Data Management

5/27/2018 Data Management

1/7

Education & TEducation & Trainingraining www.nafems.org

January 2005Page 6

IIn the automotive industry there is the vision inevery car project to perform only the legallyprescribed real crash tests and to lower the

development costs by drastically reducing thenumber of hardware-prototypes. Therefore it is

certainly necessary to increase the number ofvirtual crash tests enormously. But the crashdiscipline is only one example and the situation is

the same for almost all other fields of numericalsimulation. Additionally the simulations have thepossibility to improve the functional characteristicsof the cars by using stochastic, genetic and otheroptimisation methods. The consequence of this is asignificant increase in the number of simulationruns.

Disciplines in CAE

All of the analysis disciplines listed below require a largenumber of numerical simulations.

Front, rear, side crash

Insurance test

NVH analysis (Noise, Vibration, Harness)

Head impact

Occupant safety (OS)

Pedestrian protection

CFD aerodynamics

Durability and fatigue

Stiffness of components

Global and local dynamic stiffnesses

Functional dimensioning of doors, flaps and hoods

PowerNet (simulation of the on board supply system)

New directions and capabilities in CAE

Increasing product diversification, sharper qualityrequirements, higher market competition, more costpressure and shorter development cycles were the driving

forces for the break-through of numerical simulation. The

numerical applications cover nearly all of the virtualdevelopment process.

Trends in the automotive industry show an increasingnumber of:

product variants (USV, MPV, ),

boundary conditions (government regulations,technologies, ),

statistical verification (stochastic simulation) and

multidisciplinary optimisation (discipline combinations).

The result of these facts is once again a drastic increase in

the volume of numerical simulations.

On the other hand the cost of CAE simulation(see Figure 2) is falling because of advancinghardware and software power.

The consequences of these developments andtrends can be represented as follows:

To compare between experiment andsimulation the physical real test is more

valuable.

Functional analyses can be performed fasterand earlier in the development process.

More cost-effective and more systematicanalyses can be performed.

Deeper transparency is needed and thusdemands on documentation are higher.Figure 2: Cost in virtual vs. cost in physical prototyping

CCAE DataAE Data

ManagementManagementat Aat AUDI AUDI AGG

Dr. K. Gruber, Dr. U. Widmann, J. Reicheneder, AUDI AG, Ingolstadt,

Germany, J. Elberfeld, MSC Software GmbH, Mnchen, GermayFigure 1: Selected analysis disciplines in the car development

CFD

Aerodynamic

NVH

Analyses

Front, Rearand Side Crash


2/7

An intensive and efficient use of numerical simulation isonly possible if we succeed in rationalising the process ofnumerical analyses. Therefore consistent datamanagement is needed, which enables fast access tosimulation data and efficient handling of huge amounts ofdata.

Development of SDM

(Simulation Data Management)The starting points for the development of our SDMsystem are the management of data and the workflow. In

the following section the focus is on the CAE process andthe resulting data.

Audi CAE process

In principle the CAE process can be divided into therespective sections of pre-processing, solving, post-processing and reporting (see Figure 3).

In the pre-processing step the data of the different carcomponents are extracted out of the CAD datamanagement system. Dependent on the analysisdiscipline these geometries are meshed according tocertain guide-lines and mounted together with barriers(crash) and dummies (occupant safety, OS) to a virtual car

assembly, the so-called numerical model. In addition tothe geometry the physical parameters (e.g. contacts andvelocities) and the material properties have to be definedin the input deck. In these work steps different pre-processing applications are used.

In data management the input data and all meta datadescribing the car project and the specific computer run(discipline, load case, analyst ) are stored.

The solving step is the numerical solution of the loadcases defined in the input deck. Important for data

management are the following: The results (output decks)

Additional information (computer time, data volume ofthe output ...).

The most standardiseable section isthe post-processing. In this step thepost-processing objects (PPOs), e.g.curves, pictures, movies etc. aregenerated using different post-

processing applications. In the datamanagement system the PPOs

together with the corresponding metadata are stored.

In the reporting, the last step of theprocess, the report is generated out of

the previously produced PPOs.

Project demands for a CAE data management system

In addition to the boundary conditions resulting from theexisting work flow at Audi, the following requirements

could be identified:

Because of the enormous number of simulations thedata management system has to be able to handle thehuge amount of data.

The representation of the data has to be adaptive to fitthe requirements of the different disciplines andanalysts.

The concatenations of the objects and data must beunique so that afterwards the workflow can bereconstructed and traceability is possible.

Easy and fast access to the results with competentpreparation of the representations is required.

To avoid routine jobs for the analysts an automaticstandard evaluation and reporting is necessary.

To guarantee independence of the computer hardwareand operating system and to economise the resources(CPU and storage) of the user, a server based webapplication should be employed.

Automatic pre-processing with a link to the CADcomponent database should be realized.

