The Impact of Modelling and Simulation in Airbus Product ...The Impact of Modelling and Simulation...

The Impact of Modelling and Simulation in Airbus Product Development

8 October 2013 Matlab EXPO 2013 - Model-Based Design Session

Presented by

Sanjiv SHARMA – Technical Expert for Modelling & Simulation Methods and Tools

Matlab EXPO 2013

© AIRBUS Operations LTD. All rights reserved. Confidential and proprietary document.

Contents

• Introduction

• Overview

• Applications and Impact of Modelling & Simulation

• Addressing Modelling & Simulation Challenges

• Summary



Montage



Introduction

• Intended impact of Modelling & Simulation:

1. Reduction of cost by reducing/eliminating physical prototypes

2. Reduction of time-to-market by using readily reconfigurable models

simulations

3. Improved design maturity by extensive use of simulations

• Actual Impact arises over time

• It takes time to produce reliable models

• However, engineering the models for re-use addresses 1 & 2

• Engineering the models and conducting simulations creates

knowledge

• Knowledge thus created informs design decision-making

• Informed decision-making addresses 3, and contributes to 1 & 2.


Intended impact takes place over time; benefits may not be fully realised at the first application


Overview: Working Definitions

• Experimentation

• Discovering the “true” requirements

• Discovering the possible behaviours (time-based & event-based)

• Discovering inter-dependencies amongst the system elements

• Design

• “Sizing” the system of interest, e.g.

• Form: addresses geometry

• Fit: addresses interfaces

• Function: addresses behaviours

• Test – Verification

• Confirming that the system, at a

given design stage, conforms to

its allocated requirements



Overview: The MathWorks Tools Used

• Matlab

• Prototyping design algorithms

• Automating engineering calculations

• Data analysis and visualisation

• Simulink

• Designing control algorithms

• Simulating on-board systems

• Auto-code generation for sharing models

• Specification-in-the-loop; Software-in-the-loop; Hardware-in-the-loop

• Preparing Real-Time models for training simulators

• Stateflow

• Modelling logic-based requirements

• Modelling event-based on-board systems

• SimScape & other Sim-toolboxes

• Generally, modelling physics-based aspects of on-board systems



Experimentation (open questions)


• Exemplar questions:

• When I apply <this> stimuli what response do I get?

• What stimuli generates <this> response?

• What are the desired behaviours?

• Under what context are these behaviours exhibited?

• What interconnections can assure these behaviours?

Example: Library of model components

Example: Visualisation & Analysis

Knowledge acquisition is an iterative process; new knowledge raises new questions.


Design


Modelling as a “day-job”

System designers developing the models as

part of the design

No need for separate “over-the-wall” modelling

Modelling is an integral

part of Design

Knowledge acquired by the modelling & simulation team members is disseminated, retained and used within the design team


Testing – Verification (closed questions)


• Exemplar questions:

• When I apply <this> stimuli I shall get <that> response?

• When I apply <this> stimuli I shall NOT get <that> response?

• … within a prescribed context

Hardware in the loop

Pilot in the loop

… including training

The simulation models encapsulate the behaviours of the “system under design”; therefore approximate the system behaviours.


Challenges – Shared “Blue print”


• Creating, Engineering & Managing

Multi-perspective, Multi-disciplinary

design information for sets of products

• Evolving properties, capabilities and

behaviours of product families

• Information is distributed across the

extended enterprise

• Pedigree & Provenance

• Impact on contractual agreements

• E.g. Managing & Policing

Intellectual Property Rights


Challenges – Modelling & Simulation


• Embodying Novel & Emerging

technologies with existing ones

• Understanding their underlying sciences

• Constructing models to leverage the

intended benefits

• Developing Multi-abstraction models for

engineering & business decision-making

• Qualifying & Certifying

• Determining test strategies to verify the

desired effects


Addressing Collaboration & Interoperations


Standard specification of BDA*

Functions supporting collaboration

across companies

Specialised BDA* Engineering

Methods => Functions/Tools

supporting different company roles

Enterprise Collaboration Functions

Model Store Functions

Quality Lab Functions

Simulation Factory Functions

Modelling & Simulation Tools

Generic BDA* Platform

Specification

Company A: OEM Company B: Partner Company C: Supplier

Collaboration Standard

• Connect & control global

processes

• To be formalised as “SE” DEX

mapped to AP233 & AP239/PLCS

Technical Standard(s) enabling

exchange of detailed data e.g.

AP209, AP242, neutral & vendor

formats, ...

Multiple M&S Platforms Deployed

10 – 100 M&S

Platforms across

partner companies

* BDA: Acronym for Behavioural Digital Aircraft


CONGA Project Background

Configuration Optimisation for Next Generation Aircraft

• A 2-year project under the Technology Strategy Board’s “Building

the UK Leadership in Aerodynamics” competition

• Led by Airbus, CONGA has 6 other partners:

• Rolls Royce, EADS-UK, Aircraft Research Association, Eurostep,

MSC Software and Cranfield University (School of Engineering and

School of Applied Science)

• The main purpose of CONGA is to develop a proof-of-concept

for a “System for Creating Valued* Aircraft Configurations” using

Set-Based Design Methodology.


