2014 ASTM JoDean Morrow Lecture on Fatigue of … JoDean Morrow Presentation... · New Orleans, LA...
Transcript of 2014 ASTM JoDean Morrow Lecture on Fatigue of … JoDean Morrow Presentation... · New Orleans, LA...
1Approved for public release: Case No. 88-ABW-2013-0906
Integrity Service Excellence
Reducing Uncertainty: Reflections on Establishing
Life Limits
2014 ASTM JoDean Morrow Lecture on Fatigue of Materials
New Orleans, LA11 November 2014
J.M. Larsen1, S.K. Jha2, M.J. Caton1,R. John1, A.H. Rosenberger1, D.J. Buchanan3,C.J. Szczepanski5, W.J. Porter3, A.L. Hutson3,
P.J. Golden1, J.R. Jira1, S. Mazdiyasni1, V. Sinha4
Air Force Research LaboratoryWright-Patterson Air Force Base, OH 45433
1AFRL/RXC, 2Universal Technology Corporation3University of Dayton Research Institute, 4UES, Inc.., 5Special Metals Corp.
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In-house and Collaborative Team
GovernmentMike CatonLt. Chris FettyPat GoldenLt. Sigfried HerringJay JiraReji JohnJim LarsenSiamack MazdiyasniRyan MorrisseyAndy RosenbergerMike ShepardChris Szczepanski Lt. Steve Visalli
On-site Contractor (UDRI)Bob BrockmanMarc HuelsmanDennis BuchananDavid JohnsonKezhong LiJohn PorterHerb StumphPete Phillips
On-site Contractor (GDIT)Mike Dent
Universal Technology Corp. (UTC)Sushant Jha
Universal Energy Systems (UES)Vikas Sinha
University of Texas at San AntonioHarry Millwater
University of MichiganWayne JonesTresa PollockChrist Torbet
Ohio State UniversityAlison PolasikHamish FraserMike MillsJim Williams
Statistical Engineering Inc.Chuck Annis, Jr., P.E.
Independent ConsultantTom Cruse
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Life management of high performance turbine engines– Today and tomorrow
Fatigue variability and uncertainty– Examples
• Ti-6Al-2Sn-4Zr-6Mo ()• IN100
Future opportunities– Life management & design– Verification & validation– Optimize Performance, Safety, Reliability,
Maintainability, Affordability, Utilization
Acknowledgements:AFRL/RX & AFRL/HQAFOSR -- Multi-Scale Structural Mechanics and Prognosis (Dr. David Stargel)AFOSR -- Structural Mechanics (Dr. Victor Giurgiutiu)DARPA/DSO – Engine System Prognosis (Dr. Leo Christodoulou)
Outline
Alloys explored:Ti-10V-2Fe-3Al
Ti-6Al-2Sn-4Zr-6Mo ()Ti-6Al-2Sn-4Zr-6Mo (L-)Ti-6Al-2Sn-4Zr-2Mo ()
Ti-6Al-4VGamma TiAl
Waspaloy (Wrought)IN100 (P/M: fine grain)
IN100 (P/M: coarse grain)René-88 DT (P/M)IN718 (Wrought)
Ni Single Crystal 1484Al 7075-T651
Al-Cu-Mg-Ag alloy
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Life management of high performance turbine engines– Today and tomorrow
Fatigue variability and uncertainty– Examples
• Ti-6Al-2Sn-4Zr-6Mo ()• IN100
Future opportunities– Life management & design– Verification & validation– Optimize Performance, Safety, Reliability,
Maintainability, Affordability, Utilization
Acknowledgements:AFRL/RX & AFRL/HQAFOSR -- Multi-Scale Structural Mechanics and Prognosis (Dr. David Stargel)AFOSR -- Structural Mechanics (Dr. Victor Giurgiutiu)DARPA/DSO – Engine System Prognosis (Dr. Leo Christodoulou)
Outline
Alloys explored:Ti-10V-2Fe-3Al
Ti-6Al-2Sn-4Zr-6Mo ()Ti-6Al-2Sn-4Zr-6Mo (L-)Ti-6Al-2Sn-4Zr-2Mo ()
Ti-6Al-4VGamma TiAl
Waspaloy (Wrought)IN100 (P/M: fine grain)
IN100 (P/M: coarse grain)René-88 DT (P/M)IN718 (Wrought)
Ni Single Crystal 1484Al 7075-T651
Al-Cu-Mg-Ag alloy
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5For Official Use Only (FOUO)
Design Certification Methodology to Assure Integrity Throughout the Life Cycle
Propulsion System Integrity Program (PSIP) - MIL-STD-3024
“Safe Life” has been standard practice for engine rotors
for over 50 years. ……………………..
Used to compensate foruncertainty/lack of knowledge
log Life (e.g. Cycles or TACs)
Usa
ge (e
.g. S
tres
s)
TypicalMean
Max Safe Life
• Design and certify all components are within this “safe” zone.• All components are “not safe” if one in 1000 is predicted to initiate a crack
Untapped Performance
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Traditional Life Prediction Process
Stress-life (S-N) Fatigue Tests –All conditions
Condition n
Fit S-N data with Multi-Condition Regression
Actual/Predicted Lifetime (A/P) B.1 B50
50%
99.9%
0.1%
B50/B.1 = Scatter Factor(material + condition + model)
Component Scale-upFleet Scale-up B0.1 Lifetime
B0.1
• Data-Driven
• Distribution w.r.t. mean behavior
• Potentially untapped performance
• Needs generation of new database for new material or microstructure
• Difficult to incorporate effects of residual stress, mission, microstructure, etc.
