Computational Models in the Materials World - We are nearly there….
David Furrer Pratt & Whitney
Rollie Dutton Air Force Research Laboratory
Not Subject to the EAR per 15 CFR Part 734.3(b)(3) ©2013 United Technologies Corporation
AIAA Conference
April 10, 2013
Boston, Mass.
Engineering Materials Today
• Materials are critical for every engineered product
• Traditionally materials were developed by trial and
error processes, separate from application
requirements
• Materials are currently defined by static
specifications based on empirical data Design
Mfg Mtls
• Challenge and opportunity of
Computational Materials Engineering
is the linking of Materials,
Manufacturing Processes and
Component Designs No Technical Data per the EAR and ITAR ©2013 United Technologies Corporation
2
Thrust Specific Fuel Consumption (lb/hr/lb)
707 (JT3C)
B727 (JT8D)
MD-80 (JT8D-200)
747 (JT9D)
777
PW4000 A380
737 A320
(V2500)
Turbojet
Low Bypass Turbofan
BPR 1.1 to 1.8
Engine Certification Date
767
PW4000 94”
High Bypass Turbofan
BPR 4.5 – 5.5 BPR > 6
Evolution of System Efficiency
1950 1960 1970 1980 1990 2000 2010
©2013 United Technologies Corporation
3 Not subject to the EAR per 15 C.F.R. Chapter 1, Part 734.3(b)(3)
Propulsion History
J58 Powered SR-71
Propulsion Innovations Enabled by Materials and Processing Technology
DS blades, Cast &Wrought
disks, 1st Gen Thermal
Spray TBC coatings
1st Gen SC blades, 1st Gen
PM disk, 1st Gen EB-PVD
TBC
2nd Gen SC blades, Aluminide
coatings, 2nd Gen PM/fracture
tolerant disk
LFW Ti IBR, Dual Property Ni
Disk, TBC blades, Burn resistant
Ti, CatArc Metallic Coatings
Dual Property 3rd Gen PM disk,
High modulus blade, 2nd Gen TBC coating
4th Gen PM disk alloy,
Hybrid metallic airfoils,
3rd Gen TBC
F100 Powered F-15 / F-16
F119 Powered F-22 F135 Powered F-35
JT9D powered Boeing 747
PW1133G Powered A320neo
©2013 United Technologies Corporation
4 Not subject to the EAR per 15 C.F.R. Chapter 1, Part 734.3(b)(3)
Ni Superalloy Turbine Airfoils: Significant
Advances in Alloys and Casting Processes A
lloy T
em
pera
ture
Capabili
ty
(oF
)
Base
1960 1970 1980 1990
50
100
150
200
250
2000
Equiaxed
Columnar
Single
Crystal
PWA 1426
PWA 1484 PWA 1487
PWA 1497
PWA 1422
PWA 1480
MM247 B1900
IN100
©2013 United Technologies Corporation
5 Not subject to the EAR per 15 C.F.R. Chapter 1, Part 734.3(b)(3)
Key Technology Advances for Turbine Airfoil Materials
Time
200
400
600
800
1000
1200
1400
1600
Turb
ine T
em
pera
ture
Incre
ase
Base
1800
Convective Cooling
Film Cooling
Thermal Barrier Coatings
Advanced Casting
Material Technology
ICME is another technology to “break the curve”
©2013 United Technologies Corporation
6 Not subject to the EAR per 15 C.F.R. Chapter 1, Part 734.3(b)(3)
Materials & Product Engineering
Mechanical Properties = fn (chemistry and
microstructure)
Microstructure = fn (chemistry and processing)
Processing = fn (component geometry)
Design
Mfg Mtls
Materials, Manufacturing Methods
and Component Design are
Strongly Coupled
ICME -Integrated Computational Materials Engineering
©2013 United Technologies Corporation
7 No Technical Data per the EAR and ITAR
MIL-HBK-5H
What a Tensile Test Looks Like…..
To a Materials Engineer To a Mechanical Engineer
©2013 United Technologies Corporation
8 No Technical Data per the EAR and ITAR
Properties
True material capability
and property distributions
are controllable and
reproducible; not “random
variability”.
Properties are a fn
(chemistry, microstructure,
stain, cooling rate, etc.);
i.e. pedigree.
