Scientific Data and Knowledge Management in Aerospace Engineering

Scientific Data and Knowledge Management in
Aerospace Engineering

Korea e-Science AHM 2008 (September 8th 2008, Daejeon)
Andreas Schreiber <Andreas.Schreiber@dlr.de>
German Aerospace Center (DLR), Cologne
http://www.dlr.de/sc
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Korea e-Science AHM 2008 > Andreas Schreiber > Data and Knowledge Management in Aerospace Engineering > 08.09.2008

Outline

German Aerospace Center (DLR)
Introduction
Excurse: DLR CFD Codes
Grid Computing: D-Grid and AeroGrid
Software Tools: DataFinder, RCE, and XPS4CFD
Conclusion

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The DLR
German Aerospace Research Center
Space Agency of the Federal Republic of Germany

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Sites and employees

5,700 employees working Hamburg
in 28 research institutes and Bremen- Neustrelitz
facilities Trauen
Berlin-
Braunschweig
at 13 sites.

Göttingen
Offices in Brussels,
Paris and Washington. Köln
Bonn

Lampoldshausen

Stuttgart

Oberpfaffenhofen
Weilheim

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Introduction
Simulation in Aerospace and Avionics
Designing new space and aerospace vehicles require high-resolution
numerical simulation steps conducted in complex workflows
The complete simulation of all flow phenomena throughout the
entire flight envelope including the multidisciplinary simulation of
all involved disciplines
The multidisciplinary optimization of the overall aircraft design
as well as the design of major parts, such as the turbine engines
Involved disciplines:
Aerodynamics – Structure – Heat – Flight mechanics – Radar & Infrared
signature – Materials (physics/chemistry) – Combustion …

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Software Technology for Aerospace Simulations
Numerical Codes and Supporting Tools

Highly sophisticated and optimized numerical simulation codes
For example, high-fidelity CFD codes
Many codes available (free, commercial, proprietary)
To major CFD codes of DLR
TAU
TRACE

Simulation infrastructure and supporting tools
Grid environments
Data and workflows management tools Integrated
Integrated
Knowledge management ( documentation!) environments
environments
Preprocessing, post processing, visualization

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DLR CFD Codes

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DLR TAU Code
Finite Volume CFD Solver

Reynolds-averaged Navier-Stokes
(RANS) code
Steady and unsteady flow, hybrid grids
State-of-the-Art turbulence models
Adaptation module for local refinement
Chimera method
Completely parallelized (MPI)
Used in European industry (Airbus,
EADS)
Contact:
DLR Institute of Aerodynamics and Flow
Technology
http://www.dlr.de/as/case

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DLR TRACE Code
Turbo machinery CFD

TRACE: Turbo machinery Research
Aerodynamics Computational Environment
unsteady Reynolds-averaged Navier-Stokes
(URANS) code
Steady and unsteady flow (finite volumes)
Hybrid multi block method
Completely parallelized (MPI)
Used in European industry (Siemens, MTU
Aero Engines, Rolls Royce)

Contact:
DLR Institute of Propulsion Technology
http://www.dlr.de/at

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Simulation Infrastructure
Grid Computing in Germany – D-Grid

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German D-Grid Initiative
Grid Infrastructure for e-Science

Objectives
Building a Grid Infrastructure for science and business in Germany
Combine existing German grid activities
Integration of middleware components developed in Community Grids
Three components of the infrastructure
Networks and associated tools
Software layer for connecting tools and services
Scientific information and knowledge
Important aspects
Continuing sustainable production grid infrastructure after the end of the
funding period
Integration of additional grid communities (2./3. generation)
Business models for grid services
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D-Grid Projects
Community Grid Projects
User Services (Portals)

PartnerGrid
BauVOGrid
Astro-Grid

HEP-Grid

MediGrid

AeroGrid
Business Services, SLAs, SOA Integration, Virtualization

TextGrid

WISENT
C3-Grid

In-Grid
●●●

Knowledge Management

Grid Middleware und Grid Services
Integration Project

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General D-Grid Architecture
User/Application

Application
development GAT API GridSphere
and Plug-In
user access

Nutzer
Scheduling
Workflow Management

higher
Grid Monitoring
Functions

Datenmanagement LCG/gLite UNICORE

Accounting
Billing
Base User/VO-Mngt
services Globus
Security

Network-
distributed distributed
Data/ infrastructure
data archives compute
Software
Resources

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Specifics of the D-Grid Architecture

D-Grid supports three middleware and two data access protocols.
Combines requirements of all communities.
Goal: Support of all middleware systems by all resource providers

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D-Grid Infrastructure (2007)

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AeroGrid Project

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AeroGrid
Project Data

Grid-based cooperation between industry,
research centres, and universities in
aerospace engineering

Runtime: April 1, 2007 – March 30, 2010
Website: http://www.aero-grid.de

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AeroGrid
Use Cases and Project Goals

