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Virtual Spacecraft Design

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Data Engineering for Space

Applications

PDE Workshop Oslo 2010







Harald Eisenmann Astrium Satellites

Background

 Data Engineering was traditionally performed by

 Tool vendors

 Data exchange community

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 Little end-user involvement / interest

 Model-based systems engineering requires looking “into”

data of the different tools and thus models

 Compared to progress in some areas “databases” are

considered being too costly due to

 Applied technologies and development processes

 Lack of adequate data models

ECSS E-10-23: Engineering Database

 Lessons learnt and – questions on - way forward !

19/12/2006 p2

Context: Model-based Systems Engineering

 Model-based engineering is increasingly applied in the projects

 Bottom up – project- driven implementations ( MS Access)

 Top down driven e.g. COTS tools (e.g. E|M-CAD, SysML), TRP, …

 Along with the model-based engineering increasing needs on

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 Efficient model exchange

 Adequate tools providing model-repositories and -management

 Constraints on engineering for the underlying infrastructure in

terms of

 “Make or Buy”: Development vs investment and customization costs

 Maintenance effort vs licensing costs

 Tailored vs “Generic” with customizations

 Evolution along with the increasing demands

 For “Make” items  Model-driven Software Engineering to

 Decrease development and maintenance costs

 Increase maintainability and technology independence





19/12/2006 p3

Context: Engineering Database

Engineering

Applications

Engineering

Engineering Applications

Applications

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Reference Database









Configuration

Management









Supplier

Supplier Customer



19/12/2006 p4

Context Engineering Database

Systems Engineering S/W Engineering AIV Operation Preparation



Engineering Engineering Engineering Engineering Engineering

Applications ApplicationsApplicationsApplications Applications

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Reference Database



Reference Working







Archive









19/12/2006 p5

Configuration

Context: Model-driven Engineering

Model level N  Provide Abstraction

 Classically – template-based

– code generation

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 Technology independence!

Model Transformation  Vertical semantics

 Following trends are

observable

 Patterns are driven by – external –

Model level N-1

components

 Layered architecture of

transformation

 Lowest level is ‘code generation’

19/12/2006 p6

Context: Model-driven – DB - Engineering

 MDA adopted for Data Editing

DB Engineering









ESA-Virtual Spacecraft Design

 Key item  Data ! Data Presentation

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E-TM-10-23 Validations

 Applied for among other

 DRC (2004-2006)

Data Exchange

 SSRM (2007-2008)











 E-TM-10-23 Validations (2006 – 2008)









ESA-SSRM

 Virtual Spacecraft Design Data Handling









ESA-DRC

 Industrial applications

 SimDB, SimMF, .. Data Persistence



 SEDB





19/12/2006 p7

Data Engineering for Space Engineering

 ASCII-based: MIB (TM/TC data I/F for ESOC)

 Maturity: operational

 XTCE to come …

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 ISO-10303 – based: STEPNRF, STEPTAS

 Maturity: under ISO standardization

 ORM based

 Coverage: Monitoring and control databases

 Activities: ‘Ontology for DB development’

 Maturity: under development

 UML-based

 Coverage: Systems Engineering, E-TM-10-23A

 Activities: DRC, SSRM, VSD, (SEDB, SimDB, SimMF),…

19/12/2006 p8

 Maturity: mature prototype, used also for operational solutions

ECSS E-10-23A

 Standardization Activity in support of system

engineering  engineering database

 In terms of scope, content, format, processes

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 2004 – 2009: Definition of technical memorandum (TM)

 Scope systems engineering data

 Maturity: initial UML model but

 Some validation already performed, thorough validation in

progress ( VSD)

 Operational implementations on the way

 Next steps

 Further validation of model

 Agreement on Methodology (possible?) !

19/12/2006 p9

 Property collection

E-TM-10-23 Model Coverage

QUDV Systems Engineering







System Requirements (N-0)

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System Design AIT Environment

Engineering



Functional Decomposition



Operations

Activity





Operational

Product Structure Geometry

Concept

AIT & Verification









System Requirements (N-1)









