ML25063A278

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U.S. Nuclear Regulatory Commission Approach to Modeling and Simulation of Advanced Non-LWRs
ML25063A278
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Issue date: 03/04/2025
From: Stephen Bajorek
NRC/RES/DSA
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1 The U.S. Nuclear Regulatory Commission Approach to Modeling and Simulation of Advanced Non-LWRs; Preparing for Todays Nuclear Renaissance

2025 Update -----

Stephen M. Bajorek, Ph.D.

Office of Nuclear Regulatory Research United States Nuclear Regulatory Commission Ph.: (301) 415-2345 / Stephen.Bajorek@nrc.gov MOOSE International Workshop March 10, 2025

2 Exciting Times for Nuclear Many designs under development.

Multiple technologies.

Key mission for NRC is to be prepared... for any & all.

Advanced Reactor Landscape 3

ARDP Awardees ARC-20 Demo Reactors In Licensing Review Risk Reduction Preapplication RTR Research/Test Reactor LEGEND High-Temperature Gas-Cooled Reactors (HTGR)

Liquid Metal Cooled Fast Reactors (LMFR)

Molten Salt Reactors (MSR)

TRISO Fuel Westinghouse Columbia Basin Hydromine Lead-Cooled Micro Reactors Framatome X-energy (Xe-100)*

StarCore MIT General Atomics*

General Atomics (EM2)

GEH PRISM (VTR)

ARC Clean Technology

  • TerraPower/GEH (Natrium)*

Sodium-Cooled Kairos (Hermes l RTR)

Liquid Salt Cooled Kairos

  • ThorCon Flibe Elysium Alpha Tech Muons Southern (TP MCRE) l RTR ACU l RTR Terrestrial
  • TerraPower (MCFR)

Liquid Salt Fueled UIUC / Ultra Safe l RTR*

Stationary Oklo

  • Small Modular Light Water Reactors Boiling Water Reactor GEH BWRX-300*

Holtec SMR-300

NuScale US600 NuScale US460 Westinghouse (eVinci)

BWX Technologies X-energy Radiant

  • Alpha Tech Nano Nuclear Energy Ultra Safe Nuclear Transportable

4 NRCs Integrated Action Plan (IAP) for Advanced Reactors Near-Term Implementation Action Plan Strategy 1 Knowledge, Skills, and Capacity Strategy 2 Computer Codes Strategy 3 Flexible Review Process Strategy 4 Industry Codes and Standards Strategy 5 Technology Inclusive Issues Strategy 6 Communication

5 Independent Analysis Capability

6 Multiphysics Coupling SAM: System Level Thermo-Fluids Tensor Mechanics Module Griffin: Reactor Kinetics Temperatures & Densities Power Temperatures Displacements

7 Introduction

 The nuclear industry time constant

 New reactor designs >15 years.

 New reactor fuels >20 years.

 New analysis codes >10 years.

 BlueCRAB was conceived and initiated in 2018 as the next generation system of analysis codes for NRC evaluation of non-LWRs.

 MOOSE has exceeded expectations.

2018: Concept l

2025: Reality

8 TRACE System and Core T/H MOOSE Coupling, Tensor Mechanics PARCS Neutronics SCALE Cross-sections FAST Fuel Performance BISON Fuel Performance PRONGHORN Core T/H SAM System and Core T/H Nek5000 CFD DOE Code NRC Code GRIFFIN Neutronics Comprehensive Reactor Analysis Bundle BlueCRAB SERPENT Cross-sections Intl Code FLUENT CFD Commercial Planned Coupling Completed Coupling Input/BC Data Current View; Jan 2020

9 Evaluation Model

 Regulatory Guide 1.203 defines the Evaluation Model concept & process (EMDAP).

An evaluation model (EM) is the calculational framework for evaluating the behavior of the reactor system during a postulated transient or design-basis accident. As such, the EM may include one or more computer programs, special models, and all other information needed to apply the calculational framework to a specific event

 Elements of EMDAP include:

1.

Determine requirements for the evaluation model.

2.

Develop an assessment base consistent with the determined requirements.

3.

Develop the evaluation model.

4.

Assess the adequacy of the evaluation model.

5.

Follow an appropriate quality assurance protocol during the EMDAP.

6.

Provide comprehensive, accurate, up-to-date documentation.

Slide 10 RG 1.203 Code Development Process Identify Plant & Scenario PIRT (Phenomena Identification & Ranking Tables)

CODE Model Acceptable ?

Model Development Establish Assessment Matrix Experimental Testing & Data Evaluation Code Assessment Compare Code vs. IET and SET Application Uncertainty Methods Deficiency Yes

Slide 11 PIRT References

[6] S.J. Ball and S.E. Fisher, Next Generation Nuclear Plant Phenomena Identification and Ranking Tables (PIRTs), ORNL/TM-2007/147, NUREG/CR-6944, Vol. 1, March 2008.

