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{{#Wiki_filter:SOUTHERN CALIFORNIA Richard 1. St. OngeEDISONmeDirector, Nuclear Regulatory Affairs andED SO " Emergency PlanningAn EDISON INTERNATIONAL CompanyApril 10, 201310 CFR 50.4U.S. Nuclear Regulatory CommissionATTN: Document Control DeskWashington, DC 20555-0001Subject: Docket No. 50-361Response to Request for Additional Information (RAIs 53 and 72) RegardingConfirmatory Action Letter Response(TAC No. ME 9727)San Onofre Nuclear Generating Station, Unit 2References: 1. Letter from Mr. Elmo E. Collins (USNRC) to Mr. Peter T. Dietrich (SCE), datedMarch 27, 2012, Confirmatory Action Letter 4-12-001, San Onofre NuclearGenerating Station, Units 2 and 3, Commitments to Address Steam GeneratorTube Degradation2. Letter from Mr. Peter T. Dietrich (SCE) to Mr. Elmo E. Collins (USNRC), datedOctober 3, 2012, Confirmatory Action Letter -Actions to Address SteamGenerator Tube Degradation, San Onofre Nuclear Generating Station, Unit 23. Letter from Mr. James R. Hall (USNRC) to Mr. Peter T. Dietrich (SCE), datedMarch 18, 2013, Second Request for Additional Information (RAI 33-67)Regarding Response to Confirmatory Action Letter, San Onofre NuclearGenerating Station, Unit 24. Letter from Mr. Richard J. St. Onge (SCE) to Document Control Desk(USNRC), dated February 25, 2013, Response to Request for AdditionalInformation (RAIs 2, 3 and 4) Regarding Confirmatory Action Letter Response,San Onofre Nuclear Generating Station, Unit 25. Email from Mr. James R. Hall (USNRC) to Mr. Ryan Treadway (SCE), datedMarch 15, 2013, Request for Additional Information (RAIs 68-72) RegardingResponse to Confirmatory Action Letter, San Onofre Nuclear GeneratingStation, Unit 2Dear Sir or Madam,On March 27, 2012, the Nuclear Regulatory Commission (NRC) issued a Confirmatory ActionLetter (CAL) (Reference 1) to Southern California Edison (SCE) describing actions that the NRCand SCE agreed would be completed to address issues identified in the steam generator tubesof San Onofre Nuclear Generating Station (SONGS) Units 2 and 3. In a letter to the NRC datedOctober 3, 2012 (Reference 2), SCE reported completion of the Unit 2 CAL actions andincluded a Return to Service Report (RTSR) that provided details of their completion.P.O. Box 128 LaSan Clemente, CA 92672 q Document Control Desk-2-April 10, 2013By letter dated March 18, 2013 (Reference 3), the NRC issued Requests for AdditionalInformation (RAls) regarding the CAL response. Enclosure 1 of this letter provides theresponse to RAI 53.SCE provided the response to RAIs 2, 3 and 4 in a letter dated February 25, 2013(Reference 4). By e-mail dated March 15, 2013 (Reference 5), the NRC issued Requests forAdditional Information (RAIs) regarding the response to RAIs 2, 3 and 4. Enclosure 1 of thisletter provides the response to RAI 72.There are no new regulatory commitments contained in this letter. If you have any questions orrequire additional information, please call me at (949) 368-6240.Sincerely,Enclosure:1. Response to RAIs 53 and 72cc:A. T. Howell III, Regional Administrator, NRC Region IVJ. R. Hall, NRC Project Manager, SONGS Units 2 and 3G. G. Warnick, NRC Senior Resident Inspector, SONGS Units 2 and 3R. E. Lantz, Branch Chief, Division of Reactor Projects, NRC Region IV ENCLOSURE 1SOUTHERN CALIFORNIA EDISONRESPONSE TO REQUEST FOR ADDITIONAL INFORMATIONREGARDING RESPONSE TO CONFIRMATORY ACTION LETTERDOCKET NO. 50-361TAC NO. ME 9727Response to RAIs 53 and 72 RAI 53In Reference 9, Section 4.6.2, "[Tube-to-Tube (TTW)] Growth Model," was the regression fitslope and intercept uncertainty modeled (e.g., as was done for the burst pressure versusvoltage model in NRC Generic Letter 95-05)? If not, why is this conservative? Was the datascatter about the regression fit modeled as normally distributed? If so, provide justificationfor the adequacy of this assumption (i.e., normal distribution) to fully capture the upper tail ofthe distribution as shown in Figure 4-12 on page 4-25.RESPONSENote: RAI Reference 9 is the Operational Assessment for SONGS Unit 2 Steam Generatorsfor Upper Bundle Tube-to-Tube Wear Degradation at End of Cycle 16," prepared by IntertekAPTECH for Areva, Report No. AES 12068150-2Q-1, Revision 0, September 2012.The Monte-Carlo simulation which was used to perform the SONGS Unit 2 operationalassessment (OA) for tube-to-tube wear (TTW) relies on a correlation developed