Collaborative engineering solutions and challenges in the development of space systems

www.DLR.de • Slide 1 > Collaborative Engineering for Space System Development > Andreas Gerndt • WETICE 2012 > 2012-06-27

Collaborative Engineering: Solutions and
Challenges in Development of Space Systems
Andreas Gerndt
German Aerospace Center (DLR)
Simulation and Software Technology
Software for Space Systems and Interactive Visualization
Lilienthalplatz 7, 38108 Braunschweig, Germany


Todays Mission Plan…

- Challenges in space

- Concurrent engineering and data
handling in early phases

- Collaborative development of
spacecraft

- Model-Based Systems Engineering
for spacecraft design

- Knowledge Conservation and Reuse

- Conclusion

Fig.: German Space Operations Center at DLR


Space…

What is so special about Space and Spacecraft?


*Picture: NASA


A Current Project – Galileo

- Galileo: European Satellite Navigation System

- Small series
- 30 satellites (27 operational, 3 spare)

- Test satellite GIOVE-A1
- Manufacturer: Surrey Satellite Technologies
- Launch on Soyuz in 2005 from Baikonur

- Test satellite GIOVE-B *Picture: ESA

- Manufacturer: Galileo Industrial Consortium
- Launch on Soyuz in 2008

- Test satellite GIOVE-A2
- Planned, but cancelled!


Galileo – An Example for Complexity

- In-orbit validation
- 2 satellites built by Astrium
- Launch on new Soyuz-ST from Kourou
in Oct 2011

- Full Operational Capability satellites
- Contract of the first 14 went to OHB Systems
- Launch on Soyuz and Ariane 5 from Kourou

- Remaining satellites 11 + 3 spare
- Contract still pending

- First service available 2014 with 18 satellites
- Fully operational after 2020!

*Picture: ESA


Challenges in Space Systems Design

- Prototype development or small series
- Mission duration, easily 10-20 years
- High Costs
- Many suppliers, manufacturers, international team
- Changing interfaces to sub-systems
- Constantly changing personnel

Source: Märkische Allgemeine (2012-06-12)
- Limited contracts
- Long-lasting planning processes
- Political aspects
- Russian rocket in Kourou, French Guiana
- High design quality required
- Complex, interdisciplinary design task
- After launch, maintenance often not possible
- Space environment for tests not available
or limited on the ground


Errors Can Happen

- Hubble Space Telescope
- Launch: April 24, 1990
- Failure: mirror ground to wrong shape
- Space Shuttle repair mission

Fig.: Improved Hubble Image (right) Fig.: Endeavour astronauts, installing
corrective optics, Dec. 1993

www.DLR.de • Chart 9 > Collaborative Engineering for Space System Development > Andreas Gerndt • WETICE 2012 > 2012-06-27

Phobos Grunt – Another Failed Mission

- Mission: Samples from Mars Moon Phobos

- Launch: Nov. 9, 2011

- Failure:
- Lost communication
- Did not leave low earth orbit
to Mars
- Window to trajectory closed
- Uncontrolled re-entry
on Earth Jan. 15, 2012
*Picture: ROSKOSMOS


Apollo in the 60s


http://photojournal.jpl.nasa.gov/jpeg/PIA14839.jpg
Mars Science Lab – Curiousity – 2011


Handling Complexity, Handling the Workflow…

Our approach of supportive Software…


Our Challenges

- DLR Missions
- BIRD and TET series
- On-Orbit Verification
- Shefex
- Reentry Experiments Fig.: SHEFEX II mission, 22. June 2012
- Solar sail

- Classification
- Experiments
- Science missions
- Technology demonstration

Fig.: Solar Sail - Gossamer


Our Contribution to Handle Complexity

- Carrying out software research to
find adapted software solutions for
systems engineering challenges

- Supporting the engineers
- Automate what can be automated
- Free engineer from repetitive and
error-prone tasks
- Allow time for creative tasks
- Support collaboration in
development teams
- Improving the common
understanding of the design
problem


Space System Today… And in the Future…

- Systems Engineering: Global goals
- Ensuring high quality
- Reduction of time
- Reduction of costs

- Space System Engineering
- Almost always prototypes
- Multi-disciplinary engineering

