Transcript Energy Efficient Propulsion Systems

Energy Efficient Propulsion Systems
Execution
THERMALS
Optimization
DRAFTING
MFG
A
C
E
B
D
Simulation
CAD/CAM
Y1
J. Brent Staubach & Michael Winter
Pratt & Whitney
United Technologies Corporation
Energy & Computation
MIT
th
May 10 2006
Computing Power Will Fundamentally Change
How We Design Gas Turbines
Computer Speed
- 2x Every 18 months -
Network Speed
- 2x Every 9 months -
Tremendous
Growth
# Transistors (Ks)
Billion X Speed
• Transistor Scaling
• Manufacturing: Copper, SiGe,
• Parallelization: chip,
board, rack
• Quantum Computing
IBM & Intel
Expect Continued
Growth
Cost of a
Three
Minute
Phone
Call From
New York
To
London
Cost of
Sending
1012 Bits
Data Across
Country Has
Dropped From
$150,000 in 1970
To 12 cents
In 2000
by 2025
Hardware: 100,00X
Massive Parallel Grid
Computing, Assume
~10,000X
RELEASE THIS POWER ON DESIGN PROCESSES
• Review Current Manual Design Optimization Practices
• Computer Based Design & Key Enablers
• Future  New Design Paradigms; Less Time; Fewer People
System Engineering Process
Driven by Product Needs
Propulsion System Complexity Driving Need for More Robust Systems Engineering
Process and Tools
Variant-common F135
Turbomachinery
Integrated
Integrated TEC
TEC
&
& Augmentor
Augmentor
Lift Fan, Clutch,
& Driveshaft
3-Bearing
3-Bearing
Swivel
Swivel Duct
Duct
Roll
Roll Control
Control
Ducts
Ducts and
and Nozzles
Nozzles
LO
LO Axi-symmetric
Axi-symmetric
Nozzle
Nozzle
Controls & externals,
engine gearbox
Pratt
Pratt&&Whitney
Whitney
Rolls-Roy
Rolls-Royce
ce
Hamilt
Hamilton
onSSundstrand
undstrand
Propulsion has Become a System of Systems
Modern Gas Turbine Optimization Is An Exercise In
Managing Complexity
~ 80,000 PARTS
~5000 PART NUMBERS
~ 200 MAJOR PART NUMBERS
REQUIRING 3D FEA/CFD ANALYSIS
~ 5000-10,000 PARAMETRIC CAD
VARIABLES DEFINE MAJOR
PART NUMBERS
~ 200 MAN-YEAR ANALYTICAL
DESIGN EFFORT
~ 200 MAN-YEARS
DRAFTING / ME
EFFORT
Complexity Is Managed By Decomposing The Design,
Coordinating & Re-assembling via The SIPT/CIPT/IPT
SYSTEM
INTEGRATED
PRODUCT TEAM
CIPT
CIPT
CIPT
TURBINE
AERO
BURNER
TURBINE
STRUCTURES
AERO
CIPT
COMPRESSOR
AERO
TURBINE
STRUCTURES
BURNER
STRUCTURES
COMPRESSOR
STRUCTURES
TURBINE
COMPRESSOR
AERO
MECHANICAL
BURNER
MECHANICAL
COMPRESSOR
MECHANICAL
FAN
TURBINE
MFG.
AERO.
FAN
STRUCTURES.
FAN
MECHANICAL.
• IPTs ARE THE ORGANIZATIONAL MECHANISM THAT ENABLES A BALANCED
DESIGN - MANUAL MULTI-DISCIPLINARY DESIGN LOCAL OPTIMIZATION
Within Modules & Disciplines Sophisticated
Simulation Based Design Systems Have Evolved
Complex Designs Are Inherently & Brutally Iterative,
Bounded By Best Practice Rules . . . . . . . .
