The Advanced Fuel Cycle Initiative Overview of NEAMS Reactor Simulation Project Andrew Siegel...
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Transcript of The Advanced Fuel Cycle Initiative Overview of NEAMS Reactor Simulation Project Andrew Siegel...
The Advanced Fuel Cycle Initiative
Overview of NEAMS Reactor Simulation Project
Andrew Siegel
Argonne National Laboratory
NEAMS Reactor Meeting
May 19, 2009
NEAMS Reactor Workshop
NEAMS Campaign
20M total for FY09
Fast Reactor Simulation Component (~5.5M)
– Advanced Neutronics Modeling (ANL/INL): 3-4 FTEs
– Advanced Thermal Hydraulics Modeling (ANL/UIUC): 3-4 FTEs
– Advanced Framework Design (ANL/LLNL/UW): 3-4 FTEs
– Advanced Safety Modeling (ANL):1-2 FTEs
Other Program components
– IPSCs: Fuels (~6.5M), Separations (500K), waste forms (1M?)
– Cross cutting: V&V (2M), FMM (1M), ECT (500K), CT (500K)
NEAMS Reactor Workshop
Vision Develop process/methodologies to enable the use of computer
simulation in a fundamentally new way for operation, design, and licensing of nuclear systems.
Treat simulations as numerical experiments– Model physics instead of devices– Solve governing equations of motion on detailed 3-D grids– Do simulations prior to physical experiments --> downselect– Leverage massive computing power (petascale) + HPC expertise– Combine single-effects validation to infer behavior of integrated system
Goals– Reduce operating margins for existing designs– Explore innovative designs with minimal reliance on mock-up
experiments– Explore innovative materials for new and existing designs– Reduce regulatory cost
JFR DesignConcepts
NEAMS Reactor Workshop
Key physics models for fast reactor
Non-boiling Thermal Hydraulics
– Equations well known
– Some degree of subgrid-scale modeling generally required because of computational limitations (Re ~50K per channel)
• Many available SGS -- what is good enough for problems of interest?
• Most not developed for low-Pr flows
– Meshing issues
– Improving scalability to leverage leadership class machines
– Application to specific problems: understanding sensitivities for fast-reactor specific problems
– Embedded sensitivity analysis challenging
– initial problems: rod bundle mixing, pressure drop, upper plenum mixing, shut down heat removal
NEAMS Reactor Workshop
Key physics for fast reactor, cont.
Neutron transport
– Equations well known
– Very mature field
– Non-homogenized deterministic solutions not possible due to computing limitations
– Monte Carlo simulations still not practical for most design studies because of computing limitations
– Reducing/eliminating homogenization important for high-fidelity coupling, reducing uncertainties (particularly for new designs)
– When does data uncertainty swamp method uncertainty?
– Work on efficient algorithms, highly scalable algorithms, application to benchmark problems
NEAMS Reactor Workshop
Key physics for fast reactor, cont.
Structural mechanics
– Critical for accurate modeling of fast reactor passive safety
– Constitutive models/basic properties exist for well known materials in ideal conditions
– Potential to use lower-length-scale modeling to derive better constitutive relations
– Long-term material strength irradiation damage/thermal load issues that can potentially be studied with more fundamental modeling
Fuel
– Dynamical equations not well known
– From reactor standpoint critical to characterize properties accurately
– Legacy codes (LIFE-Metal) ok for near term
– Strong interaction with fuels modeling team necessary longer-term
NEAMS Reactor Workshop7
445TF/s / 557 TF/s64 TB / 80TB
BG/P SupercomputerAt Argonne
Top 500 List of Supercomputers
NEAMS Reactor Workshop
Integrated Performance and Safety Code
Ultimately must be capable of performing all necessary design and safety calculations -- massive effort
– Safety: DBA, BDBA (ULOHS, UTOP, ULOF)– Includes entire plant -- core, vessel, pumps, heat exchangers, …– Design: fuel cycle analysis, hot channel analysis, peak temperature, etc.
First principles calculation impossible for full-device simulations
Multi-scale approach uses detailed local simulations to derive specific parameterizations for full-device models.
Also study specific local phenomena by embedding high-fidelity solver in coarser calculation
Start by advanced methods development, validation/verification and exploration
9Work conducted byANL for the GNEP
Spatial domain (mesh) hub for coupling– Bulk of data there– Performance most sensitive there
Function interfaces (APIs), not data structures– Fewer code dependencies
Simplify connection of components, to allow horizontal, vertical integration– Take advantage of Science improvements– Components don't need to cede control– Flexibility to take best tool for each task– Finer-grained pieces give more options
Framework philosophy
May 2, 2009 JAEA Visit 11
Current development path– Highly-scalable high-order
LES/DNS • Supplemented initially with
commercial RANS, legacy lower resolution models
– Fast-running low resolution methods (sub-channel models)
• To provide rapid turn around for engineering design
– Highly-scalable high-order RANS
– RANS-informed lower resolution models
– LES-informed RANS models
– DNS-informed LES models
Lower Resolution Models(~750 points/channel)
Multi-Resolution Thermal Hydraulic Simulation Hierarchy
BoundaryConditions
ModelingParameters
Reynolds Averaged Navier Stokes(~20 K point/channel)
BoundaryConditions
ModelingParameters
Large Eddy Simulation(~5 M points/channel)
BoundaryConditions
ModelingParameters
Direct Numerical Simulation(~50 M points/channel)
Incr
easi
ng
Res
olu
tion
Increasin
g Dom
ain S
izeMulti-Resolution Approach
May 2, 2009 JAEA Visit 13
Adaptive Flux Solution Options
Homogenized assembly
Homogenized assembly internals
Homogenized pin cells
Fully explicit assembly
Unified geometrical framework
– Unstructured finite element analysis for coupling with structural mechanics and thermal-hydraulics codes
15
Comparison Between RANS and Subchannel Results
Axially-independent cross flow terms used in the subchannel model are not able to resolve the axial periodicity in the temperature due to the wire wraps (see arrows).
Temperature distribution is symmetric in the subchannel results, but skewed in the RANS results. (Unanticipated bias)
Cross flow terms from higher-fidelity modeling would result in better agreement between subchannel and RANS.
Differences Between Steady-State Subchannel and RANS Coolant Temperature Distributions in a 217-Pin Fuel Bundle.