displacements 

Matteo Ripepi Fast high-fidelity aero-servo-thermo-elastic analysis 

Inertial 

effects




Thermal solver for CFD-based aerodynamic heating 

aero-thermo-elasticity 

hypersonic aeroelastic stability problems 

aeroelastic analysis that accounts for the effect of thermal 

stresses and material degradation. 

Aerothermoelasticity will also take advantage of ROM tecniques. 

q aero 

q strd 

q cond 

q rad 

wing 

structure 

Exposed 

surface/TPS 

Control 

Heat 

transfer 

Aerodynamic 

forces 

Structural 

displacements 

Matteo Ripepi Fast high-fidelity aero-servo-thermo-elastic analysis 

Inertial 

effects









Aeroelastic applications 

highly nonlinear flow phenomena arising in critical loads conditions 

transonic flutter 

LCO involving nonlinear aerodynamics 

buffeting 

transonic flow with shocks 

and flow separation 

gust response 


PhD research proposal PhD work planning Courses Tools Planning 

Outline 


Introduction 



Courses 

Software 

Work planning 



PhD work planning 

Courses 

Credits 

Functional Analysis and PDEs (F. Gazzola) 5 

Dynamics of Multibody Systems (P. Masarati, F. Cheli) 10 

Computational Gasdynamics (L. Quartapelle) 5 

Model Identification and Data Analysis (S. Bittanti) 5 

Dynamic of Nonlinear Systems (S. Rinaldi) 5 

Other activities 

Summer schools, seminars, publications on journals, presentations 

at international conferences and exchange periods at foreign 

universities. 




Tools 

High-fidelity CFD solver AeroFoam (based on OpenFOAM) 

[Romanelli, Serioli, Mantegazza, 2010]. 

In-house potential flow solver [Parinello, Mantegazza, 2010] 

Finite element solver Code-Aster 

MultiBody Dynamics (MBDyn) 




Bibliographic research 

Familiarization with C++, PETSc, AeroFoam, CodeAster, MBDyn 

Development and implementation of dynamic mesh motion solver 

Development and implementation of model order reduction techniques 

Development and implementation of low/high fidelity aeroelastic coupling 

Development and implementation of implicit solver for CFD 

Development and implementation of thermal solver for aero-thermo-elasticity 

Validation and assessment through the application to test cases and real cases 

Courses 

Bibliography 

Codes tutorial 

Multi-model solvers 

Mesh solver 

ROMs techniques 

Implicit solver 

Thermal solver 

Applications 

Doctoral thesis 

2010 2011 2012 

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 


Bibliography 

Dowell, E.H. and Hall, K.C., “Modeling of Fluid-Structure Interaction”, 

Annual Reviews of Fluid Mechanics, 33:445-490, 2001. 

Schuster, D.M, Liu, D.D, Huttsell, L.J., “Computational aeroelasticity: 

success, progress, challenge”, J. Aircraft, 40(5):843-56, 2003. 

Lucia, D.J., Beran, P.S., Silva, W.A., “Reduced-order modeling: New 

approaches for computational physics”, Progress in Aerospace Sciences, Vol. 

40, no. 1-2, pp. 51-117. Feb. 2004. 

A. Parinello, P. Mantegazza, “Independent Two-Fields Solution for 

Full-Potential Unsteady Transonic Flows”, AIAA Journal, vol.48 no.7 

(1391-1402), 2010. 

Romanelli, G., Serioli, E., Mantegazza, P., “A “Free” Approach to 

Computational Aeroelasticity”, 48th AIAA Aerospace Sciences Meeting 

Including the New Horizons Forum and Aerospace Exposition. Orlando, Florida, 

Jan. 4-7, 2010. 

Culler, A.J. and McNamara, J.J., “Studies on Fluid-Thermal-Structural 

Coupling for Aerothermoelasticity in Hypersonic Flow”, AIAA Journal, Vol. 

48, No. 8, August 2010, pg. 1721-1738. 

AeroFoam; http://www.aero.polimi.it/freecase/ 

MultiBody Dynamics (MBDyn); http://www.mbdyn.org/

A Framework for Fast CFD-based Aero-Servo-Thermo-Elastic Analysis

Create successful ePaper yourself

Delete template?

Save as template?