© Geodise Project 2003

Grid Enabled Optimisation and Design Search for Engineering

(GEODISE)

ExpoMay 12th 2003

@ SouthamptonProf Simon Cox

Southampton University

http://www.geodise.org

Thanks to …• Nicola Reader for organisation

• … everyone for coming!

Grid Enabled Optimisation and Design Search for Engineering (GEODISE)

Southampton, Oxford and Manchester

Simon Cox- Technical Director Southampton e-Science Centre. Grid/ W3C Technologies and High Performance Computing

Andy Keane- Director of Rolls Royce/ BAE Systems University Technology Partnership in Design Search and Optimisation

Mike Giles- Director of Rolls Royce University Technology Centre for Computational Fluid Dynamics

Carole Goble- Ontologies and DARPA Agent Markup Language (DAML) / Ontology Inference Language (OIL)

Nigel Shadbolt- Director of Advanced Knowledge Technologies (AKT) IRC

BAE Systems- Engineering

Rolls-Royce- Engineering

Fluent- Computational Fluid Dynamics

Microsoft- Software/ Web Services

Intel- Hardware

Compusys- Systems Integration

Epistemics- Knowledge Technologies

Condor- Grid Middleware

The GEODISE Team ...• Richard Boardman• Sergio Campobasso• Liming Chen• Mike Chrystall• Trevor Cooper-Chadwick• Simon Cox• Mihai Duta• Clive Emberey• Hakki Eres• Matt Fairman• Mike Giles• Carole Goble• Ian Hartney• Tracey Hunt• Zhuoan Jiao

• Andy Keane• Marc Molinari• Graeme Pound• Colin Puleston• Nicola Reader• Angus Roberts• Mark Scott• Nigel Shadbolt• Wenbin Song• Paul Smart• Barry Tao• Jasmin Wason• Fenglian Xu• Gang “Luke” Xue

Expo Objectives• Demonstrate 18 month deliverables

• Technology talks by RAs

• Demos & Posters ‘deskside’ over lunch

• Talks by industrial partners

• Future plans

Design

Modern engineering firms are global and distributed

“Not just a problem of using HPC”

CAD and analysis tools, user interfaces, PSEs, and Visualization

Optimisation methods

Data archives (e.g. design/ system usage)

Knowledge repositories & knowledge capture and reuse tools.

Management of distributed compute and data resources

How to … ?

… improve design environments… cope with legacy code / systems

… integrate large-scale systems in a flexible way

… produce optimized designs

… archive and re-use design history

… capture and re-use knowledge

Design Challenges

Base Geometry Secondary Kinetic Energy

Gas Turbine Engine: Initial Design

Collaboration with Rolls-Royce

23/7/2001

RSM Construct

RSM Evaluate

Search Using RSM

Best Design

Adequate ?

RSM Tuning

Build Data-Base

CFD

DoE

Initial Geometry

CFD CFD CFD…CFD

CFDCFD

CFDCFD

CFD………

CFDCFD

CFDCluster Parallel Analysis

Design of Experiment &Response Surface Modelling

23/7/2001

Optimised Design

Geometry Secondary Kinetic Energy

23/7/2001

Distributed Systems 2003

Network

IP

HTTP

(HTML)

Compute/ Data

Moore’s Law

Grid Services

Drivers = Building Blocks + Protocols

Software

(HTML) XML

Web Services

(Proprietary, Open, Shared)

The Grid Problem“Flexible and secure sharing of resources among

dynamic collections of individuals within and across organisations”

• Resources = assets, capabilities, and knowledge Capabilities (e.g. application codes, analysis tools) Compute Grids (PC cycles, commodity clusters, HPC) Data Grids Experimental Instruments Knowledge Services Virtual Organisations Utility Services

Grid middleware mediates between these resources

Geodise will provide grid-based seamless access to an intelligent knowledge repository, a state-of-the-art collection of optimisation and search tools,

industrial strength analysis codes, and distributed computing & data resources

GEODISE

APPLICATION SERVICE

PROVIDERCOMPUTATION

GEODISE PORTAL

OPTIMISATION

Engineer

Parallel machinesClusters

Internet Resource ProvidersPay-per-use

Optimisation archive

Intelligent Application Manager

Intelligent Resource Provider

Licenses and code

Session database

Design archive

OPTIONSSystem

Knowledge repository

Traceability

Visualization

Globus, Condor, OGSA

Ontology for Engineering,

Computation, &Optimisation and Design Search

CAD SystemCADDSIDEASProE

CATIA, ICAD

AnalysisCFDFEMCEM

ReliabilitySecurity

QoS

Technologies (i) Grid Middleware(To coordinate and authenticate use of components of Geodise)

