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CASL: Consortium for the Advanced Simulation of Light Water Reactors
A DOE Energy Innovation Hub
Achievements in Addressing Challenges Facing the Light Water Reactor Industry
Dave Pointer, PhD. Deputy Lead, Thermal Hydraulics Methods
Oak Ridge National Laboratory
for
Dave Kropaczek, PhD.CASL Chief Scientist
North Carolina State University
2
CASL was the first DOE Energy Innovation Hub• Established by Former DOE Energy
Secretary Steven Chu• Modeled after the scientific management
characteristics of Manhattan Project and AT&T Bell Labs:– Addressing critical problems– Combines basic and applied research with engineering– Integrated team to take discovery to application
• Four Hubs are in operation
For more info: http://energy.gov/science-innovation/innovation/hubs
“Multi-disciplinary, highly collaborative teams ideally working under one roof to
solve priority technology challenges”
– Steven Chu
3
CASL’s Mission is to Provide Leading-Edge M&S Capabilities to Improve the Performance of Operating LWRs
VISIONPredict, with confidence, the performance and assured safety of nuclear reactors, through comprehensive, science-based M&S technology deployed and applied broadly by the U.S. nuclear energy industry
GOALS• Develop and effectively apply modern virtual reactor technology• Provide more understanding of safety margins while addressing
operational and design challenges• Engage the nuclear energy community through M&S• Deploy new partnership and collaboration paradigms
4
CASL is a National Laboratory, Industry, University Partnership
Core Physics, Inc.
CASL Founding Partners
CASL Contributing Partners
International Collaborators
5
CASL Scope: Develop and apply a “Virtual Reactor” to assess fuel design, operation, and safety criteria• Deliver improved predictive simulation
of Light Water Reactors– Focus on fuels, vessel, internals– First five year focus on PWRs, broadened to BWR and Light
Water Small Modular Reactors• Execute work in five technical
focus areas to:– Equip the Virtual Reactor with necessary physical models and
multi-physics integrators– Build the Virtual Reactor with a comprehensive, usable, and
extensible software system – Validate and assess the Virtual Reactor models with self-
consistent quantified uncertainties
Focus on Addressing Challenge Problems to Drive Development and Demonstration
6
Virtual Environment for Reactor Applications
7
M&S Key Aspect - Multi-Physics Coupling
With rigorous representation of physics feedback, simulations yield higher confidence predictions of core performance
Thermal Hydraulics
Neutronics
Fuel Performance
Fluid Temperature
Fluid Density / Void BISON
MPACT
COBRA-TF
Neutronic Power
Gamma Heating
Boron Concentration
Fuel Temperature
Clad Heat Flux
Clad Surface Temperature
MAMBA
Crud Thickness
Crud Composition (Boron)
Crud Thermal Resistance
Chemistry
APR1400 VERA Simulation
8
CASL Challenge Problems are Focused on Key Industry Reactor Performance Areas
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Application – Watts Bar 2 Initial Reactor Startup Predictions• Completed and independently verified the VERA
model in early 2016, based on input from TVA and Westinghouse
• Performed zero power physics tests calculations in March, three months prior to startup– Critical boron concentration– Control bank reactivity worths– Isothermal Temperature Coefficient
• Comparisons also made with results from Westinghouse design methods
• Performed full core SDM calculations in support of requests from TVA
• Provided increased confidence in predictions from NRC licensed design codes
HZP BOC Fission Rate Distribution in WB2
Worked performed by: J. Ritchie1 A. Godfrey2
1 Tennesee Valley Authority 2 Oak Ridge National Laboratory
10