Condition 1
Condition 2
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Low-Cycle-Fatigue Design Criteria (safe life)
• Based on statistical lower bound• 1 in 1000 components predicted to
initiate a 0.8 mm crack
Damage-Tolerant Design Criteria(fracture mechanics)
• Deterministic• 1 or 2 safety inspections during
service life
Both design criteria are met at all critical locations on a component
log Life (e.g. Cycles or TACs)
Usa
ge (e
.g. S
tres
s)
TypicalMean
Lower Bound
Cycles (or Equivalent)
Cra
ck L
engt
hai
aC
a*
Propulsion System Integrity ProgramLife-Cycle Design Philosophy (PSIP; MIL-STD-3024)
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Move Engine Lifing fromSafe-Life Approach to Retirement For Cause
8
0 10000 20000 30000 40000 50000 60000 70000
Num
ber o
f Par
ts
Life (Time or Cycles)
LCF Initiation Distribution
-3
Retire all componentswhen 1 in 1000 ispredicted to fail
B0.1 = 4000 TAC
Traditional “Safe-Life” Retirement ApproachManage to -3 Lower Bound
Before 1980s RFC program
0 10000 20000 30000 40000 50000 60000 70000
Num
ber o
f Par
ts
Life (Time or Cycles)
LCF Initiation Distribution
-3
Retire all componentswhen 1 in 1000 ispredicted to fail
B0.1 = 8000 TAC
Traditional “Safe-Life” Retirement ApproachManage to -3 Lower Bound
After 1980s RFC program
0 10000 20000 30000 40000 50000 60000 70000
Num
ber o
f Par
ts
Life (Time or Cycles)
LCF Initiation Distribution
-3
Retire all componentswhen 1 in 1000 ispredicted to fail
B0.1 = 12000 TAC
Traditional “Safe-Life” Retirement ApproachManage to -3 Lower Bound
After ERLE program
020
0040
0060
0080
0010
000
1200
014
000
1600
018
000
2000
022
000
2400
026
000
2800
030
000
3200
034
000
3600
038
000
4000
042
000
4400
046
000
4800
050
000
5200
054
000
5600
058
000
6000
062
000
6400
066
000
6800
070
000
Life (Time or Cycles)
Economic/Risk Limit = Definition of Retirement for Cause
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Yes Service
NO Retire
Usage (D
uty Cycles)
Failure Occurrences“Book Life” Today
Prognosis will Enable Transformationin Asset Management
Database:Mission History,
Maintenance, Life Extension, and Design
Prognosis
Failure physics, damage evolution,predictive models
Stat
e Aw
aren
ess
Interrogation
Prognosis Translates Knowledge and Information Richness to Physical Capability
Reduce andManage
Uncertainty
“Book Life” Today
“Book Life”Tomorrow
Dr. Leo Christodoulou
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Background•Current design and life management of turbine engine materials– Extensive fatigue testing required to produce large databases– Statistically-based life limits by extrapolation from the mean behavior
•Next-generation design and life management– Design Target Risk:
• DoD: < 5*10-8 failures/engine flight hour• FAA: < 1*10-9 failures/flight
– Safety, reliability, affordability– Reduced life-cycle cost– Reduction in uncertainty in materials life-cycle prediction– Reduce requirements for materials testing
•Overarching science and technology initiatives– DoD Engineered Resilient Systems– Materials Genome Initiative (MGI)– Integrated Computational Materials Engineering (ICME)– Big Data
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Large degree ofuncertainty associatedwith life prediction
Failu
re O
ccur
renc
e
Usage (Duty cycles)
POF = 0.1%life limit(Book life)
Failu
re O
ccur
renc
e
Duty cycles
POF = 0.1%life limit
Life-limit based on the uncertaintyin the worst-case mechanism
Crack growthrelated peak(life-limitingmechanism)
Mean-lifetimedominating peak
Total variability
Traditional (Empirical) DescriptionFatigue variability described as deviation from the expected mean-behavior
Physics-Based Description of Fatigue VariabilityFatigue variability described as separation of the mean and the life-limiting behavior
Mean behavior
Variability described w.r.t. the overall mean behavior
Nf (Cycles)
max
Overall mean behavior
Distribution in the life-limiting mechanism(crack-growth controlled)
max
Nf (Cycles)
Variability in the mean-dominating response
Opportunity: Physics-Based Descriptionof Fatigue Variability
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N. E. Frost, K. J. Marsh, and L. P. Pook"Metal fatigue, 1974." Oxford University Press, Oxford.
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Life-limiting Fatigue
Small-Crack GrowthCrack Initiation
Long-Crack Growth
Ni
? ? ?NP,small NP,long NTotal
Total Fatigue Life = NTotal
Ni NP,small NP,long
NTotal
Low-Cycle-Fatigue Life Limits: A New UnderstandingLife-limiting low-cycle-fatigue life is governed by the growth of a dominant crack from an initial crack size defined by the microstructural features & mechanisms that control crack formation.
0?
