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Energy Efficient Propulsion Systems

Energy Efficient Propulsion Systems Simulation Execution Optimization CAD/CAM J . Brent Staubach & Michael Winter Pratt & Whitney United Technologies Corporation Energy & Computation MIT May 10 th 2006 Computing Power Will Fundamentally Change How We Design Gas Turbines

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Energy Efficient Propulsion Systems

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  1. Energy Efficient Propulsion Systems Simulation Execution Optimization CAD/CAM J. Brent Staubach & Michael Winter Pratt & Whitney United Technologies Corporation Energy & Computation MIT May 10th 2006

  2. Computing Power Will Fundamentally Change How We Design Gas Turbines RELEASE THIS POWER ON DESIGN PROCESSES Computer Speed - 2x Every 18 months - Network Speed - 2x Every 9 months - Tremendous Growth Billion X Speed by 2025 Hardware: 100,00X Massive Parallel Grid Computing, Assume ~10,000X Cost of Sending 1012 Bits Data Across Country Has Dropped From $150,000 in 1970 To 12 cents In 2000 • Transistor Scaling • Manufacturing: Copper, SiGe, • Parallelization: chip, • board, rack • Quantum Computing Cost of a Three Minute Phone Call From New York To London # Transistors (Ks) IBM & Intel Expect Continued Growth • Review Current Manual Design Optimization Practices • Computer Based Design & Key Enablers • Future  New Design Paradigms; Less Time; Fewer People

  3. System Engineering Process Driven by Product Needs Propulsion System Complexity Driving Need for More Robust Systems Engineering Process and Tools Propulsion has Become a System of Systems

  4. Modern Gas Turbine Optimization Is An Exercise In Managing Complexity ~ 80,000 PARTS ~5000 PART NUMBERS ~ 200 MAJOR PART NUMBERS REQUIRING 3D FEA/CFD ANALYSIS ~ 5000-10,000 PARAMETRIC CAD VARIABLES DEFINE MAJOR PART NUMBERS ~ 200 MAN-YEAR ANALYTICAL DESIGN EFFORT ~ 200 MAN-YEARS DRAFTING / ME EFFORT

  5. Complexity Is Managed By Decomposing The Design, Coordinating & Re-assembling via The SIPT/CIPT/IPT CIPT CIPT CIPT CIPT SYSTEM INTEGRATED T P EAM RODUCT TURBINE TURBINE BURNER TURBINE COMPRESSOR TURBINE FAN AERO AERO AERO STRUCTURES AERO AERO. MFG. TURBINE BURNER BURNER COMPRESSOR FAN STRUCTURES STRUCTURES STRUCTURES STRUCTURES STRUCTURES. COMPRESSOR TURBINE BURNER COMPRESSOR FAN AERO MECHANICAL MECHANICAL MECHANICAL MECHANICAL. • IPTsARE THE ORGANIZATIONAL MECHANISM THAT ENABLES A BALANCED • DESIGN - MANUAL MULTI-DISCIPLINARY DESIGN LOCAL OPTIMIZATION

  6. Within Modules & Disciplines SophisticatedSimulation Based DesignSystems Have Evolved

  7. Complex Designs Are Inherently & Brutally Iterative, Bounded By Best Practice Rules . . . . . . . . STANDARD WORK CAD MODEL PHYSICS MODEL DESIGN SPACE - NON LINEAR - MULTI MODAL - DISCONTINUOUS - NOISEY - HIGHLY CONSTRAINED WORK INSTRUCTIONS CRITERIA VALIDATED ANALYSIS PREFERRED CONFIGURATIONS DESIGN DECISION ENGINEER MAY ITERATE 100s TO 1000s OF TIMES TO GET SATISFACTORY RESULTS -- MANUALLY !

  8. . . . and Complex Designs Are Iterated Across Disciplines & Organizations . . .

  9. . . . And Iterations Can Take Place Across The Globe • INTER-DIVISIONAL • CUSTOMERS • OUTSOURCING • PARTNERSHIPS

  10. Iterations Are Simplified By Employing A Range Of Fidelity KNOWLEDGE INFORMATION DATA PRODUCT DEVELOPMENT PHASES DESIGN SPACE VTE 2D 3D 4D 0D 1D Concept Concept Preliminary Airplane Service & Validation/ 0 I Detailed Design 5 2 Initiation Optimization 4 Design 3 Validation Support Certification NEW ENGINE STAFFING • STAFFING EXPLODES WITH FIDELITY: ANOTHER “CURSE OF DIMENSIONALITY” FIDELITY • REQUIRES EXTENSIVE KNOWLEDGE TO JUDGE LOW FIDELITY MODELS

