ML25121A026

Non-proprietary Enclosure 1 U.S. NRC Final Safety Evaluation for Westinghouse Electric Company Topical Report WCAP-18904-P/NP, Revision 0, Critical Power Experiments and D6 CPR Correlation for TRITON11 Fuel

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EPID L-2023-TOP-0054 TP WCAP-18904-P/NP
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U. S. NUCLEAR REGULATORY COMMISSION FINAL SAFETY EVALUATION BY THE OFFICE OF NUCLEAR REACTOR REGULATION WESTINGHOUSE ELECTRIC COMPANY TOPICAL REPORT WCAP-18904-P/NP, REVISION 0, CRITICAL POWER EXPERIMENTS AND D6 CPR CORRELATION FOR TRITON11 FUEL DOCKET NO. 99902038 EPID L-2023-TOP-0054

TABLE OF CONTENTS CONTENTS 1.0 Introduction..................................................................................................................

2.0 Regulatory Evaluation..................................................................................................

3.0 Technical Evaluation....................................................................................................

3.1 Review Framework for Critical Boiling Transition Models............................................

Experimental Data........................................................................................................

Credible Test Facility..............................................................................................

Accurate Data.........................................................................................................

Reproduced Local Conditions..............................................................................

Model Generation.......................................................................................................

Appropriate Mathematical Model..........................................................................

Model Coefficient Generation...............................................................................

Model Validation.........................................................................................................

Validation Error.....................................................................................................

Data Distribution...................................................................................................

Consistent Model Error.........................................................................................

Quantified Model Error.........................................................................................

Model Implementation..........................................................................................

4.0 Conclusion.................................................................................................................

4.1 Limitations and Conditions.........................................................................................

5.0 References.................................................................................................................

6.0 List of Acronyms.........................................................................................................

1.0 INTRODUCTION

By letter dated November 3, 2023 (Ref. 1), Westinghouse Electric Company (Westinghouse) submitted Topical Report (TR) WCAP-18904-P/NP, Revision 0, Critical Power Experiments and D6 CPR Correlation for TRITON11 Fuel (Ref. 2), to the U.S. Nuclear Regulatory Commission (NRC) for review and approval. The purpose of TR WCAP-18904-P/NP, Revision 0, was to describe the D6 critical power ratio (CPR) correlation used for the Westinghouse TRITON11 boiling water reactor (BWR) fuel assembly.

The complete list of correspondence between the NRC and Westinghouse is provided in Table 1 below. This includes audit documentation and any other correspondence relevant to this review.

Table 1: List of Key Correspondence Sender Document Document Date Reference Westinghouse Submittal Letter November 3, 2023 1

Westinghouse Topical Report November 3, 2023 2

NRC Acceptance Letter December 22, 2023 3

NRC Audit Plan May 28, 2024 4

Westinghouse Supporting Data May 21, 2024 6

In performing this review, the NRC staff applied a credibility assessment framework which focused on critical boiling transition1 models. The framework is fully described throughout this safety evaluation (SE).

1 Critical boiling transition is the name given to the phenomenon which occurs when a flow regime that has a higher heat transfer rate transitions to a flow regime that has a significantly lower heat transfer rate.

Historically, terms such as critical heat flux, departure from nucleate boiling, and critical power have been used. However, the NRC staff needed a way to separate the general phenomenon occurring (i.e., critical boiling transition) from a specific type of phenomenon which may occur (e.g., departure from nucleate boiling, dryout) and from the specific values of certain parameters which are often used to signify such a transition has occurred (e.g., critical heat flux, critical power).

2.0 REGULATORY EVALUATION

General Design Criterion 10 in Title 10 of the Code of Federal Regulations (10 CFR) Part 50, Appendix A, introduces the concept of specified acceptable fuel design limits (SAFDLs). In essence, SAFDLs are those limits placed on certain variables to ensure that the fuel does not fail. One such SAFDL is associated with critical boiling transition (CBT). CBT is defined as a transition from a boiling flow regime that has a higher heat transfer rate to a flow regime that has a significantly lower heat transfer rate. If the reduction in the heat transfer rate and resulting increase in surface temperature is large enough, the surface may weaken or melt. In a nuclear power plant, this condition could result in fuel damage.

In order to ensure that such a CBT does not occur, two SAFDLs have been developed, as described in NUREG-0800, Standard Review Plan (SRP), Section 4.4, Thermal and Hydraulic Design (Ref. 7):

(a) [T]here should be a 95-percent probability at the 95-percent confidence level that the hot rod in the core does not experience a DNB [departure from nucleate boiling] or boiling transition condition during normal operation or AOOs [anticipated operational occurrences].

(b) [A]tleast 99.9 percent of the fuel rods in the core will not experience a DNB or boiling transition during normal operation or AOOs.

Typically, SAFDL (a) is associated with pressurized water reactors (PWRs) and SAFDL (b) is associated with BWRs. CBT models such as the D6 CPR correlation, which, if approved, will be used on BWR fuel, are necessary to ensure that the above SAFDLs can be satisfied. The main objective of this review was to determine if the D6 CPR correlation could result in accurate predictions, such that at least 99.9 percent of the fuels rods in the core will not experience CBT during normal operation or AOOs.

Part of 10 CFR 50.36 focuses on defining technical specification (TS) safety limits. There are multiple limits that are associated with CBT models used during plant operation. These limits can be operating limits, alarms, analysis limits, and safety limits. Generally, only the safety limit and associated limiting conditions for operation (LCOs) and surveillance requirements (SRs) are included in the plants TSs. The safety limit associated with CBT is typically focused on an accurate quantification of the uncertainty of the CBT model and may also include the quantification of additional uncertainties as well.

The regulation at 10 CFR 50.34(a)(4) requires that the Preliminary Safety Analysis Report (PSAR) include determination of the margins of safety during normal operation and AOOs. One of these is the margin to CBT, which verifies through analysis that fuel failure is precluded during normal operation and AOOs.

10 CFR Part 50, Appendix B requires licensees to include certain structures, systems, and components (SSCs) in a quality assurance (QA) program that satisfies specific criteria.

Appendix B, Criterion III, requires that specified design control measures be applied to the design of safety-related SSCs, and these measures apply to safety analyses for these SSCs.

The CBT model is a key component of the safety analysis subject to 10 CFR Part 50, Appendix B.

3.0 TECHNICAL EVALUATION

The WCAP-18904-P/NP, Revision 0, TR describes how the D6 CPR correlation was developed from experimental data, how it behaves over its application domain, and how it will be applied in the future. The NRC staffs technical evaluation is focused on determining if the correlation is acceptable for use in reactor safety license calculations (i.e., that the model can be trusted). To perform this review, the NRC staff chose to use a review framework based on the framework described in NUREG/KM-0013, Credibility Assessment Framework for Critical Boiling Transition Models (Ref. 8). This NUREG/KM summarizes the knowledge that the NRC staff has developed over the course of 40 years of CBT model and analysis reviews.

3.1 Review Framework for Critical Boiling Transition Models This section discusses the review framework for CBT models used in this review. The framework is generated from a single main goal. That main goal is then logically decomposed into subgoals. Logical decomposition is the process of generating a set of subgoals which are logically equivalent (i.e., necessary and sufficient) to the main goal. This decomposition is expressed using Goal Structure Notation (GSN). Each subgoal can either be further logically decomposed into other subgoals or if no further decomposition is deemed useful, the subgoal is considered a base goal and evidence must be provided to demonstrate that the base goal is true.

For CBT models, the top goal is: The CBT model can be trusted in reactor safety analyses.

Based on the experience of multiple NRC technical staff members, a study of the previous SEs, and multiple discussions with various industry experts, this goal is decomposed into various subgoals as given in the figures below, starting with the decomposition of the main goal into the three sub-goals given in Figure 1.

Figure 1: Decomposing G - Main Goal Experimental Data Experimental data is the cornerstone of a CBT model. Not only is the data used to generate the coefficients of the model and validate the model, but previous data are often used to generate the models form. Therefore, it is essential that the experimental data are appropriate.

Demonstrating that the experimental data are appropriate is accomplished using the three sub-goals given in Figure 2 below.

Figure 2: Decomposing G1 - Experimental Data Credible Test Facility The first sub-goal in demonstrating that the experimental data are appropriate is to demonstrate that the test facility is credible. This is typically demonstrated using the two sub-goals as given in Figure 3 below.

Figure 3: Decomposing G1.1 - Test Facility No further decompositions of the sub-goals were deemed useful. Therefore, the evidence demonstrating the following goals were met is provided below.

3.1.1.1.1 Test Facility Description Test Facility Description The test facility is well understood.

G1.1.1, Review Framework for CBT Models In Section 2, Test Facility, of the WCAP-18904-P/NP, Revision 0, TR, Westinghouse provided a description of the test facility, including the various loop components as well as a description of the heater rods and the instrumentation. The test facility setup is consistent with the setup of other experimental facilities used to conduct similar experiments. The specific type of heater rods used in the FRIGG loop are commonly used to perform CBT testing. The test facility has been appropriately instrumented to measure the pressure (absolute and differential), inlet subcooling, bundle power, and inlet mass flux. Westinghouse also discussed the measurement system and the test procedures.

The FRIGG loop test facility has been assessed as part of a prior NRC staff review (Ref. 9), during which the NRC staff was able to visit the test facility to better understand its construction and operation. Additionally, in this prior review Westinghouse confirmed that the testing QA program is in compliance with Appendix B to 10 CFR Part 50. The FRIGG loop test facility has also been previously audited by the NRC staff. The description of the facility provided by Westinghouse, along with this prior assessment, provided the NRC staff with a clear understanding of the facility, what data were obtained, and how the data were obtained.