[7] USNRC, TRISO-Coated Particle Fuel Phenomenon Identification and Ranking Tables (PIRTs) for Fission Product Transport Due to Manufacturing, Operations, and Accidents, NUREG/CR-6844, 2004.

[8] R. Schmidt, et al., Sodium Fast Reactor Gaps Analysis of Computer Codes and Models for Accident Analysis and Reactor Safety, SAND2011-4145, 2011.

[9] Lap-Yan Cheng, Michael Todosow, and David Diamond, Phenomena Important in Liquid Metal Reactor Simulations, BNL-207816-2018-INRE, ADAMS Accession No. ML18291B305 (2018).

[10] Hsun-Chia Lin, et al., Phenomena Identification and Ranking Table Study for Thermal Hydraulics for Advanced High Temperature Reactor, Annals of Nuclear Energy, 124 (2019) 257-269.

[11] Farzad Rahnema, et al.,, Phenomena identification and categorization by the required level of multiphysics coupling in FHR modeling and simulation, Annals of Nuclear Energy, 121 (2018) 540-551.

[12] D. J. Diamond, N. R. Brown, R. Denning and S. Bajorek, Phenomena Important in Modeling and Simulation of Molten Salt Reactors, BNL-114869-2018-IR, Brookhaven National Laboratory, ADAMS ML18124A330, April 23, 2018.

[13] Diamond, D. J., Brown, N. R., Denning, R., Bajorek, S., 2018. Neutronics Phenomena Important in Modeling and Simulation of Liquid-Fuel Molten Salt Reactors, Advances in Thermal Hydraulics (ATH 2018); Nov. 11-15; Orlando, Florida, USA: American Nuclear Society.

[14] Bajorek, S., Diamond, D. J., Brown, N. R., Denning, R., 2018. Thermal-Hydraulics Phenomena Important in Modeling and Simulation of Liquid-Fuel Molten Salt Reactors, Advances in Thermal Hydraulics (ATH 2018); Nov. 11-15; Orlando, Florida, USA:

American Nuclear Society.

[15] J. W. Sterbentz, J. E. Werner, M. G. McKellar, A. J. Hummel, J. C. Kennedy, R. N. Wright, J. M. Biersdorf, "Special Purpose Nuclear Reactor (5 MW) for Reliable Power at Remote Sites Assessment Report; Using Phenomena Identification and Ranking Tables (PIRTs)," INL/EXT-16-40741, Revision 1, April 2017.

12 Modeling Gaps Identified by PIRTs

  • Phenomena that are significant and new with increased importance for non-LWRs relative to conventional LWRs include but are not limited to:

- Thermal stratification and thermal striping

- Thermo-mechanical expansion and effect on reactivity

- Large neutron mean-free path length in fast reactors

- Transport of neutron pre-cursors (in fuel salt MSRs)

- Solidification and plate-out (MSRs)

- 3D conduction / radiation (passive decay heat removal)

Modeling Gaps in NRC Codes

13 Reference Model Development

 Reference Models - Generic representation of a design type, based on publicly available information.

 Scenarios of interest are selected (loss-of-flow, loss-of-heat sink, rapid reactivity insertion).

 Simulations performed to demonstrate code capabilities and identify deficiencies before licensing reviews begin.

HTR-10 MSRE MCFR

Slide 14 Characterization of Design Types Plant Type No.

Description Fuel 1

HTGR; prismatic core, thermal spectrum TRISO (rods or plates) 2 PBMR; pebble bed core, thermal spectrum TRISO (pebbles) 3 GCFR; prismatic core, fast spectrum SIC clad UC (plates) 4 SFR; sodium cooled, fast spectrum Metallic (U-10Zr) 5 LMR; lead cooled, fast spectrum TBD 6

HPR; heat pipe cooled, fast spectrum Metallic (U-10Zr) 7 MSR; prismatic core, thermal spectrum TRISO (plates) 8 MSPR; pebble bed, thermal spectrum TRISO (pebbles) 9 MFSR; fluoride fuel salt, thermal spectrum Fuel salt 10 MCSR; chloride fuel salt, fast spectrum Fuel salt

- Provided an initial set of design types to model.

- Use available (public) information to slant the model towards an intended design.

- Goal #1: Test the code(s).

Find and fix flaws now.

- Goal #2: Investigate modeling assumptions.

(1D or 3D ? PKE ?)

15

Slide 16 Verification & Validation Code Assessment represents an extremely important element in the EMDAP process.

Establishes the accuracy and reliability of the code and EM

Provides a basis for uncertainty quantification Non-LWR validation is a challenge...

Small database as compared to conventional LWRs

Scaling & range of conditions may be an issue

Coupled multiphysics can require nuclear core

17 BlueCRAB V&V Report Contents

- Introduction and Code Summary

- Verification

  • Regression Testing and Coverage

- Evaluation Model Development

  • Expected Scenarios
  • Design Types Considered

- Validation

  • Gas-Cooled
  • Liquid Metal Cooled
  • Molten Salt Reactors
  • Microreactors
  • General Neutronics
  • Components
  • Appendix: Brief Description of Tests ML24079A245 Collaborative effort with thanks to:

Emily Shemon Paolo Balestra Nicolas Stauff Rui Hu Abdalla Jaoude and others

TRACE Simulations of NSTF Tests Water-Based RCCS/NSTF Review Meeting January 29, 2025 Slide 18

Slide 19 RG 1.203 Code Development Process Identify Plant & Scenario PIRT (Phenomena Identification & Ranking Tables)

CODE Model Acceptable ?

