Geometrical adaptationsfor the use of numerical simulationin a modular air traffic simulation platform

Romain KervarcGyslain HervieuxJean BourrelyPatrice Carle

Office national d’etudes et de recherches aerospatiales (Onera)29 avenue de la Division Leclerc, 92322 Chatillon, Franceromain.kervarc, gyslain.hervieux, jean.bourrely, patrice.carle@onera.fr

Abstract

More and more actors in aeronautics look for an efficient and precise wayto simulate the behaviour and impact of airplanes in their environment ina very large scale: e.g. assessing the impact on human activities of a wholeday of air traffic around an airport. To achieve this, it is necessary to com-bine various large numerical physical simulations in a functional simulationframework representing an airport, which rises interesting geometric prob-lems. In this paper, we present Onera’s simulation platform IESTA, whichis currently used for the assessment of acoustic and chemical emissions nearan airport, and we detail the geometric adaptations that were needed in or-der to make use in this platform of two Onera numerical simulation suites.

1. Introduction

1.1 The IESTA platform

Whereas the capacity demand of worldwide air transport steadily grows,air transport systems are confronted to two crucial problems: the risingfuel cost, and environmental constraints. Many research programs try toaddress this complex issue, such as Clean Sky JTI, one of the largest Eu-ropean research projects ever.As new operational concepts, new technologies, arise, many candidate so-lutions are designed. But then, a key issue is their evaluation, which isalready complicated in itself, due to the complexity of air transport sys-tems which requires to use many criteria and metrics, is also impossible inpractice: it is of course not realistic to implement an air transport solu-tion just to see what comes out. Hence, a system engineering approach isnecessary in order to be able to assess those solutions.

While a huge number of simulation tools exist, most are designed for stand-alone operation and to meet specific needs rather than to conduct analysesof system-wide performance. IESTA, a project being developed at Onera[1], aims to develop a generic simulation infrastructure and an extensibletoolbox of models in order to provide the aeronautical community withadvances in modelling and simulation tools through a global evaluationfacility. [2] describes the development process of the platform, puttinga fast-time simulation framework together with scenario generation andsimulation management utilities, databases and post-processing tools.

1.2 Acoustic and chemical pollution assessment

In this context, such a platform has two opposite goals: on the one hand,taking into account the systemic aspects of a complex air transport systemwhich is to be evaluated (i.e. many aircrafts, airports, environment, etc. ina sophisticated loop of interaction) and, on the other hand, using accuratephysical models to be able to assess the retained solutions.As for models involved in the IESTA simulation platform, the initial ef-fort concentrates on the development and the validation of a toolbox ofcompatible models to conduct high-fidelity assessments of concepts andtechnologies in order to mitigate the noise and air pollution impact of airtraffic around an airport [3]. The set of environmental models integratedinto this platform will form the core of the first IESTA application: CleanAirport. [4] gives precisions on how the underlyinf non-real-time softwaremay still be used in a context of real-time, or fast-time, simulation.

This paper deals with the issue of geometrical representation: each ofthe physical simulations encapsulated into the platform has specific needs,whereas the simulation infrastructure has to provide a visual representationof the simulated system. Due to the diversity of the physical models, theadaptation must be done case-by-case, starting from the specific needs ofeach component and ensuring step by step the consistency between physicalaspects and visualisation.In the following, two particular cases will be treated, namely the integra-tion of two Onera simulation codes, one for acoustic propagation, and theother for chemical pollutant dissemination.

2. Acoustic propagation

The environmental aspects studied in the IESTA project consists in ana-lyzing various pollution sources. One kind of pollution source which is veryimpeding for people around an airport and more precisely for inhabitantsaround an airport is the noise of the landing and taking off of the aircrafts.

