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GE Global Research

______________________________________________________________

2D/3D CFD Design OptimizationUsing the Federated Intelligent Product

Environment (FIPER) Technology

R. Sampath, R.M. Kolonay and C. Kuhne

2002GRC202, August 2002

Class 1



Copyright © 2002 General Electric Company. All rights reserved.



GE Global Research

Technical Report Abstract Page

Title 2D/3D CFD Design Optimization Using the Federated Intelligent Product Environment(FIPER) Technology

Author(s) R. Sampath Phone (518)387-6401R.M. Kolonay 8*833-6401C. Kuhne*

Component Advanced Mechanical Technologies, Niskayuna

ReportNumber 2002GRC202 Date August 2002

Number

of Pages 8 Class 1

Key Words MDA/MDO, FIPER technology, Turbine Aerodynamics, Response-SurfaceMethodology

This paper describes the application and implementation of an aircraft engine turbine bladeaerodynamic design optimization problem using a response-surface based methodology withinthe Federated Intelligent Product EnviRonment (FIPER) framework. The design problemconsidered is a shape optimization problem, in which, important blade shape parameters such asthe stagger angle, trailingedge thickness, leading-edge radius, over-turning and wedge angle arechosen such that an optimal design is achieved. In this work, the criterion for optimality is takenas the blade-row efficiency. The approach used in this work to solve this optimization problem is

to start with a baseline design, perturb the variables within a given range of validity, conduct adesign-ofexperiments (DOE) using an automated, distributed analysis DOE tool developed andgenerate a response-surface. The resulting response surface is used along with a gradient-basedoptimizer to calculate the optimal solution. The core of this paper describes in detail the FIPERarchitecture and addresses specific implementation issues in the context of solving the aboveshape optimization problem.



AIAA-2002-5479

2D/3D CFD DESIGN OPTIMIZATION USING THE FEDERATED INTELLIGENT

PRODUCT ENVIRONMENT (FIPER) TECHNOLOGY

Rajiv Sampath, Raymond M. Kolonay+

GE Global Research Center

Schenectady, NY 12301

Craig M. Kuhne

GE Aircraft Engines

Cincinnati, OH 45215

ABSTRACT

This paper describes the application and

implementation of an aircraft engine turbine blade

aerodynamic design optimization problem using a

response-surface based methodology within the

Federated Intelligent Product EnviRonment (FIPER)

framework. The design problem considered is a shape

optimization problem, in which, important blade

shape parameters such as the stagger angle, trailing-

edge thickness, leading-edge radius, over-turning andwedge angle are chosen such that an optimal design is

achieved. In this work, the criterion for optimality is

taken as the blade-row efficiency. The approach used

in this work to solve this optimization problem is to

start with a baseline design, perturb the variables

within a given range of validity, conduct a design-of-

experiments (DOE) using an automated, distributed

analysis DOE tool developed and generate a

response-surface. The resulting response surface isused along with a gradient-based optimizer to

calculate the optimal solution. The core of this paper

describes in detail the FIPER architecture and

addresses specific implementation issues in the

context of solving the above shape optimization

problem.

INTRODUCTION

Gas turbine engine development is a highly coupledmultidisciplinary process involving several

disciplines such as aerodynamics, solid mechanics

and heat transfer. In a market with ever-increasing

demands in terms of reduced design cycle time,

reduced life cycle costs and performance

improvements turbine engineers can no longer

competitive market. The need of the day is a truly

digitized design process that can provide true

concurrency between design and manufacturing. In

order to address these challenges, GE has teamed up

with Goodrich, Parker Hannifin, Engineous Software,

Ohio University, Stanford University and OAI to

develop a concurrent engineering design system as a

part of a four-year advanced technology program

supported by the National Institute of Standards and

Technology (NIST). This system referred to as the

“Federated Intelligent Product EnviRonment”

(FIPER) strives to drastically reduce design cycle

time and time-to-market by intelligently automating

elements of the design process in a linked, associative

environment, thereby providing true concurrency in

the design process. Such an approach allows for

distributed design of robust and optimized products

by employing an open, network-centric, web-based

environment1

(Fig. 1).