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Life management of high performance turbine engines– Today and tomorrow
Fatigue variability and uncertainty– Examples
• Ti-6Al-2Sn-4Zr-6Mo ()• IN100
Future opportunities– Life management & design– Verification & validation– Optimize Performance, Safety, Reliability,
Maintainability, Affordability, Utilization
Acknowledgements:AFRL/RX & AFRL/HQAFOSR -- Multi-Scale Structural Mechanics and Prognosis (Dr. David Stargel)AFOSR -- Structural Mechanics (Dr. Victor Giurgiutiu)DARPA/DSO – Engine System Prognosis (Dr. Leo Christodoulou)
Outline
Alloys explored:Ti-10V-2Fe-3Al
Ti-6Al-2Sn-4Zr-6Mo ()Ti-6Al-2Sn-4Zr-6Mo (L-)Ti-6Al-2Sn-4Zr-2Mo ()
Ti-6Al-4VGamma TiAl
Waspaloy (Wrought)IN100 (P/M: fine grain)
IN100 (P/M: coarse grain)René-88 DT (P/M)IN718 (Wrought)
Ni Single Crystal 1484Al 7075-T651
Al-Cu-Mg-Ag alloy
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Ti-6Al-2Sn-4Zr-6Mo (Ti-6-2-4-6)
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Lifetime DistributionTi-6-2-4-6, RT, R = 0.05, = 20 Hz and 20 kHz
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100 103 104 105 106 107 108 109.01
.1
1
51020305070809095
99
99.9
99.99
All data points
Lifetime, Nf (Cycles)
Pro
babi
lity
of fa
ilure
(%
)
95% confidence intervals
max
= 820 MPa
Confidence Boundson B0.1 Lifetime -- All Data
721 cycles
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100 103 104 105 106 107 108 109
.1
1
51020305070809095
99
99.9
DataBimodal fitLower boundUpper bound
Nf (Cycles)
Pro
babi
lity
of fa
ilure
(%
)
max
= 820 MPa
Bimodal Model
)()1()()( NfpNfpNf mlllt
4565 cycles
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100 103 104 105 106 107 108 109.01
.1
1
51020305070809095
99
99.9
99.99
Life-limiting distribution
Lifetime, Nf (Cycles)
Prob
abilit
y of
failu
re (
%)
95% confidence intervals
max
= 820 MPa
Confidence Bounds on B0.1 LifetimeLimiting Condition of pl → 1
5660 cycles
1)()1()()(
l
mlllt
pNfpNfpNf
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Lifetime DistributionTi-6-2-4-6, RT, R = 0.05, = 20 Hz and 20 kHz
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CDF SpaceEffect of Stress Level on Mean vs. Life-Limiting Behavior
104 105 106 107 108 109 10101
5102030
50
70809095
99
1040 MPa925 MPa900 MPa860 MPa820 MPa700 MPa650 MPa600 MPa550 MPa
Cycles to Failure
Prob
abili
ty o
f Occ
uren
ce (%
)
Life-limiting behavior
Mean-dominating behavior
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Bimodal Fatigue BehaviorTi-6Al-2Sn-4Zr-6Mo; RT
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Probability of Life-Limiting Failures
ys= 1140 MPa
Stress (MPa)
Prob
abili
ty o
f Occ
urre
nce
of L
ife-
Lim
iting
Fai
lure
s
104 105 106 107 108 109 10101
5102030
50
70809095
99
1040 MPa925 MPa900 MPa860 MPa820 MPa700 MPa650 MPa600 MPa550 MPa
Cycles to Failure
Prob
abili
ty o
f Occ
uren
ce (%
)
Failu
re O
ccur
renc
e
Duty cycles
B0.1 lifetimes
Crack-growth-controlled density (Critical heterogeneity level) Mean-dominating
density (Smaller heterogeneity scales)
Empirically-derived density
Failu
re O
ccur
renc
e
Duty cycles
B0.1 lifetimes
Crack-growth-controlled density (Critical heterogeneity level) Mean-dominating
density (Smaller heterogeneity scales)
Empirically-derived density
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24FOR OFFICIAL USE ONLY
Alternate Life-Prediction Approach
• The Mean and the worst‐case behavior separate with decreasing and respond differently to operatingvariables.
• Life Prediction based on variabilityin the worst‐case mechanism.
• Significant reduction in uncertaintywhen compared to the traditionalapproach.
• Improved reliability of design life.
1 in 1000Life limits
Failu
re Occurrence
Duty cycles
Variability incrack growth Variability in crack
Initiation + growth
1000 104 105 106 107.01
.1
1
51020305070809095
99
99.9
99.99All pointsType IType II
Cycles to Failure, Nf
Pro
babi
lity
of F
ailu
re (
%)
Type I
Type II
max
= 860 MPa
Reduction inuncertainty
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25FOR OFFICIAL USE ONLY
Alternate Life-Prediction Approach
• The Mean and the worst‐case behavior separate with decreasing and respond differently to operatingvariables.
• Life Prediction based on variabilityin the worst‐case mechanism.
• Significant reduction in uncertaintywhen compared to the traditionalapproach.
• Improved reliability of design life.
1 in 1000Life limits
Failu
re Occurrence
Duty cycles
Variability incrack growth Variability in crack
Initiation + growth
1000 104 105 106 107.01
.1
1
51020305070809095
99
99.9
99.99All pointsType IType IISimulated, Type I
Cycles to Failure, Nf
Pro
babi
lity
of F
ailu
re (
%)
Type I
Type II
max
= 860 MPa
Reduction inuncertainty
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104 105 106 107.01
.1
1
51020305070809095
99
99.9
99.99
ExperimentalExperimental (Life limiting)Predicted (Life limiting)
Nf (Cycles)
Pro
babi
lity
of F
ailu
re (
%)
max
= 860 MPa
Life-limitingpopulation
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120 140 160 180
p area
Crcak nucleation area
Occ
urre
nce
frequ
ency
p area; Crack nucleation area (m2)
Crack Initiation Size
Small-Crack Growth Variability
Predicted Life-Limiting Distribution
• Prediction of limiting life of Ti-6Al-2Sn-4Zr-6Mo
• Monte Carlo simulation based on microstructural features and small-crack growth
Mechanism-Based Probabilistic Prediction of Limiting Life
)( KfdNda
f
i
a
aap Kf
daN)(
10-12
10-11
10-10
10-9
10-8
10-7
10-6
10-5
10-4
1 10 100
Long crack
Small cracks(
max = 860 MPa)
da/d
N (
m/c
ycle
)
K (MPa-m1/2)
Ti-6-2-4-6
max = 860 MPa
R = 0.05 = 20 HzT = 23°C
Power-law fits
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100 103 104 105 106 107 108 109.01
.1
1
51020305070809095
99
99.9
99.99
Life-limiting distribution
Lifetime, Nf (Cycles)
Prob
abilit
y of
failu
re (
%)
95% confidence intervals
max
= 820 MPa
Confidence Bounds on B0.1 LifetimeLimiting Condition of pl → 1
5660 cycles
1)()1()()(
l
mlllt
pNfpNfpNf
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100 1000 104 105 106 107 108 109.01
.1
1
51020305070809095
99
99.9
99.99
Predicted life-limitingdistribution
Crack-growth- controlled failures
Lifetime, Nf (Cycles)
Prob
abilit
y of
Fai
lure
(%
)
max
= 820 MPa
Crack-Growth-Controlled Failures
B0.1 lifetime
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Bimodal Fatigue BehaviorTi-6Al-2Sn-4Zr-6Mo; RT
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How Can this Understanding Affect the Life-Cycle Design Philosophy?
