the challenge for numerical simulation and high ... · page 1 the challenge for numerical...

The challenge for Numerical Simulation and High Performance

Computing at EADS

Forum [email protected] - Supelec

Yann Barbaux, EADSDirecteur Exécutif EADS Innovation Works

EADS at a glance…

# 3

# 3

# 1

# 1

Commercial aircraft

Helicopters

Commercial Launchers

Systems of missiles

Satellites

Military transport aircraft

# 1

# 1

Combat aircraft # 1 in Europe

EADS Management Structure

Jussi Itävuori

Human Resources

Ralph D. Crosby Jr.

EADS North America

Jean J. Botti

Chief Technical Officer

Marwan Lahoud

Strategy &Marketing

Hans-Peter Ring

Finance

Chairman of the Board Bodo Uebber

Louis Gallois Chief Executive Officer (CEO)

Eurocopter

Lutz Bertling (CEO)

Defence & Security

Stefan Zoller (CEO)

EADS Astrium

François Auque (CEO)

CoordinationEADS Defence & Security

EADS Astrium

François Auque

Airbus

FabriceBrégier (COO)

Tom Enders (CEO)

Airbus MilitaryDomingoUreña-Raso

EADS Innovation Works is the Corporate Research org anization.It is part of the Chief Technical Officer’s organiz ation

A testimony from a pioneer…

But already at that time, people were looking for simulation and modeling

Early Flight simulator

Simulation of loads

Numerical simulation and HPC : summary

Numerical simulation and HPC: what is at stake from an industrial perspective ?

The “Top Ten” challenges

Conclusion

EADS : dealing with complex products in a complex environment

The aircraft is a complex system itself, which need s to be optimized through a multi-disciplinary and multi-criteria approach :

Operating in a wide variety of environments :

� Mechanics� Aerodynamics� Systems� Propulsion� On-board energy

� Market expectations (travel conditions, IFE…)

� Performance (range, speed, pax…)� Costs (acquisition, maintenance, fuel…)� Environment (noise, emissions…)� Security & safety

� Air :� Altitude (pressure, temperature)� Icing� Lightning� Winds

� Ground : taxying, storing – atmospheric conditions – EM disturbances…

As part of a complex transportation system :

� Airport infrastructures :� Docking - undocking� Security� Inter-connection / inter-operability

� Air Traffic Management� Communications

EADS : dealing with complex products in a complex environment

A complex industrial organization :

� Numerous partners and suppliers

� In numerous sites / geographical locations

� Using different languages

� Using different IT tools

� Facing increased offset demands

Numerical simulation: what is at stake ?

• Faster Development through more efficient processes– Top level efficiency & robustness for

numerical simulation

– Step change in design & data processes

– Paradigm shift in design techniques

• Reduced testing time & cost andimproved quality of design– Less testing, fewer wind tunnel models

– Increased use of high Re Testing

• Highly matured product at industrial launching phase

ETW European Transonic Wind TunnelETW European Transonic Wind Tunnel

-15%

-36%

Win

d T

unne

l Tes

t Day

s

2000 2003 2006 2009

Aircraft in development in year

?

-15%

-36%

Win

d T

unne

l Tes

t Day

s

2000 2003 2006 2009

Aircraft in development in year

?

Overall Definition Production

Work Load

Physical Physical Test Test

dominateddominated

Numerical Simulation dominated Save months &

years through integrated simulation

based development

Detailed Definition

Limit risks in decision

makingreduce development cycle

Impact of change configuration (up to

certification)

What is at stake ?

Design Processes

Analyse & DefineNeeds

DefineTechnical

RequirementsDesignPhysical

Architecture

Integration Processes

Correct

Integrate

Verify

Deliver

Workload 15% Workload 85%

Produce – Re-use - Buy

Integration Processes

Recept

Assemble

Verify

Integration

Validate

Product

Produce – Reuse - Buy

Design Processes

Analyse & DefineNeeds

DefineTechnical

RequirementsVerify

Validate

Evaluate Optimise

DesignFunctional

Architecture

DesignPhysical

Architecture

Workload 60% Workload 40%

Lean in the Right hand side

A change of approach in the V-Cycle

The « Top Ten » challenges for NumericalSimulation

� Uncertainties management

� Inverse methods

� Multi-scale modeling

� Domain decomposition

� Coupling of physics

� Techniques for model reduction

� Validation with appropriate test

� Simulation platforms

� Secure distributed simulation

� Virtual certification

Tracking Uncertainties or oversize the protections

• Poor knowledge of physical phenomena

• Bad knowledge of input parameters

• Model Uncertainty (3D model or Analytical Formula)

• Numerical Approximations• Investigation of Variability -

Complexity – Diversity• 2 classes of uncertainties in the

literacy :– Epistemic uncertainties– Aleatory uncertainties

Modeling a lightning strike

From Worse case to probability of failure

Observed vs Computed Pressure demonstrated the Model relevance Which model for acoustic sources?

