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Edit Comment Close Premium member Presentation Transcript Slide1: The New Role for CFD in IndustrySlide2: The Engineering Challenge - Reduce Development Cost without Compromising Reliability History Where We Need to be Streamline design & analysis processes Identify all possible failure modes early Fully explore the design space Account for variabilities Quantify risks, sensitivities, margins, system & component reliability “Concurrent Engineering & Robust Design Practices” Reduce Development Cost by a Factor of 8 Reduce Development Time by a Factor of 4 New Processes 73% of program cost related to Test-Fail-Fix cycleSlide3: In Concurrent Engineering & Robust Design Practices CFD is one of the Key Enabling Technologies The new role comes with a price The “bar” has been raised - design tool vs color pictures Different environment Different customers Different expectations Different success criteria CFD tools have to function in this new environment Requirements Ability to work real problems Engineering tool to be used by design engineers Turnaround times compatible with the design cycle Conceptual design (1-2 months) Preliminary design (4-6 months) Detail design (6-9 months) Quantified accuracy Acceptable costRole Of CFD in the New Environment: Role Of CFD in the New Environment Expected to provide: Flow environment definition Performance assessment Structural and thermal load prediction (static & dynamic) Test guidance (facility, measurements, instrumentation, scaling) Performance code input (parameters, loss coefficients, shape factors) Approach - Use best tool available Multiple codes - general purpose (robustness), application customized (speed) Multiple providers - developed by or jointly with strategic partners, in-house, commercial of-the-shelf, government Hierarchical physical models (turbulence/chemistry) Validated/calibrated/anchored (“degree of confidence”) Emphasis on - Provide engineering solutions and design guidance Use CFD in conjunction with engineering knowledge, other tools & common sense - part of an overall integrated design & analysis system Support all phases of design - conceptual, preliminary, detailed (final) Deliver “value” within program budget and schedule constraintsSlide5: Time from Geometry Definition to First Time through CFD Analysis Results 1 day -- 1 week -- 1 mon. -- 6 mon. -- 1 year -- Year 98 94 96 00 02 04 # of CFD Solutions/Day --1 --2 --3 0.1 2 days Today Need to be by 2004 CFD Turnaround Time Requirement for 3D, Complex Geometry, Complex Physics Analysis Results First Time Through 2 weeks Slide6: Use of CFD in Rocket Propulsion System Development - Then & NowSlide7: Rotating Machinery Thrust Chamber Flow Devices (valves, manifolds, ducts) Typical Rocket Engine ComponentsSlide8: Combustion Chamber Injector Elements Nozzle Main Injector Thrust Chamber ComponentsSlide9: Then (early eighties)First CFD Applications at Rocketdyne to Real Hardware: SSME Powerhead Flows (INS3D): First CFD Applications at Rocketdyne to Real Hardware: SSME Powerhead Flows (INS3D)Hot Gas ManifoldINS3D: Hot Gas Manifold INS3D Detailed analysis of multiple designs (two- & three-tube) Parametric analysis of turn- around duct & fuel bowl contours Significant improvements quantified Verified with air flow testsHot Gas ManifoldCFD Predictions Verified with Air Flow Tests: Hot Gas Manifold CFD Predictions Verified with Air Flow Tests Air flow test results verify CFD-based design improvementsMain InjectorINS3D: Main Injector INS3D Main Injector inflow from CFD predicted HGM/transfer duct analysis Simulated LOX post “core” via porous media assumption Subsequent detailed analysis about individual LOX posts HPOTP Ball BearingsINS3D: HPOTP Ball Bearings INS3D Investigate cause of ball bearing discoloration after flight CFD analysis characterized heat transfer around contact point where heat was generatedSSME Turbine Disk CoolingREACT: SSME Turbine Disk Cooling REACT Exploring alternative HPOTP turbine blade cooling system Approximate & model complex geometry (2-D) Understand flow environment Calculate thermal loads & temperature distribution Suggest design changes TempCFD Used to Optimize High Performance ImpellerREACT: CFD Used to Optimize High Performance Impeller REACTSlide17: Transient CFD Analysis Recommends Simple Fix to the SSME Fuel Flowmeter Anomaly REACT Wake location Abrupt shifting of flowmeter constant causes unreliable fuel utilization reading Transient CFD analyses indicate Complex interaction between the flow straightener shed wakes and the flowmeter rotor blades Anomaly is hydrodynamic in nature and not due to structural or duct vibration Origin of anomaly is unsteady forces imparted to the rotor at lower frequencies than those experienced in bluff-body shedding (as was assumed previously) Simple fix is to move back the hexagonal straightener to weaken the wake effects on the flowmeter blades (test and additional analysis planned for confirmation) Slide18: Now (2001)Multiple CFD Codes: ENIGMA General purpose, incompressible Navier-Stokes, steady/transient Finite difference, unstructured grid RANS turbulence model Fixed and rotating reference frame Customized version for FSI REACT