Accelerated Insertion of Materials Composites (AIM-C)

Transcription

1 Computational and Collaborative tools for Composite Materials National Materials Advisory Board November 23 Gail Hahn The Boeing Company Accelerated Insertion of Materials Composites (AIM-C) Jointly accomplished by a Boeing Led Team and the U.S. Government under the guidance of the ffice of Naval Aviation Systems Technology Dr. Leo Christodoulou of DARPA/DS Dr. Raymond J. Meilunas, NAVAIR

2 Report Documentation Page Form Approved MB No Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information perations and Reports, 1215 Jefferson Davis Highway, Suite 124, Arlington VA Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid MB control number. 1. REPRT DATE NV REPRT TYPE N/A 3. DATES CVERED - 4. TITLE AND SUBTITLE Computational and Collaborative tools for Composite Materials 5a. CNTRACT NUMBER 5b. GRANT NUMBER 5c. PRGRAM ELEMENT NUMBER 6. AUTHR(S) 5d. PRJECT NUMBER 5e. TASK NUMBER 5f. WRK UNIT NUMBER 7. PERFRMING RGANIZATIN NAME(S) AND ADDRESS(ES) The Boeing Company 8. PERFRMING RGANIZATIN REPRT NUMBER 9. SPNSRING/MNITRING AGENCY NAME(S) AND ADDRESS(ES) 1. SPNSR/MNITR S ACRNYM(S) 12. DISTRIBUTIN/AVAILABILITY STATEMENT Approved for public release, distribution unlimited 13. SUPPLEMENTARY NTES The original document contains color images. 14. ABSTRACT 15. SUBJECT TERMS 11. SPNSR/MNITR S REPRT NUMBER(S) 16. SECURITY CLASSIFICATIN F: 17. LIMITATIN F ABSTRACT UU a. REPRT unclassified b. ABSTRACT unclassified c. THIS PAGE unclassified 18. NUMBER F PAGES 13 19a. NAME F RESPNSIBLE PERSN Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18

3 AIM-C Alignment Tool The objective of the AIM-C Program is to provide concepts, an approach, and tools that can accelerate the insertion of composite materials into DoD systems. AIM-C Accomplishes This Three Ways Methodology - Evaluates the historical roadblocks to effective implementation of composites and offers a process or protocol to eliminate these roadblocks and a strategy to expand the use of the systems and processes developed. Product Development -Provides a software tool that facilitates evaluation of composite materials for various applications. Demonstration/Validation - Provides a mechanism for acceptance by primary users of the system and validation by those responsible for certification of the applications in which the new materials may be used. All tasks in Phase 1 support development of a Phase 2 Transition Program Approved for Public Release, Distribution Unlimited

4 Accelerated Insertion of Materials Is Achieved in AIM-C Methodology by Focusing on Real Insertion Needs (er Knowledge Base) Approach for coordinated use of Existing Knowledge Validated Analysis tools Focused Testing Application of Physics Based Material & Structural Analysis Methods Use of Integrated Engineering Processes & Simulations Uncertainty Analysis and Management Early Feature Based Demonstration Tracking of Variability and Error Propagation Across Scales Rework Avoidance Disciplined approach for pedigree management rchestrated Knowledge Management to efficiently tie together the above elements to DKB

5 How Does the IPT Use AIM-C Methodology? Master Knowledge Base Commit Document Readiness Conformance Assessment Knowledge Generation Problem Statement Plan to Meet Requirements Define Application Requirements Requirements Conformance Planning Knowledge Base

6 Knowledge Gathering Technology Readiness Levels Detail or x Readiness Levels The Same Linkage Used To Flow Down Requirements Is Used to Roll Up Knowledge And Track Progress as er Knowledge is Gathered. Exit Criteria Worksheet Use of Prior Knowledge Recommended Analyses Recommended Tests Recommended Combination of Prior Knowledge / Analysis /Test Integrated Product Team Chooses How To Meet Each Exit Criteria

7 The AIM-C Process Uses an Integrated Product Team to Commit Data to the Knowledge Base Materials Systems Engineering Certification Supportability Assembly Cost Knowledge Base Legal/Rights Producibility Strength Schedule Durability

8 Use of AIM-C Web-Based System Delivery Process Guidance and Risk Reduction Status Hat plies x direction Noodle and skin x direction AIM-C Contains Analytical Models From Constituents To Processing To Effects of Defects To Provide Analysis Supported by Test To Technology Readiness To Structural Reqs.

9 Handling Uncertainty The AIM-C Approach The First Step is Identifying and Understanding potential error sources Maintains Visibility of potential errors Forces step-by-step breakdown of the analysis/test process Forces agreement on responses of interest Classifying them allows the team to determine appropriate strategies for addressing them. Types: Aleatory Uncertainty (Variability, Stochastic Uncertainty) Epistemic Uncertainty (Lack of Knowledge, e.g., unknown geometry) Known Errors (e.g., mesh convergence, round-off error) Unknown Errors (Mistakes, e.g. wrong material inputs used) Approved for Public Release, Distribution Unlimited