Project overview

For milestone 1, which lasted from November 2001 untilJune 2002, the following tasks were performed:

Implementation of the Basis-System for crash andoccupant safety (OS).

Integration of the AUDI-scripts for post-processing.

Jobs from CAE-Bench should use LSF (Load SharingFacility).

Central database in the computer centre.

Planning of the hardware for productive use.

Request the first user feedback.

January 2005

Education & TEducation & Trainingrainingwww.nafems.org

Page 7

Figure 3: The sections pre-processing, solving and post-processing in the CAE process


3/7


Page 8

The goal of Milestone 2 (July 2002 - December 2002) wasthe expansion and the adaptation of the system and theintroduction of new disciplines. Five sub-projects weredefined:

NVH (Data model, interactive use)

CFD/Aerodynamic (Data model, interactive use)

Job submit (FlowGuide/LSF integration)

FMVSS201 (Head Impact-Greenhouse)

Expansions (Enhancements for the report, workbenchesdependent on disciplines, graphical data navigator)

Milestone 3 (January 2003 - December 2003) containedthe start of productive use, the expansion and theadaptation of the system and the introduction of furtherdisciplines. The subprojects were:

Pre-processing Enhancements for Import

Pedestrian Protection (Data model, interactive use)

PowerNet (Data model, interactive use)

Computer Aided Testing CAT (Data model, interactiveuse)

To ensure that the hardware matches productive requests,a webserver (Linux), storage server (SGI, 1.4 TByte) and apost-processing/report server were installed.

CAE-BenchSimulations in CAE-BenchAs shown in Figure 4 the productive use started inFebruary 2003. There was a cumulative import of about2000 simulations during October 2004.

Input deck

Solving, post-processing, importing in the database andreporting are supposed to work automatically. Thus it isimportant to declare all the necessary information in theinput deck. The following listing is an example.

January 2005

$

$

$ Car of the future

$ Virtual Prototype

$ Crash

$ Front

$ F8A9

$ Euro-NCAP

$ CAE

$ Gruber, Widmann, Reicheneder,

Elberfeld

$ Test Data Set

$ Crash Front Storyboard

$

$ Crash Front Master

$

$

$

Storyboard

A central part of the post-processing in CAE-Benchis the storyboard concept. The storyboard is the

complete definition of a post-processing object(e.g. curve, movie ...). Figure 6 illustrates thecreation of a curve.

Representation of the evaluation

The complete representation of the results takesplace in the web browser. The browser window isdivided into two frames. On the left hand side thereis a navigation frame and on the right hand side thelistings of the appropriate PPOs (Figure 7) arearranged.

Report

The report is generated automatically on a masterreport which is declared in the input deck. CAE-Bench provides a report editor with multiple editing

functions for handling with PPOs, i.e. adding,Figure 4: Number of simulations imported in CAE-Bench

Figure 5: VirtualInsightis the framework for theintegrated simulationenvironment of CAE-Bench


4/7

January 2005


Page 9

deleting, replacing and comparison ofvariants. The report in the web browserhas proved itself in meetings andpresentations. In addition it is possible tocreate a pdf-file.

Hardware

For the different tasks in our SDMsystem there are different servers andstorage systems (Figure 9).

One of the central units is the webserver which consists of two linuxcomputers with load balancing. They

form the user interface and manage accessrights.

The compute server stands for several clusters for CAE-solving (PamCrash, Nastran, ..).

The application servers generate thePPOs and the reports.

The database server administratesthe attributes of the calculations andthe paths to the data in the file serverand the storage system.

The file server holds the PPOs andreport data and offers a very quick

data transfer.

The input and the huge solver outputfiles are deposited in the storagesystem.

Advantages

CAE-Bench offers a set of advantages:

Standard Information is extractedfrom the solver output filesautomatically.

Access Information via Web-GUI

Use Information for Reports andComparison

One of the greatest benefits of ourSDM is the overall time saving.

We assume a time saving persimulation of about one hour. With 100simulations per engineer per year and50 engineers, we get 5000 simulationsper year. The time saving for this

example would be 5000 hours peryear. This corresponds to 3 man years.

Figure 6: The storyboard and the creation of a post-processing object

Figure 7: Representation of the PPOs in the browser

Figure 8: Report editor and representation of the report


5/7


January 2005Page 10

Thus the simulationengineer can performmore simulations, hasmore time for analyses,can get the results faster

and therefore has a bettertechnical understanding.

ChallengesCAE-Bench provides a lotof options and challenges.The following sectionsdescribe some challenges

for the next years.

Data volume grows

For instance a typical

EuroNCAP calculationgenerates approx. 2 GByte of data.

