ML13200A193
| ML13200A193 | |
| Person / Time | |
|---|---|
| Site: | Monticello  |
| Issue date: | 08/30/2012 |
| From: | AREVA NP |
| To: | Office of Nuclear Reactor Regulation |
| Shared Package | |
| ML13200A185 | List: |
| References | |
| L-MT-13-055 ANP-3138(NP), Rev 0 | |
| Download: ML13200A193 (37) | |
Text
Enclosure 13 AREVA Report ANP-3138(NP)
Monticello Improved K-factor Model for ACE/ATRIUM 1OXM Critical Power Correlation Revision 0 36 pages follow
ANP-3138(NP)
Revision 0 Monticello Improved K-factor Model for ACE/ATRIUM 1OXM Critical Power Correlation August 2012 A
AREVA NP Inc. AREVA
uontrolled uocument AREVA NP Inc.
ANP-3138(NP)
Revision 0 Monticello Improved K-factor Model for ACE/ATRIUM 1OXM Critical Power Correlation
Lontrollea Uocument AREVA NP Inc.
ANP-3138(NP)
Revision 0 Monticello Improved K-factor Model for ACE/ATRIUM 1OXM Critical Power Correlation Copyright © 2012 AREVA NP Inc.
All Right Reserved
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page i Nature of Changes Item Page Description and Justification
- 1. All This is the initial release.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 10XM Critical Power Correlation Page ii Contents 1.0 Introduction and Summary ............................................................................................ 1-1 2.0 Standard Review Plan Requirements ........................................................................... 2-1 3 .0 R evised C o rre latio n ...................................................................................................... 3-1 3 .1 R od P eaking Function ....................................................................................... 3-1 3.2 Applying Rod Peaking Function in the Critical Power Correlation ...................... 3-3 3.3 Method for Calculation Additive Constants ........................................................ 3-3 3.3.4 Additive Constants for ACE/ATRIUM 1OXM Correlation ...................... 3-8, 3.4 Additive Constant Uncertainty ......................................................................... 3-14 3.5 Critical Power Correlation Conservatisms ....................................................... 3-17 4.0 Transient Benchmarking ............................................................................................... 4-1 5 .0 [ ] K-factor Method ............................................................................. 5-1 6.0 Implementation of Improved K-factor Methodology ....................................................... 6-1 7 .0 R e fe re n c e s ................................................................................................................... 7-1 AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Paae iii Tables 3-1: Additive Constant Uncertainty for High Local Peaking ................................................ 3-16 4-1: XCOBRA-T Transient Dryout Results, [ ] .................................. 4-3 4-2: XCOBRA-T [ ] Transient Dryout Results [
......................................................................................................................... 4 -5 Figures 1-1: Comparison of Calculated to Measured Critical Power ................................................. 1-3 3-1: Adjacent Rod Identification for K-factor Calculation ...................................................... 3-9 3-2: Rods Observed to Dryout in Testing ........................................................................... 3-10 3-3: Peaked Symmetric Rods Not Observed to Dryout in Testing ...................................... 3-11 3-4: ACE/ATRIUM 1OXM Additive Constants ..................................................................... 3-12 3-5: Additive Constant Comparison ................................................................................... 3-13 AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM IOXM Critical Power Correlation Page iv Nomenclature Acronym Definition ACE AREVA Critical power Evaluator AOO Anticipated Operational Occurrence BT Boiling Transition BWR Boiling Water Reactor CPR Critical Power Ratio ECPR Experimental Critical Power Ratio; the ratio of calculated to the measured critical power LOCA Loss Of Coolant Accident MCPR Minimum Critical Power Ratio PLR Part Length Rod AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 1-1 1.0 Introduction and Summary Reference 1 presents the approved ACE/ATRIUM 1OXM critical power correlation for ATRIUM TM* 1OXM fuel. A concern with the calculation of the K-factor within the approved ACE correlation was identified. Since K-factor was integrated over the entire heated length of the assembly, it was possible for the local peaking factors in the upper lattices to contribute significantly to the K-factor used, even when dryout occurs much lower in the bundle.
Reference 2 presents a revision to the ACE critical power correlation for ATRIUM 1OXM fuel.
The Reference 2 correlation is very similar to the Reference 1 critical power correlation with a couple of exceptions. The K-factor methodology was modified in response to deficiencies found in the axial averaging process. In addition, the additive constants were revised as a result of the change to the K-factor model. Evaluations confirmed that the Reference 1 critical power correlation coefficients do not require revision as a result of these changes.
The purpose of this document is to present the ACE/ATRIUM 1OXM critical power correlation that will be used in licensing analyses for Monticello until Reference 2 is generically approved and included in the Monticello Plant Technical Specifications. The correlation presented in this document is exactly the same as that presented in Reference 2.
Reference 3 provides a description of the rod local peaking function (called K-factor). The improved K-factor method used in the Monticello ACE/ATRIUM 1OXM critical power correlation is described in this document. This modified method supersedes the one described in Reference 3 and used in Reference 1. This document also describes the minor changes in the method for determining additive constants that became necessary due to the changes in the K-factor methodology.