* Valued by multiple stakeholders, e.g. Society, Government, Customers & Manufacturers


Sets of feasible configurations Sets of competitive configurations

CONGA: High-Level Concept Diagram


Set of possible Aircraft

Concepts

Set of possible Technology

Concepts .

Set of possible Operational

Concepts

Market Projections, Needs,

Values & Expectations

Low Order

High Order

Set of possible

Technology Concepts

Set of possible

Operational Concepts

Set of

possible

Aircraft Concepts

Population sub-

sets forming

families

Sets of feasible

Configurations

http://www.google.co.uk/url?sa=i&rct=j&q=aluminium&source=images&cd=&cad=rja&docid=FFgJiHgyr6DLQM&tbnid=17AgL2sqjoQTMM:&ved=0CAUQjRw&url=http://www.realityinscale.com/epages/61537336.sf/en_US/?ObjectPath=/Shops/61537336/Products/ACC005&ei=-ZMwUZ2QEMGm0QWHroCQDA&bvm=bv.43148975,d.d2k&psig=AFQjCNFgVbzF24IC6atU6qV8lUGS4vxfMw&ust=1362224286744819

http://www.google.co.uk/url?sa=i&rct=j&q=Compositematerial&source=images&cd=&cad=rja&docid=7ky2PDAk5a2M-M&tbnid=OxAOenptoDzuOM:&ved=0CAUQjRw&url=http://en.wikipedia.org/wiki/Composite_material&ei=2JIwUbjRGMis0QWQzoGgCw&bvm=bv.43148975,d.d2k&psig=AFQjCNHA_Gwt9ptrmDq899gRUkxpkFFvXg&ust=1362224178811546

http://www.google.co.uk/url?sa=i&rct=j&q=seaplane&source=images&cd=&cad=rja&docid=prGWzBSBFoEzfM&tbnid=pig6xgQT7gJ3_M:&ved=0CAUQjRw&url=http://research.microsoft.com/en-us/um/people/sumitg/pictures/Lake-Tahoe/index.html&ei=NZcwUZjnDarS0QXZyoCgAw&bvm=bv.43148975,d.d2k&psig=AFQjCNFxsc5kyE5bLE8ho2CALLnBVqmpuQ&ust=1362225313444631


Summary

• Impacts of Modelling & Simulation

• The intended impact takes place over time; benefits may not be fully

realised at the first application

• It takes time to produce reliable models; their reuse contributes to

further time- and cost-savings

• Modelling and Simulations creates knowledge that informs design

decision-making leading to design maturity.

• Modelling & Simulation as an integral part of design

• Knowledge acquired by the modelling & simulation team members is

disseminated, retained and used within the design team

• Reuse design models for testing

• The simulation models encapsulate the behaviours of the “system

under design”; therefore approximate the system behaviours.

• Not aspects of a system can be modelled!



Summary

• Challenges for Modelling & Simulation

• Collaboration is about working together not just exchanging

• Interoperability: specially of data, information and rationale

• “Platform” neutral

• Standardisation: data model and methods for sharing the

information (MoSSEC: Modelling & Simulation collaboration in a

Systems Engineering Context)

• Multi-level Models & Simulations

• Reliable, early analyses for assessing insertion of new

technologies

• Built on scientific principles – abstracted to the level needed

depending on the design questions

• Needed for assessing a large number of design options.



Acknowledgements

Many thanks to…

• Terence Frost – Head of Design Analysis (Landing Gear)

• Chris Slack – Computational Analysis Expert (Fuel Management)

• Hubert Ellgoth – Loads and Aeroelastics (Scientific Computing Solutions)

• Etienne Coetzee – Future Projects Engineer (Nonlinear Dynamics)

• The CONGA Project Team Members, comprising

• Airbus, Rolls Royce, EADS UK, Eurostep Ltd, MSC Software,

• Cranfield University (Schools of Engineering & Applied Science)

for providing the examples and information for this presentation!




© AIRBUS Operations LTD. All rights reserved. Confidential and proprietary document. This document and all information contained herein is the sole property of AIRBUS Operations LTD. No intellectual property

rights are granted by the delivery of this document or the disclosure of its content. This document shall not be reproduced or disclosed to a third party without the express written consent of AIRBUS Operations LTD. This

document and its content shall not be used for any purpose other than that for which it is supplied. The statements made herein do not constitute an offer. They are based on the mentioned assumptions and are expressed

in good faith. Where the supporting grounds for these statements are not shown, AIRBUS Operations LTD. will be pleased to explain the basis thereof.

AIRBUS, its logo, A300, A310, A318, A319, A320, A321, A330, A340, A350, A380, A400M are registered trademarks.

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