KEY POINT = scientific challenge due to complexity of physics•A close cooperation with Astrium experts and top lev el Academics in Math led to modelling and Simulation of Acoustics at lift off

SAVINGS = better knowledge �� margin reduction• To prepare new configurations of A5: prediction of a full field of pressure around the launcher• To optimize protection: negotiation with ESA and CNES• This “success story” opened an avenue to a lot of optimization topics inside Astrium (and other BUs);

Inverse method to optimize payload protection against over-pressure during Ariane 5 lift off

Electromagnetism leads to Multi Scale Modeling

EQUIPMENTS

SYSTEMS

COMPONENTS

Millimeters - µmeters

Centimeters- Millimeters

Meters - Centimeters

ElectroMagnetic Compatibility examples:Emission: from component to systemSusceptibility : from system to component

3D +2D

Power Grounddecoupling

Calcul complet

sources moteur + nacelle

Diffraction par l’aile

Domain Decomposition techniques in convective acoustics

Nacelle

Flow around the leading edge

Absorbing material conceptCurrent model used to analyze absorbing process

Coupling of physics : modeling of the nacelle implies materials, aerodynamics and acoustic coupling

Manufacturing :

LRI Process simulation

Manufacturing :

LRI Process simulation

Engineering :

Mechanical analysisEngineering :

Mechanical analysis

Engineering :

Impact vulnerabilityEngineering :

Impact vulnerability Engineering : Lightning protection

Engineering : Lightning protectionEngineering :

Noise transmissionEngineering :

Noise transmission

Concurrent Analysis DataManagement

Multi disciplinary optimization : weak coupling example

2 levels :

Local=coupling of different physics

Global = concurrent analysis of different local optimizations

Composite Structures

−−⋅−+⋅=

)(2

11maxuf 11)1(21

)(Z

x

nfL

xpphx

ω

For A320 and A340 geometry description

Data compression stage 1: From CAD ( 104-105 ) to parametrisation ( 575)

. . .

. . .

. . .

. . .

. . .

In p u t ve c t o r (N n u m b e rs )

O u t p u t ve c t o r (n n u m b e rs )

. . .

C o m p r e s s in g A N N

- i n t e rn a l n o d e

- i n p u t / o u t p u t n o d e

Data compression stage 2 = Non-linear approximation (84 parameters of interest)

•Simplified / surrogate models is a key factor for future innovation;

•Domain of validity assessment for these models is a challenge as coupling optimization is at stake

Model Reduction �� for architect use

Full aircraft

Large component

Small component

Structural detail

Test Model

Mus

care

sear

chfo

cus

Materialcoupon

Virtual testing

Validation with appropriate test

Collaborative simulation

Loop process

PALMAS deliverables

Models building

Structure Modeling Architecture/preliminary sizing

FEM Generation

Aerodynamic(refinement of ) external shape

LoadsMass & Aero coupling

Unsteady aeroModal analysis

Masses(Fuel) System

(non-struct mass)installation

Structure sizing

Parametric A/C Geometry

Update of massesvs structure sizing

FEMn

Yes

Sizing/loadsConverged ?

MassesChanged ?

Yes

No

Correlated Masses, Loads and Structure

No

FEM0

Loop process

PALMAS deliverables

Models building

Structure Modeling Architecture/preliminary sizing

FEM Generation

Aerodynamic(refinement of ) external shape

LoadsMass & Aero coupling

Unsteady aeroModal analysis

Masses(Fuel) System

(non-struct mass)installation

Structure sizing


Update of massesvs structure sizing

FEMn

Yes

Sizing/loadsConverged ?

MassesChanged ?

Yes

No

Correlated Masses, Loads and Structure

No

FEM0FEM0

WP2.1: “PALMAS”Loop process

Deliverables

Models building

Performance assessment•Cruise• T/O• etc.

Engine Modeling * Thrust

* Positioning

Aerodynamics* Function of

external shapes

Masses•Fuel vector

• L/G• Payload

• Structure & systems

Aero shapes optim


Correlated Aero-shapes, perfo

Loop process

Deliverables

Models building

Performance assessment•Cruise• T/O• etc.