General purpose, low-speed code Navier-Stokes, steady/transient Finite volume, structured grid RANS turbulence models Fixed and rotating reference frame Customized version for conjugate heat transfer USA General purpose, high-speed code Navier-Stokes, steady/transient Finite volume, structured grid TVD, shock capturing RANS turbulence models Multispecie, H2/HC finite-rate chemistry Production Codes Multiple CFD Codes GALACSY Spray combustion code Navier-Stokes, steady/transient Finite Volume, structured grid Lagrangian/Eulerian RANS turbulence models Multiphase, multispecie, H2/HC finite-rate chemistry ICAT General purpose, high-speed code Navier-Stokes, steady/transient Finite volume, unstructured grid TVD, shock capturing RANS turbulence models Multispecie, H2/HC finite-rate chemistry New Codes TIDAL General purpose, low- to high-speed code Navier-Stokes, steady/transient Finite volume, structured grid TVD, shock capturing RANS turbulence models Multispecie, H2/HC finite-rate chemistry Multiphase (solid-gas) Turbulence Chemistry ~ ~ ~ ~ ~ ~ Mach Number PhysicsSlide20: CFD Provides Flow Distribution in Turbine Discharge Duct Enigma Flight discharge duct made compact to save weight Creates highly nonuniform flow feeding into the heat exchanger (HEX) CFD predicted flow distribution in the discharge duct and defined the inflow to the HEX Predicted inflow conditions in HEX design and analysis Resulted in a design that met requirements for the compact duct Heat ExchangerEvaluation of Advanced Concepts Enigma: Evaluation of Advanced Concepts Enigma Fuel and Oxidizer Valves - Analyze Showerhead Concepts Short Length Jetpump - Design & Analyze for Optimum Transfer Efficiency - Validate Methodology Unshrouded Impeller - Design and Analyze RotordynamicsPreliminary Design and Redesign StudiesEnigma: Preliminary Design and Redesign Studies Enigma Inducer Back-Swirl Upper Stage Engine Cross-over and Volute Design Upper Stage Engine Inducer+Kicker DesignFuture Design Environment eTango: Future Design Environment eTango eTango, An integrated centrifugal pump design and analysis software package Runs on Windows based computers Incorporates Enigma™ CFD Integrated Design and Analysis Tool Reduced Cycle Time Consolidation of Thirteen CodesSlide24: Then, Now, and the Future (1/3) Cycle Times 1988 2000 2005 Rotating Machinery Turnaround Time/ Labor (in hr.) Turnaround Time/ Labor (in hr.) Turnaround Time/ Labor (in hr.) Turbines Steady loads Dynamic loads Multistage Pumps Inducers Impellers Diffusers/Crossovers Volutes Bearings Complete Turbopump 160 / 120 320 / 240 No capability No capability 200 / 160 240 / 200 No capability No capability 20 / 16 40 / 20 No capability 4 / 4 8 / 6 40 / 32 60 / 40 4 / 2 40 / 20 120 / 80 80 / 60 No capability No capability 160 / 160 8 / 4 1 / 1 4 / 4 16 / 8 16 / 8Slide25: Then, Now, and the Future (2/3) Cycle Times 1988 1998 2003 Thrust Chambers Turnaround Time/ Labor (in hr.) Turnaround Time/ Labor (in hr.) Turnaround Time/ Labor (in hr.) Injectors Gas/Gas Liquid/Gas Combustion Chambers Flow environment Thermal environment Combustion stability Nozzle Conventional Aerospike 320 / 240 480 / 360 60 / 30 120 / 80 16 / 12 24 / 16 320 / 240 No capability No capability 40 / 20 60 / 30 No capability 8/ 6 16 / 12 120 / 60 80 / 60 No capability 16 / 8 80 / 40 1 / 1 8 / 6Slide26: Then, Now, and the Future (3/3) Cycle Times 1988 1998 2003 Flow Devices Turnaround Time/ Labor (in hr.) Turnaround Time/ Labor (in hr.) Turnaround Time/ Labor (in hr.) Ducts Manifolds Valves 1988 1998 2003 Integrated Flow Path/ Installed Performance Turnaround Time/ Labor (in hr.) Turnaround Time/ Labor (in hr.) Turnaround Time/ Labor (in hr.) VentureStar (RLV) NASP (hypersonics) No capability 160 / 120 40 / 40 No capability 240 / 120 40 / 40 120 / 80 8 / 6 2 / 1 480 / 320 No capability 40 / 32 8 / 8 80 / 60 20 / 12Slide27: Believing the Predictions - Validation/Certification/CalibrationSlide28: Lessons Learned on Validation/Calibration/Certification A general code validation procedure applicable for all codes and applications is essential and can be developed Specific evaluation criteria are highly application dependent and it is not possible to define a single general set of validation criteria Quantitative validation is only meaningful within limited classes of applications The level of validation appropriate depends on the end application The validation process must be realistically achievable within the engineering environmentSlide29: Code Validation is Essential for Engineering Design Validation is essential part of code development process Must be performed to ensure that analysis results are sufficiently reliable and accurate for intended purposes Provides necessary confidence for code/analysis system to be used as engineering tool Process offers means to quantify Code accuracy Code sensitivities Validation is a learning process Systematic approach to understand code capabilities and behavior Helps to identify code strengths and weaknesses Specifics of validation process depend on end application and intended use of analysis resultsSlide30: Phase 1 Phase 2 Phase 3 Phase 4 Step 1 - Select Flow Cases Process Direction Unit Problems Benchmark Cases Subsystem Cases Complete