CAD
MODEL
PHYSICS
MODEL
DESIGN SPACE
WORK
INSTRUCTIONS
- NON LINEAR
- MULTI MODAL
- DISCONTINUOUS
- NOISEY
- HIGHLY CONSTRAINED
DESIGN
STANDARD
WORK
CRITERIA
VALIDATED
ANALYSIS
DECISION
PREFERRED
CONFIGURATIONS
ENGINEER MAY ITERATE 100s TO 1000s OF TIMES TO GET
SATISFACTORY RESULTS -- MANUALLY !
. . and Complex Designs Are Iterated Across
Disciplines & Organizations . . .
FEED FORWARD
IPT
PROCESS
CYCLE
1D AERO
FEEDBACK
.
COOLING
FLOWS
3D
STAR AERO
PROSTAR 3.00
23-SEP-97
VIEW
1.000
1.000
1.000
ANGLE
0.000
DISTANCE
6.549
CENTER
10.138
-0.554
0.776
EHIDDEN PLOT
HEAT X
DESIGN
PLATFORM
NECK
ATTACHMENT
DISK & SEALS
X
Y
Z
.
. . And Iterations Can Take Place Across The Globe
• OUTSOURCING
• INTER-DIVISIONAL
• PARTNERSHIPS
• CUSTOMERS
Iterations Are Simplified By Employing A
Range Of Fidelity
PRODUCT DEVELOPMENT PHASES
Concept
Initiation
0
Concept
Optimization
I
Preliminary
Design
2
KNOWLEDGE
DESIGN
SPACE
0D
1D
Detailed Design
INFORMATION
2D
3
Validation/
Certification
4
Airplane
Validation
Service &
Support
5
DATA
3D
4D
STAFFING
VTE
NEW
ENGINE
FIDELITY
• REQUIRES EXTENSIVE KNOWLEDGE TO JUDGE LOW FIDELITY MODELS
• STAFFING EXPLODES WITH FIDELITY: ANOTHER “CURSE OF DIMENSIONALITY”
Result Is Manual “Human” Based
Multidisciplinary Design Optimization – At Best
SYSTEM
SYSTEM
OPTIMIZATION
ENSURE CONFORMANCE
TO CUSTOMER NEEDS &
BUSINESS GOALS
COMPONENT
OPTIMIZATION
TEAMS - HUMAN INTERACTION
EXECUTE MANUAL MDO
PART
OPTIMIZATION
ISOLATED MULTI-FIDELITY
DESIGN SYSTEMS
Labor Intensive, Compartmentalized Design Process
That Relies On Teams, Management, & Procedures
Gains Can Be Made By Shifting From “Human” To
“Computer” Based MDO
“HUMAN” BASED
“COMPUTER” BASED
Program
IPMT
Program Standard Work Flow
0
Business Plan
Concept &
Venture
Definition
I
Integrated
Business
& Project Plan
Product/ Industrial
Plan Execution & FETT
II
III
Validate, Certify,
Deliver
IV
EIS, Operational
Service
& Support
WORKFLOW, RULES,
And DESIGN ITERATIONS
AUTOMATED WITHIN
And ACROSS SYSTEMS
& DISCIPLINES
V
System
CIPT
CIPT
CIPT
Select
Concept
Program
Launch
After
FETT
Release to
Production
0
Concept
Optim ization
I
Prelim inary
Design
2
Product Design
Procurement &
Initial Validation (FETT)
3
Validation/
Certification
4
Airplane
Validation
Service &
Support
5
IPT
Concept
Optim ization
I
Prelim inary
Design