From D.Furrer,
OPTIMoM Conf., 2010
Materials Capability Definitions
Materials properties are path dependent and are often
“location-specific”. Engineering specifications often treat
entire material volume as single, homogeneous property
capabilities. Modeling and simulation can help enhance
component property capability definitions
©2013 United Technologies Corporation
9 Not subject to the EAR per 15 C.F.R. Chapter 1, Part 734.3(b)(3)
Traditional Materials Definitions
• Design Curves – Empirical; Data Driven
• Specifications
• Prints Notes
• Fixed Process Requirements
Requires Defining Material Equivalency and Methods to
Differentiate Material of One Control Pedigree from Another
©2013 United Technologies Corporation
10 No Technical Data per the EAR and ITAR
The Challenge: Need Models and Computational Infrastructure
Current materials definitions for design limit design
flexibility and final component capabilities
There is a need for:
Model-Based Materials Definitions
Goal is prediction and control of capabilities
Model-based material definitions enable location-
specific prediction, analysis and optimization
Model-based materials definitions enable greater
material, process and component definitions
©2013 United Technologies Corporation
11 No Technical Data per the EAR and ITAR
ICME Involved Linkage with Other Discipline Activities
Material Definition
MfgProcessDefinition
Component Modeling &Prediction
LifingAnalysis
Life-CycleCostAnalysis
Mechanical Design Customer
Requirements
Product
Definition
Holistic Design
Optimization
©2013 United Technologies Corporation
12 No Technical Data per the EAR and ITAR
Materials Technology Enablers Computational Models and Advanced Data Management
Spec Min
LCL
UCL
Failure below control limit Failure due to trending
X X
Goal is prediction and control of capabilities
Properties
Predicted Material and Component
Properties
Traditional empirical property
measurement and analysis migrating to
materials models
Properties
Capture of developmental and production data to
support model development
Predicted Material Properties
Predicted Property Variability
Pro
pe
rty
Serial Number
©2013 United Technologies Corporation
13 Not subject to the EAR per 15 C.F.R. Chapter 1, Part 734.3(b)(3)
Material & Process Modeling Goals
• Develop Simulation Tools that Emulate Reality
• Develop Analytical Tools that Provide Insight in
Material - Process - Property Relationships
• Implement Tools for Design and Manufacturing
Benefits
• Model-based Decisions
• Tangible Improvements obtained based on
Decisions
©2013 United Technologies Corporation
14 No Technical Data per the EAR and ITAR
Holistic Integration: Digital Thread
Design
Mfg Mtls
Example of Integrated Computational Materials & Mfg Engineering
DataMechanical Properties
Chemistry
Microstructure
Meta-Data
DataMechanical Properties
Chemistry
Microstructure
Meta-Data
DataMechanical Properties
Chemistry
Microstructure
Meta-Data
DataMechanical Properties
Chemistry
Microstructure
Meta-Data
DataMechanical Properties
Chemistry
Microstructure
Meta-Data
DataMechanical Properties
Chemistry
Microstructure
Meta-Data
DataMechanical Properties
Chemistry
Microstructure
Meta-Data
log Life (e.g. Cycles or TACs)
Usag
e (e.
g. S
tress
)
TypicalMean
Lower
Bound
System Requirements
PMDO – Preliminary
Multi-Disciplinary
Optimization
Location-Specific Optimized
Component Definition
Model-Based
Manufacturing Definition Data Capture /
Knowledge Generation
Microstructure &
Process-Sensitive
Materials Definition
Materials Genome Initiative
©2013 United Technologies Corporation
15 Not subject to the EAR per 15 C.F.R. Chapter 1, Part 734.3(b)(3)
Example of ICME Application
From R. Shankar
Cost Benefit
System Benefits
Case Study Heat Treat Forging Part Forge Wt Part Wt Burst Speed Comments
1 Constant Variable Variable -18% -15% +6% Current State of the Art
2 Variable Variable Constant -11% n/a +12% Final Part shape constrained
3 Variable Variable Variable -21% -19% +19% Full impact of tool
Final disk shape before and after
Variation in Weak Pairing Curve - Strong Pairing Curve Intersection
by changing APB Energy and Volume Fraction Independently
0
200
400
600
800
1000
0 10 20 30 40 50 60 70 80 90 100
Gamma Prime Size (nm)
Yie
ld S
tre
ng
th C
on
trib
uti
on
(M
Pa
)
Decreasing APB Energy
Increasing APB Energy
Reference Point:
APB = 0.2 J/m^2, Fraction = 0.34
APB = 0.10 J/m^2
APB = 0.16 J/m^2
APB = 0.08
APB = 0.26 J/m^2
APB = 0.31 J/m^2
Fraction = 0.02
Fraction = 0.06
Fraction = 0.18
Fraction = 0.50
Fraction = 0.75
Decreasing Volume Fraction
Increasing Volume Fraction
ys fp (T )Ni3Ald
dCiCi
i
+MftAPB
b
M 1 fp 0.43Gb
fs1 fp
1 / 2
d
2.56d APB
Gb2 1
1/ 2
fTo
T
d
dCi
1/ 2
i
Ci1/ 2
(1 fp)ky d1 / 2
fpky'd
1 / 2
Yield of Primary ’ Shearing of Secondary ’ (Pairs)
Shearing of Tertiary ’ Solid Soln StrengtheningHall-Petch
PhaseHall-Petch
Primary ‘
• Feasibility of full design
integration demonstrated Over 600 design loop runs with coupled part
geometry and material capability driving design
evolution
Realistic case studies
>50% Reduction in Design
Cycle Time
Geared Turbofan
Engine
©2013 United Technologies Corporation
16 Not subject to the EAR per 15 C.F.R. Chapter 1, Part 734.3(b)(3)
Disciplines Touched by ICMSE
• Materials
• Manufacturing
• Design
• Structures
• Quality
• Supply-Chain
Integration of Computational Materials
Science and Engineering is Complicated
©2013 United Technologies Corporation
17 No Technical Data per the EAR and ITAR
Challenges to Effective ICME Deployment
• Accurate computational models
• Efficient simulation software tools
• Data and databases for model application
• Industry standard methods and protocols
• Computational methods for design linkages
• Well trained interdisciplinary workforce
Unique engineering skill sets are required to support each challenge
©2013 United Technologies Corporation
18 No Technical Data per the EAR and ITAR
Computational Supply-Chain
A series of well-established, capable and viable
organizations that provide necessary portions
of the ICME Value Chain
Software Companies
Industry
Government Labs
Academia
– Fundamental Model
Development
– Model Integration into Software
Packages
– Maintenance of Software Tools
– Database Generation
– Application Engineering
– Customer Approval and
Certification
– Education and Training
©2013 United Technologies Corporation
19 No Technical Data per the EAR and ITAR
Engineering
Societies
Conclusions
• ICME: Potential for dramatic changes to
development time, cost, and product capabilities
• Computational materials engineering enables
virtual manufacture and component testing for
optimization and risk mitigation
• Application of ICME has several challenges:
trained practitioners; tools and methods; and
computational infrastructure
©2013 United Technologies Corporation
20 No Technical Data per the EAR and ITAR