• Globus (and GGF grid-computing protocols) Security Infrastructure (GSI) Resource Allocation Mechanism (GRAM) Resource Information System (GRIS) Index Information Service (GIIS) Grid-FTP Metadirectory service (MDS 2.0+) coupled to LDAP server

• Condor (distributed high performance throughput system) Condor-G allows us to handle dispatching jobs to our Globus system Active collaboration from with the Condor development team at

University of Wisconsin (Miron Livny)

23/7/2001

(ii) Data & Open W3C Standards(To access and interchange data)

• SRB (Storage Resource Broker)

• XML and XML Schema Representing data in a portable format

• WSDL (Web Service Description Language)

• UDDI (Universal Description, Discovery and Integration) Publish and discover information about web services

23/7/2001

(iii) Ontologies & Semantic Web(conceptualisation of a community’s knowledge of a domain)

• DAML - OIL (DARPA Agent Markup Language/ Ontology Inference Language) Genetics http://www.geneontology.org/ Virtual Enterprises Product Specifications Medicine Encyclopaedic Knowledge

http://www.cyc.com/cyc-2-1/toc.html

23/7/2001

(iv) Knowledge Technologies

23/7/2001

What we said… 28/06/2001• “Consider the CFD based design optimisation of a typical aero-engine or wing component

or system. For a single loop of the design process it is necessary to (1) specify the geometry in a parametric form which defines the permitted operations and constraints for the optimisation process (this goes beyond the STEP/ IGES interchange standards), (2) decide which code to use for the analysis, (3) generate a mesh for the problem (though this may be provided by the analysis code), (4) decide the optimisation schedule, (5) execute the optimisation run coupled to the analysis code, and finally (6) monitor and steer the search as it takes place, possibly stopping it mid run to modify or rework the design process. Such loops are typically passed through several times. In our Grid environment these operations are large-scale and physically distributed computational steps: this will stretch the computation dimension in our Grid and will be delivered out first by a wizard-based Grid demonstrator: “Geodise-W” after 18 months.”

• “Whilst this is being developed we will be working on the knowledge-based demonstrator: “Geodise-K”, which we will deliver at 36 months. Here we seek to enhance each of the components of our system by using databases, ontologies and knowledge capture tools to provide intelligent guidance and assistance to the engineer using our system. We will develop, refine and deploy knowledge bases for CAD, commercial CFD code (Fluent), user supplied/ source-available CFD code (Oxford’s Hydra), optimisation and computation services. The knowledge bases will be physically distributed: integrating these large-scale distributed data sources will stretch the data interchange dimension in our Grid beyond that already required to execute and visualise our results. A conceptual architecture of our system is shown below.”

APPLICATION SERVICE

PROVIDERCOMPUTATION

GEODISE PORTAL

OPTIMISATION

Engineer

Parallel machinesClusters

Internet Resource ProvidersPay-per-use

Optimisation archive

Licenses and code

Session database

Design archive

OPTIONSSystem

Traceability

Globus, Condor, SRB

CAD SystemCADDSIDEASProE

CATIA, ICAD

AnalysisCFDFEMCEM

Geodise-W“18 month”23/7/2001

© Geodise Project 2003

18mth deliverableGeodise

“Build complex things from lots of simple

things”

Geodise Workflow/ Integration Requirements

• Flexibility Customise the workflow and its components initially Compose a work flow via drag & drop activity node component into

an editor panel Link to knowledge and other services

• Monitoring Interact with the workflow or its components during simulation Job status Resource usage

• Maintainable Modify & re-use the workflow either in a GUI or in a human readable

file• Usability

Easy to use by engineering users

Integration & Scripting

Building Blocks

Knowledge Services

Matlab(or Jython)

Java / C#

Web ServiceGrid Service

Java / C#/ .NET

.EXE/ Fortran/ Matlab Code

Intelligent Support

Interface

Geodise Architecture

CFD-based shape optimisation using Geodise toolkitsNacelle Optimisation Problem – problem definition

The aim is to understand the effect of various geometry parameters on theaerodynamic performance of engine nacelle, there is no attempt at this stageto calculate the radiated noise from fan, it is simply assumed that the bigger the scarf angle, more reduction in noise will be achieved.