Model Development Establish Assessment Matrix Experimental Testing & Data Evaluation Code Assessment Compare Code vs. IET and SET Application Uncertainty Methods Deficiency Yes

Slide 20 Uncertainty Quantification Uncertainty Quantification (UA) is an important element of modern code development and application.

All codes are Best Estimate but few are reliably accurate. Best Estimate Plus Uncertainty (BEPU) helps to capture a Figure of Merit such as PCT, peak fuel temperature, minimum coolant level, etc..

BEPU may be especially valuable with non-LWRs, where data is lacking, test facilities are few, and prior experience is limited. Dominant parameters are not known.

Framework Considerations NRC Regulations have added uncertainty to the BEPU process.

The 1988 rule, for example states:

when the calculated ECCS cooling performance is compared to the criteria set forth in paragraph (b) of the section, there is a high level of probability that the criteria would not be exceeded.

Reg Guide 1.157 suggests that a 95% probability is adequate - -

however, this is a guide (not a regulation) and confidence level is not addressed.

Uncertainty and acceptable uncertainty methods were likewise vague in the CSAU demonstration study. Uncertainty was determined using response surface methodology, but objective was not the statistical approach.

21

Framework Considerations Framework Decisions Based On:

  • Regulatory Acceptability
  • Feasibility of Implementation
  • Extensibility of the Methodology
  • Ease of Use & Effort to Perform Analyses
  • Resources to Implement Methodology 22 Evaluation of available methods lead to the conclusion that an ordered statistics approach should be used.

Slide 23 NRC Code Uncertainty Method The NRC UQ method uses the Wilks method, often called the GRS method which is based on non-parametric order statistics and Wilks theorem:

where is the confidence level, is the percentile and N is the number of calculations. For a 95/95 estimate of a single figure of merit, N = 59.

Sample & Required Output 24 CLAD_MWR 0.106727 BUBBLY_INT_DRAG 0.0866852 ROD_BUNDLE_INT_DRAG 0.13335 DROP_INT_DRAG

-0.110067 WALL_DRAG

-0.0482339 TB_HTC 0.06447 TMIN_Scalar 0.496487 IVA_LW_HTC 0.0355458 SPV_HTC

-0.750298 SUBC_HTC

-0.0933692 IVA_VW_HTC 0.307529 CLAD_CP 0.0661528 NULL 0.215863 IHTC

-0.698476 NUCL_HTC

-0.287767 SPL_HTC 0.107232 DFFB_HTC

-0.662468 CLAD_K 0.00872011 Spearman Rank Coefficients

Slide 25 Non-LWR Parameters for Ranging Pebble bed friction (KTA)

Pebble bed effective conductivity (ZBS)

Wall heat transfer (Achenbach)

Heat transfer model (Wakao)

Near-wall porosity (bypass flow)

Wall drag Form loss Coolant thermal conductivity Coolant viscosity Coolant freezing temperature Graphite thermal conductivity Fuel thermal conductivity HX effective heat transfer area HX secondary flow rate and temperature Fluidic diode form loss Vessel wall thermal conductivity Vessel wall emissivity Pump head and coastdown rate Pump flow resistance RCCS panel emissivity Cavity natural circulation RCCS supply temperature RCCS loop flow resistance Decay heat uncertainty Reactor trip time and signal delay Initial power shape Initial confinement temperature etc.

Example: Consider the PB-FHR for a protected loss-of-flow

Slide 26 Summary & Plans BlueCRAB is well positioned to be used by the NRC for independent analysis of non-LWRs.

Additional validation is needed.

Uncertainty quantification automation needs to be developed, tested and applied in Reference Models.

MOOSE Framework has made this possible.

- Multiphysics capability with coupling

- Flexibility for multiple designs

27

28 F-C Target and LBE Selection 28 Anticipated Operational Occurrence (AOO)

Beyond Design Basis Event (BDBE)

Design Basis Event (DBE)

LBE selection is based on:

Mean frequency Mean consequence F-C Target (not an acceptance criterion!)

QHO for individual early fatality risk 10 CFR 50.34 dose limit EPA PAG dose limit 10 CFR 20 iso-dose-risk line

Slide 29 Molten Salt Reactor (Inventory Control Gap)

Chemical Reaction Primary Flow Fission Product Decay Cover Gas Gaseous Fission Products Fission Product Generation Core Fissile Material Depletion Fission Product Filtering Fuel Cycle Facility Fissile Material Addition Solid Material Plateout, Sediment System Filtering Corrosion Product, Particulate Removal

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