Predicted Distribution in a vs. N820 MPa
An Integrated Design CriterionB0.1 Lifetime
Limiting DamageTolerance Curve
Cycles
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Loading axis
F1
N2
F1
F1
N1N2
N1
Methods:• Quantitative tilt microscopy using MEXTM
• FIB sectioning through crack-initiation facet (in some cases)• EBSD analysis of the crack-initiation region
Basal plane trace
IPF map
Life-Limiting Failure
Specimentilt = 30°
Crack-initiationfacet
Faceted p
• max = 860 MPa; Nf = 49,893 cycles • Facet inclination = 31°
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Summary of Mean vs. Life-Limiting ConfigurationsSurface-Initiated Mechanisms
25
30
35
40
45
50
104 105 106 107
Life-limiting
Mean-dominatingFace
t inc
linat
ion
w.r.
t. th
e lo
adin
g ax
is (
°)
Lifetime (Cycles)
Neighboring grains
Faceted grainsResolved along the
loading axisResolved along the
facet normalFacet inclination
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soft
, p
Basal plane Inclination ≤ 30
Hypothesis: Hierarchy of Fatigue Deformation Heterogeneities
Prob
abili
ty o
f occ
urre
nce
Heterogeneity level
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0.0
0.5
1.00.0
0.51.0
0
1
2
3
Prob
abili
ty o
f occ
urre
nce
Deformation parameter
Microstructure-Based Prediction of Life-Limiting Fatigue Mechanisms in Ti-6-2-4-6
Using the Hierarchy Model of Heterogeneity levels
P(Li
fe-li
miti
ng fa
ilure
)
, str, etc.MicrostructureModel
MicrostructureModel
Compute Fatigue Heterogeneity
Parameter
Compute Fatigue Heterogeneity
Parameter
Hierarchy Model
Hierarchy Model
FatigueModel
FatigueModel
• Ellipsoid packing method1
• Statistically representative volume element• Smaller than lab-scale specimen
• CP-FEM model2• Definition of heterogeneity parameter
• Model the heterogeneity parameter distribution
• Simulate fatigue specimens (lab scale) using the hierarchy model• Spatial distribution given by the Poisson point process• Interrogate for life-limiting criterion
Probability of life-limiting mechanismProbability of life-
limiting mechanism
1C. P. Przybyla and D . L. McDowell, International Journal of Plasticity, 20102R. A. Brockman, et al.
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SummaryTi-6-2-4-6
• Study fundamental drivers of fatigue lifetime distribution – Stresses and lifetimes representative of engine rotors designs
• Total fatigue lifetime (NT) :NT = Ni + NSC + NLC
– Ni is the dominant term only in the mean lifetime as the stress level is decreased
– Ni approaches 0 cycles for the life-limiting failures
• The minimum lifetime was spent almost completely in the growth of a crack that began on the microstructural scale
• How can one preclude the rare conditions that lead to Ni 0?– Microstructure, surface treatments (e.g., residual stresses), etc.– Need to quantify the probability of life-limiting failure (Ni 0)
• Suggests alternative interpretation for integrated life-cycle design and management of turbine-engine rotor materials and components
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Life management of high performance turbine engines– Today and tomorrow
Fatigue variability and uncertainty– Examples
• Ti-6Al-2Sn-4Zr-6Mo ()• IN100
Future opportunities– Life management & design– Verification & validation– Optimize Performance, Safety, Reliability,
Maintainability, Affordability, Utilization
Acknowledgements:AFRL/RX & AFRL/HQAFOSR -- Multi-Scale Structural Mechanics and Prognosis (Dr. David Stargel)AFOSR -- Structural Mechanics (Dr. Victor Giurgiutiu)DARPA/DSO – Engine System Prognosis (Dr. Leo Christodoulou)
Outline
Alloys explored:Ti-10V-2Fe-3Al
Ti-6Al-2Sn-4Zr-6Mo ()Ti-6Al-2Sn-4Zr-6Mo (L-)Ti-6Al-2Sn-4Zr-2Mo ()
Ti-6Al-4VGamma TiAl
Waspaloy (Wrought)IN100 (P/M: fine grain)
IN100 (P/M: coarse grain)René-88 DT (P/M)IN718 (Wrought)
Ni Single Crystal 1484Al 7075-T651
Al-Cu-Mg-Ag alloy
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Model-Based Fatigue Life-LimitsMean-Based → Life-Limiting-Mechanism-Based
Mechanistic Understanding
Model-based B0.1
Crack-growth lifetime distribution(life-limiting distribution)
Mean-dominatingdistribution
Data-basedapproach
Model-Based Probability of Life-Limiting
Mechanism (Ni = 1) Probability of Life-Limiting Mechanism
Life-limitingdistributions
Distribution in Life-Limiting MechanismModel of Life-Limiting Distribution
• Life-limiting trend is different from the mean-behavior trend
• Model-based predictions focus on the life-limiting behavior
• Method also enables incorporation of new material, microstructure, residual stress, mission, etc.
