© geodise project, university of southampton, 2001-2003. cfd-based shape optimisation using...

© Geodise Project, University of Southampton, 2001-2003.http://www.geodise.org/

CFD-based Shape Optimisation Using Geodise ToolkitsApplication Demo of Grid Technologies in Engineering Design Optimisaiton

Wenbin Song, Hakki Eres and Graeme Pound Southampton e-Science Center

12 May, 2003


CFD-based shape optimisation using Geodise toolkits

• Introduction

• Overall Structure, Dataflow and Geodise toolkits

• Modelling and Simulation

• Parametric CAD modelling

• Solving the flow problem

• Optimisation using DOE and RSP methods

• Archiving of metadata and files

• Summary and Future work



Introduction

• CFD is both computation and data intensive• Automation and integration is the key• Grid provides both the environment and technology• Consistent and open standard interfacing provides easy integration of various tools across platforms• Matlab provides a flexible scripting environments

Application demo

Motivation

• Shape optimisation of 3D Engine intake• Integration of CAD, Meshing tool and Solver• Design of experiments and Response surface modeling• Search strategies



Nacelle 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

Negative Scarf InletConventional Inlet

0 1 2

Total Pressure Recovery (TPR) = 1

2pt

pt


Globus Middleware

Matlab EnvironmentOPTIONS

Data Repository

FLUENT MODELFluent Journal file (.jou )Model Metadata

GAMBIT MODELGambit Journal file (.jou )Model Metadata

CAD MODELProEngineer Part file (.prt )Input Parameter file (.inp)Command Script file (.txt)

Geodise Computation and Database Toolkits

.NET Webservice to Condor


Next


Parametric Geometry generation - .NET Webservice interface to Condor

1. Generate a proxy using user’s credentials;2. Retrieve the ProEngineer Model files from repository;3. Submit ProE job(s) to Condor pool using grid_submit;4. Poll submitted jobs;5. Retrieve results



Procedure:

• Generate a proxy using user’s credentials;• Retrieve the Gambit Journal file from repository;• Submit Gambit jobs to Grid-enabled Computing server;


Methods adopted in the mesh generation

Mesh Generation – using Grid-enabled Computing Servers (1)

• automatic mesh generation is essential• relying on the highest level entities in the model (face in the

nacelle geometry);• decide node spacing based on relative length of the edges in a

particular part or the whole model• size functions used to control local mesh pattern• 3D boundary layers




1. Determine the ref_edge_node_spacing (D):Choose ref_edge_node_spacing

If (ref_edge_node_spacing > shortest_edge)ref_edge_node_spacing (D) = shortest_edge;

End2. Determine the nominal edge_node_spacing for each edge based on the

following formula:if pow(2,i)*D<edge_length<pow(2,i+1)*D

norm_edge_node_spacing = alpha1*D*pow(I,alpha2)end

3. Determine the edge_node_spacing at the end vertex for each edge based on the nominal edge_node_spacing of all edges connected to it at that vertex, in order to obtain smooth mesh for connected large/short edges;

4. Apply boundary layers to the faces;5. Mesh the edge using double-sided, asymmetric mesh;6. Apply vertex-centered size function to faces;7. Mesh the faces;8. Mesh the volumes9. Specify boundary types and export the mesh in required format


Solving the flow problem on Grid-enabled computing resources (1)

1. Generate a proxy using user’s credentials;2. Retrieve the Fluent journal file from repository;3. Submit Fluent jobs to Grid-enabled computing resources;4. Poll the submitted jobs;5. Retrieve results


1. Nacelle Placed in a pressure far-field box;2. Extended to the far-field from maximum exterior radius;3. Pressure outlet just behind the fan exit face;4. Cruise condition (Mach =0.85, );5. Symmetry conditions applied

Boundary conditions

o4



Solving the flow problem on Grid-enabled computing resources (2)


Scarf angle

Axi

al o

ffse

t

DoE using OPTIONS


Optimisation using DoE/RSP methods – workflow and results

Problem definition

Design of Experiment

Response surface modelling

Optimisation on Response surface

Validation



Validation run using Fluent.com


Fluent Remote Simulation Facility (RSF)

• All data is fully backed-up, secured, and protected using 128 bit encryption techniques

• Managed by experts in the field of Computational Fluid Dynamics and optimized for implementation on high performance computational systems

• Global access to the facility on a 24x7 basis from a desktop browser• Continuous monitoring of all operations for secure operation• Full 128 bit data communication encryption• HTTPS access with full SSL technology• Optional VPN and dedicated communication connections• Optional "private" dedicated systems and services• Modular, scalable, reliable, secure• Redundant internet connections• Secure monitoring, backup, back office connections• https://rsolve.fluent.com/

Features:


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Job Details


Job Logs


Summary

• Design automation using Grid-enabled Matlab environment;

• Parametric Modelling methods;

• Optimisation using DoE/RSP methods

Future work

• Computation Monitoring, Steering Methods in Optimisation

• Multi-objective Optimisation

• Multi-disciplinary Optimisation (CFD, Structure, cost modelling, etc)

• Optimisation as Grid services


© geodise project, university of southampton, 2001-2003. cfd-based shape optimisation using...

Documents

geodise project

geodise toolkits modelling

geodise toolkits methods

university of southampton

txt geodise computation

flow problem optimisation

gambit jobs

proengineer model files