– Dec. 2015 – Fuel Load– May 23, 2016 – Initial criticality– June 3, 2016 – On the power grid; Begin power ascension testing– August 30, 2016 – Reactor trip from 99% power (transformer fire)– September 30, 2016 – Power Ascension Testing completed– October 19, 2016 – Full power commercial operation
Watts Bar Nuclear Plant – Unit 2
• Spring City, TN• First new nuclear plant in
U.S. since 1996 (WBN1)• Traditional four-loop
Westinghouse PWR• 3411 MWth initial rated
thermal power• Current burnup:
~50 EFPD
Image courtesy of TVA
Notable Dates:
11
Power History for PAT
Turbine generator coupling making excessive noise (5/28/2016)
Automatic trip and safety injection on steam pressure low (6/5//2016)
Automatic trip from Lo-Lo level in number 4 steam generator(6/20/2016)
Planned 10% load rejection
Manual trip due to low steam generator levels caused by a loss of feedwater flow from main feedwater pump (8/23/2016)
Planned loss of offsite power trip from 30% (7/14/2016)
Loss of bushing cooling due to excessive hydrogen leak, unable to exceed 75% power
Turbine trip from a main bank transformer failure (8/30/16)
50% load rejection
Turbine trip (6/26/2016)
Planned trip from outside of MCR (8/3/2016)
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0.6% 0.8%
3.1%
-0.7%
3.1%
0.8% 1.0%
-0.7%
0.9%
-10%
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
10%
D C B A SD SC SB SA Total
Bank
Wor
th D
iffer
ence
(%)
RCCA Bank
Startup Results*Measured MPACT
DifferenceShift
DifferenceInitial Critical Boron Concentration (ppmB) 1089 -14 -2
Isothermal Temperature Coefficient (pcm/ºF) -5.31 -0.15 --
Total Worth Error < 1%
*Measurements courtesy of TVA
Control Bank Worths
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Zero Power Criticality Measurements • Criticality Measurements taken at hot-zero-power
conditions following shutdowns• Includes various Bank D positions and transient Xenon-
135 conditions
-14 -16 -17 -17-20 -20
-22 -23-18
-13
-2-6 -7 -6
-9 -9-12 -13
-8-3
-50
-40
-30
-20
-10
0
10
20
30
40
50
Boro
n Co
ncen
tratio
n Di
ffere
nce (
ppm
)
MPACT
SHIFT
= -18 ± 3.4 ppm
= -8 ± 3.6 ppm
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VERA Boron Concentrations
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
650
700
750
800
850
900
950
1,000
1,050
1,100
1,150
5/23 5/30 6/6 6/13 6/20 6/27 7/4 7/11 7/18 7/25 8/1 8/8 8/15 8/22 8/29 9/5 9/12 9/19 9/26
Core
Pow
er (%
)
Solu
ble B
oron
Con
cent
ratio
ns (p
pmB)
Date
MeasuredVERAPower
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VERA Runtime Performance• Each quarter-core calculation has used 4234 cores on
OLCF’s Eos supercomputer
• Analysis :– 31 jobs– 3,047 hourly statepoints– 15,526 complete MPACT/CTF converged iterations– 13.3 days continuous wall time– 1.3 million core-hours – ~6 mins per statepoint
OLCF’s TITAN Supercomputer at Oak Ridge National Laboratory
16
Application - AP1000 ® PWR Advanced Core Analysis– Advanced core configuration for optimum fuel cost
and equilibrium cycle transition –Rodded depletion with MSHIMTM operation
– Excellent benchmarking opportunity for VERA with state-of-the-art in PWR core design and operation
AP1000 Sanmen site - China
Worked performed by: F. Franceschini1 D. Salazar1 A. Godfrey2
1 Westinghouse Electric Company LLC 2 Oak Ridge National Laboratory
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AP1000® PWR Advanced First Core
MSHIM BOC Power Distribution
High-resolution VERA model of the AP1000 PWR Advanced Core
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• Low Power Physics Tests (BOC)– Key startup parameters (initial critical boron, boron worth, ITC)– Rod worth
• Rod Swap and/or DRWM• Gray rods (tungsten) predictions are key• Integral and differential rod worth
• Excellent agreement for VERA vs. CE Monte-Carlo – Confirmed Westinghouse in-house predictions (nodal diffusion)
VERA simulations supporting AP1000
MA MB
MC
MD
M1
M2
AO
S1
S2
S3
S4
-15%
-10%
-5%
0%
5%
10%
15%
SHIFT MPACT Nodal Diffusion
SHIFT VERA Nodal Diffusion
HZP Critical Boron +3ppm
-9 ppm
+18 ppm
Isothermal Temp. Coeff.