19/12/2006 p10

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19/12/2006

p11

Conceptual Data Model

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19/12/2006

E-TM-10-23









p12

Data Editing









Data Exchange









Data Persistence

Data Manipulation

Data Presentation

SQL, J2EE, EJB

SQL, IBates









E-TM-10-23

SQL, Hibernate, Java, XSD

SQL, Hibernate, Java, XSD, EMF

SQL, Hibernate, Java,XMI, EMF, GMF

Technology - independence



Presentation and

Notational Model









E-TM-10-23

Engineering

Process Model

Validation: Virtual Spacecraft Design

Virtual Spacecraft Engineering Environment



Space System Design Editor Space System

Design Browser

RDE FDE ODE PDE AITDE OADE VDE

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VSEE Application Server



SSDE Services Wiki Service







SSRDB Services SSVM Services







Space System Reference Database Space System Virtual Model



Space System Space System

Functional Simulator Visualization Tool



Space System Virtual Model Integration Bus

SSRDB





19/12/2006 p13

Application of Data Model in Eclipse: VSD

SSDE

SSDE SSDE

SSDE

Specific

Specific









IO Code

SSECDM Code

Code

(UML)

SSDE TMM VSEE

SSDE

(Ecore) Data Core

Data Core

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SEML (Ecore XMI)

QUDV SSRDB

SSRDB SSRDB

SSRDB

Specific

Specific









IO Code

Code

Code









SEML API

SSRDB TMM VSEE

SSRDB

Data Core









SEML XSD

(Ecore) Data Core

VSEE model

VSEE model

SSADM

SSADM (Ecore)

(Ecore)

SSVT

SSVT SSVT

SSVT

Specific

Specific









IO Code

Code

Code

SSVDM

SSVDM VSEE

SSVT TMM SSVT

(Ecore) Data Core

Data Core









SEML TMM

(Ecore) VSEE

Data Core









19/12/2006 p14

Preliminary Assessment of E-TM-10-23

 In UML MDA terms E-TM-10-23 can be considered

as platform independent model

 Robust against (implementation) technology changes

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 E-TM-10-23 model improved S/W engineering

processes towards model-based S/W engineering

 E-TM-10-23 is well suited to be used building

applications with the Eclipse Framework

 More detailed validation activities are on the way

 But there are issues:







19/12/2006 p15

Issue Modeling in UML(-tools)

 PRO

 Commonly used, many tools (free, cheap, professional), multi-

purpose language and tools

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 Enforced diagram-oriented modeling

 Modeling vs doing layout

 Efficient textual, tabular entry of data

 Limitations in modeling means  Profiling

 Model exchange limitations

 Loss of diagrams

 Change tracking on modeling item level







19/12/2006 p16

Issue: Modeling vs Generation

Requirements  Not all ‘instances require

(N-0)

manual instantiation

Functional  Dependencies between

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Decomposition

elements

Implicit Operational  Applications

Product Definition

Structure (impl)  Implicit – Explicty structure

Explicit Operational

 TM/TC data

Product Definition  Vertical Detailing of data

Structure (expl)

 Life-cycle considerations

 merging of data

Integration Operational

Procedure Procedure



19/12/2006 p17

Issue: Library vs System Level Semantic

 Current approach explicit

models

 Clear identified entities

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 Relations between entities (

semantics, i.e. multi-disciplinary

aspects)

 Direct use for tool development

 Structure, constraints, presentations

 Where to we start instantiation?

 Common instantiation of

structure and model library?

 Categories

19/12/2006 p18

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19/12/2006

p19

Issue: Library vs Aligned Semantics

Issue: Model Management Process

ECSS?

E-TM-10-23 Issue E-TM-10-23

Data Model Analysis Data Model

1.0 and 1.1

Tailoring

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Issue Recommend.

Issue Comparison

s s

Programm A

Analysis Tailored Development

and E-TM-10-23 Data

Tailoring Data Model





Programm B

Analysis Tailored Development

and E-TM-10-23 Data

Tailoring Data Model









19/12/2006 p20

Issue: Data Engineering … there is more…

Verde

Verificatio Verification

n Model

Engineering

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DRC, SSRM, VSD …. Architecture

Data Frameworks

Engineering Data Model ?





VSD



View

Engineering View Model





?



Process Process

Engineering Model



19/12/2006 p21

Further …

 Repository of properties?

 Common representation of meta models and

Libraries?

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 Life-cycle consideration of properties and relations..

…

 while still preserving the achievements on DB

production









19/12/2006 p22

Conclusion

 Currently no common approach for

 Data models applied (coverage, level of detail, …)

 Methodologies for defining meta models

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 Tools used for the meta models

 Clear process of model maintenance

 Ownership of models

 Model management functionality

 Modeling of data is the first, models on view /

notation ( AF) and processes are to come

 Boundary between ontology's and ‘classical data

modeling’ ?



19/12/2006 p23



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