Acoustic pollution assessment in IESTA will use several pieces of softwaredeveloped at the Onera: CESAR-I, SIMOUN, and ACOUS. Those com-putations rely on an Onera acoustic model [5, 6] which is based on thegeometry of an aircraft considering the main parts which are the cause ofthe noise. These parts are: the body, the wings, the tailplanes, and otherssources which are not geometrical but also important, the engines and thelanding gears. The geometry considered by the acoustic model is a par-ticular acoustic geometry. So, aircraft geometries have been “redesigned”taking into account the acoustic model needs.

The requirements for data for this acoustic model are among others:

• Data should be provided in the IGES format and more precisely inthe 128 and 126 formats corresponding to parametric surfaces andparametric curves.

• Data should be provided cut in various patches corresponding to anelementary part of the geometry (each patch has an outgoing normal).

• Wings and tailplanes should be designed with a significant discon-tinuity between the Extrados and the Intrados (the discontinuity isabout 120 considering the wavelengths of the acoustic domain).

• Every patches should be continued on a continuous surface (continuityof the normals of the neighborhood patches).

• The surfaces must be lighted to conserve the strict minimum whichcan be considered as a stakeholder of the computation (e.g. every partas complement of the aircraft geometry are ignored such as spoiler).

Another need has been introduced to get the advantage of the geometryredesigned in three dimensions. The various aircraft 3D models should berenderable in the 3D engine based on OpenSceneGraph: Delta3D. This needdeals with the level of detail issue and the tesselation issue from parametricsurfaces.

Several scenarii have been established to represent some demonstrationcases. In this demonstration, the selected aircrafts are Airbus A319, A320,A330-200, A330-300 and A340-200; Bombardier: CRJ-200, CRJ-700 andCRJ-900; and also some Boeing aircrafts (the list of which is not definedexactly yet).

The various tasks relative to the acoustic model, which are going to bedetailed now, are summed up on Figure 1.

Figure 1. Compatibility process for the acoustic model

Data inputs The data inputs used to model the aircrafts are based onaircraft plans, wing profiles and aircraft textures. The aircraft models havebeen drawn based on the three main plans: front, side and top plans as areference for the geometry. The wings and the tailplanes have been drawnusing wing profiles which have been extruded to get the entire geometry.Some data are modified as the wing section to take into account the C

1-discontinuity to get acoustic wings and tailplanes.

Nurbs surfaces To deal with the parametric surfaces, a key choice wasthe selection of the mathematic model to manipulate such kind of surfaces.Non-Uniform Rational B-Spline (Nurbs) surface are often used in 3D mod-eller tools, quite easy to manipulate, and allow building efficiently aircraftsurfaces. The mathematic representation of the drawn Nurbs surfaces are:

S(u, v) =

∑n

i=0

∑m

j=0Ni,p(u)Nj,q(v)wi,jPi,j

∑n

i=0

∑m

j=0Ni,p(u)Nj,q(v)wi,j

(1)

C(t) =

∑n

i=0Ni,p(t)wiPi

∑n

i=0

∑m

j=0Ni,p(t)Pi

(2)

where p is the order, Ni,p and Nj,q are the Nurbs spline basis function,Pi,j are control points and the weight wi,j of Pi,j is the last ordinate of thehomogeneous point Pw

i,j .

Aircraft modelling Using sections and loft functions of the 3D modellertool Maya, the drawn geometries are quite exact compared to the real air-crafts. The surfaces are third degree Nurbs surfaces (see below) with sevenisoparms for the wings and the tailplanes (numerous isoparms have beedused to keep a correct continuity between extrados and intrados surfaces).See Figure 2 for a model example.

Nurbs process When the main geometry of a drawn aircraft is done, thesurfaces are cut in various elementary patches considering C0- and C1-continuity of Nurbs surfaces.

Figure 2. Aircraft model for an A320.