Therefore, the NRC staff concluded that goal G1.1.1 has been met.

3.1.1.1.2 Test Facility Comparison Test Facility Comparison The test facility has been verified by comparison to an outside source.

G1.1.2, Review Framework for CBT Models In Section 2.8, Comparison to Outside Source, of TR WCAP-18904-P/NP, Revision 0, Westinghouse provided a discussion comparing the FRIGG loop to an outside source. The discussion included details regarding a series of comparative full-scale dryout experiments performed at both the FRIGG and ATLAS test facilities and consistency in the resultant data and data trends. Because the FRIGG loop was compared to the ATLAS facility and demonstrated to have very similar predictions, the NRC staff concluded that goal G1.1.2 has been met.

Accurate Data The second sub-goal in demonstrating that the experimental data are appropriate is to demonstrate that the experimental data have been accurately measured. This is typically demonstrated using the seven sub-goals as given in Figure 4 below.

Figure 4: Decomposing G1.2 - Accurate Data No further decompositions of the sub-goals were deemed useful. Therefore, the evidence demonstrating the following goals were met is provided below for the FRIGG loop test facility.

3.1.1.2.1 Test Procedures Test Procedures The test procedure used to obtain the data is appropriate.

G1.2.1, Review Framework for CBT Models In Section 3.3, Measurement Data Validation Criteria and Procedures, of TR WCAP-18904-P/NP, Revision 0, Westinghouse provided a description of its test procedure and discussed how each state point was reached, including the approach to dryout, the steady state criteria, and the dryout criteria. Because Westinghouse is applying a logical approach to dryout by narrowing in on a state point, ensuring that a steady state has been reached, ensuring that any deviations during the approach to dryout are small, and ensuring there is a consistent definition applied in identifying dryout, the NRC staff concluded that goal G1.2.1 has been met.

G1.2 The experimental data have been accurately measured.

3.1.1.2.2 Statistical Design of Experiment Statistical Design of Experiment The experiment has been appropriately statistically designed (i.e., the value of a system parameter from any test was completely independent from its value in the test before and after the test.)

G1.2.2, Review Framework for CBT Models In Section 3, Test Program, of TR WCAP-18904-P/NP, Revision 0, Westinghouse described its method for determining the state points, indicating that a parameter variation matrix was created, and a randomization procedure was applied. Westinghouse also provided details on the order of choosing parameters, [

]

Westinghouse also included repeated test points to demonstrate repeatability and ensure there were no biases in the testing. Because Westinghouse is selecting random state points inasmuch as the testing allows and used repeated test points to ensure there was no bias during testing, the NRC staff concluded that goal G1.2.2 has been met.

3.1.1.2.3 Instrumentation Uncertainties Instrumentation Uncertainties The instrumentation uncertainties are low.

G1.2.3, Review Framework for CBT Models In Section 2.5, Instrumentation, of TR WCAP-18904-P/NP, Revision 0, Westinghouse provided a list of instrumentation uncertainties. Each of these uncertainties is relatively small, approximately [

] Because these instrumentation uncertainties are relatively small and within the range of normal instrumentation, the NRC staff concluded that goal G1.2.3 has been met.

3.1.1.2.4 Diverse Instrumentation Diverse Instrumentation The instrumentation is diverse and redundant.

G1.2.4, Review Framework for CBT Models In Section 2.5, Instrumentation, of TR WCAP-18904-P/NP, Revision 0, Westinghouse presented the variables defining the operating conditions of the tests and described the instrumentation used to measure these variables. Westinghouse stated that [

]

Because Westinghouse is [

] the NRC staff concluded that goal G1.2.4 has been met.

3.1.1.2.5 Instrumentation Calibration Instrumentation Calibration The instrumentation is routinely calibrated.

G1.2.5, Review Framework for CBT Models In Section 3.3, Measurement Data Validation Criteria and Procedures, of TR WCAP-18904-P/NP, Revision 0, Westinghouse indicated that instrumentation is routinely calibrated to assure the accuracy of the data. Additionally, a heat balance measurement involving power, mass flow, and temperature is performed at the beginning of each test campaign to confirm measurements are accurate and assumed power losses in the test section are valid. Because Westinghouses procedures require instrumentation calibration on a regular basis and the accuracy of the instrumentation is confirmed before each test campaign, the NRC staff concluded that goal G1.2.5 has been met.

3.1.1.2.6 Repeated Test Points Repeated Test Points The uncertainty in the critical heat flux or critical power is quantified through repeated tests at the same state points.

G1.2.6, Review Framework for CBT Models In Section 3.3, Measurement Data Validation Criteria and Procedures, of TR WCAP-18904-P/NP, Revision 0, Westinghouse indicated critical power reference test points at various conditions were repeated throughout the testing campaign to assure that measurements were stable and reproduceable. Because the reference test points in each group were generally performed for the same conditions and power distributions, the test point groupings can effectively be used to separate out the repeatability (i.e., uncertainty) of the experimental facility from the variation in the D6 CPR correlations predictions between similar tests. The relative standard deviation in measured critical power for each group of reference test points is approximately [ ] For comparison, Section 2.5, Instrumentation, of the TR presents the estimated uncertainty in the critical power due to measurement uncertainty of the major operating condition variables alone as [ ] In addition to the measurement uncertainty, there is a randomness associated with the dryout transition phenomenon itself as well as difficulty in returning the test facility to the same exact state point for each critical power reference test. Based on experience and observations from prior tests, the NRC staff expects these uncertainties will not be large (between 1 - 2 percent of measured critical power in total),

and when they are considered in conjunction with the measurement uncertainty, the [

] standard deviation in measured critical power for each group of reference tests is reasonably consistent. Because the variability in measured CPs is consistent for each group of reference test points and reasonably consistent with other uncertainties associated with the test facility, the NRC staff concluded that goal G1.2.6 has been met.

3.1.1.2.7 Quantified Heat Losses Quantified Heat Losses The heat losses from the test section are quantified, appropriately low, and duly accounted for in the measured data.

G1.2.7, Review Framework for CBT Models In Section 3.3, Measurement Data Validation Criteria and Procedures, of TR WCAP-18904-P/NP, Revision 0, Westinghouse confirmed that a heat balance measurement is performed at the beginning of each test campaign. The heat balance involves power, mass flow, and temperature, and it is performed to confirm that measurements are accurate, and power losses assumed for the test section are valid. The process involves comparisons of the power generated by the heater rod bundle and the output power from each power supply for every data point taken in the heat balance measurement, and these comparisons must be within [

] of each other. Through this approach, Westinghouse was able to identify whether any systemic biases exist and whether any heat balance errors existed unique to a given test

campaign. If any biases or errors were identified, Westinghouse would [

] As such, the heat losses from the test section are quantified, accounted for in the analysis, and have only a minor impact. Therefore, the NRC staff concluded that goal G1.2.7 has been met.

Reproduced Local Conditions The third sub-goal in demonstrating that the experimental data are appropriate is to demonstrate that the local conditions in the reactor have been reproduced in the experiment.

This is typically demonstrated using the five sub-goals as given in Figure 5 below.

Figure 5: Decomposing G1.3 - Reproduced Local Conditions No further decompositions of the sub-goals were deemed useful. Therefore, the evidence demonstrating the following goals were met is provided below.

3.1.1.3.1 Equivalent Geometries Equivalent Geometries The test bundle used in the experiment should have geometric dimensions equivalent to those of the fuel bundle used in the reactor for all major components.

G1.3.1, Review Framework for CBT Models In Section 2.2, Test Section, of TR WCAP-18904-P/NP, Revision 0, Westinghouse provided a description of the test bundle. The bundle is a full prototypical TRITON11 bundle with 109 heater rods. It contains three types of part-length rods, of which two are two-thirds length and one is one-third length. The heater rods are supported laterally by eight Inconel spacer grids of the TRITON11 design. The spacer grid axial elevations are consistent with the TRITON11 fuel bundle. To ensure the inlet flow distribution in the testing is similar to that in the reactor, an orifice plate is installed at the inlet of the flow channel. Being prototypical, the rod diameter of the test bundle is also consistent with the rod diameter of the fuel bundle.

While most of the test bundle dimensions were very similar to the fuel bundle, some dimensions of the test bundle were slightly different than those from the fuel bundle, and these dimensions may impact dryout. The NRC staff specifically noted slight variations in the flow area of the bundle and in the distance from the end of the heated length of the test section to the upper most spacer grid. Westinghouse discussed the differences in flow areas between the test channel and the fuel bundle in Section 2.2 of the TR. Considering the slightly different thermal expansion properties of the test section materials, the cold flow area of the test section is slightly smaller than that of the fuel bundle by approximately [ ] Westinghouse accounts for this difference through mass flux adjustments to the CPR correlation.

Westinghouse confirmed that the inner dimensions of the channel and the rod pitch were not impacted. The NRC staff concluded that this small difference would have a minimal impact on the critical power performance, and it is nonetheless appropriately accounted for via the mass flux adjustment.

Regarding the distance between the end of the heated length of the test section and the upper most spacer grid, Westinghouse indicated this distance varies somewhat depending on reactor type, and the distance used is that which is expected to be most limiting with respect to critical power. This distance corresponds to the longest distance between the top of the spacer grid and the end of the heated length. The NRC staff agreed with this approach because it is representative of BWR/4-6 type plants and would result in a conservative calculation for BWR/2-3 type plants, where the distance between the top spacer grid and the end of the heated length is shorter. Because of the shorter distance, the grid deposition enhancement effect would be more effective at the end of the heated length (as it is closer to the spacer grid) and would thus support a slightly higher critical power.