2
Product Design
Procurement &
Initial Validation (FETT)
3
Validation/
Certification
4
Airplane
Validation
Service &
Support
5
I
Prelim inary
Design
I2
Product Design
Procurement &
Initial Validation (FETT)
3
Validation/
Certification
Airplane
Validation
Service &
Support
Concept
Initiation
3
4
IPT
1 1 1 1 1
2 2 2 2 2
3 3 3 3 3
4 4 4 4 4
IPT
1 1 1 1 1
2 2 2 2 2
3 3 3 3 3
4 4 4 4 4
IPT
NON-ANALYTICAL
2
IPT
NON-ANALYTICAL
1
IPT
NON-ANALYTICAL
LEVELS OF FIDELITY
Module
Concept
Initiation
Part
1 1 1 1
Concept
Initiation
Concept
Optim ization
2 2 2 2
2.5
4
5
Engineering Standard Work Flow
3 3 3 3
4 4 4 4
-- LABOR INTENSIVE --
SYSTEM
SUB-SYSTEM A
SUB-SYSTEM B
MANUAL WORK FLOW per PROCESS
MAPS
AUTOMATE WORKFLOW
MANUAL CAD/CAE MODEL BUILDING
& EXECUTION per STANDARD WORK
AUTOMATE MODEL BUILDING & EXECUTION
MANUAL EXPLORATION TO FIND
OPTIMAL DESIGNS THAT MEET
TECHNOLOGY LEVELS
AUTOMATE DESIGN EXPLORATION
Technologies Are Progressing To Enable Large Scale
Computer Based MDO
SYSTEM ANALYSIS
INTEGRATION FRAMEWORKS
PHYSICS
MODELS
COST
MODELS
CAD/CAM
MODELS
FIPER
CHALLENGES
-CYCLE BALANCE
-2ND FLOWS
-TRANSIENTS
ASSESSMENT
MODELING
STANDARD
WORK
COMPUTE
RESOURCES
MDO
ROBUST
PARAMETRIC
MASTER MODEL
COMPUTER BASED
MDO
NAVIGATE
THE VIRTUAL
DESIGN SPACE
PHYSICS
- SOLVE TURBULENCE
- MULTIDISCIPLINARY ANALYSIS (MDA)
- MATERIAL PROPERTIES
- PROBABILISTICS
COST
- MFG
- MAINTENANCE
- NEGOTIATED
GRID COMPUTING
CHALLENGES
-LARGE ASSEMBLIES
-TOPOLOGICAL
-GENERATIVE
- DIRECT MFG
CHALLENGES
-SECURITY
- POLITE COEXISTENCE
- FAULT TOLERANCE
Implementation Path:
Electronic Enterprise Engineering
LIBRARY OF
“WRAPPED” TOOLS
INTEGRATION
FRAMEWORK
ELECTRONIC
PROCESS MAPS
ELECTRONIC
IPT
COMPUTER BASED
OPTIMIZATION
SYSTEM
OPTIMIZER
A
IPT 1&2
IPT 1
B
A
A
B
IPT 2
C
G
C
B
B
D
E
C
CERTIFIED
EMBEDDED
KNOWLEDGE
CONTROLLED
E
D
E
F
F
G
G
VALIDATED
B
C
IPT 3
G
INTEGRATE
THIRD PARTY
& LEGACY TOOLS
INDUSTRY
ACCEPTED
COMMERCIAL
TOOLS
INTEGRATED
INTO
ELECTRONIC
PROCESS MAPS
& ASSOCIATED
WITH WORK
INSTRUCTIONS
OPTIMIZER
A
OPTIMIZER
C
A
C
IPT 3
D
E
F
G
WORK FLOW
MANAGEMENT
AUTOMATE
ITERATION
COLLABORATIVE
ENGINEERING
SATISFY
CRITERIA
SECURE B2B
GRID
COMPUTING
Large Scale Computer Based MDO Is Already
Practical
3D Aero-Vibratory Shape Optimization Of A Cooled Turbine Airfoil
(Single Row RANS CFD, Cooled UG Parametric Model, 3D ANSYS Vibes)