As an application of the FIPER system, here, a novel

implementation of a turbomachinery blade design

system is discussed. The design problem being

considered is a shape-optimization problem in which

the task is to optimize the blade cross-section by

varying shape parameters such as the stagger angle,

trailing-edge thickness, leading-edge radius, over-

turning and wedge angle in order to maximize the

blade-row efficiency. In the main part of this paper,this design problem is discussed along with the

techniques used to solve this problem within the

FIPER framework.

BACKGROUND

FIPER draws extensively on several prior GE



AIAA-2002-5479

projects like the top-down Product Control Structure

(PCS), Fig. 2, and the Linked Model Environment

(LME), Fig. 3, form the backbone of the geometry

aspects of FIPER. Since these projects have been

described in previous publications2,3

, only key

the design and manufacturing process, so that at all

times participants in the design and manufacturing

process have access to the same valid geometry

information. Taking advantage of the

UNIGRAPHICS®

WAVE top-down geometry

linking capability, a PCS for turbine engines was

developed, specifying interfaces between the different

engine subsystems and giving control of theseinterfaces to the groups responsible for system-level

design. Each subsystem group owns its own interfaces

between individual components.

Understanding that different disciplinary engineering

design and analysis tools require geometry at

different levels of detail, the concept of a "context

model" was introduced. The context model represents

a disciplinary context-specific, yet fully associative,

"view" of the master model geometry. Feature

suppression is extensively used in context models.

For example, a bolt hole, which is important for the

stress analyst, may not be required for a thermal or

CFD analysis and therefore would be suppressed in

the thermal/fluids context model. These context

models are then linked to the respective disciplinary

analysis tools, e.g. FEA, CFD, cost, producibility,

etc, in the LME , see Figure 3.

FIPER extends the concept of the geometric Master

Model with the introduction of the “Intelligent Master

Model” (IMM). Intelligence is added through

extensive use of Knowledge-Based Engineering

(KBE) systems in the design process. Initially, rules

for geometry generation were captured separately

Figure 1: The FIPER Project



AIAA-2002-5479

Figure 3: Linked Model Environment

FIPER ARCHITECTURE

Traditionally MDA and MDO efforts have led to

systems that are monolithic, hard-wired systems, that

tend to provide only limited capabilities for

distributed computing and collaboration of variousdesigners located at spatially disjoint facilities

5.

Moreover, they rarely support a plug-and-play type

architecture where one analysis or simulation tool can

easily be substituted by another essentially fulfilling

the same function, with either a faster newer method,

or potentially at a higher level of fidelity. Today, the

web offers the vehicle for efficient data transfer

across the globe, but its capabilities are so far only

beginning to be utilized by the engineering and designcommunity. This is the case even though much of

engineering development in a project these days

occurs at spatially different locations. FIPER

addresses this deficiency by providing a network-

centric infrastructure supporting distributed

engineering services in a Peer-to-Peer paradigm.

FIPER federates processes, tools, methods,

documents, knowledge bases, and data into a

dynamic, distributed environment with its underlyingservices. Some services are generic (for example,

optimization algorithms or knowledge-based

systems), and thus, are not associated with a

particular IMM context but are globally available

within FIPER. Members of a federation agree on

basic notions of administration, identification, and

FIPER is composed of various service providers; any

of these can come and go and the system can respond

to changes in its environment in a reliable way

(network centricity). The services connected to

FIPER discover each other and cooperate in a

distributed environment (service centricity). Users

can request to use multiple services and check the

status of their submissions in different locations

through HTTP portal with thin web clients (web

centricity).

The three neutralities FIPER deploys are location

neutrality, protocol neutrality, and implementationneutrality, Figure 4. Services need not be co-located;

they are discovered and then join the federation,

which simplifies management of the entire software

environment (location neutrality). In addition, the

way clients communicate with a service provider is

not essential. A service proxy can use any protocol,

for example, Remote Method Invocation (RMI), IIOP

or even a plain socket communication. Clients are not

aware of what protocols are used and where theimplementations reside (protocol neutrality).