  11. Result Is Manual “Human” Based Multidisciplinary Design Optimization – At Best SYSTEM OPTIMIZATION ENSURE CONFORMANCE TO CUSTOMER NEEDS & BUSINESS GOALS COMPONENT OPTIMIZATION TEAMS - HUMAN INTERACTION EXECUTE MANUAL MDO PART OPTIMIZATION ISOLATED MULTI-FIDELITY DESIGN SYSTEMS SYSTEM • Labor Intensive, Compartmentalized Design Process • That Relies On Teams, Management, & Procedures

  12. Gains Can Be Made By Shifting From “Human” To “Computer” Based MDO “HUMAN” BASED “COMPUTER” BASED WORKFLOW, RULES, And DESIGN ITERATIONS AUTOMATED WITHIN And ACROSS SYSTEMS & DISCIPLINES -- LABOR INTENSIVE -- SUB-SYSTEM B SUB-SYSTEM A SYSTEM MANUAL WORK FLOW per PROCESS MAPS MANUAL CAD/CAE MODEL BUILDING & EXECUTION per STANDARD WORK MANUAL EXPLORATION TO FIND OPTIMAL DESIGNS THAT MEET TECHNOLOGY LEVELS AUTOMATE WORKFLOW AUTOMATE MODEL BUILDING & EXECUTION AUTOMATE DESIGN EXPLORATION

  13. Technologies Are Progressing To Enable Large Scale Computer Based MDO INTEGRATION FRAMEWORKS SYSTEM ANALYSIS FIPER • CHALLENGES • CYCLE BALANCE • 2ND FLOWS • TRANSIENTS ROBUST PARAMETRIC MASTER MODEL ASSESSMENT MODELING COMPUTER BASED MDO NAVIGATE THE VIRTUAL DESIGN SPACE PHYSICS CHALLENGES -LARGE ASSEMBLIES -TOPOLOGICAL -GENERATIVE - DIRECT MFG • - SOLVE TURBULENCE • - MULTIDISCIPLINARY ANALYSIS (MDA) • MATERIAL PROPERTIES • PROBABILISTICS GRID COMPUTING COST • CHALLENGES • SECURITY • POLITE COEXISTENCE • FAULT TOLERANCE - MFG - MAINTENANCE - NEGOTIATED

  14. Implementation Path: Electronic Enterprise Engineering COMPUTER BASED OPTIMIZATION LIBRARY OF “WRAPPED” TOOLS INTEGRATION FRAMEWORK ELECTRONIC PROCESS MAPS ELECTRONIC IPT IPT 1&2 IPT 1 SYSTEM OPTIMIZER IPT 2 G A E C H D F B OPTIMIZER IPT 3 OPTIMIZER IPT 3 VALIDATED CERTIFIED EMBEDDED KNOWLEDGE CONTROLLED INTEGRATE THIRD PARTY & LEGACY TOOLS INDUSTRY ACCEPTED COMMERCIAL TOOLS INTEGRATED INTO ELECTRONIC PROCESS MAPS & ASSOCIATED WITH WORK INSTRUCTIONS WORK FLOW MANAGEMENT COLLABORATIVE ENGINEERING SECURE B2B AUTOMATE ITERATION SATISFY CRITERIA GRID COMPUTING B A G E D D A F E F C G C B B C G B C A

  15. Large Scale Computer Based MDO Is AlreadyPractical 3D Aero-Vibratory Shape Optimization Of A Cooled Turbine Airfoil (Single Row RANS CFD, Cooled UG Parametric Model, 3D ANSYS Vibes)

  16. Large Scale Computer Based MDO Is AlreadyBecoming Practical 3D Shape Optimization Based On Hybrid Genetic Algorithm & Rule System (3D RANS Multi Row CFD, Population Size 80, Total Runs 2400, Run Time 48 hrs on 40CPUs) Discovered “bowed” rotor To control tip leakage Vortex

  17. Efficient Scalable System Problem FormulationsAre Becoming Understood For Gas Turbine Design

  18. Will Enable New Design Paradigms CUSTOMER NEEDS UNDERSTAND THE FUTURE CREATE TECHNOLOGY IMPROVE MODELS RE-FORMULATE PROBLEM UPGRADE COMPUTER BASED DESIGN “MACHINE” RUN 24/7 365 DAYS A YEAR CONTINUOUS DETAILED DESIGN SOLVE ALL POSSIBLE APPLICATIONS @ TECHNOLOGY READINESS LEVEL ENGINEERS COMPUTER BASED DESIGN CUSTOMER REQ. EXCEED TECHNOLOGY LESS TIME FEWER PEOPLE

  19. Powering Change………….Powering Freedom

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