AIRFOIL
SHAPE
3D AERO
CFD
PARAMETRIC
CAD
MESH
OPTIMIZER
CAMP BELL DI AGRAM
STRESS
MODE 1
EFFICI ENCY
MODE 3
MODE 4
Aero Xsections
0.5
0.4
Area
MODE 2
VIBRATORY
ANALYSIS
0.3
Initial
0.2
Iteration 515
0.1
0
AreaS1 AreaS2 AreaS3 AreaS4 AreaS5
Large Scale Computer Based MDO Is Already
Becoming Practical
3D Shape Optimization Based On Hybrid Genetic Algorithm & Rule System
(3D RANS Multi Row CFD, Population Size 80, Total Runs 2400, Run Time 48 hrs on 40CPUs)
DELTA TURBINE EFFICIENCY
LOSS CONTOURS
150 VARIABLES
15 CONSTRAINTS
0.6
0.4
LOSS CONTOURS
Discovered “bowed” rotor
To control tip leakage
Vortex
0.2
0.0
0
10
20
GENERATION
30
Efficient Scalable System Problem Formulations
Are Becoming Understood For Gas Turbine Design
REPRESENTATION
PROBLEM FORMULATION
ALGORITHMS
MIN:
MANUFACTURING COST
ST:
DOC+I, RANGE, NOISE, EMISSIONS
VARIABLES: SYSTEM DISCRETE & CONTINUOUS
CONFIGURATOR
DISCRETE PARAMETERS,
--- Nspool, GEAR, ROTATION, MIXED, MOUNTS, etc.
CYCLE
T RIAL
A
B
C
D
E
F
G
1
2
3
4
5
6
7
8
1
1
1
1
2
2
2
2
1
1
2
2
1
1
2
2
1
1
2
2
2
2
1
1
1
2
1
2
1
2
1
2
1
2
1
2
2
1
2
1
1
2
2
1
1
2
2
1
1
2
2
1
2
1
1
2
RESPONSE SURFACE
MODELS
CONTINUOUS PARAMETERS
-- BPR, FPR, OPR, WS, CET, Wc, RPMi, etc
ROBUST
DESIGN
$
WT
FULL
ENGINE
MODEL
FLOWPATH
HIGH FIDELITY PARTS
DESIGN
OF
EXPERIMENT
SFC
T
CE
N2
CE
T
VEHICLE ANALYSIS
(0D, 1D, 2D, 3D)
BP
R
COMPRESSOR (i)
BURNER (i)
TURBINE (i)
MIN: COST LOCAL
ST: JOB TCKT & SW
VAR: RADI & AIRFOILS
MIN: COST LOCAL
ST: JOB TCKT & SW
VAR: RADI & LENGTHS
MIN: COST LOCAL
ST: JOB TCKT & SW
VAR: RADI & AIRFOILS
MEANLINE
MEANLINE
MEANLINE
MIN: WEIGHT & COST
ST: JOB TCKT & SW
VAR: MECHANICALS
MIN: WEIGHT & COST
ST: JOB TCKT & SW
VAR: MECHANICALS
MIN: WEIGHT & COST
ST: JOB TCKT & SW
VAR: MECHANICALS
LIFE
LIFE
WEIGHT
COST
LIFE
WEIGHT
COST
WEIGHT
COST
W
c
R
FP
NUMERICAL
OPTIMIZATION
Y1
x2
Xi+1 = Xi - ifi
x1
APPROXIMATION
TO HIGH FIDELITY
Will Enable New Design Paradigms
CUSTOMER NEEDS
UNDERSTAND THE FUTURE
CREATE TECHNOLOGY
ENGINEERS
COMPUTER BASED DESIGN
RUN 24/7 365 DAYS
A YEAR
CONTINUOUS
DETAILED DESIGN
IMPROVE MODELS
RE-FORMULATE PROBLEM
SOLVE ALL POSSIBLE
APPLICATIONS @
TECHNOLOGY
READINESS LEVEL
UPGRADE COMPUTER
BASED DESIGN “MACHINE”
CUSTOMER REQ. EXCEED TECHNOLOGY
LESS TIME
FEWER PEOPLE
Powering Change………….Powering Freedom