System Two-Step Four Phase Validation Process Actual system hardware Complete flow physics All relevant flow features Limited test data with large uncertainity Most IC’s and BC’s unknown Subsystem or component hardware Moderately complex flow physics Multiple relevant flow features Test data with moderate uncertainity Some IC’s and BC’s measured Special hardware Two elements of complex flow physics Two relevant flow features Experimental data with moderate/low uncertainity Most IC’s and BC’s measured Simple geometry One element of complex flow physics One relevant flow feature Experimental data with low uncertainity or exact solution All IC’s and BC’s measured or known Phase 1 Phase 3 Step 2 - Validate Code Process Direction Unit Problems Benchmark Cases Subsystem Cases Complete System • Run unit problems • Verify integrity • Assess accuracy, convergence, & functionality • Run Benchmark Cases • Assess Physical Models • Establish Grid Distribution Requirements • Run simplified partial flow path • Assess agreement with data • Run Actual Configuration • Compare With Test Data Process Direction Phase 2 • Establish Grid Distribution Requirements Phase 4Validation Requirements Depend on Intended Use of Analysis Results: Validation Requirements Depend on Intended Use of Analysis Results Three design phases defined Conceptual - Initial definition concept layout Preliminary - Refined concept definition Detail - Final detailed design leading to hardware Different levels of code validation may be acceptable for each design phase Conceptual Predict qualitative behavior of flow and parametric trends Phase 1 and 2 validation acceptable Preliminary - Refined concept definition Conceptual plus quantitative predictions (wider range of uncertainty) Phase 3 validation required Detail - Final detailed design leading to hardware Preliminary plus improved quantitative predictions (reduced range of uncertainty) Phase 4 validation requiredSlide32: 2D Duct Boundary Layer Annular Flow with Rotation Flow Over Airfoil Acoustic Pulse Acoustic Duct Impeller Impeller/Diffuser Interaction Turbine Blade Cracking Phase 1 Phase 2 Phase 3 Phase 4 Validation Needed for New Application Completed Validation Building Block Approach Uses Completed Validation Cases for New Applications Rotor-Stator Interaction Acoustics in Complex DuctsSlide33: Looking into the Future - CFD Technology NeedsSlide34: Technology Needs (1/5) Preprocessing Defined as the process of going from CAD drawing to CFD geometry model and eventually to CFD mesh Most time consuming (> 65%) and labor intensive (>70%) phase of CFD analysis for most applications Can benefit from automating the mechanical portions of the process through better links, scripts, and templates Need Reliable geometry repair tools, unstructured grid generators for viscous flows & better coordination with solver developers for dynamic grid adaptation capabilitySlide35: Technology Needs (2/5) Solvers Performance of next generation solvers being developed is critical for CFD in industry Need Solvers that can use both structured and unstructured adaptive grids for steady-state and transient analysis with a 100X improvement in computational time Turnaround time has to be drastically reduced even though problems to be analyzed will be much more difficult Solvers have to be compatible with the scalable heterogeneous computing environment industry has adoptedSlide36: Technology Needs (3/5) Physical Models (Turbulence, Chemistry, Transition) Turbulence modeling a major issue Workhorse models of the 1-, 2-equation RANS variety Better performance by higher order RANS models not yet fully demonstrated on complex geometries Compressibility, heat transfer and transient flow issues not resolved Chemistry interaction modeling computationally very expensive For 100X solver speed-up, LES may be feasible for certain problems Chemistry modeling adequate for most applications Equilibrium and reduced kinetics models available for most fuels Reduced fast mechanisms needed for hydrocarbons Multiphase flow modeling still an art, but progress depends on availability of fast solvers for model testing Transition modeling generally not an engine concern (except for may be inlets) Need Robust and accurate turbulence modelsSlide37: Technology Needs (4/5) Postprocessing Defined as Diagnostic data interpretation Data reduction Graphics and visualization Data management and documentation Processing of the sheer size of data being generated already an issue and will get worse (e.g. transient analysis) Need Software that can efficiently and accurately access, reduce, manipulate, manage, and store data in a multi-platform hardware environmentSlide38: Technology Needs (5/5) Validation The quality data can come from many sources Analytical solutions Very high fidelity simulations (e.g. DNS) Benchmark experiments Subcomponent tests (e.g. impeller) Component tests (e.g. turbopump) System tests (e.g. complete engine) Lack of quality data for code validation biggest roadblock to more extensive use of CFD Need High quality experimental data and databases for code & model validation You do not have the permission to view this presentation. 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