Transcript RANS-based CFD Simulations of Wire-Wrapped Fast

Advanced Thermal
Hydraulics Simulation
– Part II
David Pointer
Carlos Pantano - UIUC
Jeff Smith
Hank Childs – LLNL
Adrian Tentner
Paul Fischer
James Lottes
Aleks Obabko
Yulia Peet
Andrew Siegel
- Argonne National Laboratory
RANS-based simulations
 Commercial CFD codes STAR-CCM+ and STAR-CD
– Finite volume solution of the well-known Reynolds-averaged form of
the Navier-Stokes equations.
 Second order solution using
 Face flux based differencing (COMET)
 SIMPLE predictor-corrector solution algorithm
 Algebraic multi-grid pre-conditioning
 two-equation realizable k-epsilon turbulence model
2
Allowed Mesh Types in Star-CCM+
 Radial cross-sections showing computational mesh distributions in the 7-pin
RANS simulations for:
– (a) the block-structured mesh
– (b) the trimmed cell mesh
– (c) the generic polyhedral mesh.
3
Allowed Mesh Types in Star-CCM+
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LES vs RANS
 Comparison of velocity magnitude distributions
 LES
 RANS
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Initial Comparison of LES / RANS Results
 RANS using Star CD k-eps
 Close comparison of results  RANS can predict cross-flow
velocities in the wire-wrap case.
 Pressure-drop comparisons underway.
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Allowed Mesh Types in Star-CCM+
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19-pin simulations
 Relative transverse velocity magnitude
8
Comparison of 3 Reynolds Numbers
Relative transverse velocity magnitude
Re = 6000
Re=9000
Re=50000
37-pin Simulations
Relative transverse velocity magnitude
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Predicted Dimensionless Pressure Loss
Coefficient from RANS Simulations vs.
Correlations
 The dimensionless pressure loss coefficient is the pressure drop
normalized by the dynamic head, so that Cp=f (L/D).
 The Cheng & Todreas correlation assumes that there are three
fundamental sub-channel types: interior, edge, and corner. Each of the
three types of sub-channel frictional losses is calculated separately. The
bundle friction factor is then averaged.
 The Rehme correlation is a simpler single equation formulation based on
representative geometric parameters.
Number of
Pins
7*
19
37
Cheng &
Rehme
Todreas
Correlation
Correlation
1.116 ± 14% 1.179 ± 5%
1.088± 14%
1.041 ± 5%
1.075 ± 14%
0.943 ± 5%
RANS
Simulation
Prediction
2.282
1.199
1.059
* Small 7-pin assemblies are not within the range of applicability of the correlations
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217-pin heated assembly
 Defined a “typical” SFR assembly for
initial comparisons between CFD code
predictions and SASSYS subchannel
model predictions
– 217 pins
•
•
•
•
8 mm pin outer diameter
Pitch-to-diameter ratio of 1.135
1.03 mm diameter wire wrap
20 cm wire wrap lead length
– Assumed power distribution
• Uniform radial power
• Cosine axial distribution
– Simplified boundary conditions
• Uniform inlet velocity
– 5.8 m/s
• Constant pressure outlet
• Specified wall heat flux on pin surfaces
• Adiabatic can surface
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Axially coarsened polyhedral meshes
Nominal Cell
Aspect Ratio
Number of Cells
Predicted
Pressure Loss
(kPa)
1:16
7507243
76.01
1:8
9769722
77.00
1:4
14955523
82.01
Changes in pressure loss are mostly form losses, coarsening of surface representation may be introducing artificial surface roughness.
13
Simplifed wire wrap representation
 Minimal effect on flow field
– Slight increase in size of low velocity region on leeward side of wire
Transverse velocity magnitude
(inlet velocity = 5.8 m/s)
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217 pin SFR Assembly simulation
Polyhedral mesh with simplified wire wrap representation
 Coolant Temperature (K)
 Pin Surface Temperature (K)
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217 pin SFR Assembly simulation
Polyhedral mesh with simplified wire wrap representation
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MAX – A Thermal Mixing Experiment
 LDRD funded project
– Define validation requirements
for high-fidelity methods
– Evaluate/Demonstrate
advanced measurement
capabilities
– Develop methods for analysis
and correlation of large 4-D
data sets
• 10-100 TeraBytes per test
– Develop methods and
visualization capabilities for
validation comparisons of
detailed 4-D data
– Provide data set for initial
validation of individual
advanced methods and
integrated multi-scale code
systems
RANS Simulations of MAX Thermal Mixing Experiments
 The computational model of the
nominal geometry was developed
from a simplified CAD
representation
 The surfaces defined by the CAD
model are triangulated and used
as the basis for a tetrahedral
mesh.
 The tetrahedral are then collapsed
into generic polyhedra to form the
mesh shown.
 Boundary Conditions
– uniform velocity, constant
temperature inlets
– constant pressure outlet
– no-slip adiabatic walls
 Short turn-around time allows
RANS to be applied to
configuration studies
RANS Simulations of MAX Thermal Mixing Experiment
 Steady state simulations
– default segregated flow solver
– SIMPLE algorithm
– Rhie- Chow interpolation for
pressure- velocity coupling
– algebraic multi-grid preconditioning.
– 1st-order upwind differencing scheme
– secondary gradient terms in the
diffusion step were retained
– Realizable k-epsilon turbulence model
with a two-layer all y+ wall treatment
(Norris & Reynolds)
 RANS simulations predict the development
of a very sharp interface between the two
jets
 Complex mixing pattern in the surrounding
fluid after the jets have impinged on the
upper surface.