Two parameters were first chosen: scarf angle and axial offsetPerformance is measured using Total Pressure Recovery

Conventional Inlet

0 1 2

Total Pressure Recovery (TPR) = 1

2pt

pt

Negative Scarf Inlet

Parallel Grid-enabled evaluations of multiple design jobs

Within the Matlab hosting environment:• Define the problem;• Generate a proxy using user’s credentials;• Retrieve the CAD definition file from repository;• Retrieve the Gambit Journal file from repository;• Retrieve the Fluent Journal file from repository;• Submit CAD-Gambit-Fluent jobs sequentially or in parallel;

(gd_cfdone, gd_cfdanalysis)a) Submit ProEngineer jobs to Windows Condor Pool via Webservice interface;

(grid_submit, grid_status)b) Submit Gambit jobs to Grid-enabled Computing Servers;

(gd_jobsubmit, gd_job_status)c) Submit Fluent jobs to Grid-enabled Computing Servers;

7. Postprocess results and archiving data files. (gd_archive, gd_datagroupadd)

CFD-based shape optimisation using Geodise toolkits

Scarf angle

Axi

al o

ffse

t

DoE using OPTIONS

CFD-based shape optimisation using Geodise toolkits

Optimisation using Design of Experiment/ Response Surface Modelling

Problem definition

Design of Experiment

Response surface modelling

Optimisation on Response surface

Validation

1. Generate a proxy using user’s credentials;2. Load in DoE data;3. Create the RSM model;4. Genetic Algorithms search on the RSM;5. A further gradient-based search on GA result

CFD-based shape optimisation using Geodise toolkits

Optimisation using DoE/RSM models and two-stage approach

© Geodise Project 2003

Geodise Demo 1

Arcadia-Options DemoMatlab

Geodisefile archive

Globus server

gd_archive.m

gd_objsubmit.m

gd_jobpoll.m

gd_objvalue.m

Matlab

optionsmatlab.dll

projectstruct.xml

arcadiaobjfun.m

x5

x5

x5

© Geodise Project 2003

Geodise Demo 2

Deliverables Summary• Application

CFD (Adjoint & Hydra, Fluent & RSF) CAD (ProE)

• Optimisation Options toolkit

• Computation/ Middleware Compute Toolkit

Globus & Condor Using UK Level 2 Grid SMS

Workflow in Matlab• Database

XML Toolkit Database Toolkit

Archive for Files Archive for Metadata Query & Retrieve

• Knowledge Acquisition Ontology Services Workflow Construction

Advice Services Ontology driven editing

“Build complex

things from lots of simple

things”

APPLICATION SERVICE

PROVIDERCOMPUTATION

GEODISE PORTAL

OPTIMISATION

Engineer

Parallel machinesClusters

Internet Resource ProvidersPay-per-use

Optimisation archive

Intelligent Application Manager

Intelligent Resource Provider

Licenses and code

Session database

Design archive

OPTIONSSystem

Knowledge repository

Traceability

Visualization

Globus, Condor, OGSA

Ontology for Engineering,

Computation, &Optimisation and Design Search

CAD SystemCADDSIDEASProE

CATIA, ICAD

AnalysisCFDFEMCEM

ReliabilitySecurity

QoS

The future of design optimisationDesign Optimisation needs integrated services• Design improvements driven by CAD tools coupled to

advanced analysis codes (CFD, FEA, CEM etc.)• On demand heterogeneous distributed computing and data

spread across companies and time zones.• Optimization “for the masses” alongside manual search as

part of a problem solving environment.• Knowledge based tools for advice and control of process as

well as product.Geodise will provide grid-based seamless access to an intelligent

knowledge repository, a state-of-the-art collection of optimisation and search tools, industrial strength analysis

codes, and distributed computing and data resources