Westinghouse made note of three additional geometry differences in TR WCAP-18904-P/NP, Revision 0: 1) heated lengths of the part-length rods in the test section versus a fuel bundle, 2)

[

] and 3) potential shifts in axial position of spacer grids during testing. With regard to the partial length rods, Westinghouse indicated there may be slight differences due to slight

differences in plenum length, and this can result in differences in the end of the heated length.

However, Westinghouse discussed how these differences are explicitly accounted for in the D6 CPR correlations R-factor model, which is [

] Additionally, since dryout typically occurs well above the part-length rods, Westinghouse considers the effect to be insignificant. The NRC staff concluded that this approach is acceptable because dryout typically occurs at higher axial elevations and Westinghouse is nonetheless explicitly accounting for any potential performance impact.

With regard to [

] The NRC staff notes that this may introduce slight differences in [ ] which could cause

[ ] However, Westinghouse indicated that, [

] any minor effects this approach might introduce are likely to have a negligible impact. The NRC staff concluded that this is acceptable because

[ ] and will disappear well before the higher axial elevations at which dryout typically occurs.

With regard to potential axial shifts in grid spacers during testing, Westinghouse provided a discussion in Section 3.4, Shift in Axial Position of Spacers, of the WCAP-18904-P/NP, Revision 0, TR. [

]

While there were slight differences between the test bundle and the fuel bundle, those differences were either accounted for in the application of the D6 CPR correlation or were determined to have a minimal impact on the models prediction, as explained above. Therefore, the NRC staff concluded that goal G1.3.1 has been met.

3.1.1.3.2 Equivalent Grid Spacers Equivalent Grid Spacers The grid spacers used in the test bundle should be prototypical of the grid spacers used in the reactor assembly.

G1.3.2, Review Framework for CBT Models In Section 2.2, Test Section, of TR WCAP-18904-P/NP, Revision 0, Westinghouse indicated the eight Inconel spacer grids used within the heated length of the test section are of TRITON11 design. The only deviation from production TRITON11 spacer grids is [

] Aside from this, the spacer grids used in the test section are the same as those used in the reactor fuel bundle. Therefore, the NRC staff concluded that goal G1.3.2 has been met.

3.1.1.3.3 Axial Power Shapes Axial Power Shapes The axial power shapes in the test bundle should reflect the expected or limiting axial power shapes in the reactor bundle.

G1.3.3, Review Framework for CBT Models In Section 1.2, Test Conditions in FRIGG Loop, of the WCAP-18904-P/NP, Revision 0, TR, Westinghouse stated [

] In Section 1.3, D6 CPR Correlation Model and Validation, of the TR, Westinghouse indicated [

] With regard to [

] The NRC staff concluded that this is reasonable; [

] the changes in prediction bias and standard deviation were insignificant.

Because the power shapes tested represent those experienced [

] and because the shapes tested are consistent with the power shapes commonly tested for CPR correlations, the NRC staff concluded that goal G1.3.3 has been met.

3.1.1.3.4 Radial Power Shapes Radial Power Shapes The radial power peaking in the test bundle should reflect the expected or limiting radial powers in the reactor bundle.

G1.3.4, Review Framework for CBT Models For BWR CPR analysis, the radial power dependence is captured in the R-or K-factors. These factors are used in a single-channel model to account for all radial power dependences, and when combined with the additive constants, account for all radial dependences in the fuel bundle. Therefore, the NRC staff expects the radial power shapes that are tested to be sufficient to: (1) obtain additive constants and (2) ensure that a complete set of R-factors or K-factors can be calculated.

In Section 3.2.5, Lateral Power Distribution, of TR WCAP-18904-P/NP, Revision 0, Westinghouse provided justification for the radial powers tested. The testing focused on

[

] In addition, Westinghouse also performed realistic power tilts that result from inserted control rods, and these power tilts were repeated for all combinations of mass flow, pressure, and inlet subcooling

[ ]

Because Westinghouses testing focused on ensuring that the radial power distributions applied in the experiment covered the range needed to obtain key values for the CPR model for each rod and were also consistent with actual bundle design and expected operating conditions, the NRC staff concluded that goal G1.3.4 has been met.

3.1.1.3.5 Differences between Test and Reactor Differences between Test and Reactor Any differences between the test bundle and the reactor bundle should have minimal impact on the flow field. This includes components that are not in the reactor bundle but that are needed for testing purposes.

G1.3.5, Review Framework for CBT Models Except for those differences addressed in the preceding subsections, there were no differences between the prototypical test section assembly and the TRITON11 fuel assembly. Therefore, the NRC staff concluded that goal G1.3.5 has been met.

Model Generation There are numerous ways to generate the CBT model. While some methods of model generation are based on first principle physics, CBT models are still largely empirical in nature.

Therefore, there is no single correct way to generate the model. The form of the model is often based on previous model forms, machine learning techniques, and engineering judgment.

Demonstrating the model generation is appropriate is accomplished using the two sub-goals given in Figure 6 below.

Figure 6: Decomposing G2 - Model Generation Appropriate Mathematical Model The first sub-goal in demonstrating that the model was generated in a logical fashion is to demonstrate that the models form is appropriate. This is typically demonstrated using the two sub-goals as given in Figure 7 below.

Figure 7: Decomposing G2.1 - Model Form

No further decompositions of the sub-goals were deemed useful. Therefore, the evidence demonstrating the following goals were met is provided below.

3.1.2.1.1 Model Parameters Model Parameters The mathematical form of the model contains all the necessary parameters.

G2.1.1, Review Framework for CBT Models In Section 3.1, Range of Test Parameters, of the WCAP-18904-P/NP, Revision 0, TR, Westinghouse stated the D6 CPR correlation for TRITON11 fuel inherits the same basic correlation form as the D5 CPR correlation used for SVEA-96 Optima3' fuel (Ref. 10).

Westinghouse further discussed the selected form of the D6 CPR correlation in Section 4.1, Selected Correlation Form, stating physical considerations and empirical data trends from the FRIGG testing of SVEA-96 Optima3 were used to derive the D5 correlation form. The NRC staff notes this statement applies also to the D6 CPR correlation because it inherits the basis of the D5 CPR correlation.

Westinghouse states in Section 4.1 of the TR that the expressions for critical quality as a function of mass flux, pressure, inlet sub-cooling, axial power distribution, and R-factor are identical to the D5 CPR correlation. The main differences between the D6 and D5 CPR correlations are new values to the fitting coefficients (the D6 CPR correlation coefficients are fitted against corresponding FRIGG data) and [

] The NRC staff examined the various parameters comprising the mathematical form of the model and noted the D6 CPR correlation contains terms for [

] all of which the NRC staff concluded are necessary for the modeling of dryout. Because the model form contains those key parameters typically found to be important in modeling dryout, and because the model coefficients are fitted against FRIGG data, the NRC staff concluded that goal G.2.1.1 has been met.

3.1.2.1.2 Model Form Model Form The reasoning for choosing the mathematical form of the model should be discussed and should be logical.

G2.1.2, Review Framework for CBT Models Westinghouse discussed the mathematical form chosen for the steady state D6 CPR correlation, as well as the sub-models supporting it, in Section 4.3, D6 Steady-State CPR Correlation, of TR WCAP-18904-P/NP, Revision 0. The steady state form of the model and its supporting models were discussed in sufficient detail to provide understanding to the NRC staff.

Westinghouse discussed the transient form of the D6 CPR correlation in Section 4.4, D6 Transient CPR Correlation, of TR WCAP-18904-P/NP, Revision 0. The transient form of the D6 CPR correlation is a generalization of the steady-state form and is based on the same correlation expression with the same coefficients. Thus, at steady-state conditions, the two forms are equivalent. The primary difference between the two forms resides with the treatment of the [

] The transient form of this parameter is determined through the [

] The practical benefit of this approach is the ability of the model to [

] The NRC staff concluded that this is appropriate because [

] Ultimately, the demonstration that this method is acceptable was provided in predicting the critical power during the transients testing. The transient tests demonstrated that the transient version of the D6 CPR correlation, and therefore Westinghouses use of [ ] was able to conservatively or accurately predict the transient dryout performance, as discussed below in Section 3.1.3.5.3, Transient Prediction, of this SE.

The NRC staff noted that the formulation of [ ] for the transient D6 CPR correlation

[

] The NRC staff noted this same treatment during its review of the D5 CPR correlation. However, as discussed in the NRC staffs SE for the D5 CPR correlation (Ref. 9), and as supported via Westinghouses response to RAI-SNPB-20 in the same review, [

] Given the extent to which the D6 CPR correlation inherits the form and function of the D5 CPR correlation, the NRC staff concluded there is reasonable assurance that a similar effect would result were a [

] Further, the NRC staff determined that the D6 CPR correlation has adequate quantification of its uncertainty through comparison to experimental data (as discussed in Section 3.1.3.4, Quantified Model Error, of this SE).

Therefore, [ ] the NRC staff concluded the correlation is appropriate for the safety analyses.

Because Westinghouse provided acceptable details defining the functions and variables that comprise the D6 CPR correlation, the NRC staff concluded that goal G2.1.2 has been met.

Model Coefficient Generation The second sub-goal in demonstrating that the model was generated in a logical fashion is to ensure that the process for generating the models coefficients is appropriate. This is typically demonstrated using the three sub-goals as given in Figure 8 below.

Figure 8: Decomposing G2.2-Model Coefficient Generation No further decompositions of the sub-goals were deemed useful. Therefore, the evidence demonstrating the following goals were met is provided below.

3.1.2.2.1 Training Data Training Data The training data (i.e., the data used to generate the coefficients of the model) should be identified.

