Reducing Uncertainty: Reflections on Establishing Life Limits 2014 - PowerPoint PPT Presentation

Reducing Uncertainty: Reflections on Establishing Life Limits 2014 ASTM JoDean Morrow Lecture on Fatigue of Materials New Orleans, LA 11 November 2014 J.M. Larsen 1 , S.K. Jha 2 , M.J. Caton 1 , R. John 1 , A.H. Rosenberger 1 , D.J. Buchanan 3 , C.J. Szczepanski 5 , W.J. Porter 3 , A.L. Hutson 3 , P.J. Golden 1 , J.R. Jira 1 , S. Mazdiyasni 1 , V. Sinha 4 Air Force Research Laboratory Integrity  Service  Excellence Wright-Patterson Air Force Base, OH 45433 1 AFRL/RXC, 2 Universal Technology Corporation 3 University of Dayton Research Institute, 4 UES, Inc.., 5 Special Metals Corp. Approved for public release: Case No. 88ABW-2015-0198 1 Approved for public release: Case No. 88-ABW-2013-0906

In-house and Collaborative Team Government Universal Technology Corp. (UTC) Mike Caton Sushant Jha Lt. Chris Fetty Pat Golden Universal Energy Systems (UES) Lt. Sigfried Herring Vikas Sinha Jay Jira Reji John University of Texas at San Antonio Jim Larsen Harry Millwater Siamack Mazdiyasni Ryan Morrissey University of Michigan Andy Rosenberger Wayne Jones Mike Shepard Tresa Pollock Chris Szczepanski Christ Torbet Lt. Steve Visalli Ohio State University On-site Contractor (UDRI) Alison Polasik Bob Brockman Hamish Fraser Marc Huelsman Mike Mills Dennis Buchanan Jim Williams David Johnson Kezhong Li Statistical Engineering Inc. John Porter Chuck Annis, Jr., P.E. Herb Stumph Pete Phillips Independent Consultant Tom Cruse On-site Contractor (GDIT) Mike Dent Approved for public release: Case No. 88ABW-2015-0198 2

Outline Life management of high performance turbine engines Alloys explored: – Today and tomorrow Ti-10V-2Fe-3Al Ti-6Al-2Sn-4Zr-6Mo (  ) Fatigue variability and uncertainty Ti-6Al-2Sn-4Zr-6Mo (L-  ) – Examples Ti-6Al-2Sn-4Zr-2Mo (  ) Ti-6Al-2Sn-4Zr-6Mo (  ) • Ti-6Al-4V • IN100 Gamma TiAl Waspaloy (Wrought) Future opportunities IN100 (P/M: fine grain) – Life management & design IN100 (P/M: coarse grain) – Verification & validation René-88 DT (P/M) – Optimize Performance, Safety, Reliability, IN718 (Wrought) Maintainability, Affordability, Utilization Ni Single Crystal 1484 Al 7075-T651 Acknowledgements: Al-Cu-Mg-Ag alloy AFRL/RX & AFRL/HQ AFOSR -- Multi-Scale Structural Mechanics and Prognosis (Dr. David Stargel) AFOSR -- Structural Mechanics (Dr. Victor Giurgiutiu) DARPA/DSO – Engine System Prognosis (Dr. Leo Christodoulou) Approved for public release: Case No. 88ABW-2015-0198 3

Outline Life management of high performance turbine engines Alloys explored: – Today and tomorrow Ti-10V-2Fe-3Al Ti-6Al-2Sn-4Zr-6Mo (  ) Fatigue variability and uncertainty Ti-6Al-2Sn-4Zr-6Mo (L-  ) – Examples Ti-6Al-2Sn-4Zr-2Mo (  ) Ti-6Al-2Sn-4Zr-6Mo (  ) • Ti-6Al-4V • IN100 Gamma TiAl Waspaloy (Wrought) Future opportunities IN100 (P/M: fine grain) – Life management & design IN100 (P/M: coarse grain) – Verification & validation René-88 DT (P/M) – Optimize Performance, Safety, Reliability, IN718 (Wrought) Maintainability, Affordability, Utilization Ni Single Crystal 1484 Al 7075-T651 Acknowledgements: Al-Cu-Mg-Ag alloy AFRL/RX & AFRL/HQ AFOSR -- Multi-Scale Structural Mechanics and Prognosis (Dr. David Stargel) AFOSR -- Structural Mechanics (Dr. Victor Giurgiutiu) DARPA/DSO – Engine System Prognosis (Dr. Leo Christodoulou) Approved for public release: Case No. 88ABW-2015-0198 4

Design Certification Methodology to Assure Integrity Throughout the Life Cycle Propulsion System Integrity Program (PSIP) - MIL-STD-3024 Untapped Performance Usage (e.g. Stress) Typical Mean Max Safe  Life log Life (e.g. Cycles or TACs) “Safe Life” has been standard • Design and certify all components are within this “safe” zone. practice for engine rotors • All components are “not safe” if for over 50 years. one in 1000 is predicted to initiate a …………………….. crack Used to compensate for uncertainty/lack of knowledge 5 For Official Use Only (FOUO) Approved for public release: Case No. 88ABW-2015-0198

