Systems Design - New Paradigm K Sudhakar Centre for Aerospace Systems Design & Engineering January 28, 2004

Systems Design Requirements Capture Design Process System Specification

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

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 - Requirements Capture Design the Design Process Specify Design Process

Meta Design  MDO Meta Design Elements MDO Elements

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.

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!

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

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

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

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

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

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

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

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)

MDO Framework Database Configuration Server Execution Manager MDO Controller Name Server Data Server OPT1 Optimizer Manager OPT2OPT3 AM1 Analysis Manager AM2AM3 GUI Control Data A1 A2 A3 A4 A5 Execution sequence A13 Execution Unit A12 A13 A14 Execution sequence of execution units A22 A1 A2 A3 A4 A5 Parallel Execution 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

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?

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

3D-Duct : Automation for CFD Generation of entry and exit sections using GAMBIT Clustering Parameters Conversion of file format to CGNS using FLUENT Mesh file Generation of structured volume grid using parametrization Duct Parameters (β 1, β 2, α y, α z ) Entry & Exit sections Conversion of structured grid to unstructured format Unstructured CGNS file CFD Solution using FLUENT End-to-end (Parameters to DC 60 ) automated CFD Cycle. Objective/Constraints evaluation Using UDFs (FLUENT) DC 60 CFD Solution Continuation Solution

3D-Duct : Automation for Design Generation of structured volume grid using parametrization Entry & Exit sections Conversion of structured grid to unstructured format CFD Solution using FLUENT Objective/Constraints evaluation Using UDFs (FLUENT) DC 60 Optimization Duct Parameters (β 1, β 2, α y, α z ) Continuation Solution Unstructured CGNS file CFD Solution

3D-Duct : Design Space Reduction (0.61, 0.31, 1.0, 1.0) Optimized duct from low fidelity rules DC P LOSS (-0.4, 1.5, 0.3, 0.6) (0.1, 0.31, 0.2, 0.6) P Highly infeasible From low fidelity rules Marginally infeasible from low fidelity rules P – Parameters; P LOSS – Total Pressure Loss

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%.

3D-Duct : Design Process Parametrization Low fidelity Analysis DOE in reduced space CFD analysis at DOE points RS for PR & DC 60 Optimization Constraints LFA Optima

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

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