-0.3pcm/F
+0.8pcm/F
+0.3pcm/F
Delta Boron and ITC vs. KENODelta Rod Worth (%) vs. KENO
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CRUD-induced power shift (CIPS)• Deviation in axial power shape
– Cause: Boron uptake in CRUD deposits in high power density regions with subcooled boiling
– Affects fuel management and thermal margin in many plants• Power uprates will increase potential for CRUD growth
Need: Multi-physics chemistry, flow, and neutronicsmodel to predict CRUD growth
CRUD deposits
CR
UD
mas
s ba
lanc
e
Thot
Tcold
Crud deposited or released by
particle and soluble mass
transfer
Crud carried over from prior cycles,
available for release
Dissolved and particulate corrosion products circulate in
coolant
Nickel/ironreleased by corrosion
-20-15-10
-505
1015
0 5000 10000 15000 20000Cycle Burnup (MWD/MTU)
Axial
Offs
et (%
)
Measured AOPredicted AO
20
Application - Perform Core Design and CIPS Analysis of a Future Core Design and Compare to Industry Risk Analysis• Project with collaboration with Duke Energy
investigating application of VERA to Catawba Unit 2, Cycle 22 (current cycle)
• Industry CIPS Risk Analysis Follows EPRI Guidelines – Does not directly assess impact on CIPS on key parameters - axial offset, shutdown margin, etc.
• CASL simulation first of a kind direct analysis of CIPS axial offset for three core designs –Explicitly including the feedback of of boron on power distribution and calculating A/O
• Shows more aggressive core designs may be acceptable
Worked performed by: T. Lange1 J. Young2 B. Black2
1 University of Tennessee2 Duke Energy
21
Catawba Nuclear Station
• Catawba Nuclear Station– York, SC outside of Charlotte
• Two Unit Westinghouse 4-loop PWR– Unit 1 currently on cycle 23– Unit 2 beginning cycle 22
• Duke performs all core designs and safety analyses (except LOCA)
• Cycle 22 design efficiency limited by perceived risk of CRUD-Induced Power Shift (CIPS)
22
VERA Radial Boron Comparison305 cm high @ 350 EFPD
Low Risk Medium Risk High Risk
23
Additional Axial Offset vs. Core Crud Boron
BOA Risk Level Max Core Crud Boron Additional AO Normalized Additional AOLow Risk 0.292 -1.75% * 0.00%Medium Risk 0.350 -2.03% 0.28%High Risk 0.410 -2.36% 0.61%
* Historical BOA risk analysis(0.3 lbm => -1.50% Additional AO)
Exceeding established CRUD boron thresholds results in marginal Additional AO when feedback incorporated
24
Departure from nucleate boiling (DNB)
• Local clad surface dryout causes dramatic reduction in heat transfer during transients (e.g., overpower and loss of coolant flow)
• Current limitations:– Absence of detailed pin modeling in TH
methods results in conservative analysis– Detailed flow patterns and mixing
not explicitly modeled in single- and two-phase flow downstream of spacer grids
• Power uprates require improved quantification of margins for DNB or dryout limits
Need: High-fidelity modeling of complex flow and heat transfer for all pins in core downstream of spacer grids
Boiling Curve
25
Application - Simulation of Steamline Break without offsite power (DNB Event)• Hot Zero Power Steamline Break (HZP SLB) is a cooldown event that
challenges fuel thermal limit (e.g. DNB)– Increased steamflow Reduced RCS temperature and pressure
Positive reactivity insertion Reactor core power and peaking factor increase DNB challenge
– Condition 4 event analyzed to meet Condition 2 acceptance criteria• HZP SLB cases considered in plant safety analysis
– With offsite power available and Reactor Coolant Pumps (RCPs) in operation (high flow)
– Without offsite power and natural circulation (low flow)• Problem statement:
– Which HZP SLB case is more DNB limiting, high or low flow?– Analysis of low flow case requires more effort and cost, if it is the
limiting case with respect to DNB
Work performed by: C. S. Brown1, H. Zhang2, V. Kucukboyaci3, Y. Sung3
1 North Carolina State University2 Idaho National Laboratory3 Westinghouse electric Corporation
VERA-CS 4-Loop Core Model• 56,288 channels
• 112,064 gaps • 50,952 fuel rods, 4,825 GT/IT
• ~60 axial nodes
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Study of HZP Steamline Break DNB Limiting Case
• Study based on CASL codes and technology developed and ready for application– Quasi-steady state VERA-CS
(MPACT/CTF) for high resolution full core modeling and simulation
– Core inlet temperature and flow distributions based on CFD modeling and simulation