max = 1150 MPa; Nf = 2,210Critical microstructural neighborhood for Ni = 1
Crack Initiation Size
da/d
N
K
Small cracks
Prob
abili
ty
Nf (Life-Limiting)
B0.1
P(Li
fe-li
miti
ng
mec
hani
sm)
Volume
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Mechanism Mapping for Kt = 1w.r.t. Stress Level
950
1000
1050
1100
1150
1200
1250
100 1000 104 105 106 107
Surf. NMPSubsurf. NMPSurf. poreMean lifetime
max
(M
Pa)
Nf (Cycles)
IN100650°C
Surface NMP
Subsurface NMP
Surface pore
max = 1150 MPa; Nf = 2,210Surface NMP Subsurface NMPSurface pore
Fine Grain IN100 (650°C)
950
1000
1050
1100
1150
100 1000 104 105 106 107
Surface NMPSubsurface NMPSurface poreSubsurface pore
max
(M
Pa)
Nf (Cycles)
Coarse Grain IN100 (650°C)
Surface pore Subsurface NMP
Approved for public release: Case No. 88ABW-2015-0198
39For Official Use Only
100 1000 104 105 106.001.01
.115
102030507080909599
99.999.99
99.999
Cycles to Failure, Nf
Prob
abili
ty o
f Fai
lure
(%
)
1100 MPa Data
Model Prediction and Validation
950
1000
1050
1100
1150
1200
1250
100 1000 104 105 106 107
Mean lifetime
max
(M
Pa)
Nf (Cycles)
IN100650°C
max = 1150 MPa; Nf = 2,210Surface NMP
Transgranular
20 m
Subsurface NMP
Transgranular40 m
Surface pore
Mixedmode
10 m
Experimental Observations of Mechanism Variations
Incorporation of Crack-Initiation Mechanism in Life Prediction
For Official Use Only
• There are competing mechanisms for crack-initiation• Incorporating these mechanisms in life prediction models can lead to lower uncertainty and better
utilization of residual useful life
Simulation of Crack-Initiating Features
0
100
200
3000
100
200
300
01020304050
0
100
200
300
SpecimensPore
Non-metallic Particle (NMP)
Plate
Step 1
Step 2
Approved for public release: Case No. 88ABW-2015-0198
40For Official Use Only
Model-Based Fatigue LimitsProbability of Occurrence of Life-Limiting Mechanism
• Model-based probability of occurrence of life-limiting mechanism (Ni = 1)
• Volumetric effect on the probability of occurrence enables scale-up to component feature volumes
Non-metallic particlePores
SimulatedPlate
Componentfeature volume
Lab-scale specimen
Interrogate simulated specimens for microstructuralcondition representing Ni =1
0.0001
0.001
0.01
0.1
1
0.01 0.1 1 10 100
P-life-limiting
Prob
abili
ty o
f fin
ding
a c
ondi
tion
lead
ing
to li
fe-li
miti
ng m
echa
nism
, Pl
Surface layer volume (mm3)
Lab-
scal
esp
ecim
en
Feat
ure
volu
me
Approved for public release: Case No. 88ABW-2015-0198
41Courtesy of John Leugers, AFRL/RW Public Release #88ABW‐2012‐2266
100 1000 104 105 106.01
.1
1
51020305070809095
99
99.9
99.99538°C, Subsurface initiation
566°C, Subsurface initiation593°C, Subsurface initiation
621°C, Subsurface initiation650°C, Subsurface initiation677°C, Subsurface initiation593°C, predicted life-limiting distribution
Cycles to Failure, Nf
Pro
babi
lity
of F
ailu
re (
%)
593°C, Surface initiation
Model-Based Fatigue Life LimitsSmooth Geometry
0.0001
0.001
0.01
0.1
1
0.01 0.1 1 10 100
P-life-limiting
Prob
abili
ty o
f fin
ding
a c
ondi
tion
lead
ing
to li
fe-li
miti
ng m
echa
nism
, Pl
Surface layer volume (mm3)
Lab-
scal
esp
ecim
en
Probability of occurrence of life-limiting mechanism
max = 1150 MPa; Nf = 2,210Life-limiting mechanism:Surface NMP Initiation
20 m
Life-limiting distribution
max = 1000 MPa
max = 1000 MPaT = 538°C
• Life-limiting mechanism ≡ Crack initiation from surface NMP
• 1 out of 76 specimens failed by surface NMP at 1000 MPa (T = 538 – 677°C)
• Reasonable agreement between data and predictions of the predicted probability of occurrence and the life-limiting distribution
Feat
ure
volu
me
Approved for public release: Case No. 88ABW-2015-0198
42
Mechanism-Based Prediction of Life-Limiting Distribution
1150 MPa
1100 MPa
10-7
10-6
10-5
10-4
10-3
10-2
4 6 8 10 30 50 70
Long cracks (No dwell)
Small cracks, pore crack initiation (1150 MPa)
Small crack, NMP crackinitiation (1150 MPa)
da/d
N (
mm
/cyc
le)
K (MPa-m1/2)
650°C; 0.33 Hz; R = 0.05
0
1
2
3
4
5
6
7
20 35 50 65 80 95 110
125
140
155
170
Initiation Size (m)
Freq
uenc
y
Fine GrainCoarse Grain
NMP crack-initiation size distribution
Variability in small-crack growth rate
Inputs Predictions
100 1000 104 105 106.01.115
102030507080909599
99.999.99
Predicted life-limitingdistribution
Cycles to Failure, Nf
Pro
babi
lity
of F
ailu
re (
%)
100 1000 104 105 106.01
.115
102030507080909599
99.999.99
Predictedlife-limitingdistribution
Cycles to Failure, Nf
Pro
babi
lity
of F
ailu
re (
%)
Approved for public release: Case No. 88ABW-2015-0198
43
1150 MPa
1100 MPa
10-7
10-6
10-5
10-4
10-3
10-2
4 6 8 10 30 50 70
Long cracks (No dwell)
Small cracks, pore crack initiation (1150 MPa)
Small crack, NMP crackinitiation (1150 MPa)
da/d
N (
mm
/cyc
le)
K (MPa-m1/2)
650°C; 0.33 Hz; R = 0.05
0
1
2
3
4
5
6
7
20 35 50 65 80 95 110
125
140
155
170
Initiation Size (m)
Freq
uenc
y
Fine GrainCoarse Grain
NMP crack-initiation size distribution
Variability in small-crack growth rate
Inputs Predictions
Comparison to Data-Based Method
Over-conservative
Anti-conservative
100 1000 104 105 106.01.115
102030507080909599
99.999.99
1150 MPa(10 random tests)Predicted life-limitingdistribution
Cycles to Failure, Nf
Pro
babi
lity
of F
ailu
re (
%)
100 1000 104 105 106.01
.115
102030507080909599
99.999.99
1100 MPa(15 tests)Predicted life-limitingdistribution
Cycles to Failure, Nf
Pro
babi
lity
of F
ailu
re (
%)
Approved for public release: Case No. 88ABW-2015-0198
44
Mechanism-Based Prediction of Life-Limiting Distribution
1150 MPa
1100 MPa
10-7
10-6
10-5
10-4
10-3
10-2
4 6 8 10 30 50 70
Long cracks (No dwell)
Small cracks, pore crack initiation (1150 MPa)
Small crack, NMP crackinitiation (1150 MPa)
da/d
N (
mm
/cyc
le)
K (MPa-m1/2)
650°C; 0.33 Hz; R = 0.05
0
1
2
3
4
5
6
7
20 35 50 65 80 95 110
125
140
155
170
Initiation Size (m)
Freq
uenc
y
Fine GrainCoarse Grain
NMP crack-initiation size distribution
Variability in small-crack growth rate
Inputs Predictions
100 1000 104 105 106.01.115
102030507080909599
99.999.99
1150 MPa, ExperimentLife-limiting pointsPredicted life-limitingdistribution
Cycles to Failure, Nf
Pro
babi
lity
of F
ailu
re (
%)
100 1000 104 105 106.01.115
102030507080909599
99.999.99
1100MPa,20 testsPredictedlife-limitingdistribution
Cycles to Failure, Nf
Pro
babi
lity
of F
ailu
re (
%)
Approved for public release: Case No. 88ABW-2015-0198
45DISTRIBUTION C: Distribution authorized to US Government agencies and their contractors (Critical Technology), XX October 2013.