Usage scenarios
Use of computing resources via the AeroGrid
Collaboration in designing engine components
Co-operative further development of TRACE code

Project goals
Allow cooperation in research and development projects
Use of up-to-date program versions, data, and compute resources
across all locations
Detailed documentation of history of a computational process that leads
to a certain result (“Provenance”)

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Service-Provider A
Service-Provider A
WebDAV/
WebDAV/ Resources
Resources
AFS/SRB/
AFS/SRB/
Cooperation in AeroGrid GridFTP/…
GridFTP/…

UNICORE6
UNICORE6
Data/ Tools
User
User GridSphere
GridSphere Meta data
Data
Data Server
Server
Code
Code Management
Management
Developer
Developer Tool
Client
Client
Workflow
Workflow
Service*
Service*
CPU Resources

Grid Interfaces
Web
Web Service-Provider B
Service-Provider B
Portal
Portal
Simulation
Simulation Resources
WebDAV/
WebDAV/ Resources
User
User AFS/SRB/
AFS/SRB/
GridFTP/…
GridFTP/…

UNICORE6
UNICORE6
Data/ Tools
Workflow
Workflow GridSphere
GridSphere Meta data
Client*
Client* Server
Server

Workflow
Workflow
Service*
Service*
* Workflow service and client are not part of the project. CPU Resources
They will be added for later user communities.

...
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Provenance
Origin and Authenticity of Results

Provenance of computational processes
Recorded documentation of processes as they take place
With this documentation, we can determine:
the origin of electronic data and
the compliance of the process that led to the data

Definition of provenance
The Provenance of some information is the history of its creation

Related Terms
“Data Lineage” is another word for Provenance
Provenance is NOT “Logging”

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Provenance
Example Queries

Given some data item, what was the simulation case?
Given some parameter, in what simulation(s) has it been used?
What data has been recorded in a simulation with a specific parameter?
What simulations have been run using a given model (aircraft design)?
Given two/more simulations with the same setup, what is the result and
the difference in provenance?
What have been the initial conditions for this simulation?
What were the termination criteria?
How often has the workflow been executed?
What specific algorithm/version has been used in computations?
What were the hosts participating in the simulation run?

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Provenance
Benefits for Aerospace Applications

Clean documentation of distributed simulation workflows

Ability to analyze and reason over all conducted computations
Understanding of computations and their results
Tool based support for analyses

Allows checking for requirements
Compliance to legal and business regulations

Proof and reproducibility of results

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Example
Provenance Information in Simulations
Process d2
control File-Server
m1
i0 c-4
c4
c1 c-1 d1
c2 c-2 c3 c-3

Pre- i1 Parameter i2 Simulation i4
Visualization
Processing variation
i3 Relationen:
Interactions:
- r0: i0 causes i1
Configuration State - r1: i1 causes i2
of the Actors - r2: i2 causes i3
Process flow - r3: i2 causes i4
Monitoring - r4: i3 causes i2
- r5: i2 causes m1
Data management - r6: i2 causes d1
- r7: i0 causes d2
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AeroGrid User Interfaces

Portal
Web-basaed access
Devlopment based on GridSphere

Client applications
Automation of recurring tasks
Integration in existing working
environments

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Data Management Client Software
DataFinder

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DataFinder
Short Overview
DataFinder
Efficient management of scientific and technical data
Focus on huge data sets

Development of the DataFinder by DLR
Available as Open-Source-Software

Primary functionality
Structuring of data through assignment of meta information and self-
defined data models
Complex search mechanism to find data
Flexible usage of heterogeneous storage resources
Integration in the working environment

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DataFinder
Uses

Large-scale simulations
aerodynamics
material science
climate
…

Measured data
wind-tunnel experiments
earth observations
traffic data
…

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DataFinder Overview
Basic Concept

Client-Server solution
Based on open and stable standards, such as XML and WebDAV
Extensive use of standard software components (open source /
commercial), limited own development at client side

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DataFinder
Mass Data Storage using “Data Stores“

Storage
Logical View User Client Locations
“Data Stores”

External Medias
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(CD, DVD,…)

Data Structure
Mapping of Organizational Data Structures
Object
Object (file)
(collection)
Relation File 1 Project Mega
Code Ultra
User Eddie

Simulation I
Key Value

Project Mega
Code Ultra
User Eddie
Key Value

File 2 Project Mega
Code Ultra
User Eddie

Project A Simulation II
Key Value

Project Mega Project Mega
Code Ultra Code Ultra
User Eddie User Eddie
Key Value Key Value

Experiment
User Project Mega
Project B
Project Mega
Project
Code
User
Key
Mega
Ultra
Eddie
Value

Code Ultra Code Ultra
User Eddie User Eddie
Key Value Key Value

Attributes
Project C
Project
Code
User
Key
Mega
Ultra
Eddie
Value
(meta data)

