ML25161A162

10 - NRC - Extremely Low Probability of Rupture Update

ML25161A162
Person / Time
Issue date:	06/17/2025
From:	Mendoza H, Nellis C NRC/RES/DE
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Download: ML25161A162 (1)

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E x t r e m e l y L o w P r o b a b i l i t y o f R u p t u r e C o d e U.S. Nuclear Regulatory Commission Office of Nuclear Regulatory Research Division of Engineering Reactor Engineering Branch Hector Mendoza U.S. Nuclear Regulatory Commission Office of Nuclear Regulatory Research Division of Engineering Reactor Engineering Branch NRC Update 2025 Christopher Nellis

Agenda 2

• Background

• xLPR Version 3.0

• What is the xLPR Framework?

• Why are we replacing the Framework?

• Project Objectives

• Project Timeline

• Language Selection

• Current Status

• Future Plans

• xLPR Development for CISCC

E x t r e m e l y L o w P r o b a b i l i t y o f R u p t u r e ( x L P R ) C o d e O v e r v i e w 3

> Probabilistic fracture mechanics (PFM) software tool for nuclear power plant piping integrity risk analysis

> Joint effort by the NRCs Office of Nuclear Regulatory Research and the Electric Power Research Institute (EPRI), now in second major version (v2.3 soon to be v2.4) with a third major version being developed (v3.0)

> Capable of modeling the effects of stress-corrosion cracking (SCC) and thermal fatigue

> Used by NRC and EPRI staff and contractors to risk-inform industrywide emerging piping integrity issues via probabilistic approaches 06/17/2025 INDUSTRY/NRC MATERIALS TECHNICAL EXCHANGE MEETING

4 x L P R M o d u l a r D e s i g n Modular Design

> Each FORTRAN module contains the physical models behind xLPR

> Crack Initiation, Crack Growth, Inservice Inspection, etc

> Each module developed by technical experts

> Allows flexibility of future development Framework

> Reads input parameters

> Performs sampling on probabilistic parameters

> Interfaces with FORTRAN modules containing physical models

> Collects module outputs

K n o w n F r a m e w o r k N e e d s Performance Adaptability

• Move away from requiring access to Commercial Off-the-Shelf (COTS) software

• Reduce the learning curve to making modifications

• Replace certain features that are proprietary and locked from users

• Currently there is limited parallelization capacity

• 4 cores for free GoldSim version

• 10 cores for subscription GoldSim

• Memory issues with large sample sizes

• 32-bit COTS application limits improvements to performance 5

xLPR 3.0 Project Goals 6

Goal #01 Increase flexibility by gaining full control of the source code.

Goal #03 Increase capacity by enabling access to more memory resources and minimizing repetitive human operator tasks.

Goal #02 Increase maintainability by leveraging agile processes and modern software development tools.

Goal #04 Increase performance through increased parallelization on large virtual machines.

x L P R 3. 0 7

Programming Language Evaluations Candidates: Python, C++, Fortran, Java, and Go Establish Requirements and Software Architecture Development Infrastructure Top-down GitHub integration, doorstop for requirements management, and automated testing tools Perform MoSCoW analysis for requirements (Must Have, Should Have, Could Have, Wont Have) and establish the new, high-level software architecture Run Development Process Establish product goals and supervise ongoing development Software Release and Training Process for Developing the New Framework

xLPR 3.0 Timeline 8

Project start Programming language selection Create development plan Complete deterministic runs Complete probabilistic runs Complete beta version Develop SQA and documentation Develop training materials Finalize release

Language Recommendation 9

Fortran Java Python Go C++

• Developed evaluation criteria for Framework programing language

• Consulted with development team and stakeholders to rank according criteria

• Conducted evaluations to make informed decision on Framework language

Evaluation Criteria 10

• Ranked Topics

• Support for statistical functions

• Support for visualization

• Support for unit conversions

• Ease of distributed computing

• Object-Oriented design

• Ease of parallelization

• Computational speed

• Handling of large data structures

• Extensibility

• Memory Requirements

• Operating environment support

• Memory safety

• Fortran Interface

• Excel Interface

• Ranked Topics

• Excel Interface

• Availability of online resources

• Future NRC/EPRI Engineer Knowledge

• Ease of initial development

• Ease of code maintenance

• Ease of learning/gain proficiency in language

• NRC-EPRI coding team experience

• Distribution of executable

• Licensing of third-party libraries

• Typing

• Webhosting

• Interfaces

• Testing

Language Selection 11

• Go has a syntax similar to C++ and Java and is simpler to learn

• Go eliminates aspects of C++ that are problematic and emphasizes features that improve maintainability

• The Go language is designed to limit dependencies that make code hard to modify

• Go was designed to simplify parallel computing and make threads more efficient

• Go compiles to an executable that incorporates Fortran routines and simplifies distribution

xLPR 3.0 Timeline 12 Project start Programming language selection Create development plan Complete deterministic runs Complete probabilistic runs Complete beta version Develop SQA and documentation Develop training materials Finalize release

Framework Conversion 13

• 4000+ unique elements in the GoldSim framework need to be converted into Go code

• Create new interfaces between the Go Framework and the compiled FORTRAN DLLs

• Confirming consistency of outputs from DLLs compared to xLPR 2.3

x L P R 3. 0 S u m m a r y T h e x L P R c o d e i s c o n t i n u i n g t o e v o l v e a s a h i g h t e c h n o l o g y p l a t f o r m f o r n u c l e a r s y s t e m s a n d c o m p o n e n t i n t e g r i t y a s s e s s m e n t.

x l p r @ n r c. g o v o r x l p r @ e p r i. c o m f o r f u r t h e r i n f o r m a t i o n 14

• Selected Go programing language for Framework

• Proceeding through manual conversion of GoldSim elements into Go functions

• Anticipate completion in early 2026

15 x L P R U s e C a s e s Latest NRC Use Cases xLPR is used in support of NRRs LIC-504 analysis of the risk of the emergent French Stress Corrosion Cracking OE to the US PWR fleet (ML24162A131) xLPR used to perform analyses in NRR review of Leak-before-Break (LBB) regulatory approach (ML21217A088 and ML22088A006)

Developing PFM tool in xLPR to model CISCC of dry storage canisters in FY25 Using the tool with site-specific conditions to assess CISCC, report in FY26

CISCC Modeling Research Objectives 16 Risk-inform aging of dry fuel storage by chloride-induced stress corrosion cracking (CISCC) of stainless-steel canisters Build on previous work assessing uncertainties in modeling CISCC including key environmental and material parameters ML24183A005 Develop a probabilistic fracture mechanics (PFM) tool to model CISCC of stainless-steel canisters to risk-inform the impact of site-specific conditions as follow on work to RG 3.78

xLPR Development for CISCC 17 Additional modules and framework modification to model Chloride-induced stress corrosion cracking (CISCC) to xLPR Developing CISCC crack initiation and crack growth modules Supplementary modules for stress intensity factor and weld residual stress Framework modification to support unique CISCC problem space

S u m m a r y x l p r @ n r c. g o v o r x l p r @ e p r i. c o m f o r f u r t h e r i n f o r m a t i o n 18 x L P R 3. 0 a n t i c i p a t e d f o r r e l e a s e i n e a r l y 2 0 2 6 D e v e l o p m e n t o f x L P R m o d u l e s f o r C I S C C e x p e c t e d t o b e c o m p l e t e i n 2 0 2 5 a n d i n u s e f o r s i t e s p e c i f i c a n a l y s i s i n 2 0 2 6