Aeroelastic Coupling in Sonic Boom Optimization
of a Supersonic Aircraft
Authors' e-mails:
Mariano.Vazquez@sophia.inria.fr
Alain.Dervieux@sophia.inria.fr
koobus@darboux.math.univ-montp2.fr
This web page is no more than a brief summary of the project. For
the complete sources, please refer to the "Up-to-date publication's list"
section and download the papers available, here.
This research is part of the project:
under way in INRIA - Sophia Antipolis, France.
Research sketch:
A three module scheme
The coupled aerodynamic-aeroelastic optimization problem is then divided
in two phases, that repeat iteratively until a convergence criteria is achieved.
To a first aeroelastic analysis phase it follows an aerodynamic
optimization stage. Each phase corresponds to a different module, and
a there is a third module connecting them, a remeshing tool, due to
the fact that the optimizer modifies only the surface discretization, and
so a corrected volume mesh is needed as a link between the optimization and
analysis modules.
The aeroelastic analysis module: a
loosely coupled fluid-structure solver.
The aerodynamic optimization module: an aerodynamic
optimizer.
The remeshing module: a remeshing tool.
The aeroelastic analysis module
The solution of the coupled fluid-structure problem is computed by a
staggered solution procedure in time. This kernel yields a coupled
fluid-structure static analysis using a pseudo time advancing scheme with
two stages: a fluid evaluation stage followed by a structural computation,
based in the pressure distribution given by the preceding one. At the first,
fluid stage, a mesh conforming to the structure deformation is built by moving
the vertices with a pseudo-structural model. Then the flow is advanced towards
steadiness on this mesh. The spatial discretization of the compressible flow
Euler equations is based on a finite volume method, using a second order
space accurate scheme based on Roe solver. For addressing the problem
of flow simulations on moving grids, an Arbitrary Lagrangian Eulerian
formulation is incorporated in the flow solver (in the present case of static
coupling, this is not essential when the mesh is moving from the initial position
to the new one). Next, at the structural stage, the pressure loads are applied
to the structure and the resulting displacements are computed. The structure
is represented by a finite element model on a thin plate, embedded
in the wing, which is a simplified model of the internal structure. The displacements
are finally transferred to the wet surface wing, producing a deformed volume
mesh. This volume mesh is the output of the aeroelastic analysis module.
References:
C. FARHAT and M. LESOINNE,
On the accuracy, Stability and Performance of the Solution of Three-Dimensional
Non-Linear Transient Aeroelastic Problems by Partitioned Procedures.
AIAA paper 96-1388. 1996.
C. FARHAT and M. LESOINNE and N. MAMAN,
Mixed explicit/implicit time integration of coupled aeroelastic problems:
three-field formulation, geometric conservation and distributed solution.
Int. J. Num. Meth. Fluids. 21, pp. 807-835.
1995.
The aerodynamic optimization module
The aerodynamic optimizer is an evolution of that of the first stage of the project. It is a CAD-Free
based algorithm: the design parameters space is set by the physical positions
of each of the skin discretization nodes placed in the shape to be optimized.
Here, the shapes derived from the the iterative optimization process are
characterized using a transpired perturbation. According to this,
to each of the skin nodes it is assigned a scalar which corresponds to a
(small) displacement in its normal direction. High frequency effects in space
are dramatically reduced by using a multilevel preconditioner applied
to the shape gradient. In order to cope with the probably very large number
of parameters defining the target shape, a discrete adjoint problem
is solved. The optimization algorithm is designed to reduce the sonic
boom downards emission keeping some target aircraft performance properties,
basically lift and/or drag. The incidence angle is corrected at each
iteration to recover the lift that the shape modifications could not improve,
given a target lift.
References:
Check the project's web page, here.
The remeshing module
The remeshing module works as an interface between the aeroelastic
module and the optimization one. The aeroelastic module already includes
a remeshing algorithm to take into account the shape deformations. They are
transferred to the optimization module as a modified volume grid, called
thecruise mesh for a given coupling iteration, suitable to be the
optimizer input. On the other hand, the optimizer's output is a shape
correctiondefined on the surface nodes according to the transpiration
condition. Through a remeshing algorithm that adapt the mesh to the new,
optimized surface, a corrected volume grid is produced. This volume grid
will be used in turn as input by the aeroelastic module. The algorithm generates
a new mesh by moving the nodes of the input one with a pseudo-structural
model, under the constraint that the new boundary nodes are the result of
the movement on input ones with the input shape correction.
Results:
This is a brief collection of the latest results. For a thorough
gallery, refer to the Up-to-date project's publication's list. The
wings of the Dassault Aviation projected Supersonic Bussiness Jet
(SBJ) are optimized according to the proposed scheme. The isolated
wings, extracted from the available original geometry, are taken as a starting
point case.
Figure 1. SBJ wings. Left, wing discretization showing location of three cross-sectional
cuts. Right,
plate used to model the aeroelastic behaviour.
Figure 2. SBJ wings. Coupled scheme convergence through the coupling iterations.
Left, Per-surface-node (called "Mean") Aeroelastic Displacements.
Right, Mean Optimization Deformation.
Outboard airfoil
|
Middle airfoil
|
Inboard airfoil
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Figure 3. SBJ wings. Comparison of the optimized
landed coupled and rigid airfoils at the three
locations. Also the cruise coupled optimized
airfoils are shown.
|
Lift coefficient
|
Incidence angle
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Sonic boom term in the cost functional
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Figure 3. SBJ wings. Evolution
of different
parameters for each of the
coupling iterations.
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Mariano Vázquez is the web page's owner.