usingmeasured Unit 3 TTW depths. The correlating independent variable is the total wear index.This work is described in summary form in Section 4.6.2 of RAI Reference 9. Elements ofthe residual analysis of the TTW growth model development process are shown in Figure4-12 of RAI Reference 9. The two issues identified in RAI 53 are addressed in thisresponse.1. Regression Model UncertaintyIn NRC Generic Letter 95-05 (Reference R1), the implementation consisted of developing asampling method discussed in References R2 and R3. This approach samples from aprediction interval equation which accounts for several components of uncertainty includingthose involving the slope of the regression line, the intercept, and the basic error-of-estimatefrom the data set. The form of the sampling equation is given by:Ys = YCor +/- ta/2,N-2 Sy/x[ 1 + 1/N + (X-x')2 /((N-1)Sx2 ) 0.5where:Y= Sampled value of YYCor = Value computed from regression lineta/2,N-2 = t-distribution with N-2 degrees of freedomSy/x = Standard error of estimate from the correlationN = Number of data pointsX = Value of independent variablex' = Mean of independent variable valuesSx2 = Sample variance of independent variable valuesExamination of the above equation shows that the most important component is the size ofthe data set (N) from which the correlation was developed. In this case, over 320 datapoints were used. A simplified estimate of the effect of neglecting these terms yields amultiplier of 1.0031 on the standard error of estimate. The other affected componentinvolves the use of the t-distribution rather than the normal distribution for the probabilisticsampling component. In general for sample sizes greater than approximately 30, thePage 2 of 12 difference is considered negligible for use in simulation. In the case of the Unit 3 data, thedifference at the 95th percentile is negligible being approximately 0.3% (1.6497 vs. 1.645). Itwas not necessary to explicitly address the uncertainties in slope and intercept variablesfrom the regression analysis since it is inconsequential to the simulation results.2. Statistical Treatment of the Regression ModelIn Figure 4-12 of RAI Reference 9, the distribution of the residuals is well represented by anormal cumulative distribution function. Deviations from normality are observed only at thelower and upper extremes (outside the 95th percentile bounds). For the lower tail, thedeviation is conservative. For the upper tail, the deviation can become non-conservativewhen sampling beyond the upper 97th percentile level (e.g., when the number of TTWinitiations is large so that there is a greater chance in having an extreme value for TTWgrowth as a sample outcome).To validate that any deviation from normality from the upper tail does not significantly impactthe OA results, the TTW growth model was modified. This was accomplished by separatelyfitting the upper tail of the residuals with a Beta distribution to give a more precise fit to theresiduals above the 95th percentile. This modification was done for the 70% power modeland involved changing the logic in the algorithm to select the value for growth rateuncertainty when the standard normal parameter exceeds 1.645 (above the upper 95%).The results from the re-evaluation are given in the table below:Allowable Inspection Interval for Probability of Burst (POB) = 5%(RAI Reference 9, Case I -ETSS Depth Sizing)Normal Distribution of Residuals Normal Distribution of Residuals(Full Sample Range) (Adjusted Above 95th Percentile)1.33(1) (Years at Power) 1.24(2) (Years at Power)Notes:1) Results from RAI Reference 92) Results from modified modelThe above comparison between the two methods of treating the regression error shows asmall difference in the allowable inspection interval calculated from the OA. The change ininspection interval is less than 7%. For the planned inspection interval of 5 months (0.42years at power), the deviation in the upper tail beyond 95% has a negligible effect on theallowable inspection interval for Unit 2 due to the much shorter operating period.Page 3 of 12 References:RI. Generic Letter 95-05: Voltage-Based Repair Criteria for Westinghouse SteamGenerator Tubes Affected by Outside Diameter Stress Corrosion Cracking,(August 3, 1995).R2. Statistics Manual, Crow, Davis, and Maxfield, Dover Press, New York, Page 163.R3. Applied Regression Analysis, Second Edition, Draper and Smith, John Wiley