G2.2.1, Review Framework for CBT Models In Section 1.2, Test Conditions in FRIGG Loop, of the WCAP-18904-P/NP, Revision 0, TR, Westinghouse identified the D6 CPR correlation was developed based on [ ] steady-state critical power data points and that [ ] of these data were used for optimizing (i.e.,

training) the correlation coefficients. Because Westinghouse identified the data used for training, the NRC staff concluded that goal G2.2.1 has been met.

When training a correlation, it is ideal to use as little of the available data as possible because there will be greater confidence in the ability of the correlation to predict outside of the data on which it was trained. As such, a portion of the available data is typically reserved for validation purposes. TR Section 1.2 indicates that, when determining the correlation mean and standard deviation errors, the database was divided randomly into subsets of training and validation data.

Westinghouse expands upon this in Section 5.2, Correlation Mean and Standard Deviation Errors, of the WCAP-18904-P/NP, Revision 0, TR, indicating the data were randomly and

repeatedly subdivided into groupings of [ ]

for training, [ ] for validation, and that the random subdividing was repeated a total of [ ] times. The NRC staff notes this approach

[

] This is discussed further in Section 3.1.3.4.1, Error Data Base, of this SE.

3.1.2.2.2 Coefficient Generation Coefficient Generation The method for calculating the models coefficients should be described.

G2.2.2, Review Framework for CBT Models Westinghouse provided a discussion of the method used to develop the D6 CPR correlation coefficient in Section 4.6, Determination of D6 Coefficients, of the WCAP-18904-P/NP, Revision 0, TR. A least squares method was used to optimize the correlation and R-factor coefficients by systematically minimizing the sum of the square differences between the predicted and measured critical power. [

] The general coefficient fitting procedure involves [

] The NRC staff observed that dryout data was obtained for [

] This provides additional assurance that the D6 CPR correlation has been appropriately trained on data obtained from across the intended application range.

Because Westinghouses method for generating the models coefficients was fully described and reasonable, the NRC staff concluded that goal G2.2.2 has been met.

3.1.2.2.3 BWR Specific Parameters BWR Specific Parameters The method for calculating the R-or K-factors and the additive constants (for both full-length and part-length rods) should be described. Further, a description of how such values are calculated if dryout is not measured on the rod under consideration should be provided (BWRs only).

G2.2.3, Review Framework for CBT Models Westinghouse provided the equations used to generate the R-factors and rod constants in Section 4.5, D6 R-Factor, of the WCAP-18904-P/NP, Revision 0, TR. In Section 4.6, Determination of D6 Coefficients, of the TR, Westinghouse described [

] The NRC staff observed that dryout data was obtained from the FRIGG tests for [

]

Because Westinghouses method for generating the BWR-specific parameters was fully described, the NRC staff concluded that goal G2.2.3 has been met.

Model Validation As defined by Oberkampf and Roy (Ref. 11), validation is the accumulation of evidence which is used to assess the claim that a model can predict a real physical quantity. Thus, validation is a never-ending process as more evidence can always be obtained to bolster this claim. However, at some point, when the accumulation of evidence is considered sufficient to make the judgment that the model can be trusted for its given purpose, the model is said to be validated.

Demonstrating that the model validation is appropriate is accomplished using the five sub-goals given in Figure 9 below.

Figure 9: Decomposing G3 - Model Validation Validation Error Validation Error The correct validation error has been calculated.

G3.1, Review Framework for CBT Models For critical power correlations, the validation error should be based on the measured critical power obtained from experimental tests and the predicted critical power of the test assembly used in these experimental tests. Within the WCAP-18904-P/NP, Revision 0, TR, Westinghouse uses these terms (the predicted and measured critical powers) to calculate the error in the D6 CPR correlation (i.e., the validation error). Additionally, Westinghouse provided this data to the NRC staff in Reference 6. Because Westinghouse is comparing critical powers predicted by the D6 CPR correlation to critical powers measured in the experimental tests for the TRITON11 test assembly, and because Westinghouse supplied this data to the NRC staff for review, the NRC staff concluded that goal G3.1 has been met.

Data Distribution The second sub-goal in demonstrating that the models validation was appropriate is to demonstrate that the data is appropriately distributed throughout the application domain. This is typically demonstrated using the six sub-goals as given in Figure 10 below.

Figure 10: Decomposing G3.2 - Data Distribution No further decompositions of the sub-goals were deemed useful. Therefore, the evidence demonstrating the following goals were met is provided below.

3.1.3.2.1 Validation Data Validation Data The validation data (i.e., the data used to quantify the models error) should be identified.

G3.2.1, Review Framework for CBT Models In Section 1.2, Test Conditions in FRIGG Loop, of TR WCAP-18904-P/NP, Revision 0, Westinghouse identified that [

] Thus, approximately [ ] of the data was effectively used for validation during the development of the D6 CPR correlation. Because Westinghouse identified the data used for validation, the NRC staff concluded that goal G3.2.1 has been met.

3.1.3.2.2 Application Domain Application Domain The application domain of the model should be mathematically defined.

G3.2.2, Review Framework for CBT Models In Section 7, Conclusions, of the WCAP-18904-P/NP, Revision 0, TR, Westinghouse provides the boundaries of the application domain of the D6 CPR correlation. The NRC staff concluded that this domain is reasonable because it is similar to other CPR correlation domains and encompasses the expected operating ranges of BWRs. Because the application domain provided by Westinghouse is similar to other CPR correlation domains, and because this application domain is consistent with the expected operating ranges of BWRs, the NRC staff concluded that goal G3.2.2 has been met.

3.1.3.2.3 Expected Domain Expected Domain The expected domain of the model should be understood.

G3.2.3, Review Framework for CBT Models In Section 3, Test Program, of the WCAP-18904-P/NP, Revision 0, TR, Westinghouse provided plots showing the data collection range and typical application range of the D6 CPR correlation. The range of typical application identified in the following plots is defined as the expected domain:

Pressure versus Mass Flux (Figure 3-6)

Pressure versus Inlet Subcooling (Figure 3-7)

Pressure versus R-factor (Figure 3-11)

Inlet Subcooling versus Mass Flux (Figure 3-8)

R-factor versus Mass Flux (Figure 3-9)

Inlet Subcooling versus R-factor (Figure 3-10)

From these plots, the expected domain of the model can be understood. Because Westinghouse provided the plots identifying the expected domain of the model, the NRC staff concluded that goal G3.2.3 has been met.

3.1.3.2.4 Data Density Data Density There should be adequate validation error data density throughout the expected and application domains.

G3.2.4, Review Framework for CBT Models As discussed above, Westinghouse provided the figures that define the application and expected domains of the D6 CPR correlation in Section 3, Test Program, of the WCAP-18904-P/NP, Revision 0, TR. A review of the data density in these domains is limited to the 2D comparison of each of the most important parameters (i.e., pressure mass flux, subcooling, and R-factor). The sparse regions identified in this section are further addressed below in Section 3.1.3.2.5, Sparse Regions, of this SE.

Pressure versus Mass Flux Figure 3-6 of the WCAP-18904-P/NP, Revision 0, TR displays the experimental measurements taken in terms of [

] However, the graph demonstrates that there is [

] Therefore, the NRC staff respectively identified these regions as Sparse Region (A) and Sparse Region (B).

Pressure versus Inlet Subcooling Figure 3-7 in the WCAP-18904-P/NP, Revision 0, TR displays the experimental measurements taken in terms of [

] This region has been identified as Sparse Region (C).

Pressure versus R-Factor Figure 3-11 in the WCAP-18904-P/NP, Revision 0, TR displays the experimental measurements taken in terms of [

]

[ ] this has been identified as Sparse Region (D).

Inlet Subcooling versus Mass Flux Figure 3-8 in the WCAP-18904-P/NP, Revision 0, TR displays the experimental measurements taken in terms of [

] These observations are also true of the application domain. Therefore, there is sufficient spread and density of data through the expected and application domains.

R-Factor versus Mass Flux Figure 3-9 in the WCAP-18904-P/NP, Revision 0, TR displays the experimental measurements taken in terms of [

] These have been respectively identified as Sparse Region (E) and Sparse Region (F).

Inlet Subcooling versus R-Factor Figure 3-10 in the WCAP-18904-P/NP, Revision 0, TR displays the experimental measurements taken in terms of [

] This range has been identified as Sparse Region (G).

Data Density Conclusions With the exception of the sparse regions identified (which will be addressed below in Section 3.1.3.2.5, Sparse Regions, of this SE), Westinghouse has provided details of the data distribution and density in the expected and application domains. The NRC staff notes that distribution and density of the data is consistent with that expected in critical power testing.

Therefore, the NRC staff concluded that goal G3.2.4 has been met.

3.1.3.2.5 Sparse Regions Sparse Regions Sparse regions (i.e., regions of low data density) in the expected and application domains should be identified and justified to be appropriate.

G3.2.5, Review Framework for CBT Models The NRC staff identified the following sparse regions inside the expected and application domains in Section 3.1.3.2.4, Data Density, of this SE:

(A) A region defined by [ ]

(B) A region defined by [ ]

(C) A region defined by [ ]

(D) A region defined by [ ]

(E) A region defined by [

]

(F) A region defined by [ ]

(G) A region defined by [

]

To address use of the D6 CPR correlation in Sparse Region (A), Westinghouse indicated in Section 4.2, Extrapolation in Mass Flux, of TR WCAP-18904-P/NP, Revision 0, that, while the correlation will be applied at [

] This is conservative.