Traditional Life Prediction Process Stress-life (S-N) Fatigue Tests – Fit S-N data with Multi-Condition All conditions Regression • Data-Driven 99.9% B50/B.1 = Scatter Factor • Distribution w.r.t. (material + condition + model) mean behavior 50% • Potentially Condition 1 untapped performance 0.1% Condition 2 • Needs generation B.1 B50 Condition n Actual/Predicted Lifetime (A/P) of new database for new material or microstructure Fleet Scale-up  B0.1 Lifetime Component Scale-up • Difficult to incorporate effects of residual stress, mission, B0.1 microstructure, etc. 6 Approved for public release: Case No. 88ABW-2015-0198

Propulsion System Integrity Program Life-Cycle Design Philosophy (PSIP; MIL-STD-3024) Damage-Tolerant Design Criteria Low-Cycle-Fatigue Design Criteria (fracture mechanics) (safe life) Deterministic Based on statistical lower bound • • 1 or 2 safety inspections during 1 in 1000 components predicted to • • service life initiate a 0.8 mm crack Usage (e.g. Stress) a C Crack Length Typical Mean Lower Bound  * a a i log Life (e.g. Cycles or TACs) Cycles (or Equivalent) Both design criteria are met at all critical locations on a component 7 Approved for public release: Case No. 88-ABW-2013-0906 Approved for public release: Case No. 88ABW-2015-0198

Move Engine Lifing from Safe-Life Approach to Retirement For Cause LCF Initiation Distribution LCF Initiation Distribution Retire all components Retire all components Number of Parts Number of Parts After 1980s Before 1980s when 1 in 1000 is when 1 in 1000 is predicted to fail RFC program predicted to fail RFC program Traditional “Safe-Life” Traditional “Safe-Life” Retirement Approach Retirement Approach -3  -3  Manage to -3  Lower Bound Manage to -3  Lower Bound 0 10000 20000 30000 40000 50000 60000 70000 0 10000 20000 30000 40000 50000 60000 70000 Life (Time or Cycles) Life (Time or Cycles) B 0.1 = 8000 TAC B 0.1 = 4000 TAC LCF Initiation Distribution Economic/Risk Limit = Definition of Retirement for Cause After ERLE Retire all components Number of Parts when 1 in 1000 is program predicted to fail Traditional “Safe-Life” -3  Retirement Approach Manage to -3  Lower Bound 0 10000 20000 30000 40000 50000 60000 70000 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000 22000 24000 26000 28000 30000 32000 34000 36000 38000 40000 42000 44000 46000 48000 50000 52000 54000 56000 58000 60000 62000 64000 66000 68000 70000 Penetrate the LCF Distribution Life (Time or Cycles) B 0.1 = 12000 TAC 8 Approved for public release: Case No. 88ABW-2015-0198 Life (Time or Cycles)

Prognosis will Enable Transformation in Asset Management Dr. Leo Christodoulou Yes  Service Failure physics, “Book Life” Today “Book Life” Today damage evolution, Failure Occurrences predictive models Interrogation “Book Life” State Awareness Tomorrow Usage (Duty Cycles) Prognosis Reduce and Manage Uncertainty Database: Mission History, Maintenance, Life Extension, and Design NO  Retire Prognosis Translates Knowledge and Information Richness to Physical Capability Approved for public release: Case No. 88ABW-2015-0198 9

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 10 Approved for public release: Case No. 88-ABW-2013-0906 Approved for public release: Case No. 88ABW-2015-0198

Opportunity: Physics-Based Description of Fatigue Variability Physics-Based Description of Fatigue Variability Traditional (Empirical) Description Fatigue variability described as separation of the mean Fatigue variability described as deviation from the expected mean-behavior and the life-limiting behavior Overall mean behavior Mean behavior Distribution in the life- Variability described w.r.t. limiting mechanism the overall mean behavior (crack-growth controlled) Variability in the mean- dominating response  max  max N f (Cycles) N f (Cycles) Life-limit based on the uncertainty Crack growth in the worst-case POF = 0.1% related peak mechanism (life-limiting life limit Failure Occurrence mechanism) (Book life) Large degree of POF = 0.1% Mean-lifetime Failure Occurrence uncertainty associated life limit dominating peak with life prediction Total variability Usage (Duty cycles) Duty cycles Approved for public release: Case No. 88ABW-2015-0198 11

N. E. Frost, K. J. Marsh, and L. P. Pook "Metal fatigue, 1974." Oxford University Press, Oxford. 12 Approved for public release: Case No. 88-ABW-2013-0906 Approved for public release: Case No. 88ABW-2015-0198