andSons, New York, Page 30, 1981.Page 4 of 12 RAI 72Reference 1, Response to RAI 3 -This response did not fully address RAI question 3. What isthe sensitivity of the results in Figure 5-4 of Reference 4 to the different formulations of wearindex in Equations 1 through 5?RESPONSENote: RAI Reference 1 is SCE's "Response to Request for Additional Information (RAls 2, 3,and 4) Regarding Confirmatory Action Letter Response," dated February 25, 2013.Note: RAI Reference 4 is the "Operational Assessment for SONGS Unit 2 Steam Generatorsfor Upper Bundle Tube-to-Tube Wear Degradation at End of Cycle 16," prepared by IntertekAPTECH for Areva, Report No. AES 12068150-2Q-1, Revision 0, September 2012.The wear index represents the complete state of wear degradation in a tube due to contact withtube supports. As discussed in the response to RAI 3, the justification of the wear index used inRAI Reference 4 is the ability of the wear index, as a correlating parameter, to describe theSONGS Unit 3 tube-to-tube wear (TTW) in terms TTW depth and maximum depths of TTW after0.926 years at power. This was accomplished by selecting the correlation equation developedby regression analysis of the Unit 3 data that achieved the best fit. A standard approach inengineering modeling is to apply "goodness of fit" criteria in the selection process. Thisapproach provides a basis for selecting the mathematical combination of wear indices to yieldthe best correlation. Statistical regression analysis and goodness-of-fit verification (R2 andstandard deviation of the residuals) are the means by which an empirical correlation can bedeveloped that best explains what is physically observed with minimum uncertainty. From thisapproach, the total wear index based on the summation of anti-vibration bar (AVB) and tubesupport plate (TSP) wear was established.The wear index selection process evaluated several alternative definitions and determined thegoodness-of-fit for each. Of the five model variations discussed in the response to RAI 3, thefirst four have similar properties in terms of the fraction of the data variation explained by theregression model (R2), and the standard deviation of the residuals (proportional to the standarderror of estimate) which is a measure of variance in the prediction ability of the model. Forthese criteria, it was concluded that Alternatives 1 through 4 are essentially equivalent havingsimilar capability in correlating the observed NDE data to each definition of the wear index.The wear index definition from Alternative 4 (the summation of AVB and TSP wear) wasselected as the definition of the wear index. This alternative resulted in the ability to define theTTW depth prediction model in terms of a single wear related quantity with accuracycomparable to a more complex model of the group.Alternative 5 redefined the wear index in terms of AVB wear only. As demonstrated in Table 1of the response to RAI 3, this alternative does not describe wear degradation as well asAlternatives 1 through 4. Because of the greater variance for the AVB wear index model, it wasexpected that this definition for the wear index would give a more limiting result for probability ofburst (POB) than the current total wear index model.To respond to this RAI, a separate and complete operational assessment (OA) model wasdeveloped using a wear index based on AVB wear only, to demonstrate the effect of analternate definition on POB. Comparison of the two wear index models (AVB wear only and thePage 5 of 12 total wear index as the sum of AVB and TSP) is shown in Figure 1 for Unit 2 and Figure 2 forUnit 3. For Unit 2, the change in definition doesn't appear significant but small differences inindices greater than 60% through-wall (TW) will affect the development of the probability ofinitiation (POI) model. For Unit 3, the AVB wear index effectively reduces the range of the indexfrom greater than 300%TW to less than 200%TW. This change in definition compresses thescale of both the initiation and TTW growth rate models and affects the shape of the POI modelfor Unit 2.Figure 3 shows the existence of TTW in Unit 3 plotted as the presence or non-presence of TTWagainst the AVB wear index. Logistic regression analysis was used to produce the Unit 3 curve.Following the same benchmarking procedure in RAI Reference 4, the Unit 3 curve was adjustedto develop the model for Unit 2. The Unit 2 curve transitioned