Integrating System-Level Reliability into Multi-Disciplinary Component Design

1. Incorporating System-level Probabilistic Reliability Into the Multi-disciplinary Component Design Process A status reportpresented to Dr. William E. Vesely Manager, Risk Assessment – Code Q, NASA Headquarters by N&R Engineering and Management Services, Inc. Parma Heights, Ohio 44130 NRengineering.com Bill Strack, John Gyekenyesi, and Vinod Nagpal November, 2007

2. N&R Engineering Many Relevant Software Tools Already Exist • Discipline Example code • Constituent-level material properties models CEMCAN • Design modeling codes ANSYS • Finite element modeling structural analysis ANSYS, NESTEM • Manufacturing process models ProCAST • Life prediction methods NASAlife • Probabilistic reliability analysis (PRA) QRAS, SAPHIRE • However: • These are independent codes that cannot communicate with each other. • Most of these codes ignore uncertainties – they are deterministic simulations. • What is needed: A user-friendly framework to integrate existing NASA and commercial codes into an overall reliability simulation that accounts for uncertainties and permits data sharing.

3. Vision for Reliability Analyses N&R Engineering Vision: Most future reliability analyses will account for uncertainties – both aleatory and epistemic. Design processes will consider system reliability as a constraint at the component level. Goal: • Develop a physics-based, multi-disciplinary future design tool (PRODAF) that enables this vision -- utilizing existing deterministic codes.

4. Review of PRODAF Development Status

5. N&R Engineering NASA GRC Physics-based Probabilistic Reliability Roadmap PRODAF: Probabilistic Design and Analysis Framework Code Q funding Other funding Complementary funding sources PRODAF - SBIR Phase II - Code Q Capability PRODAF SBIR Phase I SUA Code AE Applications to real problems NESTEM 1999 2001 2003 2005 2007 2009 Year

6. N&R Engineering Example SUA Problem: Probabilistic NASAlife

7. N&R Engineering Example Help Message Develop a robust online help system to guide users -- select codes and inputs, detect input errors, suggest error recovery strategies. Example: Provide guidance on how to select a distribution type for new users.

8. N&R Engineering Example Architecture to Implement the PRODAF Vision

9. Main PRODAF User Interface

10. N&R Engineering PRODAF Design Space Options • Execute the design process for a single design point • Perform a parametric design space exploration • Optimize a set of design variables – deterministically • Optimize a set of design variables – probabilistically

11. N&R Engineering Example MDO Problem Turbine engine performance code - fan pressure ratio - compressor pressure ratio Airplane performance, weight, economics code - wing loading - wing aspect ratio - wing LE sweep angle Data interface

12. N&R Engineering PRODAF Optimization Manager

13. N&R Engineering Generalized Reliability Analysis Procedure Initial Focus Region (Centered at Mean Values) Design of Experiments Optimal Symmetric Latin Hypercube FORM, SORM, Monte Carlo based on ResponseSurface Limit State Approximation Adaptive Response Surface FORM, SORM, MC results close enough? Minimum Distance in Focus Region Sequential Quadratic Programming Yes No Focus Region Update Adaptive Importance Sampling Convergence to MPP? Failure Probability No Yes

14. N&R Engineering OSLH Design: Example 9x2 Latin Hypercube Designs

15. N&R Engineering MPP Search : Numerical Example Focus region 3 Focus region 4 X2’ Focus region 2 Focus region 1 Limit state X1’

16. N&R Engineering PRODAF FY2007 Tasks Provide confidence bounds that account for uncertainties in the uncertainty parameters. Surrogate adaptive response surface approach for optimization using a 2-phase global/local MPP search method to handle non-linear, implicit limit state functions. Facilitate physics-based progressive failure modeling of complex systems. Provide a mechanism for distributed computing capability.

17. CDF System failure probability Application of PRODAF to Shaft/Disk/24-Blade System 1800 RPM, Tshaft = Tdisk = 600 °F, Tblade = 400-700 °F, Time = 50,000 sec.

18. N&R Engineering Current PRODAF Development Tasks SBIR II:“Physics-based Probabilistic Design Tool with System-Level Reliability Constraint” Code Q:“Physics-based Multi-disciplinary PRA Design System for Reliability” PRODAF Development Task SBIR IICode QStatus Task 1 – Develop confidence intervals with uncertain uncertainties  75% Task 2 – Develop rapid adaptive response surface methodology  100% Task 3 – Develop progressive failure modeling of complex systems  60% Task 4 – Develop executive code (GUI, distributed computing, help)   80% Task 5 – Provide automatic code/data interfacing during design process  100% Task 6 – Interface process-based cost modules such as P-BEAT  2% Task 7 – Validate code and usefulness with commercial customer (GE)  2% Task 8 – Provide example applications to relevant NASA problems  25% Task 9 – Author comprehensive methodology/theory and users manual  55% Task 10 – Develop robust reliability-based design space optimization 85% Task 11 – Provide robust online user helpsystem 60% Task 12 – Establish a code and data management system  90%

19. N&R Engineering PRODAF Milestones and Deliverables as Defined in Original Proposal Methodologies Software Deliverables 1 2 3 4 5 6 1 2 3 4 7 5 8 9 10 A B C Methodology Milestones Software Milestones . 1. Response surface methodology and coding complete 2. System-level progressive failure methodology complete 3. Confidence interval methodology complete 4. Code interfaces, cost module, 1st example problem complete 5. Robust design space optimization methodology complete Deliverables (in addition to quarterly/annual progress reports) A PRODAF software version 1.0 (includes confidence intervals and response surface features) B PRODAF software version 2.0 (includes all methodologies/features) C Final Theoretical Report and Users Manual 6. Code/database management system 7. Online help system completed 8. Distributed computing implemented 9. External evaluation/validation complete 10. Ares application examples completed