Other requests for this document shall be referred to Air Force Research Laboratory, AFRL/RXCM.
Understanding Crack Growth atFracture Critical Locations
Machining, shot peening, glass-bead peening, blend repair => surface residual stresses
• Notched specimens simulate fracture-critical features of components– Simulate crack growth under stress gradients (notches)– Simulate crack growth with shot peened residual stresses
0.0
1.0
2.0
3.0
4.0
5.0
0 3000 6000 9000 12000
LSG, boreLSG, faceSP = 6A, boreSP = 6A, face
Cra
ck L
engt
h (m
m)
Total Cycle Count, N
IN100 (cg): 650°C0.333 Hz, R = 0.05Kt,net = 1.8net = 680.6 MPa
Shot PeeningBenefit
Approved for public release: Case No. 88ABW-2015-0198
46Courtesy of John Leugers, AFRL/RW Public Release #88ABW‐2012‐2266
Model-Based Fatigue Life LimitsBenefit of Surface Residual Stress
ææææææ
æææææææææææ
æææ
æ
ææ
æææ
æ
ææææ
æ
æ
æææ
æ
æ
ææ
ææ
æææææ
æææææææ æ ææææ
0.0 0.1 0.2 0.3 0.4 0.5-1000
-800
-600
-400
-200
0
200
Distance mm
Resid
ualS
tress
MPa
1000 104 105 106.01
.115
102030507080909599
99.999.99
Without SPresidual stress
With SPresidual stress
Cycles to Failure, Nf
Pro
babi
lity
of F
ailu
re (
%)
650°C900 MPa
B0.1
Benefit of RS
0
5x103
1x104
1.5x104
2x104
2.5x104
3x104
3.5x104
300 350 400 450 500 550 600 650 700
Without RSWith SP RS
B0.
1 Li
fetim
e (C
ycle
s)
Temperature (°C)
With shot-peen RS
Without RS
900 MPa
Measured shot-peen RS profiles
• Benefit of shot-peen residual stress can be readily incorporated in the proposed model-based life limits
Approved for public release: Case No. 88ABW-2015-0198
47For Official Use Only
Applicability to Notched Geometries-Motivation-
Notch Locations are often Life Limiting • Air Hole• Bolt hole• Tang• Snap Fillet• …
Point Solution @ 650°Cfor Kt = 1.89
103 104 105 106.001
.01
.1
1
5102030
50
70809095
99
99.9
99.99
99.999Kt = 1.89
800 MPa900 MPa
800 MPa900 MPa
Cycles to FailurePe
rcen
t
Prediction
T= 650˚C; f=0.33 Hz; R=0.05
All lifing methods have to predict notch life
Elastic‐Plastic Notch Analysis
MechanicalSpecimen
Approved for public release: Case No. 88ABW-2015-0198
48For Official Use Only
Model-Based Fatigue Life-Limits Process for Components
Bolt hole
Fillet
Model-based probability of life-limiting mechanism (Ni = 1)
K solution for fracture-critical features
Component Stress Analysis
K
a
Life-limiting distributionB0.1 limit
Nf (life-limiting)
Prob
abili
ty
Feature 1
Feature 2
P(Li
fe-li
miti
ng
mec
hani
sm)
Volume
Model-based B0.1
Surface RSMicrostructureMission
• Model-based B0.1 method can be scaled up to a component or feature
• Variables such surface RS, microstructure, and mission are inputs to the model
Approved for public release: Case No. 88ABW-2015-0198
49
Life management of high performance turbine engines– Today and tomorrow
Fatigue variability and uncertainty– Examples
• Ti-6Al-2Sn-4Zr-6Mo ()• IN100
Future opportunities– Life management & design– Verification & validation– Optimize Performance, Safety, Reliability,
Maintainability, Affordability, Utilization
Acknowledgements:AFRL/RX & AFRL/HQAFOSR -- Multi-Scale Structural Mechanics and Prognosis (Dr. David Stargel)AFOSR -- Structural Mechanics (Dr. Victor Giurgiutiu)DARPA/DSO – Engine System Prognosis (Dr. Leo Christodoulou)
Outline
Alloys explored:Ti-10V-2Fe-3Al
Ti-6Al-2Sn-4Zr-6Mo ()Ti-6Al-2Sn-4Zr-6Mo (L-)Ti-6Al-2Sn-4Zr-2Mo ()
Ti-6Al-4VGamma TiAl
Waspaloy (Wrought)IN100 (P/M: fine grain)
IN100 (P/M: coarse grain)René-88 DT (P/M)IN718 (Wrought)
Ni Single Crystal 1484Al 7075-T651
Al-Cu-Mg-Ag alloy
Approved for public release: Case No. 88ABW-2015-0198
50For Official Use Only
Mission Usage
0
20
40
60
80
100
Time
% M
ax S
tres
sModel-Based Life-limits:
Deconstruct Uncertainty to Capture Benefits
Notch Analysis
3D Effects,etc.