Considering the two following Nurbs surfaces:

M(u, v) =

∑n

i=0

∑m

j=0Ni,p(u)Nj,q(v)wi,jPi,j

∑n

i=0

∑m

j=0Ni,p(u)Nj,q(v)wi,j

Q(s, t) =

∑n

i=0

∑m

j=0Ni,p′(s)Nj,q′(t)w′

i,jP′

i,j∑n

i=0

∑m

j=0Ni,p′(s)Nj,q′ (t)w′

i,j

the C0- and C

1-continuity are described respectively by conditions 3 and 4:

∀u ∈ [0, 1] ∀s ∈ [0, 1] (M(u, 0) = Q(s, 1)) (3)

∀u ∈ [0, 1] ∀s ∈ [0, 1]

M(u, 0) = Q(s, 1)∂M∂u

(u, 0) = ∂Q∂s

(s, 1)∂M∂v

(u, 0) = ∂Q∂t

(s, 1)

(4)

Of course, those conditions may be generalised to other sides if necessary.

The acoustic model needs continuous surfaces, and, if the precision of thecomputation is not sufficient, the various elementary patches may presentC1-discontinuity, as shown on Figure 3.

Figure 3. Discontinuity of patches on a A320 wing.

IGES export All patches are exported with outgoing normals in the IGESformat and more precisely 126 and 128 IGES format corresponding to Nurbscurve and Nurbs surface. See Figure 4 for an example.

Figure 4. Split aircraft model for an A320.

Tessellation process From Nurbs surfaces designed to establish the acous-tic geometry, tessellation methods have been used generating semi-automaticallylevel of detail (LOD) to be renderable in the 3D Real Time engine Delta3D.A first tessellation allows a very thin representation of the model using poly-gons. This first tessellation is the reference to texture the model. ThreeLOD has been chosen to optimize 3D real time rendering. The rules estab-lished for these LOD are based on geometry and texturing. Respectively, forLOD0, LOD1, LOD2: 82862, 48470, 25472 polygons, and 1024px×1024px,512px×512px, 256px×256px for each texture.The real time scene to render is composed by a maximum of 10 aircraftsin the camera field. Some tests have been done on the aiming machine toknow exactly how many polygons could be rendered at a time t.The tessellation is based on computing the various Ni,p(u) and Nj,q(v).The tessalation chosen in our case is a uniform tessellation. The normalsare computed using the computation of tangents at each point of interest.

Texturing process The texturing is based on the reference geometry cor-responding to the first tessellation. Each Nurbs surface are converted inpolygons which could be textured easily with a 3D modeler tool (Maya).This texturing is a very high definition texturing including elements likeengines, wheels, . . . as may be seen on Figure 5.

LOD process The reference geometry corresponding to the first tessella-tion is reduced using polygonal reduction to get the three LOD. Nurbsgeometry could be the reference to tessellate each level of detail with cor-

Figure 5. An A320 engine.

responding parameters however, this method involve to reiterate the tex-turing process which is quite fastidious. Reducing the reference geometrycorresponding to the 1st tessellation, only one texturing process is done onthis reference geometry. The u, v coordinate of the texture are also reducedbut there is no deformation (approximately no deformation based on thefinal result of the textured aircraft).Figure 6 represents, from left to right and from top to bottom, the A320model with the initial tessellation, the first level with 82682 polygons, thesecond level with 48470 polygons, and the third level with 25472 polygons.

Figure 6. The various LOD for the A320 model.

FLT export The three LOD are exported as only one Openflight file. TheOpenscenegraph 3D real time engine reads it and deals with the variousLOD using the distance between the object and the camera. The final

model including the textures in high definition is shown on Figure 7.

Figure 7. The final A320 model.

3. Chemical dispersion

Another very impeding pollution source consists in chemical emissions.Their assessment will be done using an Onera software chain calledCEDRE [7].

In this simulation, the ground and the buildings on the scene are consideredseparately to study chemical propagation around the airport. The geometryconsidered by the chemical model is a specific geometry where the minimumlength considered is about 5 meters, and its needs must be taken intoaccount.

The requirements for data for this chemical model are among others:

• Data should be furnished in the STL format and more precisely bytriangulation of the mesh and exporting each triangle in the STLformat (normals are not useful is this case).