For application at [

] This is conservative. The NRC staff also notes that sparseness of data at these ranges [ ] is common in testing due to limitations in the testing facilities, and further, Sparse Region (A) is outside the range of practical application and is therefore of limited importance. Therefore, the NRC staff concluded that, given the conservative treatment of D6 CPR correlation for these ranges [ ] and with consideration of the range of practical application, the implementation of the D6 CPR correlation in these ranges [ ] is acceptable and the justification for Sparse Region (A) is adequate.

Regarding use of the D6 CPR correlation in Sparse Region (B), the NRC staff notes the D6 CPR correlation extensively inherits the form and function of the D5 CPR correlation (as discussed in Section 3.1.2.1.2, Model Form, of this SE). The D6 CPR correlations behavior with respect to pressure is therefore expected to be substantially similar to the D5 CPR correlations behavior. In Section 3.1.3.3.3, Model Trends, of the NRC staffs final SE for the D5 CPR correlation (Ref. 9), the NRC staff concluded the D5 correlation trends correctly in terms of pressure. The NRC staff presently notes the critical quality response of the D5 and D6 CPR correlations as a function of pressure (Figure 5-2 of WCAP-17794-P-A (Ref. 10) and Figure 4-2 in TR WCAP-18904-P/NP, Revision 0, respectively) are both smoothly varying and well-behaved. Based on this, the NRC staff expects the D6 CPR correlation will predict reasonably well between the data obtained in the expected domain and the data obtained just outside the expected domain. Therefore, the NRC staff concluded that the sparse data in this region is acceptable.

To address the use of the D6 CPR correlation in Sparse Region (C), Westinghouse indicated that the D6 correlations behavior with inlet subcooling has a linear trend, and that this linear trend is the same well-known linear trend observed and reported for the D5 (Ref. 10) and SVEA-96 Optima2 (Ref. 12) CPR correlations. The NRC staff concluded that this linear trend and the use of historical evidence justifies Sparse Region (C) in the application domain.

To address the use of the D6 CPR correlation in Sparse Region (D), Westinghouse stated in Section 4.5.1, Generalized R-factor Model, of the WCAP-18904-P/NP, Revision 0, TR that the calculation of bundle minimum CPR is based on the maximum of all individual rod R-factors in each axial cross-section. In the optimization of the bundle U-235 enrichment and Gd distributions, the R-factor is minimized at the burnup of maximum reactivity (the so-called k-inf peak) which typically occurs towards the end of the first cycle. R-factors at both lower and higher burnups will be somewhat greater but, for the D6 CPR correlation, R-factors will typically not exceed [ ]

unless the adjacent control rod is deeply inserted. In the case of a deeply inserted control rod resulting in a high R-factor (at any burnup), the actual bundle power will be strongly suppressed to an extent that, although the critical power is reduced by the high R-factor, the bundle CPR will be non-limiting. Moreover, higher R-factors generally correspond to conditions of fewer rods near dryout. Based on this, the NRC staff concluded that this region is likely to be non-limiting and the sparse data in this region is acceptable.

Regarding Sparse Region (E), the NRC staff noted that, as discussed in previous NRC reviews (Ref. 9), R-factor values for [ ]

are characterized by off-nominal conditions in mass flux, pressure, or inlet subcooling.

Additionally, while Sparse Region (E) is within the model application domain, it is well outside the expected domain; a reactor is not expected to operate in this region. Based on this, the NRC staff concluded that the R-Factors in Spare Region (E) are likely to be non-limiting, and the sparse data in this region of the application domain is therefore acceptable.

Regarding Sparse Region (F), the D5 (Ref. 9) and D6 R-factors are not directly comparable for conditions with [

] Higher R-factors correspond to fewer rods near dryout and as mentioned above, strong power tilts resulting in R-factors above [ ] are typically only obtained by a deeply

inserted control rod, and this results in a non-limiting CPR. Therefore, the NRC staff concluded that the R-factors in Sparse Region (F) would likely not result in limiting conditions and justifies the sparse distribution of data in this region of the expected domain.

Regarding Sparse Region (G), [

] the NRC staff noted the discussion provided above for the justification of Sparse Region (F) is applicable. As mentioned above, R-factors above [ ] are typically only obtained by a deeply inserted control rod, which results in a non-limiting CPR. R-factors in the range of [ ] are less common than R-factors [ ] and are typically less limiting since a higher R-factor corresponds to fewer rods near dryout. Moreover, the interpolation in subcooling by the D6 CPR correlation to the range of [ ] Kelvin from data at lower and higher subcooling which include [ ] R-factors is considered reasonable due to the simple linear dependence of critical power on subcooling as demonstrated empirically for the latest three generations of Westinghouse BWR fuel designs as discussed in Section 3.5 of WCAP-18904-P/NP, Revision 0. Therefore, the NRC staff concluded that the R-factors in Sparse Region (G) would likely not result in limiting conditions and justifies the sparse distribution of data in this region of the expected domain.

Because satisfactory justification was provided for each of the sparse regions in the application domain, as discussed above, the NRC staff concluded that goal G3.2.5 has been met.

3.1.3.2.6 Restricted Domain Restricted Domain The model should be restricted to its application domain.

G3.2.6, Review Framework for CBT Models In Section 7, Conclusion, of TR WCAP-18904-P/NP, Revision 0, Westinghouse identified the ranges of input variables over which the D6 CPR Correlation is justified for application. Based on previous reviews (Ref. 9), Westinghouse typically implements CPR correlations in a manner such that the computer code in which the correlation is implemented will issue a warning if the correlation is being used outside its application domain. Should such an occurrence arise, it would generally be a result of a fuel bundle existing at off-nominal conditions outside the correlation application domain. The error issued would prompt an investigation to ensure that the bundle in question has no realistic possibility of influencing the overall results of the calculation (i.e., ensure the bundle in question is far from being CPR limiting for the entire core).

The NRC staff confirmed with Westinghouse during the regulatory audit conducted in June of 2024 (Refs. 4 and 5) that the D6 CPR correlation implementation is consistent with this approach. Because this approach ensures the D6 CPR correlation will be applied within the defined application domain, the NRC staff concluded goal G3.2.6 has been met.

Inconsistencies in the Models Error The third sub-goal in demonstrating that the models validation is appropriate is to demonstrate that the model error is consistent over the application domain. This is typically demonstrated using the three sub-goals as given in Figure 11 below.

Figure 11: Decomposing G3.3 - Inconsistencies in the Models Error No further decompositions of the sub-goals were deemed useful. Therefore, the evidence demonstrating the following goals are met is provided below.

3.1.3.3.1 Poolability Poolability The validation error should be investigated to ensure that it does not contain any subgroups that are obviously not from the same population (i.e., nonpoolable).

G3.3.1, Review Framework for CBT Models In Table 5-1 of TR WCAP-18904-P/NP, Revision 0, Westinghouse provides results of a statistical analysis of the D6 CPR correlation. The table includes results for the overall database and results for [

] The results demonstrate that the critical power behavior of the D6 CPR correlation for the subgroups of axial power shape is similar. In Section 5.1, D6 Performance Relative to FRIGG Database, of the TR, Westinghouse states the similarity in results [

] indicates that those datasets are poolable and can be combined when evaluating correlation statistics. The NRC staff concluded that, for the present application, this assertion is reasonable. The results presented in Table 5-1 are approximations (i.e., statistics) of the underlying means and standard deviations (i.e.,

parameters) of the populations characterizing the D6 CPR correlations performance [

] Because the means and standard deviations are similar and because there is no indication physically or phenomenologically that the [

] should each be treated differently, it is reasonable to pool the axial power profile data for determining the overall performance of the D6 CPR correlation. Because the axial power profile data subgroups are a logical delineation of the

data and because these subgroups were demonstrated to be poolable, the NRC staff concluded that goal G3.3.1 has been met.

3.1.3.3.2 Non-Conservative Subregions Non-Conservative Subregions The expected domain should be investigated to determine if contains any non-conservative subregions which would impact the predictive capability of the model.

G3.3.2, Review Framework for CBT Models In Section 5, D6 Steady-State CPR Validation, of the WCAP-18904-P/NP, Revision 0, TR, Westinghouse provides plots of the D6 CPR correlation critical power prediction error versus each model parameter. Westinghouse asserts, and a visual suggestion indicates, these plots do not show any signs of non-conservative subregions. That is, subregions within the prediction error output space that suggest the critical power predictive performance of the D6 CPR correlation is not unequally biased and the predictive uncertainty does not vary within the application domain.

Using a method similar to the one suggested by Kaizer (Ref. 13), the NRC staff analyzed the application domain for potential non-conservative subregions. The analysis utilized the top 5 percent of critical power prediction errors as the reference set of results for examination of all subregions defined for each model parameter. The NRC staff found no evidence of a non-conservative subregion. Because analysis of the application domain demonstrated that there was no evidence of a non-conservative subregion in the application domain and that any potential subregion would have negligible impact on the D6 model, the NRC staff concluded that goal G3.3.2 has been met.

3.1.3.3.3 Model Trends Model Trends The models predictions trend as expected in each of the various model parameters.

G3.3.3, Review Framework for CBT Models In TR WCAP-18904-P/NP, Revision 0, Westinghouse provides numerous plots of model trends:

Figure 3-6 through Figure 3-11 demonstrate that the data used to train and validate the D6 CPR correlation are trending correctly in terms of power, pressure, mass flux, and inlet subcooling.

Figure 5-3 through Figure 5-6 demonstrate that the validation error is independent of each of the D6 CPR correlations independent variables.

