CASL: Consortium for the Advanced Simulation of Light Water Reactors A DOE Energy Innovation Hub

Transcription

1 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 Multi-disciplinary, highly collaborative teams ideally working under one roof to solve priority technology challenges Steven Chu For more info: 2

3 CASL s Mission is to Provide Leading-Edge M&S Capabilities to Improve the Performance of Operating LWRs VISION Predict, 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 3

4 CASL is a National Laboratory, Industry, University Partnership International Collaborators CASL Founding Partners Core Physics, Inc. CASL Contributing Partners 4

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 selfconsistent quantified uncertainties Focus on Addressing Challenge Problems to Drive Development and Demonstration 5

6 Virtual Environment for Reactor Applications 6

7 M&S Key Aspect - Multi-Physics Coupling Thermal Hydraulics Fluid Temperature Fluid Density / Void COBRA- TF BISON Fuel Performance Fuel Temperature Clad Heat Flux Clad Surface Temperature Neutronics Chemistry Neutronic Power Crud Thickness Gamma Heating Crud Composition (Boron) Boron Concentration MPACT MAMBA Crud Thermal Resistance APR1400 VERA Simulation With rigorous representation of physics feedback, simulations yield higher confidence predictions of core performance 7

8 CASL Challenge Problems are Focused on Key Industry Reactor Performance Areas 8

9 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. Ritchie 1 A. Godfrey 2 1 Tennesee Valley Authority 2 Oak Ridge National Laboratory 9

10 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 MW th initial rated thermal power Current burnup: ~50 EFPD Notable Dates: Dec 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 Image courtesy of TVA 10

11 Power History for PAT 50% load rejection 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) Turbine trip (6/26/2016) Planned loss of offsite power trip from 30% (7/14/2016) Planned 10% load rejection 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) Manual trip due to low steam generator levels caused by a loss of feedwater flow from main feedwater pump (8/23/2016) Turbine generator coupling making excessive noise (5/28/2016) Planned trip from outside of MCR (8/3/2016) 11

12 Startup Results* Measured MPACT Difference Shift Difference Initial Critical Boron Concentration (ppmb) IsothermalTemperature Coefficient (pcm/ºf) % 8% Control Bank Worths 6% Bank Worth Difference (%) 4% 2% 0% -2% -4% 0.6% 0.8% 3.1% -0.7% 3.1% 0.8% 1.0% -0.7% 0.9% -6% -8% Total Worth Error < 1% -10% D C B A SD SC SB SA Total RCCA Bank *Measurements courtesy of TVA 12

13 Zero Power Criticality Measurements Criticality Measurements taken at hot-zero-power conditions following shutdowns Includes various Bank D positions and transient Xenon- 135 conditions MPACT = -18 ± 3.4 ppm Boron Concentration Difference (ppm) SHIFT = -8 ± 3.6 ppm

14 VERA Boron Concentrations 1,150 Measured VERA 1,100 Power 100% 90% 1,050 80% 1,000 70% Soluble Boron Concentrations (ppmb) % 50% 40% 30% Core Power (%) % % 650 0% 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 Date 14

15 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 15

16 Application - AP1000 PWR Advanced Core Analysis Advanced core configuration for optimum fuel cost and equilibrium cycle transition Rodded depletion with MSHIM TM 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. Franceschini 1 D. Salazar 1 A. Godfrey 2 1 Westinghouse Electric Company LLC 2 Oak Ridge National Laboratory 16

17 AP1000 PWR Advanced First Core High-resolution VERA model of the AP1000 PWR Advanced Core MSHIM BOC Power Distribution 17

18 VERA simulations supporting AP1000 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) 15% Delta Rod Worth (%) vs. KENO Delta Boron and ITC vs. KENO 10% 5% 0% MC M2 AO S2 S4 HZP Critical Boron SHIFT +3 ppm VERA -9 ppm Nodal Diffusion +18 ppm -5% -10% -15% MA MB M1 S1 S3 MD SHIFT MPACT Nodal Diffusion Isothermal Temp. Coeff pcm/f +0.8 pcm/f +0.3 pcm/f 18

19 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 CRUD deposits Axial Offset (%) Measured AO Predicted AO Cycle Burnup (MWD/MTU) CRUD mass balance T hot T cold Crud deposited or released by particle and soluble mass transfer Dissolved and particulate corrosion products circulate in coolant Crud carried over from prior cycles, available for release Nickel/iron released by corrosion Need: Multi-physics chemistry, flow, and neutronics model to predict CRUD growth 19

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. Lange 1 J. Young 2 B. Black 2 1 University of Tennessee 2 Duke Energy 20

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) 21

22 VERA Radial Boron Comparison 305 cm 350 EFPD Low Risk Medium Risk High Risk 22

23 Additional Axial Offset vs. Core Crud Boron BOA Risk Level Max Core Crud Boron Additional AO Normalized Additional AO Low Risk % * 0.00% Medium Risk % 0.28% High Risk % 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 23

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 Boiling Curve Need: High-fidelity modeling of complex flow and heat transfer for all pins in core downstream of spacer grids 24

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 VERA-CS 4-Loop Core Model 56,288 channels 112,064 gaps 50,952 fuel rods, 4,825 GT/IT ~60 axial nodes Work performed by: C. S. Brown 1, H. Zhang 2, V. Kucukboyaci 3, Y. Sung 3 1 North Carolina State University 2 Idaho National Laboratory 3 Westinghouse electric Corporation 25

26 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 STAR-CCM+ Vessel Modeling CFD Inlet Temperature & Flow High Flow VERA Pin Powers High Flow VERA Core T coolant 26

27 SLB Hot Channel Parameter Comparisons High flow case is more DNB limiting than low flow case due to higher heat flux Parameter High-Flow Low-Flow W-3 DNBR (Wilks 95/95) DNB Limiting Elevation (cm) Max. Pin Linear Power (W/cm) Heat Flux (W/m 2 ) Equilibrium Quality Mass Flux (kg/m 2 /s) VERA-CS based process demonstrated for future plant specific application 27

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 PCI is possible in many rods and assemblies PCI is controlled by local effects PCI has system wide influence Need: 3D fuel performance model to assess complex, coupled physics and irregular geometries responsible for PCI fuel failures 28

29 Application Braidwood C10 & C13 PCI Failure Analysis Cycle 12 Cycle 10 Cycle 9 Cycle 13 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 Units Fluence 5.62e e25 n/m 2 Plenum Pressure MPa Pellet-Clad Gap micron Rod Average Burnup MWd/tU Peak Stress Axial Location m Worked performed by: N. Capps 1 J. Rashid 1 B. Wirth 2 1 Structural Integrity Associates 2 University of Tennessee 29

30 BISON Fuel Failure Analysis Methodology 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) 40 Model Multiple Cycles Run Bison for Every Pin Select Pins of Interest Local Effects Analysis 20 0 Critical Boron Difference (ppm) 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 Cycle Burnup (EFPD) 30

31 Stress Analysis of C13 U22S-D03 Failed Rod 2-D R-θ stress results in MPa PCI 60 mil MPS C D * N/A * N/A 416 E D R-θ stress results in MPa PCI 60 mil MPS C D * N/A * N/A 493 E Cycle 10 Cycle 13 Cycle 10 Cycle 13 The surrounding rods have similar calculated stresses and did not fail, therefore, an external factor must have contributed to the failure Clad stress is related to the fuel centerline temperature which is directly related to the startup power history 31

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 Promise Through Improved Fuel Performance & Reduced Fuel Cost 32

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