Simulate lifetime
SurfaceResidual Stresses
0.0
1.0
2.0
3.0
4.0
5.0
0 3000 6000 9000 12000
LSG, boreLSG, faceSP = 6A, boreSP = 6A, face
Cra
ck L
engt
h (m
m)
Total Cycle Count, N
IN100 (cg): 650°C0.333 Hz, R = 0.05Kt = 1.8, net = 680.6 MPa
Microstructural Hierarchies
Transgranular
max = 1150 MPa; Nf = 2,210Surface NMP
Transgranular
Surface pore
Mixed mode
Subsurface NMP Crystallographic
Model‐based life limit
Approved for public release: Case No. 88ABW-2015-0198
51For Official Use Only
0.0
0.5
1.00.0
0.51.0
0
1
2
3
Multi-scale Physics and Mechanicsof Materials Fatigue Life Limits
What controls life-limit uncertainty?
Mechanisms Simulations
Approved for public release: Case No. 88ABW-2015-0198
52
Top-down approach – determine the
physics of fatigue damage and lifetime
variability
Integrated ComputationalMaterials Engineering (ICME) for Life
Meso-scale• Fracture modes, small-crack growth, fracture
morphology, and local neighborhood• Characterizing smaller flaws
Micro-scale• Crack-initiating
microstructural arrangements and mechanisms
• NDE of microstructure features
Nano-scale• Slip
mechanismspromoting crack initiation
Probabilistic life-prediction on the component-scale by integrating lab-scale information
10,000 m
Slip traces
Crackorigin
Macro-scale• Fatigue crack development
and growth from a life-limiting locationin a component
• Detecting “large” cracks
Approved for public release: Case No. 88ABW-2015-0198
For Official Use Only (FOUO)
New Engines• Minimize life-cycle
uncertainty
Digital material life-cycle and design• Optimize for full life
53
Reliability• Deconstruct Uncertainty• Microstructure-based lifing
Affordability• Much less testing• NDE: Tailored POD
Maintainability• Integrated life cycle• Optimize for maintainability
Manufacturing• Optimized processes• Digital Thread life-cycle data
Model-based Life-limit ApproachImplications -- Based on Predicted Risk
Verification & Validation• Probabilistic risk• Validation material science
Life-cycle Design• Materials / microstructures• Components / features
Sustainment of Legacy Engines• Understand & reduce
life-cycle uncertainty
Approved for public release: Case No. 88ABW-2015-0198
54
Related Publications
• S. K. Jha, C. J. Szczepanski, R. John, and J. M. Larsen, “Demonstration of a Method for Predicting the Probability of Life-Limiting Fatigue Failures,” to be submitted, Engineering Fracture Mechanics
• S. K. Jha, C. J. Szczepanski, R. John, and J. M. Larsen, “Deformation heterogeneities and their role in life limiting fatiguefailures in a two-phase titanium alloy,” Acta Materialia, Vol. 82, pp. 378-395, 2015.
• A. L. Hutson, S. K. Jha, W. J. Porter, and J. M. Larsen, “Activation of life-limiting fatigue damage mechanisms in Ti-6Al-2Sn-4Zr-6Mo,” International Journal of Fatigue, Vol. 66, pp. 1-10, 2014.
• S. K. Jha, R. John, and J. M. Larsen, “Incorporating small fatigue crack growth in probabilistic life prediction: Effect of stress ratio in Ti-6Al-2Sn-4Zr-6Mo,” International Journal of Fatigue, Vol. 51, pp. 83-95, 2013.
• J. M. Larsen, S. K. Jha, C. J. Szczepanski, M. J. Caton, R. John, A. H. Rosenberger, D. J. Buchanan, P. J. Golden, and J. R. Jira, “Reducing uncertainty in fatigue life limits of turbine engine alloys,” International Journal of Fatigue, Vol. 57, pp. 103-112, 2013.
• C. J. Szczepanski, S. K. Jha, P. A. Shade, R. Wheeler, and J. M. Larsen, “Demonstration of an in situ microscale fatigue testing technique on a titanium alloy,” International Journal of Fatigue, Vol. 57, pp. 131-139, 2013.
• C. J. Szczepanski, P. A. Shade, M. A. Groeber, J. M. Larsen, S. K. Jha, and R. Wheeler, “Development of a microscale fatigue testing technique,” Advanced Materials and Processes, Vol. 171, pp. 18-21, 2013.
• M. E. Burba, M. J. Caton, S. K. Jha, and C. J. Szczepanski, “Effect of aging treatment on fatigue behavior of an Al-Cu-Mg-Ag alloy,” Metallurgical and Materials Transactions A, Vol. 44, pp. 4954-4967, 2013.
• S. K. Jha, C. J. Szczepanski, P. J. Golden, W. J. Porter, III, and R. John, “Characterization of fatigue crack initiation facetsin relation to lifetime variability in Ti-6Al-4V,” International Journal of Fatigue, Vol. 42, pp. 248-257, 2012.
• C. J. Szczepanski, S. K. Jha, J. M. Larsen, and J. W. Jones, “The role of local microstructure on small fatigue crack propagation in an a+b titanium alloy, Ti-6Al-2Sn-4Zr-6Mo,” Metallurgical and Materials Transactions A, Vol. 43, pp. 4097-4112, 2012.
• A. H. Rosenberger, D. J. Buchanan, D. A. Ward, and S. K. Jha, “The variability of fatigue in notched bars of IN100,” Superalloys 2012, pp. 143-148, 2012.
• S. K. Jha, C. J. Szczepanski, C. P. Przybyla, and J. M. Larsen, “The hierarchy of fatigue mechanisms in the long-lifetime regime,” VHCF-5, pp. 505-512, 2011.
Approved for public release: Case No. 88ABW-2015-0198
55
Related Publications
• C. J. Szczepanski, S. K. Jha, J. M. Larsen, and J. W. Jones, “The role of microstructure on sequential stages of the very high cycle fatigue behavior of an a+b titanium alloy, Ti-6Al-2Sn-4Zr-6Mo,” VHCF-5, pp. 225-230, 2011.