Engine Modeling * Thrust

* Positioning

Aerodynamics* Function of

external shapes

Masses•Fuel vector

• L/G• Payload

• Structure & systems

Aero shapes optim


Correlated Aero-shapes, perfo

WP2.2: “H/S aero & perfo”

ROBOPT

« common » M&S(parametric concepts)

«co

mm

on»

M&

S(a

ero-

data

)

« common » data

Virtual Plateaux

AeroCity

Trade-offs

Optimization

Collaborative simulation

CollaborativeCollaborative

DistributedDistributedworkwork

Data exchanges Data exchanges �� Model exchangesModel exchangesPLM PLM ((productproduct lifecyclelifecycle Management)Management) �� SLM SLM (Simulation (Simulation lifecyclelifecycle Management)Management)

Security for collaborative M&S, including HPC

Problem– Commercial and Military Security Issues– Legislation– Authorisation and Authentication– Access control to data and services– Multiple security levels, data and applications

Solution (tested or under test)– SIMDAT provides a commercial-grade trust and security infrastructure based on

industrial Web Service specifications

– GRIA contributes dynamic trust (from NextGRID) for relationship management

– NEC’s end-to-end Security infrastructure has been integrated with GRIA for message level security and security context negotiation

– PKI Infrastructure for authentication of users.

– Service manager has control of his service offerings.

– Data ownership and access control.

KEY POINT = acceptance (and not scientific)•To make Airworthiness Bodies comfortable with Virtu al certification: more than 10 years of validation & comparisons, demonstration wi th Airbus and suppliers …

SAVINGS = time cycle• To optimize antennas sitting at low cost by simulation• To facilitate and prepare the retrofit or the installation of specific antennas by simulations• To support suppliers with better requirements to limit risks during integration process (later in the cycle)

Dedicated mock-up to perform model validation; High performance computing is compulsory to get confidence

“Virtual Certification”: a milestone in 2006For Antenna Sitting: Green light by DGAC authoritie s

Challenges highly linked to HPC performance Challenges highly sensitive today

� Uncertainties management

� Inverse methods

� Multi-scale modeling

� Domain decomposition

� Coupling of physics

� Techniques for model reduction

� Validation with appropriate test

� Simulation platforms

� Secure distributed simulation� Virtual certification

Same problematic in « System of Systems approach » in military domain

Preparation of simulation

(Tools)

Performing the simulation

Visualization and post processing

Real time simulations

Support functions:

•Security,

•Repository

•…

Technical repository;:

•Interface spe.,

•Data model

•…

Models environments scenarios

Secured communication

Configuration management

Save, store, capitalize �� knowledge

Lean in the left hand side

… and simulation dedicated to a « virtual » bird, spacecraft …

« hardware in the loop

Preparation of simulation

(Tools)

Performing the simulation

Visualization and post processing

Hardware in the loop

Support functions:

•Security,

•Repository

•…

Technical repository;:

•Interface spe.,

•Data model

•…

Models environments scenarios

Secured communication

Configuration management

Save, store, capitalize �� knowledge

Conclusion 1

M&S can be a leverage to innovation if:

� Certification bodies fully support new methodologies based on Virtualization (� more than 10 years for the “simple” antenna sitting topic)

� Suppliers are closely embedded and can provide relevant model based on our requirements (�optimization of equipment and architecture is at stake): sharing benefits of simulation

� Risk assessment and margin reduction can be addressed by simulation (� methodology, tools and best practices will be brought by other domains than Aeronautics) “from worst case analysis to the probability of feared events”

Conclusion 2

Needs for Numerical Simulation are increasing rapidly; needs in the domain of modeling of physics will be fulfilled only if computing costs are “reasonable” (including pre-treatment)EADS needs vary in time / importance depending on Bus & programs, resulting in mostly 2 approaches:

� Outsourced capabilities in the right part of the “V”

� Internal capabilities for the R&D and for the left part of the “V”

� Cloud Computing is an option

Security for distributed simulation in the extended enterprise is a key issue

EADS supports European Initiatives

FuSim: Full Flight Simulation – Ease Design Process

• Real-time simulation of maneuver flight of a comple te aircraft – Aerodynamics: Full unsteady Navier-Stokes simulation of flow

– Structures: Full finite element modeling of the airplane

– Flight control: Full simulation of maneuver flight

– Integration: Full interaction of all disciplines

• Loads and stress for the airplane in the whole enve lope– Intelligent analysis of the flight envelope

– Provision of all aerodynamic data for all components and total aircraft

– Prediction of sensitivities – shaping the optimum

• Digital prediction of “Flight Performance” and “Hand ling” prior to first flight– Investigation of flight scenarios and maneuvers

– Full knowledge about aircraft behavior in flight

• Virtual certification prior to production– Full knowledge of product characteristics

– Fully guaranteed prediction accuracy

What if Louis Blériot…

Had known simulation ?

� TAU Navier-Stokes CFD

� A380 Landing Configuration incl.Landing Gear

Aircraft in Flight

Wind TunnelExperiment

Numerical Flow Simulation

A380 Take-off

TAU Navier-Stokes Computation

DNW Test

Application

Landing Take off

De-rotateApproachγγγγ= -3°°°°

Flare

50 ft

Lift offRotate

35 ft

Lift and drag effects

due to groundGround effect

on tailplane

Ground interferencewith engine jet

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