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DataFinder in AeroGrid
Turbine Simulation

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Turbine Simulation
Data Model

Simulation steps (example):
1. splitCGNS
Preparing data for TRACE
2. TRACE (CFD solver)
Main computation
3. fillCGNS
Conflating results
4. Post Processing
Data reduction and
visualization

Automation with customized
DataFinder

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Turbine Simulation: Graphical User Interface

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Turbine Simulation: Customized GUI Extensions
1
2
1. Create new simulation
2. Start a simulation
3. Query status
3
4. Cancel simulation
5. Project overview
4

5

Customization based
on user requirements!
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Turbine Simulation
Starting External Applications

1. CGNS Infos / ADFview / CGNS Plot
2. TRACE GUI
3. Gnuplot

1

2
Integration with
3 other tools!
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Integration Platform and Workflow Management
Reconfigurable Computing Environment (RCE)

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Beyond DataFinder…

Use cases for “lightweight” tools like DataFinder
Simple recurring tasks
Easy and fast customization (but “static” workflows!)
Instant access to distributed storage resources
Easy installation

Additional complexity requires more sophisticated systems
Dynamic (large) workflows
Complex configurable user interface
Use of existing services

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Reconfigurable Computing Environment (RCE)

The RCE general purpose integration platform
Used to manage collaborative engineering processes
Provision of commonly used software components
Data management, graphical user interface, distributed computing,
workflow component
Concentration on the application specific software components

Developed as a service oriented software framework
Using OSGi as service platform (for Java)
Eclipse for graphical user interface

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RCE Architecture

Macro
Notification
Config.

Ext. Code

Application Server
SOAP

Communication
RMI

Application

Privilege
Wrapper

Broker
Data
Application

GUI
… …
… Reconfigurable Computing Environment
OSGi/Eclipse Equinox
Java Virtual Machine

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RCE
DB Server
Distributed System

Communication
SOAP

Applic. Server
RMI

Privilege
Broker
Data
Application
…

RCE
GUI OSGi/Eclipse Equinox
Communication SOAP
Applic. Server

RMI
Privilege
Broker
Data
GUI

…
Ext. Code
RCE

Communication
SOAP

Applic. Server
Simulation
OSGi/Eclipse Equinox RMI

Privilege
Wrapper

Broker
Data

…

RCE
OSGi/Eclipse Equinox
Java Virtual Machine Simulation

Desktop

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GUI Example
Shipbuilding Industry

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Use Cases at DLR
RCE as integration platform
IMENS (Multi disciplinary design of space re-entry vehicles)
Simulation of hot structures
RCE-based environment for coupled,
distributed simulation in Grids

CEF (Concurrent Engineering Facility)
Collaborative early design of space vehicles
Mission planning
Experts for all disciplines in one room
RCE-based software infrastructure
Reuse of existing Excel-spreadsheets

XPS4CFD (Expert System for CFD)

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Integration with Microsoft Excel

If you cannot avoid Excel:
Solution 1: Use Excel, integrate interfaces to computational resources
into Excel
Solution 2: Integrate Excel into execution environment and
workflow system

RCE-Excel-Integration
Excel user interface integrated
Excel is nice!
into RCE/Eclipse It's ugly to use, but nice.
Excel files stored in RCE data And in the end all data
management
Sharing data with other RCE ends in Excel.
Hans Rosling
components

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Expert System for Aerospace Engineers
XPS4CFD

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XPS4CFD (1)

Assistance of users of DLRs CFD-software TAU
Provide best-practices and guidelines, depending on specific problems
and facts
Rule-based system using JBoss Drools as the rule engine
Eclipse Rich Client Platform application, based on RCE

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XPS4CFD (2)

Combined with a Lucene search engine for finding relevant documents
Easily maintainable and extensible by experts, not programmers
Forms and graphical editors for adding, changing and deleting
rules, workflows and documents
Generators for automatic creation of the fact model and UI
elements like interview-components

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Choosing and Planning a Scenario

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Guiding Users Through a TAU Workflow (1)

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Creating Rules

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Creating Forms

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Creating Workflows

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Expert System
Additional Use Cases (related to space/aerospace)

Health monitoring
Monitoring health status of
astronauts and pilots
Managing knowledge about
irregular health parameters
Send alarms

Astronaut assistance
Assist astronauts in standard
procedures and problem situations
Configurable for all subsystems of
space crafts

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Conclusion
Putting All Together…
Expert
Expert feedback analysis
User System
System
Shares Knowledge
Uses Knowledge generate workflow

Works with data
Data &
Data &
Search meta data Workflow
trace Provenance
Workflow user
Select resources Management
Management action Store

execute workflow
Software tools
trace
Generate workflow description workflow
execution
Executes workflows in Grids
Record Provenance info

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Questions?

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Scientific Data and Knowledge Management in Aerospace Engineering

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