The comparison between measured and predicted critical power data is shown in Figure 1-1.
The correlation experimental critical power ratio (ECPR) mean with the improved K-factor methodology and updated additive constants is [ ] and the ECPR standard deviation is
[ ]. The ECPR mean and standard deviation from Reference 1 were [ ] and
[ ] respectively.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 1-2 The range of applicability of the critical power correlation is unchanged from Reference 1. The modified correlation is applicable to Monticello steady-state design and analysis, core monitoring, MCPR safety limit, anticipated operational occurrences (AOO's), accidents, LOCA, and instability analysis for the ATRIUM 1OXM fuel design.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 1-3 Figure 1-1: Comparison of Calculated to Measured Critical Power AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Paae 2-1 2.0 Standard Review Plan Requirements There are no critical power correlation specific requirements in the standard review plan.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-1 3.0 Revised Correlation All modern critical power correlations contain a function that accounts for rod peaking. This function is called K-factor in the ACE formulation of the correlation. The model equation for the
[(3.1)
ACE correlation is given in Equation 3.1 of Reference 1 (including symbol definitions). The revision is in the [ ] term:
The K-factor, [
]
This assumption was found to be inappropriate because (1) it allows downstream conditions above the location of dryout to non-physically influence the critical power, and (2) it provides equal weighting to all axial locations (low power regions as well as regions far from the location of dryout). Both of these problems were found to be capable of influencing the predicted results in a non-conservative manner.
3.1 Rod Peaking Function The K-factor characterizes the rod peaking effect on the bundle critical power. The critical power varies inversely with K-factor. That is, as K-factor increases in value, the critical power decreases in value. [
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Paqe 3-2 This description of the local rod peaking function is unchanged from the description in References 1 and 3.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-3 3.2 Applying Rod Peaking Function in the CriticalPower Correlation
] The maximum of the averaged K-factors over all the rods was then chosen for use in the critical power correlation according to Equation 3.46 in Reference 3.
This averaging of the axial K-factor distribution for each rod was found to be inappropriate for the reasons discussed in Section 3.0 and is therefore excluded in the improved K-factor method.
[
] Thus this solution explicitly addresses both problems noted in Section 3.0.
In the improved method, [
3.3 Method for CalculationAdditive Constants The spacers and bundle geometry characteristics influence the critical power behavior of the individual rods within the fuel bundle. Therefore, a factor is needed to distinguish the critical power performance of each rod. These position dependent factors are termed additive constants. Additive constants can be considered as a flow/enthalpy redistribution characteristic for a given bundle and spacer design.
In critical power testing, [
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-4 In accordance with the [ ] the CHF database was randomly divided into a defining data set and a validating data set.
Approximately [ ] was set aside as the validating set of data. The remaining [ ] form the defining data set and were used to develop the critical power correlation. The additive constants for all the rod positions were determined from the defining data set. The calculation of additive constants uses the same partition of data as was used during the critical power correlation development. [
]
The defining and validating data sets used for correlation development in Reference 1 are unchanged. The additive constants are determined [
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-5 AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-6 AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-7 AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-8 3.3.4 Additive Constants for ACE/ATRIUM 1OXM Correlation The revised ATRIUM 1OXM additive constants are shown in Figure 3-4. For comparison purposes, both the revised ATRIUM 1OXM additive constants and the ACE/ATRIUM 10XM additive constants from Reference 1 are presented in Figure 3-5. The observed changes in additive constant are generally small and [
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-9 Figure 3-1: Adjacent Rod Identification for K-factor Calculation AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-10 Figure 3-2: Rods Observed to Dryout in Testing AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-11 Figure 3-3: Peaked Symmetric Rods Not Observed to Dryout in Testing AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-12 Figure 3-4: ACEIATRIUM 1OXM Additive Constants AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-13 Figure 3-5: Additive Constant Comparison AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Paqe 3-14 3.4 Additive Constant Uncertainty The overall uncertainty in additive constants is determined [
]. The following steps are applied:
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-15 The resulting overall additive constant uncertainty for the Monticello ACE/ATRIUM 1OXM correlation is [ ]. The additive constant uncertainty from Reference 1 is [ I An additional high peaking uncertainty is imposed in the MCPR safety limit methodology for those rods whose local peaking exceeds [
] Table 3-1 shows the results of these calculations.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Paae 3-16 Table 3-1: Additive Constant Uncertainty for High Local Peaking AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 3-17 3.5 CriticalPower CorrelationConservatisms With the improved K-factor model, the Monticello ACE/ATRIUM 1OXM correlation has an average ECPR of [ ] with a standard deviation of [ ] . For the Reference 1 correlation, the average ECPR was [ ] with a standard deviation of [ ]. The correlation was used to assess each rod in each of the tests. The associated critical powers of each rod were then compared to the measured critical power and a count made of the number of rods which were predicted to be in boiling transition (BT) and this was compared to the number of rods actually observed to be in boiling transition in the experimental data. With the improved K-factor methodology and additive constants, this ratio of predicted to measured rods in boiling transition is [ ]. This compares with a value of [ ] in Reference 1.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 4-1 4.0 Transient Benchmarking An industry accepted standard in BWR transient methodology is that steady-state dryout correlations are conservative for use in transient methodology. Transient dryout tests [
] were performed to reconfirm this for the ATRIUM 1OXM fuel design when using the ACE/ATRIUM 1OXM critical power correlation.