• Data should be furnished considering separated elements as the limitsof the scene box, the ground and the buildings.

• Each exported elements should be continuous, as an example thelimit of the box should be used the extremities of the ground to beconsistent with themselves.

• The meshes should be continuous, no holes are accepted because thedifferent meshes are the limit of domains where CEDRE implementsits own mesh.

Another need has been introduced to get the advantage of the geometryredesigned in 3D. The scene data are used to perform visualization usingthe 3D real time engine Openscenegraph.

Several scenarii have been established to represent some demonstrationcase. In this demonstration, the selected scenes are two real airports(Toulouse-Blagnac and Paris-Charles de Gaule, as well as a generic airportcalled “ENAC Airport”.

The various tasks relative to the chemical model, which are going to bedetailed now, are summed up on Figure 8.

Figure 8. Compatibility process for the chemical model

Data inputs The data inputs used to model the scene are based on grounddata, building data and also textures. Ground data comes from DTEDdata which have been converted to create a local database. Building datacomes from building semi-automatic creation using satellite pictures. Theground textures are obtained using satellite pictures. For generic buildings,generic textures are used. Specific textures are also used for some buildingslike terminals.

Scene modelling The scene modeling is performed using the 3D modellertool Maya, but also various plugins to improve some functionalities likeensuring consistency between the ground and buildings.

CEDRE process The input data must be made suitable for the CEDREchain, which implies removing polygon discontinuity. Some example aredetailed on Figure 9.

Figure 9. Polygon discontinuity: from left to right, an intersection ofbuildings, a hole in the ground, and an atrophied polygon.

Some buildings also had to be simplified to ease the mesh definition by

CEDRE. No automatic method could be used in this way, so this was donemanually, as shown on Figure 10.

Figure 10. Original (left) and simplified (right) mesh.

STL export The final scene is exported after a triangulation of the finalmeshes. The format is simple format which lists all the triangles of thescene. The five sides of the box, the ground and the buildings are exportedindividually. The STL export is represented on Figure 11.

Figure 11. Original (left) and simplified (right) mesh.

IVE Export For the visualization of the scene, some LOD has been nec-essary, especially for taxiways to be distinguishable. The final format isthe IVE format which is an optimized format for the Openscenegraph 3Dengine used in our case. The textures are compressed in the DDS formatto lighten the final scene size. The visualisation is depicted on Figure 12.

4. Conclusion and perspectives

The combination of various physical numerical simulation software intoa modular simulation platform rises interesting geometrical issues, whichhave been addressed here in two cases, yielding a promising approach for

Figure 12. Visualisation of the ENAC Airport.

the simulation of complete air traffic systems.The first application realised, Clean Airport, should be very useful for theassessment of environmental impact of new air traffic system concepts.On a longer term, the extension of this technique to various other physicalmodel is planned in order to provide the IESTA platform with a wide varietyof built-in simulation modules and let it enlarge its scope.

References

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[2] Romain Kervarc, Andre Elie, Thomas Dubot, and Jean Bourrely.IESTA: a modular distributed simulation platform for the evaluationof air transport systems. In Proceedings of the 9th Meeting on AppliedScientific Computing and Tools (MASCOT08), 2008.

[3] Luis Basora, Sebastien Aubry, Muriel Brunet, Thomas Chaboud, andThomas Riviere. A model toolbox facility to evaluate innovative solu-tions for a cleaner airport. In Alain Boutier and Rolf Haupt, editors,Proceedings of the 9th ONERA-DLR Aerospace Symposium, 2008.

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[5] Jean Bulte. Simplified acoustic modelling of aircraft noise during take-off and landing. ONERA Technical Report RT12/F00201, Office na-tional d’etudes et de recherches aerospatiales (ONERA), 2003.

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[7] Phillipe Chevalier and al. Cedre: development and validation of amultiphysic computational software. In Proceedings of the 91st EuropeanConference for Aerospace Science, 2005.