Extracted Data
 To facilitate quantitative comparisons of characteristic data from simulations
of different design options, data was extracted along lines at the mid-plane
of the “fish tank”
Extracted Data - Nominal Configuration
Mesh resolution studies
1.4
Finer
Velocity Magnitude (m/s)
1.2
Fine
Nominal
1
Coarse
Coarser
0.8
0.6
0.4
0.2
0
-1.4
-0.9
-0.4
Position (m)
0.1
0.6
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MAX Experiment for TH Validation
 Initial RANS / LES Comparisons:
– Average velocity distributions on two centerline cuts
• RANS: 2 million gridpoints, steady state
• LES: 23 million gridpoints, unsteady (still in initial transient)
– TKE comparisons similar
A
B
A
B
Pointer, Lomperski, Fischer., Validation of CFD Methods for Advanced SFR
Design: Upper Plenum Thermal Striping and Stratification, ICONE17-75740,
2009
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Other Leveraged Efforts
 Very High Temperature Reactor Integrated Multi-Physics Simulation
 2-Phase Boiling Model
 Coarse Finite Element Design Simulations
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VHTR Single Fuel Block Column
 Completed coupled CFD/Neutronics
simluations of a single column of
prismatic VHTR fuel blocks
– DeCART 2D/1D MOC
– STAR_CD Steady RANS
 CFD model uses 8.8 million
computational cells
– Polyhedral elements allow
conformal meshing of solid and
fluid components
• Improved numerical
performance for conjugate heat
transfer
– Includes upper and lower plenum
volumes
– Flow splits between channels are
simulated rather than specified
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DeCART/STAR-CD Mesh Mapping
 Initial mapping utility uses a simple approach in which DeCART zones are
associated with all STAR-CD cells whose centroid falls within that zones.
 Global conservation is enforced within any single material across the entire
domain
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Coupled Full Block Model Results
T
q’’’
 Power distribution from DeCART,
reflects temperature feedback
from CFD
 Temperature feedback
exaggerated, due to greatly
increased F/M ratio for single
block
 After CFD initialization, coupled
simulation required 4.2 hours on
32 cores for 9 data exchanges
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2-Phase Boiling CFD
 Generation 1:
• Bubbly flow topology used in all cells.
• Spherical vapour bubbles surrounded
by continuous liquid phase.
• Used for previous BFBT calculations
 Generation 2:
• Bubbly flow, Mist flow and Transition
topologies
• Bubbly flow topology: Spherical
bubbles surrounded by liquid
• Mist flow topology: Spherical droplets
surrounded by vapor
• Preliminary liquid film models
• Used for current BFBT calculations
 Generation 3:
• Bubbly flow, Mist Flow, Transition,
and Sharp Interface topologies
• Uses 2-D Topology Map based on α
and α gradients
• Inter-phase surface transport planned
• Developed jointly by Adapco,
Argonne, Sarov Labs, VNIIEF
BFBT BWR Benchmark Simulation Results
Exit Quality = 25%
Microscopic
Distribution
(CT Scan
Data)
Channel
Averages
(Calculated
from CT
Scan Data)
Predicted
void fraction
Percent Error
Predicted
void fraction
Percent Error
Coarse Finite Element Design Simulations
 Solve ConvectionDiffusion
 Use imposed flow field
based on RANS or LES
simulations
 Relatively fast running
– A few minutes on a
few hundred nodes
 High-order numerical
accuracy
 High-order spatial
accuracy
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Duplicate spacer grid design experiment methodology
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Off-Set Injection Point
No Spacers
Effect of
Nominal Spacer
Effect of Spacer
With 0.5 * H/D
Thermal
Diffusion x 2
Thermal
Diffusion x 4
32
CONCLUSIONS – RANS (and other)
 The applicability of commercial RANS-based CFD tools to hydrodynamic
analysis of wire-wrapped sodium-cooled fast reactor fuel assemblies has been
demonstrated
 RANS-based CFD predictions compare well with LES predictions
 Sensitivity of predictions to Reynolds number is low
– Re=9000 is probably sufficient for hydrodynamic studies
 Broad axial and radial mesh density sensitivity studies have been completed for
7-, 37-, and 217-pin models
 Sensitivity of bulk predictions to mesh structure is low, but mesh structure
impacts resolution of jet structures and recirculation regions on leeward side of
pins.
 Completed initial benchmarking study comparing predicted pressure drop versus
lumped parameter correlations and experimental data
 Completed study comparing predicted temperature distributions versus
conventional sub-channel models based on lumped parameter correlations
 Demonstrated initial course mesh conduction diffusion solver
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Current/Future Work – RANS (and other)
 Comparisons with legacy experimental data
in progress
– Turbulent diffusion in HEDL experiments
 217 pin simulations with conjugate heat
transfer in fuel, cladding and sodium bond
gap
 Simulations of alternate spacer options
– Engineered can walls
– Reduced diameter edge row wire wrap
 Implementing thermophysical property
functions for liquid sodium, clad and fuel.
 Beginning to extend simulations to ex-core
regions
 Initiate development of standalone finite
element subchannel simulation tool and finite
element network flow solver
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Questions?
35
Extra Slides
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Central Injection Point
No Spacers
Effect of
Nominal Spacer
Effect of Spacer
With 0.5 * H/D
Thermal
Diffusion x 2
Thermal
Diffusion x 4
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Side Channel Injection Point
No Spacers
Effect of
Nominal Spacer
Effect of Spacer
With 0.5 * H/D
Thermal
Diffusion x 2
Thermal
Diffusion x 4
38