|
AES=V=
Download "Aeroelastic Application of
AES=V="
Download "Meshing around with AES=V="
Download "Mollifyer in section Warping"
|
   |
|
|
|







|

Flat
layout & secundary drawings

Flat
layout

3 D Contour
&Vector (xyz-c-uvw) projection plots
|

Quasi
3D & secundary drawings

2 D line
and symbol (xy) plots
2D
vector drawing mode demos
Drawings
of
sectional pressure & geometric
distributions at selected spanstation
comparing 11 datasets calculated for a
transporttype wing at several Mach and
AOA combinations
|
|
|
|
|
PURPOSE
- Visualization & Analysis &
Comparison of calculated and experimental
data.
INPUT
- Simple & Uniform data input
format of multiple data sets
- Datasets are composed of multiple
datasheets.
- Datasheet have a columnwise
tabular format
- The structure of a sheet can be
line, patch,block, random, line segment,
triangular, quadrilateral ..
OUTPUT
- Screen
- Postscript files
- ppm files
OPERATION
- GUI based on GLUI, GLUT and OpenGL
- Can also be executed in
batch.
SPECIALS
(Pre and Postprocessing)
- Warping of datasets by
efficient volume spline class methods (FSI
data or Digital Pressure
Painting).
- Mollifying of
datasets to seed scarse trusted data
in an other baseline dataset. The
results is cardinal with respect to the
trusted data and adheres to the trends
of the baseline dataset.
- Cutting planes (geometric slicer)
- H continuation of harmonic data
- Surface
Gridding & Design
- Multiple patches
- Patch creation/redistribution &
assembling
- Volume
Gridding
- Multiple blocks
- Hexaeder, tetraeder & prismatic
meshes
- Hyperbolic, elliptic & algebraic
generation
- Elliptic smoothing
- Analysis
- Chimera tagging
- Flutter and
Time Trace Analysis
- PK,PH,K & HK,HH Flutter Analysis
- Spectral Analysis of Time Traces
- MIMO identification
|
GRAPHICS
- Multiple figures with
multiple datasets
- 2 D line and symbol (xy) plots
- 2 D Vector (xy-uv) plots
- 2 D contour (xy-c) plots
- 2 D shading (xy-#) plots
- 3 D line and symbol (xyz)
projection plots
- 3 D Vector (xyz-uvw) projection
plots
- 3 D contour (xyz-c) projection
plots
- 3 D shading (xy-#) projection
plot
- Quasi 3D figures with multiple
dataheets
- Flat layout figures with multiple
datasheets.
- OpenGL visualization mode
- Multiple datasets (multiple
sheets)
- 3D geometry (xyz) (patches,
grids)
- 3D Vectors/Displacements
(uvw)
- 3D Scalars (c)
- Contour Lines and Shading
& Scatter
- Symmetric/anti-symmetric
extentions,
with respect to ground & wall
- Blanking
- Et cetera
|
|
|
- OpenGL
visualization mode demo

- OpenGL
visualization mode demo
- Surface pressure,
velocity & geometric
distributions comparing 11
datasets calculated for a transporttype
wing at several Mach and AOA
combinations
OpenGL
visualization mode demo
- Volume pressure, velocity
& geometric distributions
comparing 11 datasets calculated for
a transporttype wing at several Mach
and AOA combinations
|

Planar
Cutting
demo
The volume data (left)
is intersected with 6 cuts (right) which
are connected with triangulars

The first cut connected with
triangulars

- The first cut as scattered data
|
|
|
|
|
|
|
|
|
Mollifying
There are many occasions in which characteristic
data describing A/C systems are
scarce/coarse (reduced in order) due to economic
reasons (wind tunnel testing, flight testing and
Hi-Fi CFD simulations). Examples are tabular
data for engines, lift & drag aerodynamic
forces, high-fidelity generalised forces needed
in flutter certification, Hi-Fi CFD data in
optimization processes. Often a correction
method or surrogate model is developed to
continue/interpolate the data.
The mollifyer can be regarded as
injecting the valuable (accurate) scarse data in
an already existing dataset in a black box
manner. The approach is suitable for impact
assessment of design changes, starting data for
optimization and reverse engineering.
Mollifyer demo

The upper left data is injected in the
baseline data (lower left) resulting in the
upper right data. Note that the injected
data is invariant for the mollifying.
|
Mollifyer
demo
The result is cardinal with respect to
the trusted data and adheres to the
trends of the baseline dataset.

The injected scattered data is
visualized after triangularization

Contours of the baseline and the
mollifyed data
|
|
|
|
|
Warping Demo

- The scattered FEM data
(left) is warped to the
aerodynamic surface (right). The scattered
data is also presented at the right.
|
- Warping Demo

- The scattered FEM data
(left) is triangularized. The
scattered triangularized
data is
also presented at the right.
|
|
|
|
|
GRID
GENERATION
|
|
|
- A single block grid generated
about 5
- components.

- A single block grid generated
about 9
- components.
|
A
A single block grid generated about 6
- components
- A single block grid generated
about transportype AC
|