Figure 5-8 through Figure 5-10 demonstrate that the D6 CPR correlations prediction of critical power is behaving as expected in terms of mass flux and inlet subcooling for [

]

The NRC staff notes the D6 CPR correlations predictive trends presented in these plots are consistent with those of previously reviewed, similarly constructed CPR correlations (Ref. 9) and exhibit the expected behavior of the phenomena pertinent to predicting critical power. Per the second bullet above in this Section 3.1.3.3.3, these plots also demonstrate the D6 CPR correlations validation error is consistent over the range of each parameter. Therefore, the NRC staff concluded that goal G3.3.3 has been met.

Quantified Model Error The fourth sub-goal in demonstrating that the models validation is appropriate is to demonstrate that the model error is appropriately quantified over the application domain. This is typically demonstrated using the three sub-goals as given in Figure 12 below.

Figure 12: Decomposing G3.4 - Quantification of the Models Error

No further decompositions of the sub-goals were deemed useful. Therefore, the evidence demonstrating the following goals are met is provided below.

3.1.3.4.1 Error Data Base Error Data Base The validation error statistics should be calculated from an appropriate database.

G3.4.1, Review Framework for CBT Models In Section 3.2, Justification for Range of Test Parameters, of TR WCAP-18904-P/NP, Revision 0, Westinghouse provides justification for the selection of and ranges of test parameters from which it constructed the database for training and validation of the D6 CPR correlation. Westinghouse also provides justification for the determination of the correlations predictive error in Section 3.2 of the TR. The NRC staff reviewed the list of parameters and associated testing ranges and concluded 1) the list of test parameters is acceptably representative of inputs necessary to model phenomena pertinent to prediction of critical power, and 2) the ranges of each test parameter is appropriate as they encompass both the domain over which the model will be applied (i.e., the application domain) and the nominal and anticipated operating states of BWRs (i.e., the expected domain).

In Section 1.2 of the TR, Westinghouse identified that [

]

The continuous, [

]

As discussed in Section. 3.1.2.2.1 of this SE, a portion of the available database is typically reserved for validation purposes, and the correlation is trained on the remaining data. [

]

[

] which is conservative.

Calculation of the validation error statistic (i.e., the critical power error) with respect to the validation data is discussed in Section 3.1.3.4.2 of this SE.

Because the selection of test parameters and the ranges over which data was collected for these parameters is acceptable, and because Westinghouse performed a sensitivity analysis demonstrating the correlations predictions are independent of the data being predicted (i.e.,

training data or validation data), the NRC staff concluded that goal G3.4.1 has been met.

3.1.3.4.2 Statistical Method Statistical Method The validation error statistics should be calculated using an appropriate method.

G3.4.2, Review Framework for CBT Models In Section 5.2, Correlation Mean and Standard Deviation Errors, of TR WCAP-18904-P/NP, Revision 0, Westinghouse calculated a [

] for the predictive capability of the D6 CPR correlation for the validation data. As discussed in Section 3.1.3.4.1 of this SE, the D6 CPR correlation database

[

] The continuous, [

] Each time the database was partitioned, the correlation coefficients were optimized using the training data subset and the mean and standard deviation errors were determined for the validation. The average mean and standard deviation errors over all the validation data subsets were used to determine the final correlation and performance statistics. The NRC staff concluded that this approach is reasonable because it is consistent with standard practice wherein the mean and variance are generally determined from the total population of validation error. Westinghouses treatment of the bias is discussed further in Section 3.1.3.4.3, Appropriate Bias for Model Uncertainty, of this SE.

In Section 4.6, Determination of D6 Coefficients, of TR WCAP-18904-P/NP, Revision 0, Westinghouse identifies the number of degrees of freedom of the data [

] In this way, Westinghouse determined the number of degrees of freedom to be [ ] The NRC staff concluded that this approach is reasonable because it is consistent with the general method applied for calculating degrees of freedom (Ref. 14).

Figure 5-1 in the WCAP-18904-P/NP, Revision 0, TR presents [

] Through assessment of this figure and via a confirmation analysis of the data provided in the TR, the NRC staff determined the validation error is most [ ]

The NRC staff concluded that goal G3.4.2 has been met because the mean and standard deviation of the D6 CPR correlation have been correctly calculated from the validation error data set using methods consistent with established practice, the number of degrees of freedom has been correctly calculated, and the correlation bias has been applied in a conservative manner.

3.1.3.4.3 Appropriate Bias for Model Uncertainty Appropriate Bias The models uncertainty should be appropriately biased.

G3.4.3, Review Framework for CBT Models Using the approach of data partitioning (discussed in Section 3.1.3.4.1, Error Data Base, of this SE), Westinghouse calculated in Section 5.2, Correlation Mean and Standard Deviation Errors, of TR WCAP-18904-P/NP, Revision 0, a [

] for the predictive capability of the D6 CPR correlation for the validation data. Westinghouse stated the small negative bias is conservatively neglected.

The NRC staff concluded that this is reasonable because, similar to the D5 CPR correlation, a negative bias implies the D6 CPR correlation predicts a critical power lower than the measured values, which is conservative; interpreting the correlation to have a mean prediction error of 0 percent will inherently introduce a conservatism. Additionally, Westinghouse [

] which is conservative.

Because Westinghouse biased the mean prediction error of D6 CPR correlation to be greater than the error of the supporting validation database, and because Westinghouse rounded the standard deviation error of the D6 CPR correlation to be larger than that of the supporting validation database, the NRC staff concluded goal G3.4.3 has been met.

Model Implementation The fifth sub-goal in demonstrating that the models validation was appropriate is to demonstrate that the model will be implemented in a manner consistent with its validation. This is typically demonstrated using the three sub-goals as given in Figure 13 below.

Figure 13: Decomposing G3.5-Model Implementation No further decompositions of the sub-goals were deemed useful. Therefore, the evidence demonstrating the following goals were met is provided below.

3.1.3.5.1 Same Computer Code Same Computer Code The model has been implemented in the same computer code that was used to generate the validation data.

G3.5.1, Review Framework for CBT Models The validation database that was used to quantify the mean prediction error and standard deviation error of the D6 CPR correlation was generated for steady-state conditions. With regard to the computer code used for steady-state applications, Westinghouse states in Section 5, D6 Steady-State CPR Validation, of TR WCAP-18904-P/NP, Revision 0, that, due to the nature of the CPR correlation assumptions under steady-state conditions (based on equilibrium state in closed channels), the validation and associated statistics are independent from the computer code in which the correlation has been implemented (neglecting small differences due to nodalization and water properties). This is consistent with the generation of the validation data for other CPR correlations that are similar to D6 and have been part of prior NRC staff reviews, such as the D5 CPR correlation (Ref. 9). The NRC staff therefore concluded that this is reasonable.

However, correlation validation for transient applications is not independent of the computer code in which the correlation is implemented. Regarding transient applications, Westinghouse indicated in Section 6.1, Introduction, of the WCAP-18904-P/NP, Revision 0, TR that the D6 CPR correlation will be implemented in the BISON-SLAVE channel model of the BISON transient analysis code (Ref. 15), and in Section 6.4, Implementation Validation for BISON Code, Westinghouse provides validation results of BISON against the FRIGG database of transient tests (discussed further in Section 3.1.3.5.3, Transient Prediction, of this SE) as an example of transient application. Because this demonstrates that the transient analysis code is validated against a database of pertinent transient tests, the NRC staff concluded that the approach presented for the implementation and validation of the D6 CPR correlation in transient applications is reasonable.

Because the D6 CPR correlation does not rely on subchannel methods for its steady state validation, which are computer-code specific, and because the transient implementation of the D6 CPR correlation in BISON has been validated against the FRIGG database of transient tests, the NRC staff concluded goal G3.5.1 has been met.

3.1.3.5.2 Same Methodology Same Methodology The models prediction of the critical boiling transition is being applied using the same evaluation methodology used to predict the validation data set for determining the validation error.

G3.5.2, Review Framework for CBT Models Unlike DNB models which are implemented in a subchannel code that utilizes multiple complex closure relations, the implementation of the D6 CPR correlation is comparatively simple. A single fuel assembly channel is modeled with R-factors accounting for radial powers and additive constants accounting for thermal hydraulic effects. Given the relative simplicity of the D6 CPR correlation and Westinghouses description of the procedures for implementation and validation (discussed above in Section 3.1.3.5.1, Same Computer Code, of this SE), the implementation and application of the D6 CPR correlation in the BISON code is virtually identical to that when determining the steady state validation error in Section 5.2, Correlation Mean and Standard Deviation Errors, of the WCAP-18904-P/NP, Revision 0, TR. Therefore, the NRC staff concluded goal G3.5.2 has been met.

3.1.3.5.3 Transient Prediction Transient Prediction The model results in an accurate or conservative prediction when it is used to predict transient behavior.

G3.5.3, Review Framework for CBT Models

In Section 6 of TR WCAP-18904-P/NP, Revision 0, Westinghouse discusses the application of the D6 CPR correlation in transient applications when using the BISON-SLAVE channel model.

To demonstrate appropriateness of this application, Westinghouse compared the results of transient dryout analyses against transient experiments that were performed in the FRIGG test loop with the TRITON11 fuel geometry. The analyses considered [

] for power increase transients, flow reduction transients, and combinations of power increase and flow reduction transients. It should be noted that the selected transient cases are [

]

In total, [ ] transient tests were simulated with the BISON-SLAVE channel model of the BISON code. Of these tests, 45 are classified as power increase transients, [ ] are classified as flow reduction transients, and [ ] are a combination of power increase and flow reduction.

