ML20192A097

04 - Probabilistic Fracture Mechanics Regulatory Guide for Industry / NRC Materials Programs Technical Information Exchange Public Meeting

ML20192A097
Person / Time
Issue date:	07/14/2020
From:	Patrick Raynaud, David Rudland NRC/NRR/DNRL, NRC/RES/DE/CIB
To:
Rezai A, 301-415-1328
References
Download: ML20192A097 (9)

Text

Industry / NRC Materials Programs Technical Information Exchange Probabilistic Fracture Mechanics Patrick Raynaud, Senior Materials Engineer, RES/DE/CIB David Rudland, Senior Level Advisor, NRR/DNRL

PFM Guidance Development Documents Technical Letter Report on NRCs preliminary thoughts on increasing confidence in PFM analyses (publicly available in ADAMS at ML18178A431)

PFM NUREG technical basis

- NRR review complete

- Being revised by NRC staff and SNL to more precisely define PFM graded approach Draft Regulatory Guide

- Draft completed by RES

- Reviewed by NRR

- Pending revisions based on final graded approach (still being finalized)

Report titled Application of Probabilistic Analysis Techniques in Probabilistic Fracture Mechanics

- Reviewed by RES

- Final draft nearly completed by SNL FAVOR Example Study Report

- Initial draft reviewed by RES

- Still undergoing revisions by SNL NUREG and RG drafts to tentatively be made available for public comment late CY2020, other reports may be made public for information only 07/14/2020 Industry / NRC Annual Technical Exchange 2

Technical Basis Document Details PFM NUREG: Each chapter drills down deeper into the details:

- Chapter 1: Introduction and Background

- Chapter 2: Contents of PFM submittal - includes description of graded approach and recommended contents of PFM submittal, mirrors Regulatory Guide

- Chapter 3: Analytical Steps in a PFM Submittal - includes descriptions of the steps and actions that may be taken as part of developing a PFM study, in support of developing the contents of a PFM submittal as described in Chapter 2

- Chapter 4: Methods Used in PFM Analysis - detailed descriptions of individual statistical analysis methods that may be used in a PFM study, and useful in performing the steps and actions described in Chapter 3 Application studies report

- Illustration of methods and concepts that may be used in a PFM analysis

- Centers around a simple example problem: shear stress on a helical weld on a pressurized cylindrical tank FAVOR example study report

- Illustration of the steps and actions in Chapter 3 of the NUREG

- Centers around hypothetical RPV problem: acceptability of continued operations of a single Reactor Pressure Vessel (RPV) following an inspection which identified two indications in the beltline region 07/14/2020 Industry / NRC Annual Technical Exchange 3

PFM Graded Approach EPRI proposed minimum requirements for PFM applications and their documentation in EPRI BWRVIP 2019-016 white paper:

Suggested Content for PFM Submittals to the NRC, ML19241A545 NRC reviewed the white paper and took EPRIs recommendations into consideration while developing a graded approach for PFM In many cases, NRC proposes to reduce the amount of documentation compared to EPRIs recommendations In some cases, NRC proposes additional documentation For each major topic in a PFM application, documentation categories are defined depending on the features of the specific application

- SQA and V&V

- Models

- Inputs

- Uncertainty propagation

- Convergence

- Sensitivity analyses

- Output uncertainty characterization

- Sensitivity studies Categories are independent from each other: can be in different categories for different topics 07/14/2020 Industry / NRC Annual Technical Exchange 4

PFM Graded Approach DRAFT Example 1: SQA and V&V 07/14/2020 Industry / NRC Annual Technical Exchange 5

Category Description Submittal Recommendations QV-1 NRC-approved code NOTE: NRC approved code yet to be precisely defined QV-1A Exercised within validated range Demonstrate code applicability within validated range QV-1B Exercised outside of validated range Provide justification for new applicability range (additional V&V may be necessary)

QV-1C Modified SQA summary and V&V description for modified portions of the code Demonstration that the code was not broken as a result of changes Detailed documentation available for further review upon request (audit)

QV-2 Commercial, off-the-shelf (COTS) software designed for the specific purpose of the application Demonstrate code applicability Description of the software and its pedigree Software and documentation available for review upon request (audit)

QV-3 Custom code Summary of SQA program and implementation Summary of V&V activities (data, benchmarking...)

Very simple applications: possibly provide source code instead of standardized SQA and V&V

PFM Graded Approach DRAFT Example 2: Models Baseline Documentation:

- Gaps and limitations in the code capabilities for the analysis, combined with a strategy for mitigating identified gaps, and communication of any remaining issues or risks

- Descriptions of the model or models applied in the PFM analysis code to a sufficient level of detail that a competent analyst familiar with the relevant subject area could independently implement the model(s) from the documentation alone. Model forms can either be theoretical, semi-empirical, or empirical

- Establish a basis for all significant aspects of the model(s). This may consist of raw data or published references. Any algorithms or numerical methods (e.g., root-finding, optimization, etc.) needed to implement the model(s) should also be documented or referenced.