Furthermore, the clients who use the FIPER services

do not need to know what languages are used and

how a service is implemented (implementation

neutrality). In all, FIPER provides accessibility

through a web centric architecture, self-manageability

using federated services, scalability via network

centricity, and adaptability with the power of plug-

and-play capability.

Proxy ProxyClientService

Provider

FIPER

Federation of Services

Proxy

discover

and join

register

and publish

protocol

(protocol

neutrality)

(location

neutrality)

(implementation

neutrality)



AIAA-2002-5479

A set of components that provides the

infrastructure for federating services in a

distributed environment

A programming model that supports the

production of reliable distributed

environment

The functionality to register services and

resolve service requests

Java and the emerging JiniTM technology are at the

heart of this system. Services are found and resolved

through a "lookup" service (Figure 5). New servicesare added to the look-up service by a process called

"discover and join". When plugged into the

environment, the service first uses a discovery

protocol to locate an appropriate lookup service and

then joins, or registers, with the lookup service.

Services can communicate with any other generic

service in the entire federated product space. In the

case of FIPER, this is achieved by an IMM context,

user, or service posting a need which is resolved by alookup service. The lookup service connects the

requesting entity to an entity that has the functionality

to supply the service. Figure 5 illustrates this in a

given space with four services; CAD, KBE,

Optimization and Robust Design, and the Simulation

Engine. Each service provider must be Java wrapped

in order to join the federation, but it can have its own

framework of execution. A service could be based on

RMITM, CORBATM, Java Native Interface (JNITM),

Microsoft COMTM /DCOMTM, or even simple socket

connection.

FIPER. For the purpose of the NIST project FIPER

focuses on the services necessary for the design and

manufacture of a product. Specifically, the domains

of Design for Six Sigma/ Multidisciplinary

Optimization (DFSS/MDO), CAD/KBE, Engineering

Analysis & Sensitivities, Pre/Post processing, and

Data Repositories are addressed. Services are

provided by a service provider (which is typically a

computer program, for example, an engineering

analysis package, that has been wrapped to operate

within the FIPER environment). A service provider

can offer multiple services, and the same service can

be offered by multiple service providers. The FIPERtask submitted by the client is matched against the

services offered by the various service providers, and

the proper service is selected based on service

attributes.

Several engineering service providers are currently

implemented in the FIPER environment such as

UNIGRAPHICS®

for a variety of CAD and geometry

services, PATRAN

®

and ICEM

®

primarily for finiteelement and CFD meshing services, ANSYS®

for

finite element meshing, boundary condition, analysis,

and post processing services. Several in-house GE

proprietary codes are used as service providers for

addressing the deterministic as well as probabilistic

design of turbomachinery components.

Members of a federation agree on the basic notions of

administration, identification, and policy. The

resulting federation provides the simplicity of access,ease of administration and support for sharing

services provided by a large monolithic system, while

retaining the flexibility, and control provided by a

plug-and-play architecture.

Clients define and submit their jobs via web

browsers. A FIPER service manager then dispatches

each job into tasks. These tasks (or exertions) can be

executed sequentially, in parallel, or combination of

both in the FIPER environment, depending on their

input/output data dependency. If a parallel strategy is

chosen, tasks are dropped into spaces (by using

JavaSpacesTM, for example) for distributed

computation. Each service provider agent, if present,

picks up appropriate tasks and generates results and

t th b k t th O th th h d



AIAA-2002-5479

also allows for real-time monitoring and editing of

jobs submitted through the system. This allows the

user the flexibility to modify a submitted job during

any stage of its execution. This is particularly

important in multidisciplinary optimization problems,

wherein, there is greater probability for user errors or

service failures. If such a situation arises, the FIPER

job monitor would be very effective in

reviewing/editing the failed task and resuming the

execution of the optimization problem.

TURBINE BLADE AERODYNAMIC DESIGN

The design of a new aircraft engine from scratch is anextremely rare occurrence in today’s competitive

environment. “New” designs are most often derived

from existing engines. Derivative engine design is

accomplished by first scaling from an existing design,

then optimizing this derivative geometry on the basis

of a list of design criteria. Modifications from this

scaled geometry are made as required to meet the

design detailed criteria, such as component life and

aerodynamic performance.