The indication of dryout was a temperature change rate of [

] Figures 6-10 through 6-11 of WCAP-18904-P/NP, Revision 0, provide comparisons between the measured dryout and predicted critical powers. [

] An accurate prediction includes predicting CPR less than or equal to 1.0 when the temperature change rate was greater than the dryout criterion and predicting a CPR greater than 1.0 when the temperature change rate was less than the dryout criterion.

[

] Therefore, the D6 model was able to accurately predict transient behavior [

] Because Westinghouse demonstrated that the D6 CPR correlation is able to accurately predict the CPR behavior for transient conditions representative of AOOs, the NRC staff concluded that goal G3.5.3 has been met.

4.0 CONCLUSION

Based on evidence provided in Section 3.1.1, Experiential Data, of this SE, the NRC staff concludes that the experimental data supporting the D6 CPR correlation is appropriate. Based on the evidence in Section 3.1.2, Model Generation, of this SE, the NRC staff concludes that the D6 CPR correlation was generated in a logical fashion. Based on the evidence in Section 3.1.3, Model Validation, of this SE, the NRC staff concludes that the D6 CPR correlation has sufficient validation as demonstrated through appropriate quantification of its error. Therefore, based on the cumulative evidence, the NRC staff concludes that the D6 CPR correlation can be trusted in reactor safety analyses (i.e., can be used to determine that 99.9 percent of the rods in

the core do not experience critical boiling transition during normal operation or AOOs) and is acceptable for use in such analyses subject to the conditions and limitations listed below in Section 4.1, Limitations and Conditions, of this SE.

4.1 Limitations and Conditions The following limitations and conditions must be met for the use of the D6 CPR correlation.

1. The D6 CPR correlation is approved over the application domain specified in Section 7, Conclusions, of the WCAP-18904-P/NP, Revision 0, TR. This information is repeated below for convenience as Table 4-1:

Table 4-1: Application Domain of the D6 CPR Correlation

[

]

The D6 CPR correlation is approved for use in evaluations of the Safety Limit Minimum CPR utilizing the statistical parameters specified in Section 5.2, Correlation Mean and Standard Deviation Errors, of the WCAP-18904-P/NP, Revision 0, TR. This information is repeated here for convenience:

The D6 CPR correlation uncertainty (standard deviation error) = [ ]

The D6 CPR correlation bias (mean error) = [ ]

Any application deviation from the modeling options would require re-validation similar to the validation provided in the WCAP-18904-P/NP, Revision 0, TR. Any application to a new fuel type or new mixing vane spacer type, any decrease in the design limits, or any expansion of the application domain would require prior NRC review and approval.

5.0 REFERENCES

1. Harper, Z. S., Westinghouse, Letter to NRC, Submittal of Westinghouse Topical Report WCAP-18904-P/NP, Revision 0, Critical Power Experiments and D6 CPR Correlation for TRITON11 Fuel, LTR-NRC-23-30, dated November 3, 2023 (ADAMS Accession No. ML23307A183 (Publicly Available)).

2. Westinghouse, TR WCAP-18904-P/NP, Revision 0, Critical Power Experiments and D6 CPR Correlation for TRITON11 Fuel, dated November 2023 (ADAMS Accession Nos.

ML23307A184 (Proprietary Version, Non-Publicly Available) and ML23307A185 (Nonproprietary Version, Publicly Available)).

3. Lenning, E., NRC, Email to Zozula, C., Westinghouse, Completeness Determination and Withholding Determination for the Westinghouse Electric Company Topical Report WCAP-18904-P/NP, Revision 0, Critical Power Experiments and D6 CPR Correlation for TRITON11 Fuel, (EPID L-2023-TOP-0054), dated December 22, 2023 (ADAMS Package Accession No. ML23354A065 (Non-Proprietary/Publicly Available)).

4. George, G., Letter to Zozula, C., Westinghouse, Regulatory Audit Plan for the U.S.

Nuclear Regulatory Commission Regulatory Audit on June 10-14, 2024, for the Review of Westinghouse Electric Company Topical Report WCAP-18904-P/NP, Revision 0, Critical Power Experiments and D6 CPR Correlation for TRITON11 Fuel (EPID L-2023-TOP-0054), dated May 28, 2024, (ADAMS Accession No. ML24144A225 (Non-Proprietary/Publicly Available)).

5. George, G., Letter to Zozula, C., Westinghouse, Audit Report for the U.S. Nuclear Regulatory Commission Regulatory Audit for the Review of Westinghouse Electric Company Topical Report WCAP-18904-P/NP, Revision 0, Critical Power Experiments and D6 CPR Correlation for TRITON11 Fuel, dated October 17, 2024, (ADAMS Accession No. ML24278A134 (Non-Proprietary/Publicly Available)).

6. Harper, Z. S., Westinghouse, Letter to U.S. Nuclear Regulatory Commission, Submittal of Data to Support the NRC review of WCAP-18904-P/NP, Critical Power Experiments and D6 CPR Correlation for TRITON11 Fuel, LTR-NRC-24-14, dated May 21, 2024 (ADAMS Package Accession No. ML24143A149 (Publicly Available)).

7. NRC, Section 4.4, Thermal and Hydraulic Design, of NUREG-0800, Standard Review Plan for the Review of Safety Analysis Reports for Nuclear Power Plants: LWR Edition, Revision 2, dated March 2007 (ADAMS Accession No. ML070550060).

8. NRC, NUREG/KM-0013, Credibility Assessment Framework for Critical Boiling Transition Models - Draft for Comment, dated March 2019 (ADAMS Accession No. ML19073A249).

9.

NRC, U. S. Nuclear Regulatory Commission Office of Nuclear Reactor Regulation Final Safety Evaluation for Topical Report WCAP-17794-P, Revision 0, and WCAP-17794-NP, Revision 0, 10x10 SVEA Fuel Critical Power Experiments and New CPR Correlation: D5 for VEA-96 OPTIMA3 Westinghouse Electric Company CAC No. MF3368; EPID L-2014-TOP-0002, dated July 28, 2020 (ADAMS Accession Nos. ML20176A561 (Proprietary version, Non-publicly available) and ML20176A566 (Non-Proprietary version, Publicly available).

10. Westinghouse, TR WCAP-17794-P-A and WCAP-17794-NP-A, 10x10 SVEA Fuel Critical Power Experiments and New CPR Correlation: D5 for SVEA-96 Optima3, dated September 2020 (ADAMS Accession Nos. ML20283A823 (Proprietary Version, Non-Publicly Available) and ML20283A817 (Nonproprietary Version, Publicly Available)).

11. Oberkampf, W.L., and C.J. Roy, Verification and Validation in Scientific Computing, Cambridge University Press, Cambridge, United Kingdom, 2010.

12. Westinghouse, TR WCAP-16081-P-A and WCAP-16081-NP-A, 10x10 SVEA Fuel Critical Power Experiments and CPR Correlation: SVEA-96 Optima2, dated March 2005 (ADAMS Accession Nos. ML051260213 (Proprietary Version, Non-Publicly Available) and ML051260171 (Nonproprietary Version, Publicly Available)).

13. Kaizer, J. S., Identification of Non-Conservative Subregions in Empirical Models Demonstrated Using Critical Heat Flux Models, Nuclear Technology, Vol. 190, 65-71, 2015.

14. Lurie, D., and Moore, R. H., Applying Statistics, Revision 1, NUREG-1475, March 2011 (ADAMS Accession No ML11102A076 (Nonproprietary version, Publicly Available)).

15. Westinghouse, TR CENPD-292-P-A & CENPD-292-NP-A, BISON - One Dimensional Dynamic Analysis Code for Boiling Water Reactors: Supplement 1 to Code Description and Qualification, dated July 1996 (ADAMS Accession Nos. ML19353D883 (Proprietary Version, Non-Publicly Available) and ML20129C275 (Nonproprietary Version, Publicly Available)).

6.0 LIST OF ACRONYMS AOO anticipated operational occurrence BWR boiling-water reactor CBT Critical boiling transition CFR Code of Federal Regulations CHF critical heat flux CP critical power CPR Critical Power Ratio DNB departure from nucleate boiling DNBR departure from nucleate boiling ratio G

Goal GSN goal structure notation HTRF Columbia Universitys Heat Transfer Research Facility MDNBR minimum departure from nucleate boiling NRC U.S. Nuclear Regulatory Commission PWR pressurized-water reactor R-or K-factor relative power factor SAFDL specified acceptable fuel design limit SE safety evaluation SRP Standard Review Plan Principal Contributors: K. Heller J. S. Kaizer Date: August 6, 2025

NRC RESOLUTION OF WESTINGHOUSE PROPRIETARY MARKINGS AND VOLUNTARY COMMENTS TABLE The table is a record of Westinghouses proprietary markup and voluntary comments contained in Enclosure 2 (ADAMS Accession No. ML25043A273 (Non-publicly available/Proprietary)) to the publicly available letter dated February 12, 2025 (ADAMS Accession No. ML25043A274) that Westinghouse submitted following the issuance of the draft SE issued by the NRC via email dated December 20, 2024 (ADAMS Accession No. ML24278A174) for proprietary review. The table includes the NRC staffs resolution.

Comment page and line number refer only to the draft SE and will not correspond to the final SE as pages and line numbers have shifted.

Table: Resolution of Comments Draft SE Page No./

Line No.

Westinghouse Suggested Revision NRC Resolution 8/3-4 Editorial Comment Suggested wording: The second sub-goal in demonstrating that the experimental data are appropriate is to demonstrate that the experimental data have been accurately measured.

The NRC staff finds the suggested wording change acceptable.

8/6-7 Editorial Comment Suggested wording in Figure 4:

The experimental data have been accurately measured.

The NRC staff finds the suggested wording change acceptable.