Furthermore, any significant assumptions, approximations, and simplifications made should be discussed, including their potential impacts on the analysis

- Identification of important uncertainties or conservatisms

- A description of the computational expense of the model and how that might affect analysis choices NOTE: Highlighted items are part of EPRIs recommendations Category Description Submittal Recommendations M-1 Model from a code in category QV-1A or QV-1B within the same validated range Reference existing documentation for that model in the NRC approved code, demonstrate that current range of model is within previously approved validated range M-2 Model from a code in category QV-1A or QV-1B outside the validated range Same as M-1, except demonstrate validity of the model for new applicability range (document comparison of model predictions for entire new range to applicable supporting data, including quantitative goodness-of-fit analyses)

M-3 Model derived from a category M-1 or M-2 model Same as M-2, plus detailed description of changes to the M-1 or M-2 model, with justification for the validity of the new model.

M-4 Well established model not previously part of an NRC approved code Baseline Documentation M-5 First-of-kind model not yet published in a peer-reviewed journal Same as M-4, plus perform and document model sensitivity studies to understand trends in the model, as compared to expected model behavior and to the data used to develop the model.

07/14/2020 Industry / NRC Annual Technical Exchange 6

PFM Graded Approach DRAFT Example 3: Inputs From EPRI document:

- Document the inputs in detail, including specifying their values and whether they are treated as deterministic or probabilistic (and if probabilistic, document the distribution from which the inputs are sampled)

• I-1D/R

- Provide the basis for the input values used, including why the input basis is considered sufficiently reliable for the application

• I-3D/R and I-4D/R

- Document use of interpolation, extrapolation, and truncation schemes, as well as curve fitting of data

• I-3D/R and I-4D/R

- Document the approach for treatment of correlation or statistical independence of inputs, along with the corresponding basis for the approach

• I-3D/R and I-4D/R

- Ensure that selected or sampled inputs remain consistent and physically valid if inputs are dependent on each other, e.g., due to physical processes

• I-3D/R and I-4D/R

- Present the method and basis for treating epistemic and aleatory uncertainties

• I-1R, I-2R, I-3R, and I-4R Input Category High Input Knowledge Low Input Knowledge Deterministic Random Deterministic Random Low Importance I-1D I-1R I-2D I-2R High Importance I-3D I-3R I-4D I-4R Category Submittal Recommendations I-1D List input value.

I-1R List input distribution type and parameters. If applicable, list uncertainty classification (aleatory or epistemic).

I-2D Same as I-1D, plus: when lack of data, justification for the use of expert judgement, if applicable.

I-2R Same as I-1R, plus: when lack of data, justification for the use of expert judgement, if applicable.

I-3D Same as I-1D, plus: rationale for setting the input to deterministic, rationale (method and data) for selection of its numerical value, along with any known conservatisms in that numerical value and the rationale for such conservatisms references to documents that contain the foundation for input choices, correlations between inputs and how they are modeled, verification that correlated inputs remain consistent and physically valid.

I-3R Same as I-1R, plus: rationale (method and data) for selection of each distribution, including any known conservatisms in the specified input distributions and the rationale for the conservatism, references to documents that contain the foundation for input choices, correlations between inputs and how they are modeled, verification that correlated inputs remain consistent and physically valid.

I-4D Same as I-3D, plus: when lack of data, justification for the use of expert judgement, if applicable.

I-4R Same as I-3R, plus: when lack of data, justification for the use of expert judgement, if applicable.

07/14/2020 Industry / NRC Annual Technical Exchange 7

Recent PFM Audit Lessons Learned/First Impressions

• At prior Materials Technical Exchange meeting (May 2019), NRC presented thoughts on EPRI 3002014590 as compared to BWRVIP 2019-016 - with the draft PFM Regulatory guide in mind

• Ongoing audit of PFM code for Licensee alternative to inspection interval that uses EPRI 3002014590 as basis

• With BWRVIP-2019-016 and the draft PFM Reg Guide in mind, staff had some first impressions on PFM tool used 07/14/2020 Industry / NRC Annual Technical Exchange 8

Recent PFM Audit Lessons Learned/First Impressions

• PFM code audit is a useful tool to better understand code details and basis

• Self-contained technical basis would be desirable

- Having basis details in references makes the review cumbersome and not timely

• Traceable V&V Effort would be desirable

- A clear link between V&V plan and V&V tests and results would help staff have confidence in code

• Documented rationale/basis for conservative assumptions

- Overly conservative assumptions may undermine uncertainty discussion 07/14/2020 Industry / NRC Annual Technical Exchange 9