- The Vision: One system model
- All design information collected in Source: TSTI
one central database
- Consistent, single-point-of-truth
- Easy access to the knowledge
- Right presentation in the right tool


Space System Development – Models from Today

- Having a Structured Design Process but
- V-Model… and many, many more
- Segmentation and Barriers
- Scattered tool and data landscape
- Most exchange document-based
- Many project partners, suppliers involved

Fig.: V-Model (US Depart.
of Transportation, 2006)

Fig: Barriers explained from Cross- Fig: ECSS space mission life-cycle
Domain Dependency Modeling– How to
achieve consistent System Models with
Tool Support and VDI 2206


The Vision of Creating a Common Data Model

- Covering all the different data sources
- Bringing the tool fragments together

- Covering all the different design stages
- Bringing the lifecycle fragments together

Source: US Air Force
Status Quo: Fragmentation Dream of a “Unified”
and Inconsistency of Data Digital Master Model


A unified data model – Our approach

- Benefit of one common data source
- Bringing experts AND their tools together

Data Exchange

Data Exchange Common Data Store

Data Exchange


Common Data Source in Early Phases

- Concurrent Engineering Facility
- Interdisciplinary design process
- Bringing experts together
- Open communication/discussion
- Common design understanding
- Tool support – Data Model

- Study of one up to two weeks
- Good spacecraft estimation Fig.: Concurrent Engineering Facility at DLR
- High level of quality
- Margins below 5 - 20%

- Gain in time and cost
- from 6-9 months to 3-6 weeks*
*Ref: DiDominizio and Gaudenzi – A Model for Preliminary Design Procedures of Satellite Systems,
in Concurrent Engineering, June 2008, vol. 16, no. 2, pp. 149-159, DOI: 10.1177/1063293X08092488


Transparent Collaborative Modeling for the CEF

- Data Model is transparent to the engineers
- One common source of data
- Transparent commit and update actions

CEF Point of View

Update Commit

IT Point of View

Model


Our Approach Virtual Satellite
- Dedicated Software to support concurrent engineering
- Tailored to the process
- Supporting the engineers
- Incorporating Analysis Tools
- Mass budgeting
- Mode dependent power consumption


Example: Sensitivity Analysis

- Design evaluation by automatic analysis
- On-the-fly analysis of the data model
- Sensitivity analysis – Understanding impact of changes
- Special views to data, quickly interpretable and accessible

 Derive next actions in the design process, decision support

Internal
Data Model


Exploring New Ways….

Like Collaborative Configuration and Beyond…


Visual Modeling – A New Approach
- Visualization as supporting tool in modeling
- Bringing paper sketches into the model
- Abstract parameters towards concrete understandable images
- Avoiding loss of information by communication
- Model provides global view of changes and meta data


An Example of CE Design Evolution


The Shift of Responsibility from One to All
- Today: One configuration engineer within the CEF
- Each with their own proprietary tools
- Future: All engineers takeover responsibly
- Create different views out of data model

Sharing Visualization
Parameters

Model


Example: Integrated Tool in the Design Process
- E.g. Catia can be generated from the common model
- Standard engineering tool for configuration
- Challenge to get data back to model
- Later phases demand even more tools

Model


Modeling in Virtual Reality – The Next Step

- Model representation in virtual environments
- Immersive experience of perceiving the model
- Bringing experts into CAVE or in front of Powerwall
- Does this break the concurrent engineering process?
- Design modification in virtual environments
- Interacting with the virtual environment
- Directly affecting the common data model
- Directly analyzing the impact either in VR or model

VR World CEF World

Model


Multi-Disciplinary Visualization

- Visualization as a supporting tool in CEF studies
- Integration with simulation data (e.g. thermal, power, structure)
- Incorporation of scientific visualization
- Comparison of design variants


Distributed Collaboration
- Simulations are time consuming in particular in later phases
- Distribution to data processing centers (parallelizing)
- Needs distributed applications

- Experts are seldom - Difficult to hold on
- Need distributed CEF in particular for later phases

- Saves money and costs – “Just In Time” engineer

*Picture: ESA

OCDS Model


Distributed Collaboration – Drawbacks
- What about latencies?
- Is there enough understanding for the other domains?
- Intercultural aspects
- Is this breaking the ideas behind concurrent engineering?
- Quick, agile iterations needed

Building Walls – Minimizing Communication

Update Commit


From Modeling to Analysis and Verification …

But what can we get out of it?