The limiting transient tests of interest are the simulated load rejection without bypass (LRNB) events that consist of power and pressure ramps and flow decay and the simulated loss of flow events that consist of flow decay and power decay. The power, pressure, and flow were all controlled by a function generator. The forcing functions were programmed to produce the transient rod surface heat flux typical of the various events.
A total of [ ] ATRIUM 1OXM LRNB and loss of flow transients were run which were either measured or predicted to have dryout. Of these [ ] transient critical power tests, [
] The initial conditions for these tests are given in Table 7-7 of Reference 1.
Evaluations of the transient critical power tests were repeated using the improved K-factor methodology. [
] The AREVA NP transient thermal hydraulic code XCOBRA-T (References 5 and 6), was used to predict the transient test results using the ACE/ATRIUM 1OXM critical power correlation. The test power forcing function provides the boundary condition of power, which is modeled in XCOBRA-T [
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 4-2
[
I The results [ ] are summarized in Table 4-1.
[
I The transient benchmark results with the modified correlation are consistent with those presented in Reference 1.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Paqe 4-3 Table 4-1: XCOBRA-T Transient Dryout Results, [ I AREVA NP Inc.
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 4-4 Table 4-1: XCOBRA-T Transient Dryout Results, (continued)
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 4-5 Table 4-2: XCOBRA-T [ I Transient Dryout Results
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 5-1 5.0 [ ] K-factor Method With the improved K-factor method, the critical power correlation is used to [
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 6-1 6.0 Implementation of Improved K-factor Methodology The improved K-factor methodology has been implemented into MICROBURN-B2 (Reference 8), SAFLIM3D (Reference 7), XCOBRA (Reference 11), XCOBRA-T (References 5 and 6), RELAX (Reference 9), and RAMONA5-FA (Reference 10). It will be used in Monticello core design and analysis, core monitoring, MCPR safety limit methodology, AOO's, LOCA, and other codes and methods that use the critical power correlations.
The MCPR safety limit methodology performs a rod-by-rod evaluation to estimate the number of rods in BT associated with a particular safety limit. [
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Monticello Improved K-factor Model for Revision 0 ACE/ATRIUM 1OXM Critical Power Correlation Page 7-1 7.0 References
- 1. ANP-10298PA Revision 0, "ACE/ATRIUM 10XM Critical Power Correlation," AREVA NP Inc., March 2010.
- 2. ANP-10298PA Revision 0, Supplement 1P Revision 0, "Improved K-Factor Model for ACE/ATRIUM 1OXM Critical Power Correlation," AREVA NP, Inc., December 2011.
- 3. ANP-10249PA Revision 1, "ACE/ATRIUM-10 Critical Power Correlation," AREVA NP Inc.,
September 2009.
- 4. C. Bennett and N. L. Franklin. "Statistical Analysis in Chemistry and the Chemical Industry," Marbern House, October 1987.
- 5. XN-NF-84-105(P)(A) Volume 1 and Volume 1 Supplements 1 and 2, "XCOBRA-T: A Computer Code for BWR Transient Thermal-Hydraulic Analysis," Exxon Nuclear Company, February 1987.
- 6. XN-NF-84-105(P)(A) Volume 1 Supplement 4, "XCOBRA-T: A Computer Code for BWR Transient Thermal-Hydraulic Core Analysis Void Fraction Model Comparison to Experimental Data," Advanced Nuclear Fuels Corporation, June 1988.
- 7. ANP-10307PA Revision 0, "AREVA MCPR Safety Limit Methodology for Boiling Water Reactors," AREVA NP Inc., June 2011.
- 8. EMF-2158(P)(A) Revision 0, "Siemens Power Corporation Methodology for Boiling Water Reactors: Evaluation and Validation of CASMO-4 / MICROBURN-B2," Siemens Power Corporation, October 1999.
- 9. EMF-2361(P)(A) Revision 0, "EXEM BWR-2000 ECCS Evaluation Model," Framatome ANP Richland, Inc., May 2001.
- 10. BAW-10255PA Revision 2, "Cycle-Specific DIVOM Methodology Using the RAMONA5-FA Code," AREVA NP Inc., May 2008.
- 11. XN-NF-80-19(P)(A) Volume 3 Revision 2, "Exxon Nuclear Methodology for Boiling Water Reactors, THERMEX: Thermal Limits Methodology Summary Description," Exxon Nuclear Company, Inc., January 1987.
- 12. [
]
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