As an application of the FIPER system, a turbine

blade aerodynamic design optimization problem is

presented. Blade shape parameters (see Fig 6.) such

as the stagger angle, trailing-edge thickness, unguided

turning, over-turning and wedge angle are chosen

such that the blade-row efficiency is maximized.

Blade row efficiency defines the overall aerodynamic

performance of the turbine blade-row and is an

indicator of the performance of the engine as a whole.

blade is considered (and this implies that 3D losses

are accounted for in the aerodynamic analysis). The

process map used in the 2D/3D CFD based design of

the blade is illustrated in Fig. 7. As described, the

first step in the design process is to start with a scaled

airfoil design. This design data is copied to the

optimization workspace to be modified by the design

process. This is followed by an update process in

which important blade shape parameters are modified

to enforce blade shape change. This is followed by

the execution of a blade generation/stacking program

in order to generate the appropriate blade shape.

Once the blade geometry is defined, the next step isthe generation of a 2D/3D grid. The 2D/3D grid is

used in a corresponding CFD analysis to evaluate the

performance of the blade design. This entire loop is

executed for each DOE run. The outputs from this

DOE are used to generate a response surface to

optimize the design. In this work, due to the non-

linear nature of the transfer function, a 2nd

order

central-composite design6

augmented with a one-

factor-at-a-time (OFAT) DOE design close to theoptimal point is employed. The upper bounds, lower

bounds, variable limits are chosen in order to ensure

an approximate transfer function that was within the

required accuracy bounds.

Figure 8 shows the internals of the 2D/3D CFD

design tool developed within the FIPER system. As

described in this figure, five major service providers

were developed to automate the 2D/3D CFD based

optimization process map shown in Fig. 7. A database

manager service to manage data transfer between the

aero database containing the scaled airfoil data and

the FIPER system. A morphing service to generate

the morphed or mapped geometry for each DOE run.

This service updates the airfoil shape parameters

(such as stagger, wedge angle, etc), regenerates the

airfoil design sections and then stacks the blade

sections to generate the 3D blade. A gridding or

meshing service provider is developed to generate the

2D/3D blade-to-blade grid. GE in-house application

is the service provider for the 3D gridding. Another

GE proprietary code is the service provider for the

2D gridding. A blade-to-blade CFD analysis service

provider is developed to execute the 2D/3D blade-to-

bl d CFD l i H i t ll d l d



AIAA-2002-5479

Copy baseline design to

optimization workspace

Update airfoil shape

parameters

Morph the airfoil

sections

Stack the airfoil sections

to generate 3D airfoil

Generate 2D/3D grid

Execute 2D/3D CFD

Analysis

Calculate optimization

objective function

Evaluate design

constraints

Generate

DOE Table

Generate Response

SurfaceOptimizer

Figure 7: 2D/3D CFD Optimization Process Map

Figure 8: Integration of 2D/3D CFD Design

Process Using FIPER Architecture

All services are published at a remote HP

workstation. Emerging JavaSpacesTM technology is

used to develop a distributed DOE execution

environment. In particular, a FIPER space is created

in which the various DOE runs are dropped as tasks.

Depending on the availability of the various service

providers (multiple instances of these service

providers were published across the network), the

tasks are picked up by the various providers and are

executed and the results attached to the context model

and sent back to the user for review. After execution,

each service sends back a detailed report which can

be perused by the experienced engineer to make

appropriate design decisions. In order to speed-up theconvergence of the CFD analysis the flow results

from the baseline case were used as the initial starting

flow solution for the various DOE runs. Fig. 9 shows

the initial and optimal blade profiles calculated using

this system. This case corresponds to the 1st

rotor in a

2-stage high-pressure turbine. (Note: The turbine

blade example considered herein is strictly a

caricature of a real turbine blade problem; no

information contained in this paper is representativeof turbine blades produced by GE. Also, due to

restrictions dealing with sharing proprietary

information, only normalized quantities will be

presented in this paper). All the angle blade shape

parameters (stagger, wedge, overturning) were varied

from the baseline values by +/- 5 degrees while the



AIAA-2002-5479

the nominal design as the starting flow solution (this

technique was employed to accelerate the

convergence of the CFD solution), the 3D-CFD

design took close to 45 minutes per DOE iteration

while the 2D-CFD case took about 10-15 minutes per

DOE iteration. All the DOE runs were executed in

parallel on 5 HP servers distributed across the

network. As an extension of this work, currently CFD

solution of multiple blade rows is being considered.