10 Handling Uncertainty The AIM-C Approach Prior knowledge is useful in determining likelihood of occurrence. 6 Number of Composite Mnfg. Defects Per Year 5 Example: Past experience with Similar designs suggest that 3/4 of Stiffened panel defects are: Delaminations Cure Cycle Inconformities Ply wrinkles, or Voids/Porosity 4 Number of Defects /G SC R AT ST EP C N D IT I N U G ED /N IC M KE IS L D C /M IS AL IG N ED U T F C N T IN U R C LU SI N (F..D.) ID S V SI TY P R C U R E D EL AM /D IS B N C D YC LE -IN C R /M IS W R IN KL ED PL YS Tools such as DE/ANVA and Sensitivity Analysis are useful in quantifying a variable s influence on the result. A Domain Independent Comprehensive Tool Set to Analyze the Space Distributed Computing Boeing EMDS Robust Computational System (RDCS) Min cost, Weight Robustness Nominal Point Max Performance Typical Case Worst Case Deterministic Sensitivity Variable Ranking Sensitivity Analysis Min Cost, Weight Max Reliability Interface to External Processes (e.g. Explorer) Probabilistic ptimization External Process Interface Parametric Analysis of a Set of Multidisciplinary Codes Connected Together Space Exploration Response Surface Scans Deterministic ptimization Risk Reliability Probabilistic Analysis Reliability Based Ranking Probabilistic Sensitivities & Scans Taguchi

11 Handling Uncertainty The AIM-C Approach Quantifying Uncertainty If its important, and you can t remove it by design, quantify it. Testing or Probabilistic Analysis Tools are applied. A Domain Independent Comprehensive Tool Set to Analyze the Space Distributed Computing Boeing EMDS Min cost, Weight Robustness Nominal Point Max Performance Typical Case Worst Case Deterministic Sensitivity Variable Ranking Sensitivity Analysis Min Cost, Weight Max Reliability Interface to External Processes (e.g. Explorer) Probabilistic ptimization External Process Interface Parametric Analysis of a Set of Multidisciplinary Codes Connected Together Space Exploration Response Surface Scans Deterministic ptimization Risk Reliability Probabilistic Analysis Reliability Based Ranking Probabilistic Sensitivities & Scans Taguchi

12 Data from Knowledge, Analysis, and Test Combined Data Allowables with Uncertainty Data contain replicates => can estimate stress allowables (quantiles with confidence bands) RDCS allows simulation of physical data with sources of randomness including batch effects (aleatory or random uncertainty) => can simulate allowables. Combined data: allowables with uncertainty bands Bayesian uncertainty band on allowable Allowable estimate = quantile with confidence band. This is the aleatory content Aleatory and Bayesian are kept separate

13 Encoded Heuristics 1.8E+11 1% s 1.6E+11 E1 For IM7/977-3 By Analysis Data Points 1.4E+11 63% s 1.2E+11 5% s E1 (Pa) 1.E+11 38% s 8.E+1 25% s 6.E+1 4.E+1 % s Hat plies x direction 2.E+1.E+ % 2% 4% 6% Percent 45s 8% 1% Noodle and skin x direction DKB Re-creation Processing data passed to Structural Analyses Producibility TRL BD 3% AD 6% Technology Readiness Level tflange (B) 13% DKB tskin (A) 53%, ANVA, Explorer, & Probabilistic ptimization RDCS Links RISK AIM-C Significant Accomplishments wflange (D) 22% T e s t D a ta C 7 6 S h i f te d 8 C 6 S h i f te d 1 C 5 S h i f te d 1 2 C 5 4 S h i f te d 1 4 C 4 3 S h i f te d 1 8 C S h i f te d 1 6 C 3 Activity Steps Moving to Qualification 2 T re f = 6 C T im e t o f a i lu r e [ l o g m i n ] -2 2 C r itic a l J 1 M a s te r C u r v e 1 εvm matrix 5. Pilot Production 4. Lab/Prototype Production 3. Beaker/Bench Product 2. Theoretical/Beaker Product 1. Concept Exploration Activity Steps Moving to Certification Stress [MPa] T i m e t o f a il u r e [ lo g m in ] M a s t e r c u r v e o f t r a n s. t e n s ile s t r e n g t h o f la m in a te s ( T 3 /8 2 8 ) 8 Critical J1 [e-3] ε J1 matrix 6. Pre-Production M a s te r C u r v e Stress [MPa] fiber 7. Qualified Mat l/process SIFT/Accelerated Testing M a s te r C u r v e 8 2 εvm 9. Industry Std 8. Production AIM-C Methodology Links Readiness Levels T e st d a ta a n d m a ste r c u r v e o f r e s in t e n s ile s t r e n g t h ( r e s in ) Invariant Plots: J1, εvonmises (x) Readiness Level 1. Disposal 9. Production System 8. Flight Test 7. Ground Test 6. Component Test 5. Maturation (Subcomponents) 4. Preliminary (Stable Mat l & Process + Elements) 3. Proof of Concept Prototype 2. Concept Definition 1. Concept Exploration A A Physics Based 3D SIFT & Fracture Failure Theories J1 fiber xrl 1 5 J1 fiber matrix εvm fiber εvm matrix ε 2 J1 Structures Strength [MPa] Y - P r e d i c te d tr a n s v e rs e te n s i o n 6 Y - S h i fte d te s t d a ta R e d u c e d tim e to fa ilu r e [ lo g m in ] = f( tim e a n d te m p e ra tu r e ) R e d u c e d tim e to f a ilu r e [ lo g m in ] Durability Materials & Processing

14 What s the Benefit of AIM-C? Traditional Test Supported by Analysis Approach RISK A Time to Insertion Readiness AIM Provides an Analysis Approach Supported by Experience, Test and Demonstration RISK A Time to Insertion Readiness Reduced by 55% GP ppt