20. N&R Engineering PRODAF Project Organization NASA COTRs Dr. Shantaram S. Pai & Ed Zampino N&R Project Manager Dr. Vinod K. Nagpal N&R Engineering Mr. William Strack N&R Engineering Dr. Sankaran Mahadevan Vanderbilt University Dr. Satchi Venkataraman San Diego State University Confidence interval methodology Optimization with uncertainty Response surface methodology System-level progressive failure Robust design space optimization Software development On-line help system Distributed computing Dr. John Z. Gyekenyesi N&R Engineering Software testing General Electric Life prediction methodology Manufacturing processes Example applications

21. N&R Engineering FY07 PRODAF Code Q Funding Contractual effort: $253K Proposed TasksFY07 Validate code and usefulness with commercial customer (GE) 77K Provide example applications to relevant NASA problems 21 Develop robust reliability-based design space optimization 55 Provide robust online user help system, theory, users manuals 57 Establish a code and data management system 43 Total $253K Funding actually provided in FY07: $110K

22. N&R Engineering Proposed FY08 PRODAF Code Q Funding Contractual effort: $320K Proposed Tasks FY08 Validate code and usefulness with commercial customer (GE) 90K Provide example applications to relevant NASA problems 140 Add cost estimating modules to PRODAF 60 Provide theory and users manuals 30 Total $320K

23. N&R Engineering Summary PRODAF willprovide engineers with user-friendly tools to conduct a broad spectrum of probabilistic reliability analyses using existing deterministic modeling codes. It will provide a practical reliability-based design framework that captures the impact of uncertainties.

24. Backup Charts

25. N&R Engineering The Systems Uncertainty Analysis (SUA) Tool Fortran C/C++ Excel spreadsheet Multiple runs

26. N&R Engineering PRODAF Code Database Manager

27. N&R Engineering PRODAF Probabilistic Manager

28. N&R Engineering PRODAF Uncertainty Definition Dialog

29. N&R Engineering Uncertainty in Statistical Parameters • Parameters estimated from data with measurement errors • Random and bias errors • Parameters estimated from limited number of samples  • Scenario 1: Actual test data available –small sample size O(10) • Scenario 2: Population distribution and sample size known • Scenario 3: Population distribution known, sample size unknown • Scenario 4: Population distribution unknown, sample size known • Scenario 5: Population distribution and sample size unknown • Parameters specified by experts (no test data)  • Scenario 6: Bounds specified but distribution is not • Scenario 7: Bounds specified with most likely value

30. N&R Engineering “Physics-based Multi-disciplinary PRA Design System for Reliability” Tasks Option AOption B Adv. Development $cx1 $cy1 DDT&E cx2 cy2 Production cx3 cy3 Launch cx4 cy4 LLC $cx $cy Integrate cost module into PRODAF (e.g., NAFCOM) including optimum sparing strategy Enable automatic code/data interfacing during the design process CEV-SM Develop NASA-relevant application example Comprehensive theory and users manuals

31. N&R Engineering Acronyms CALCE Center for Advanced Life Cycle Engineering’s code to estimate failure probability of printed circuit cards CEMCAN Ceramic Matrix Composites Analyzer NASAlife NASA life prediction code NESTEM Hybrid of NESSUS and CSTEM codes PRODAF Probabilistic Design and Analysis Framework code QRAS Quantitative Risk Assessment System (PRA code) SAPHIRE Systems Analysis Programs for Hands-on Integrated Reliability(PRA code) SUA Systems Uncertainty Analysis code

32. N&R Engineering Example Probabilistic Analysis Using SUA SSME Fuel Turbopump Temperature SSME system model Critical Space Shuttle reliability component is the SSME high-pressure fuel turbopumps Probabilistic sensitivity factors Fuel turbopump temperature

33. N&R Engineering Probabilistic Analysis of ISS Electrical Power System (EPS) ISS EPS Uncertainties Power Output of the ISS EPS Probabilistic Sensitivities

34. N&R Engineering Application of Probabilistic Methods to Honeywell Blade Mistuning DoD SBIR

35. N&R Engineering PRODAF NESTEM to QRAS Interface No provision in QRAS to import component data – uses multiple Paradox binary relational database tables to store internally generated input data. NESTEM or CALCE NESTEM or CALCE files files Phase I C++ interface code Phase II C++ interface code Fetch probabilistic data Fetch probabilistic data Process data to get Pfail Process data to get Pfail file Create Delphi input Modify QRAS DB Call Delphi code to modify QRAS DB Display results to user Display results to user QRAS QRAS

36. N&R Engineering Example QRAS Interface using NESTEM and CALCE

37. N&R Engineering Example Architecture for Physics-based Probabilistic Design with System-Level Reliability Constraint SUA Code Q PRODAF

38. N&R Engineering Manufacturing Process Simulation Interface Development of Probabilistic Structural Analysis Integrated with Deformation Resistance Annular Welding Simulation: Dr. Anantanarayanan, Delphi Energy & Chassis Systems DEFORM Simulation Residual stress for SS316 ProbDRAW pre-processor - Import IGES files to DEFORM files - Convert cdb ANSYS files to DEFORM files - Setup and run DEFORM - Integrate with NESTEM - Integrate with other mfg. simulation codes Completed Underway Unfunded