Benefit of Model-Based Systems Engineering

- Automatic code generation
- Simulation code
system
- On-Board software (AOCS, …) simulation

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Example One: ESA - Universal Modeling Framework

- Modeling framework
- Currently used for operational simulators
- Simulation Model Portability 2.0 (SMP)
- ESA Simulation Standard
- Supports graphical modeling

- Benefit of the model
- Generates framework code
- Behavior implemented manually
- Generates consistent documentation

- What about the logic and algorithms?
- Is it possible to model the behavior…


Verifying the Model in Early Phases
Model
- Does our model fulfill the requirements?
- Like having enough fuel
- Like gathering enough science data

- Are the requirements sufficient?
- Can I gather enough data in 5 years?
- Is there enough fuel to fly 10 years?

- Solution by Verification
- Check if model satisfies requirements?
- If not, change model and/or requirements


Model Verification

- Model verification means:
- Proof of correctness of the model
against requirements
- Changes can be verified as quick
as possible
- Two common approaches Model
- By simulation
- By formal methods

- Verification by simulation:
- ESA – SimVis

- Verification by formal methods:
- Our current research


Verifiable Model - Creation
- We have parameters like
- Power consumption
- Data collected

- We have values for operational modes
- Science mode
- Orbit maintenance
- Creating state model out of parameters and modes


Verifiable Model - Requirements

- Formalizing our requirements
- Natural language processing
- Creating temporal logic

- Store requirements to model
- Extending the model Model
- Requirements mapping

- Using a Standard Model Checker
- Well established in other domains
- Checking fulfillment of requirements
- Exhaustive search in state space


Drawback in Model Checking

- State Explosion Problem
- Not enough computational power
- Not enough memory

- Need to avoid calculation latencies Model
3405
- Checking multiple hours…
- Feedback is not direct… seconds

- Is this still concurrent engineering?

- We need different practical approaches
- What about heuristics?


What about Heuristic Approaches?
- Multidimensional state space problem
- What about way-finding algorithms
- Leading us to the mission goal

- For example we have the mission of
- Flying two years
- But never exceeding the battery charge

Constraint area

Goal area


Our Models are Good and Helpful…

But do we always want to start from scratch?


Conserving the Models – SimMoLib

- What is needed to reuse existing models
- A repository of models
- A way of finding them
- A trust in quality and functionality

- SimMoLib offers some of this
- Easy to use web search
- Standardized model description
- Quality assessment

- But what about model dependencies
- SimMoLib is looking for answers


WieMod – An Approach of Exchanging Models
- Transformation of simulation models
- But do not change behavior
- What about graphical layout of blocks e.g. used in Simulink

- It was research and it is still not solved
- First promising results, but…
- Behavior often depending on simulation environment
- No exchange and enhancement over lifecycle
MATLAB/
Modelica SMP2 Virtuos/M Simulink

semantic model graphical
model

WieMod MATLAB/
DSL Simulink


The WieMod Process – Reuse in Different Stages

- Simulation model designed in stages
- Models and documents for each stage
- Sim. model is stored with all stages
- Conservation in various detail

- Successful reuse
- After each stage
- Not always complete new model needed
- For different simulation environments
- Replacing Implementation
- Most stages can be reused directly

Fig.: CoMetS 2011 – Schaus et al.
Collaborative Development of a Space
System Simulation Model


This is it…

And how to get further…


Conclusions from our Research

- We are carrying out software research for engineers …
- to enhance a common understanding of systems across domains
- to relieve the engineer from highly complex tasks
- to archive and reuse the engineer’s experience
- to increase system robustness and correctness from mission to
mission

- But software will not replace
the engineer’s creativity to
develop new and innovative
missions


Acknowledgement
Volker Schaus, Philipp M. Fischer, Daniel Lüdtke,
Meenakshi Deshmukh, Hao Zhang, Michael Bock, Olaf
Maibaum, Olaf Frauenberger, Robin Wolff, …

*Picture: NASA

Collaborative engineering solutions and challenges in the development of space systems

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