Variant_1_EuroNCAP/Input 117.660 KB Input Data

Variant_1_EuroNCAP/Output 1.943.986KB Results

Variant_1_EuroNCAP/Misc 2.797 KB Descriptions

Variant_1_EuroNCAP 2.064.446 KB total sum

In addition the conditions for the future will push the datavolume even higher. We anticipate an increasing:

number of engineers

number of simulations

types and sizes of simulations

types and sizes of tests.

Subsequent requirements are:

Consistent data management

Easy transparent access to data

Efficient management of huge amounts of data

Concepts for archiving

Standard report at certain milestones

A further challenge will be the automaticgeneration of quick surveys of all disciplinesinvolved in a car project. Dependent on theparticular milestone classification numbers have

to be calculated (see Figure 11).

CA-Integration

Product definition is based on geometric design,functional design and physical verification.

Product life cycle management is based on CADdata management, configuration management,component management and logistics.

Simulation Data Management fills the gap between CAEand CAT data management. Its basis is CAE/CAT datamanagement and CAx integration.

A scheme of CA data interfaces is shown in Figure. 13.The interfaces between the CAx data is formed byintegration layers. In the case of CAE the framework isCAE-Bench, applications for example are PamCrash,Nastran and Abaqus.

CAE Process Chain expands CAE NetworkOne of our tasks in the next few years will be the CAE-Integration of the different companies in the VW groupincluding external engineering companies, systemdevelopers and system suppliers. It requires access andsearch capabilities on distributed data bases for a globalinformation management, i.e. wide area CAE network.

Figure 10: Data volume over time with 2 GByte per simulation

Figure 9: Hardware architecture of the CAE-Bench installation at Audi


6/7

January 2005


Page 11

Global data grids

Global data grids are able to enhanceSDM and the simulation workflow.Referring to this we identify the followingitems:

1. IT infrastructure for distributed

engineering data grids

Technology and requirements for

hardware operating systems network

distributed databases authentication

2. Data sharing, data exchange,

distributed data and databases

Integration of multiple organisations,

disciplines and locations

Management, transfer and

synchronisation of distributed raw data

(files)

Data access and exchange for distributed schema (data

model)

Process integration in distributed data grids

3. Security of data and data access

Authorisation for

Multiple disciplines (access rights/policies) Multiple locations (encryption)

Partner integration (e.g. external suppliers)

4. Encryption of data for collaboration with

suppliers

Encryption technology for data transfer

Hiding (partial encryption) of simulation

models

5. Standardised data representation Data schemas for collaboration and data

exchange

Interfaces for data exchange

Integration of applications

Processes for collaboration

6. Integration of applications (tools)

Standards for application integration

Post-processing tools

Solvers

Stochastic tools

Parametric tools

7. Integration of different frameworks

Standards for

Data access,

Data exchange and

Open software (LMS/Virtual.Lab, ESI/Composer,Dassault/VPM)

Figure 11: Quick survey of all disciplines in a car project

Figure 12: CA-integration


7/7


January 2005Page 12

8. CAD integration and pre-processing for distributed data grids

Neutral and standardised CAD interface

CAD-CAE data exchange

Parametric design

CAD framework

Variation of CAE simulation models

Automatic meshing of assemblies

9. CAT integration for distributed data grids

Standardised interfaces for data access and exchange

Data integration vs. replication

Standardisation for compare

CAE-CAT process integration

Standards of data format (e.g. curves, movies, etc)

10. Knowledge discovery and data mining

Data mining technologies

Data mining in distributed databases

Formulation of queries and researches

Definition of similarity for compare Fuzzy research

Automated learning

Integration of external tools

Interfaces for data mining

ConclusionEffective rationalisation can only be achieved

through the analysis of the discipline dependentCAE-process. CAE-Bench provides standardisedevaluation and archiving of key-results anddescriptive documents. It is an open system based

upon SDM Technology from MSC.

At Audi, CAE-Bench has been in productive usefor more than a year. The system fits ourdemands. Staff members are relieved of standardoperations. Now they have additional time forspecific considerations.

Further ActivitiesThe next activities will be the extension of theprocess chain by pre-processing, thedevelopment of concepts for CA-integration and

the establishment of global data-grids.

References[1] Doing the Right Thing First. MSC.SoftwareFocus, Volume 1, Spring 2003, pp. 8-12

[2] Elberfeld, J.: SDM - Integrated DataManagement for the Optimisation ofComputation and Simulation Processes.MSC.Software Focus European Edition, Volume1, Spring 2003, pp. 4-7

[3] Gruber K.; Widmann U.; Reicheneder, J.;Elberfeld, J.: CAE Data Management at AUDI

AG.

[4] NAFEMS-Seminar: "Die Integration dernumerischen Simulation in denProduktentwicklungsprozess", Wiesbaden(Germany) 2003

ContactContactJosef Reicheneder,AUDI [email protected]

Figure 14: CAE Process chain expands CAE Network

Figure 13: CA data interfaces

Data Management

Documents

Transcript of Data Management