• M. J. Caton and S. K. Jha, “Small fatigue crack growth and failure mode transitions in a Ni-base superalloy at elevated temperature,” International Journal of Fatigue, Vol. 32, pp. 1461-1472, 2010.
• R. John, D. J. Buchanan, M. J. Caton, and S. K. Jha, “Stability of shot peen residual stresses in IN100 subjected to creep and fatigue loading,” Procedia Engineering, Vol. 2., pp. 1887-1893, 2010.
• S. K. Jha, R. John, and J. M. Larsen, “Nominal vs local shot-peening effects on fatigue lifetime in Ti-6Al-2Sn-4Zr-6Mo,” Metallurgical and Materials Transactions A, Vol. 40, pp. 2675-2684, 2009.
• R. John, D. J. Buchanan, S. K. Jha, and J. M. Larsen, “Stability of shot-peen residual stresses in an a+b titanium alloy,” Scripta Materialia, Vol. 61, pp. 343-346, 2009.
• S. K. Jha, H. R. Millwater, and J. M. Larsen, “Probabilistic sensitivity analysis in life prediction of an a + b titanium alloy,” Fatigue and Fracture of Engineering Materials and Structures, Vol. 32, pp. 493-504, 2009.
• S. K. Jha, J. M. Larsen, and A. H. Rosenberger, “Towards a physics-based description of fatigue variability behavior in probabilistic life prediction,” Engineering Fracture Mechanics, Vol. 76, pp. 681-694, 2009.
• C. J. Szczepanski, S. K. Jha, J. M. Larsen, and J. W. Jones, “Microstructural influences on very-high-cycle fatigue-crack initiation inTi-6246,” Metallurgical and Materials Transactions A, Vol. 39, pp. 2841-2851, 2008.
• S. K. Jha, M. J. Caton, and J. M. Larsen, “Mean vs. life-limiting fatigue behavior of a nickel-based superalloy,” Superalloys-2008, pp. 565-572, 2008.
• W. J. Porter III, K. Li, M. J. Caton, S. K. Jha, B. B. Bartha, and J. M. Larsen, “Microstructural conditions contributing to fatigue variability in P/M nickel-base superalloys,” Superalloys-2008, pp. 541-548, 2008.
• S. K. Jha, M. J. Caton, and J. M. Larsen, “A new paradigm of fatigue variability behavior and implications for life predictions,” Materials Science and Engineering A, Vol. 468, pp. 23-32, 2007.
• S. K. Jha and J. M. Larsen, “Random heterogeneity scale and probabilistic description of the long-lifetime regime of fatigue,” VHCF-4, pp. 385-396, 2007.
Approved for public release: Case No. 88ABW-2015-0198
56
Related Publications
• C. J. Szczepanski, S. K. Jha, J. M. Larsen, and J. W. Jones, “The role of microstructure on the fatigue lifetime variability in an a+b titanium alloy, Ti-6Al-2Sn-4Zr-6Mo,” VHCF-4, pp. 37-44, 2007.
• S. K. Jha, J. M. Larsen, and A. H. Rosenberger, “The role of competing mechanisms in the fatigue-life variability of a titanium and gamma-TiAl alloy,” JOM, Vol. 57, pp. 50-54, 2005.
• S. K. Jha, M. J. Caton, J. M. Larsen, A. H. Rosenberger, K. Li, and W. J. Porter, “Superimposing mechanisms and their effect on the variability in fatigue lives of a nickel-based superalloy,” Materials Damage Prognosis, TMS, pp. 343-350, 2005.
• S. K. Jha, J. M. Larsen, and A. H. Rosenberger, “The role of competing mechanisms in fatigue life variability of a nearly fully-lamellar g-TiAl based alloy,” Acta Materialia, Vol. 53, pp. 1293-1304, 2005.
• K. S. Ravi Chandran and S. K. Jha, “Duality of the S-N fatigue curve caused by competing failure modes in a titanium alloy and the role of Poisson defect statistics,” Acta Materialia, Vol. 53, pp. 1867-1881, 2005.
• C. Annis, J. M. Larsen, A. H. Rosenberger, S. K. Jha, and D. H. Annis, “RFTh, a random fatigue threshold probability density for Ti6246,” Materials Damage Prognosis, TMS, pp. 151-156, 2005.
• C. J. Szczepanski, A. Shyam, S. K. Jha, J. M. Larsen, C. J. Torbet, S. J. Johnson, and J. W. Jones, “Characterization of the role of microstructure on the fatigue life of Ti-6Al-2Sn-4Zr-6Mo using ultrasonic fatigue,” Materials Damage Prognosis, TMS, pp. 315-320, 2005.
• S. K. Jha, J. M. Larsen, and A. H. Rosenberger, “The role of fatigue variability in life prediction of an a+b titanium alloy,” Materials Damage Prognosis, TMS, pp. 1955-1960, 2005.
• S. K. Jha, J. M. Larsen, A. H. Rosenberger, and G. A. Hartman, “Mechanism-based variability in fatigue life of Ti-6Al-2Sn-4Zr-6Mo,” Journal of ASTM International, Vol. 1, 2004.
• M. J. Caton, S. K. Jha, A. H. Rosenberger, and J. M. Larsen, “Divergence of mechanisms and the effect on the fatigue life variability of Rene’88DT,” Superalloys-2004, pp. 305-312, 2004.
• S. K. Jha, J. M. Larsen, A. H. Rosenberger, and G. A. Hartman, “Dual fatigue failure modes in Ti-6Al-2Sn-4Zr-6Mo and consequences on probabilistic life prediction,” Scripta Materialia, Vol. 48, pp. 1637-1642, 2003.
• S. K. Jha and K. S. Ravi Chandran, “An unusual fatigue phenomenon: duality of the S-N fatigue curve in the b titanium alloy Ti-10V-2Fe-3Al,” Scripta Materialia, Vol. 48, pp. 1207-1212, 2003.
Approved for public release: Case No. 88ABW-2015-0198