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Systems Design - New Paradigm

Systems Design - New Paradigm. K Sudhakar Centre for Aerospace Systems Design & Engineering http://www.casde.iitb.ac.in/ January 28, 2004. Requirements Capture. Design Process. System Specification. Systems Design. System. Discipline-1. Discipline-2. Discipline-3. Meta Design.

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Systems Design - New Paradigm

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  1. Systems Design - New Paradigm K Sudhakar Centre for Aerospace Systems Design & Engineering http://www.casde.iitb.ac.in/ January 28, 2004

  2. Requirements Capture Design Process System Specification Systems Design

  3. System Discipline-1 Discipline-2 Discipline-3 Meta Design Designers Design Process Systems Engineering Systems Engineering? Need to view things from one level higher than your work requires Meta Design

  4. Requirements Capture Design the Design Process Specify Design Process Meta-Design • Increase breadth of knowledge used in decisions • Increase depth of knowledge used in decisions • Shorten design cycle time • Ability to systematically explore design space • - -

  5. Meta Design Elements Meta Design  MDO MDO Elements

  6. Researcher’s Perception • Multi-disciplinary : Increased breadth • Design – process of translating requirements into product specifications. • Optimization – Formal method of locating the ‘best’ under ‘constraints’ • Implies use of high fidelity tools. Increase depth.

  7. Industry Perception • Not a turnkey solution to design! • Only a tool in the hands of designer to • State design problems formally • Integrate appropriate fidelity analysis • Explore design space • Improve design starting from a baseline • If we can find an optima we will be happy! • If we find global optima we will celebrate!

  8. Aerodynamics Objective Structures Analysis Parameters Requirements as Constraints Controls -ilities Trajectory Optimization Systems Design

  9. An Example – HSCT (1991-’99)! • HSCT-2 • 5 design variables, 6 constraints • WINGDES, ELAPS, Range equation, engine deck • Time for one cycle = 10 minutes • HSCT-3 • 7 design variables, 6 constraints • ISAAC, COMET, Range equation. Engine deck • Time for one cycle = 3 hours • HSCT-4 • 271 design variables, 31,868 constraints • CFL3D, USSAERO, GENESIS, FLOPS, ENG10 • Time for one cycle = 3 days

  10. HSCT - 4 • Detailed problem definition took more than 1 year to extract from people • Requirements document touched 100 pages merely to define analysis process, tools used and data flow • 90% of work went into preparing analysis codes for MDA and integrating them in a proper sequence

  11. Where are we? • Strengths exist in disciplinary analysis • No focus on Analysis for Design • No focus on verification / validation to characterize uncertainties • No attempt to capture knowledge with traceability

  12. CASDE @ Workshop on Framework for System Analysis, ISSA, New Delhi, October 13, 2003 Need for groups to • Define design problem • Define needs for Analysis for Design • Extract / Establish traceability • Perform Verification / Validation to characterize uncertainty • Explore design methodologies

  13. New Paradigms • MDO – the process • Frame Works – to deploy the process • Multi-criteria decision making • Design under uncertainty Components • Surrogate Modeling (DOE, RSM, DACE) • Sensitivity Analysis

  14. Analysis Xnom Ynom p p • Characterisation • How to propagate • V&V, levels of fidelity • How to fuse • Characterisation Xnom X Ynom Y Design Under Uncertainty • How to assemble System Analysis • How to state design problem?

  15. Frame Work • Essential infrastructure • Disciplinary autonomy, but system level integration. (Distributed, heterogeneous environment) • Tools availability • Requirement Capture for Frame Work? • Commercial Frame Works – iSIGHT, Phoenix Integration, . . . • CASDE MDO FrameWork Version-II (March 2004)

  16. GUI Optimizer Manager Execution sequence A2 Configuration Server A4 A13 A1 A5 MDO Controller OPT1 OPT2 OPT3 Data Server A3 Database Execution Manager Execution Unit Control Name Server Data A5 A4 A14 A12 A13 A22 AM1 AM2 AM3 A3 A2 Analysis Manager A1 Execution sequence of execution units Parallel Execution MDO Framework • Architectural design - Intuitive GUI, OO principles, standards based • Problem formulation - Iterative & branching formulations, legacy codes, multiple optimizers • Problem execution - Automatic execution, parallel & distributed • Information access – DB management visualization, monitoring

  17. 3D-Duct : An Example • Duct design in the past? • Is improvements in breadth, depth possible? • Statement of design problem? • Analysis Tools - Identification, V&V and Integration • Focus on shrinking design cycle time • Design process?

  18. 3D-Duct : Problem Formulation Entry Exit Location and shape (Given) • Objective/Constraints • Pressure Recovery • Distortion • Swirl Optimum geometry of duct from Entry to Exit ?

  19. 3D-Duct : Automation for CFD Duct Parameters (β1, β2, αy, αz) Clustering Parameters Generation of structured volume grid using parametrization Generation of entry and exit sections using GAMBIT Entry & Exit sections Mesh file Conversion of structured grid to unstructured format Conversion of file format to CGNS using FLUENT Unstructured CGNS file Continuation Solution CFD Solution using FLUENT End-to-end (Parameters to DC60) automated CFD Cycle. CFD Solution DC60 Objective/Constraints evaluation Using UDFs (FLUENT)

  20. 3D-Duct : Automation for Design Duct Parameters (β1, β2, αy, αz) Generation of structured volume grid using parametrization Entry & Exit sections Conversion of structured grid to unstructured format Optimization Unstructured CGNS file Continuation Solution CFD Solution using FLUENT CFD Solution DC60 Objective/Constraints evaluation Using UDFs (FLUENT)

  21. Optimized duct from low fidelity rules Marginally infeasible from low fidelity rules Highly infeasible From low fidelity rules P (0.61, 0.31, 1.0, 1.0) (0.1, 0.31, 0.2, 0.6) (-0.4, 1.5, 0.3, 0.6) PLOSS 1.42 2.0 3.53 DC60 6.19 16.28 24.21 P – Parameters; PLOSS – Total Pressure Loss 3D-Duct : Design Space Reduction

  22. 3D-Duct : Simulation Time • Strategies • Continuation Method • Parallel execution of FLUENT on a 4-noded Linux cluster Time for simulation has been reduced to around 20%.

  23. CFD analysis at DOE points RS for PR & DC60 DOE in reduced space Low fidelity Analysis Optimization Constraints Parametrization 3D-Duct : Design Process LFA Optima

  24. Life Cycle Emphasis Design CE Manufacturing Supportability Systems Design Emphasis Aerodynamics Propulsion Structures MDO Controls Time into the process CONCURRENT ENGINEERING Vs MDO Source: AIAA MDO White Paper, 1991

  25. Visithttp://www.casde.iitb.ac.in/MDO/ Thank You

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