– Sensitivity and Uncertainty quantification for limiting case determination (59-case study)
• VERA-CS coupled code predictions confirmed high flow case is more DNB limiting than low flow case
High Flow – VERA Pin Powers High Flow – VERA Core Tcoolant
CFD Inlet Temperature & FlowSTAR-CCM+ Vessel Modeling
27
SLB Hot Channel Parameter Comparisons
VERA-CS based process demonstrated for future plant specific application
High flow case is more DNB limitingthan low flow case due to higher heat flux
Parameter High-Flow Low-FlowW-3 DNBR (Wilks 95/95) 3.42 4.12
DNB Limiting Elevation (cm) 45.9 30.5
Max. Pin Linear Power (W/cm) 264.3 178.5
Heat Flux (W/m2) 801.4 558.7Equilibrium Quality -0.047 -0.114Mass Flux (kg/m2/s) 4529.1 466.9
28
Pellet-Clad Interaction (PCI)• PCI failure potential limits reactor performance associated with power uprates, higher burnup, fuel rod
manufacturing quality and operating flexibility during power changes• Requires new 3D multi-physics simulation capability to reduce uncertainties in assessing PCI failure
conditions during normal operation and in the presence of anomalies
Need: 3D fuel performance model to assess complex, coupled physics and irregular geometries responsible for PCI fuel failures
PCI is controlled by local effects
PCI is possible in many rods and
assemblies
PCI has system wide influence
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Cycle 9
Cycle 12
Application – Braidwood C10 & C13 PCI Failure Analysis
• Make use of the characteristics of Cycle 10 failed rod (M12S-B06), which exhibited MPS-PCI class of failure, to characterize or predict Cycle 13 failure (U22S-D03)
• Determine the minimum pellet defect (MPS) size required to exceed the stress failure threshold limit
Rod Characteristics M12S-B06 U22S-D03 UnitsFluence 5.62e25 5.68e25 n/m2
Plenum Pressure 7.57 7.00 MPaPellet-Clad Gap 17.8 17.8 micron
Rod Average Burnup 30.6 30.4 MWd/tUPeak Stress Axial
Location1.3 .8 m
Cycle 10
Cycle 13
Worked performed by: N. Capps1 J. Rashid1 B. Wirth2
1 Structural Integrity Associates2 University of Tennessee
30
-120
-100
-80
-60
-40
-20
0
20
40
0 50 100 150 200 250 300 350 400 450 500
Cri
tica
l B
oro
n D
iffe
ren
ce (
pp
m)
Cycle Burnup (EFPD)
Cycle 1
Cycle 2
Cycle 3
Cycle 4
Cycle 5
Cycle 6
Cycle 7
Cycle 8
Cycle 9
Cycle 10
Cycle 11
Cycle 12
Trend
BISON Fuel Failure Analysis Methodology
Model Multiple Cycles
Run Bison for Every Pin
Select Pins of Interest
• A methodology for analysis of PCI challenge problem with VERA has been implemented and demonstrated:– Perform 2D (R-Z) fuel performance simulations to screen ever rod in the core for PCI
indicators – Selected pins of interest and perform 3-D (R-θ-Z) or 2-D (R-θ) Local Effects Analysis– Assess PCI risk based on stress failure thresholds (determined from 3-D or 2-D)
Local EffectsAnalysis
31
Stress Analysis of C13 U22S-D03 Failed Rod
PCI 60 mil MPS2 3 4 5 2 3 4 5
C 306 316 315 412 418 418D 317 307* N/A 309 406 418* N/A 416E 308 305 306 400 406 420
PCI 60 mil MPS2 3 4 5 2 3 4 5
C 407 416 416 495 480 498D 413 415* N/A 403 480 494* N/A 493E 412 412 410 483 482 493
2-D R-θ stress results in MPa
3-D R-θ stress results in MPa
• The surrounding rods have similar calculated stresses and did not fail, therefore, an external factor must have contributed to the failure
Cycle 10
Cycle 13
Cycle 10
Cycle 13
Clad stress is related to the fuel centerline temperature which is directly related to the startup power history
32
Strategic Applications of VERA• Commercial power industry
– NSSS and Fuel Vendors: new plant and fuel design– Owner / Operators: independent evaluation, margin enhancement, issue evaluation, backstop for licensing– EPRI: uprate, aging and issue evaluations– Consultants and support industry: tools for utility support
• US Naval reactors has requested a copy of VERA• Research and academia
– VERA is being deployed as an education tool for new engineers (currently 6 universities are using)– VERA is being adopted by universities as a research tool– Potential experimental collaboration with research reactors– VERA’s framework can support evaluation of certain Accident tolerant fuel concepts, including Mo clad
• NRC has expressed interest in VERA and is initiating a Test Stand
CASL Tools Can Support Delivering the Nuclear PromiseThrough Improved Fuel Performance & Reduced Fuel Cost
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www.casl.gov
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