This will allow the designers to consider the entire

stage performance as the objective function rather

than limit themselves to blade-row efficiency

estimates.

Normalized Stagger = 1.0

Normalized leading edge radius = 1.0Normalized trailing edge radius = 1.0

Normalized over turning = 1.0

Normalized wedge angle = 1.0

Normalized blade row efficiency = 1.0

Normalized Stagger = 1.1208

Normalized leading edge radius = 1.009

Normalized trailing edge radius = 0.971

Normalized over turning = -0.4548



Figure 9: Initial and Optimal 3D Blade Designs



AIAA-2002-5479

Normalized stagger = 1.0



Normalized over turning = 1.0



Normalized stagger = 1.140



Normalized over turning = -0.0369



Figure 10: Initial and Optimal 2D Blade Designs

CLOSING REMARKS

A robust network-centric MDA/MDO environment

has been developed and applied to an engineering

design problem. The concepts of an engineering

analysis code as a service provider and of a “FIPERcontext” as a generic means of supplying problem-

specific information to the generic service provider

have been implemented. The FIPER framework has

been applied to a number of sophisticated engineering

and design problems, one of which, the aerodynamic

analysis and CFD based design of a turbine blade,

forms the basis of this work. The framework takes

advantage of a number of key technologies for

distributed network-centric computing, primarilyJINITM, RMITM, and JavaSpacesTM.

The user has the ability to access the system via a

web browser from anywhere in the world to submit

jobs, check the status of jobs, or to review results.

The system also provides the user the capability to

JavaSpacesTM technology. Email notification after the

execution of jobs provides URL links to the

significant output which the user can study through a

web browser, from anywhere in the world.

Currently, the FIPER team is expanding the capability

to do system-level optimization studies wherein

disciplines such as aerodynamics, heat transfer and

mechanical analysis are all coupled. The results from

these efforts will be presented in subsequent

presentations.

Acknowledgments

This research is jointly funded through the National

Institute for Standards and Technology-Advanced

Technology Program (NIST-ATPTM

) and the General

Electric Company. The authors would like to

acknowledge this support, as well as the valuable

input from the whole FIPER team. In particular, the

authors would like to acknowledge the help and

valuable input from Shashi Talya, Anurag Gupta,

Sanjay Goel, Rohinton Irani and Michael Sobolewskiin developing the CFD-based optimization tool within

the FIPER system.

References

[1] Federated Intelligent Product Environment,

Technical Proposal, OAI, General Electric,

Goodrich, Parker Hannifin, Engineous Software,

Ohio University, Stanford University, April,

1999.

[2] Röhl P.J.; Kolonay R. M. et al.: A Federated

Intelligent Product Environment. Proceedings,

8th

AIAA/USAF/NASA/ISSMO Symposium on

Multidisciplinary Analysis and Optimization,

Long Beach, CA, September 2000.

[3] Rohl, P. J.; Kolonay R. M. et al.: Intelligent

Compressor Design in a Network-Centric

Environment. Proceedings, ASME Computers in

Engineering Conference, Pittsburgh, PA,

September 2001.

[4] Intent User Manual, Heide Corporation,

Medfield, MA, 2000.

[5] Rohl, P. J., A Multilevel Decomposition

Procedure for the Preliminary Wing Design of a

High-Speed Civil Transport Aircraft, Doctoral

Th i G i I tit t f T h l Atl t



R. Sampath 2D/3D CFD Design Optimization Using the Federated Intelligent 2002GRC202

R.M. Kolonay Product Environment (FIPER) Technology August 2002

C. Kuhne

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