13/5-6 Editorial Comment Suggested wording: It contains three types of part-length rods, of which two are two-thirds length and one is one-third length The NRC staff finds the suggested wording change acceptable.

13/17 Editorial Comment Suggested wording: Considering the slightly different thermal expansion properties of the test section materials The NRC staff finds the suggested wording change acceptable 15/16-19 Proprietary Markings Please mark proprietary as shown:

[

]

The identified text is directly quoted from the TR and is proprietary therein. Thus, the NRC staff finds the suggested proprietary markup acceptable.

Table: Resolution of Comments (Continued)

Draft SE Page No./

Line No.

Westinghouse Suggested Revision NRC Resolution 15/31-32 Proprietary Markings Please mark proprietary as shown: [

]

The NRC staff finds the suggested proprietary markup acceptable.

22/27 Editorial Comment Suggested wording:

Demonstrating that the model validation is appropriate is accomplished using the five sub-goals for consistency with page 36, line 22.

Because this maintains consistency with Figure 9 of the SE, the NRC staff finds the suggested wording change acceptable.

28/40 Editorial Comment Suggest changing sparce to sparse for consistency with other uses within the SER.

The NRC staff finds the suggested wording change acceptable because it updates the text to be consistent with the rest of the SE.

29/19 Editorial Comment Suggest changing sparce to sparse for consistency with other uses within the SER.

The NRC staff finds the suggested wording change acceptable because it updates the text to be consistent with the rest of the SE.

29/24-37 Technical Comment Suggested wording:...each axial cross-section. In the optimization of the bundle U-235 enrichment and Gd distributions, the R-factor is minimized at the burnup of maximum reactivity (the so-called k-inf peak) which typically occurs towards the end of the first cycle. R-factors at both lower and higher burnups will be somewhat greater but, for the D6 CPR correlation, R-factors will typically not exceed

[ ] unless the adjacent control rod is deeply inserted. In the case of a deeply inserted control rod resulting in a high R-factor (at any burnup), the actual bundle power will be strongly suppressed to an extent that, although the critical power is reduced by the high R-factor, the bundle CPR will be non-limiting.

Moreover, higher R-factors generally correspond to conditions of fewer rods near dryout. Based on this...

The NRC staff finds the suggested wording provides additional clarity to the original text and a pertinent discussion point (i.e., higher R-factors result from deeply inserted control rods, but the resulting bundle power will be suppressed such that the bundle CPR will be non-limiting) regarding acceptability of the sparse data in Sparse Region (D). Therefore, the suggested wording change is acceptable.

Table: Resolution of Comments (Continued)

Draft SE Page No./

Line No.

Westinghouse Suggested Revision NRC Resolution 29-30/48-15 Technical Comment Suggested wording: Regarding Sparse Region (F), the D5 (Ref. 9) and D6 R-factors are not directly comparable for conditions with [

] Higher R-factors correspond to fewer rods near dryout and as mentioned above, strong power tilts resulting in R-factors above [ ] are typically only obtained by a deeply inserted control rod which results in a non-limiting CPR. Therefore, the NRC staff concluded that the R-factors in Sparse Region (F) would likely not result in limiting conditions and justifies the sparse distribution of data in this region of the expected domain. Regarding Sparse Region (G), [

] the NRC staff noted the discussion provided above for the justification of Sparce Region (F) is applicable. As mentioned above, R-factors above [ ] are typically only obtained by a deeply inserted control rod which results in a non-limiting CPR. R-factors in the range of [

] are less common than R-factors [

] and are typically less limiting since a higher R-factor corresponds to fewer rods near dryout.

Moreover, the interpolation in subcooling by the D6 CPR correlation to the range of [ ] Kelvin from data at lower and higher subcooling which include [ ] R-factors is considered accurate due to the simple linear dependence of critical power on subcooling as demonstrated empirically for the latest three generations of Westinghouse BWR fuel designs as stated in WCAP-18904.

The NRC staff finds the suggested wording provides additional clarity to the original text as well as an additional pertinent discussion point, that the D6 R-factor model is more sensitive to power tilting due to accounting for cross flow effects that manifest in the absence of the SVEA cross in TRITON11 fuel. As such, the NRC staff finds the suggested wording acceptable, but adds minor modifications to the text for consistency with the rest of the SE:

Regarding Sparse Region (F), the D5 (Ref. 9) and D6 R-factors are not directly comparable for conditions with [

] Higher R-factors correspond to fewer rods near dryout and as mentioned above, strong power tilts resulting in R-factors above [ ] are typically only obtained by a deeply inserted control rod, and this results in a non-limiting CPR.

Therefore, the NRC staff concluded that the R-factors in Sparse Region (F) would likely not result in limiting conditions and justifies the sparse distribution of data in this region of the expected domain. Regarding Sparse Region (G), [

] the NRC staff noted the discussion provided above for the justification of Sparse Region (F) is applicable. As mentioned above, R-factors above [ ] are typically only obtained by a deeply inserted control rod, which results in a non-limiting CPR. R-factors in the range of [ ] are less common than R-factors [ ] and are typically less limiting since a higher R-factor corresponds to fewer rods near dryout. Moreover, the interpolation in subcooling by the D6 CPR correlation to the range of [ ] Kelvin from data at lower and higher subcooling which include

[ ] R-factors is considered reasonable due to the simple linear dependence of critical power on subcooling as demonstrated empirically for the latest three generations of Westinghouse BWR fuel designs as discussed in Section 3.5 of WCAP-18904-P/NP, Revision 0.

Table: Resolution of comments (Continued)

Draft SE Page No./

Line No.

Westinghouse Suggested Revision NRC Resolution 30/16 Editorial Comment: Suggest changing sparce to sparse for consistency with other uses within the SER.

The NRC staff finds the suggested wording change acceptable because it updates the text to be consistent with the rest of the SE.

31/12-13 Proprietary Markings Please mark proprietary as shown: [

]

The NRC staff finds the suggested proprietary markup acceptable.

31/15-16 Proprietary Markings Please mark proprietary as shown: [

]

The NRC staff finds the suggested proprietary markup acceptable.

31/20-21 Proprietary Markings Please mark proprietary as shown: [

]

The NRC staff finds the suggested proprietary markup acceptable.

31/22-23 Proprietary Markings Please mark proprietary as shown: [

]

The NRC staff finds the suggested proprietary markup acceptable.

32/31-32 Proprietary Markings Please mark proprietary as shown: [

]

The NRC staff finds the suggested proprietary markup acceptable.

37/19-33 Technical Comment Westinghouses intention is to implement the D6 in all our dynamic codes according to the approved methodologies and BISON application was used as a demonstration example. As such, we suggest Westinghouse provides validation results of BISON against the FRIGG database of transient tests (discussed further in Section 3.1.3.5.3, Transient Prediction, of this SE) as an example of application.

The NRC staff concluded that the implementation and validation of the D6 CPR correlation in transient applications is reasonable.

The NRC staff partially agrees with the suggested text change and makes the following changes:

Westinghouse provides validation results of BISON against the FRIGG database of transient tests (discussed further in Section 3.1.3.5.3, Transient Prediction, of this SE) as an example of transient application. Because this demonstrates the transient analysis code is validated against a database of pertinent transient tests, the NRC staff concluded that the approach presented for the implementation and validation of the D6 CPR correlation in transient applications is reasonable.

Table: Resolution of comments (Continued)

Draft SE Page No./

Line No.

Westinghouse Suggested Revision NRC Resolution 38/29 Proprietary Markings Please mark 45 as proprietary The NRC staff does not agree with the suggested proprietary markings.

Section 6.3.3 on Page 6-2 of both proprietary version and non-proprietary/publicly available (ML23307A185) version of TR WCAP-18904, Revision 0, show the relevant text as non-proprietary with no proprietary markings around 45.

38/31-32 Editorial Comment Suggested wording: The indication of dryout was a temperature change rate of The NRC staff finds the proposed editorial change acceptable because it maintains consistency with the text in WCAP-18904-P/NP, Revision 0.

39/9-10 Technical Comment Suggested wording: Therefore, the D6 model was able to accurately predict transient behavior [ ]

The NRC staff agrees with the suggested wording change; discussions within Section 6.3 of WCAP-18904-P/NP, Revision 0, indicate the intent of the tests was to predict whether dryout occurred for each of the relevant transient tests, and predicting dryout for a test where dryout occurred is considered an accurate prediction.

39/13-14 Proprietary Markings Suggest combining the consecutive proprietary brackets.

The NRC staff partially agrees with the suggested proprietary markup. For transparency in its findings, the NRC staff finds the portion of the text indicating accurate predictive capability of the D6 correlation should be non-proprietary. The NRC staff suggests the following markup:

[

] Therefore, the D6 model was able to accurately predict transient behavior [

]

Table: Resolution of comments (Continued)

Draft SE Page No./

Line No.

Westinghouse Suggested Revision NRC Resolution 39/15-19 Technical Comment Suggested wording: [

] Because Westinghouse demonstrated that the D6 CPR correlation is able to accurately predict the CPR behavior for transient conditions representative of AOOs The NRC staff agree with the suggested wording change; discussions within Section 6.3 of WCAP-18904-P/NP, Revision 0, indicate the intent of the tests was to predict whether dryout occurred for each of the relevant transient tests, and predicting dryout for a test where dryout occurred is considered an accurate prediction.

40/24 Editorial Comment Suggest changing Kg to kg in Table 4-1.

The NRC staff agree with the suggested editorial change because it corrects a typo.

43/21 Editorial Comment Suggest adding CPR (critical power ratio) to list of acronyms.

The NRC staff agree with the suggested editorial change because it includes an acronym that is frequently used throughout the SE.