to probability of unity as the AVBwear index approached 200% TW. An acceptable benchmark was achieved when the modelproduced about two detected indications at the estimated threshold detection level for the+PointTM probe. This process was discussed in the response to RAI 9. The results from thebenchmarking simulation of 1000 trial calculations are shown in the histogram in Figure 4. Thebenchmarking performed produced similar outcomes as the total wear index model.The development of the TTW growth model based on the AVB wear index is discussed in theresponse to RAI 3. The regression line for the TTW maximum depth data is shown in Figure 5having an intercept of 19.638, a slope of 0.2206 and a standard deviation of the residuals of12.63.Figure 6 compares the POB results for the 70% power OA for the two wear index definitions.The 70% OA in RAI Reference 4 established an allowable inspection interval of 1.33 years atpower or 16 months based on the total wear index. For the wear index based on AVB wear, theallowable inspection interval becomes 1.15 years at power or 14 months. The reduction in theinspection interval is about 2 months. This difference is not significant since the moreconservative AVB wear index results confirm that significant margin exist for the planned 5month inspection interval. The more conservative results for the AVB wear index are primarilythe result of greater scatter (regression error) evident in the residuals in the regression process.Based on the goodness-of-fit comparisons discussed in the response to RAI 3, and theresponse of RAI 72, the total wear index (Alternative 4) is the optimum model (of thealternatives evaluated) for this degradation mechanism. It is expected that the more complexAlternatives 1 through 3 will give similar POB results as the total wear index model(Alternative 4), having nearly identical scatter in the residuals.Page 6 of 12 SONGS-2 Wear Index Histogram (after 1.718 Years at Power)220u 1402= 1200S10080Ez 6040200AVB Wear Index, (%TW)SONGS-2 Wear Index Histogram (after 1.718 Years at Power)220200 *2E-088--j180160u 140aU 120U010080z 6040200Total Wear Index, (%TW)Figure 1- Unit 2 Histograms for AVB Wear Index andTotal Wear Index Model DefinitionsPage 7 of 12 SONGS-3 Wear Index Histogram (after 0.926 Years at Power)220200 -3E-088 _N 3E-089180160U 140C" 1200 t6100.80-E2 60-4020AVB Wear Index, (%/TW)SONGS-3 Wear Index Histogram (after 0.926 Years at Power)220200 -3E-088111312-089180 -160 --0U140 -S120 -0100z 604020-Total Wear Index, (%/,TW)Figure 2 -Unit 3 Histograms for AVB Wear Index andTotal Wear Index Model DefinitionsPage 8 of 12 Tube-to-Tube Wear Initiation Model.0170J214-0.0o..0)0/0U1.00.90.80.70.60.50.40.30.20.10.0*SONGS-3Oata-A"B WI---SONGS-3 Regression Fit -AVB WI-A--SONGS-2 Initiation Model -AVB Wl-E-SONGS-2 Initiation Model -Total WI--._ ..... ... ....... .II * -0 20 40 60 80 100 120 140 160 180 200Wear Index, WI (%TW)Figure 3 -Comparison of Initiation Models for the AVB and Total Wear IndexDefinitionsPage 9 of 12 U0Initiation Model Benchmarking Results (1000 Trials)220200 -A E Total Wear Index"AVB Wear Index180160140120100806020-20Number of TTW InitiationsFigure 4 -Unit 2 Benchmarking Results for the AVB and Total Wear Index ModelDefinitionsPage 10 of 12 Tube-to-Tube Wear Depths -ETSS 27902.2 SizedIa.0010090807060504030201000 20 40 60 80 100 120AVB Wear Index, (%TW)140 160 180 20(Figure 5 -Unit 3 Tube-to-Tube Wear Depths versus AVB Wear IndexPage 11 of 12 Operational Assessment for TTW for Mid-Cycle 17 for 70% Power Operation0.160.14-0.12 -00~0.10o 0.08S0.0600.04-0.020.00IfI I I--- ETSS 27902.2 Sizing, Total Wear Index Model---ETSS 27902.2 Sizing, AVB Wear Index Model---Mid-Cycle 17 (5 Months at Power)--Cycle 17 (1.578 Years at Power)-SIPC Margin, P09 <= 0.05--I-S___ i +-----.4 -I- I0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1Inspection Interval, (Years at Power)1.2 1.3 1.4 1.5 1.6Figure 6 -Probability of Burst Results for the AVB and Total Wear Index ModelsPage 12 of 12 | {{#Wiki_filter:SOUTHERN CALIFORNIA Richard 1. St. OngeEDISONmeDirector, Nuclear Regulatory Affairs andED SO " Emergency PlanningAn EDISON INTERNATIONAL CompanyApril 10, 201310 CFR 50.4U.S. Nuclear Regulatory CommissionATTN: Document Control DeskWashington, DC 20555-0001Subject: Docket No. 50-361Response to Request for Additional Information (RAIs 53 and 72) RegardingConfirmatory Action Letter Response(TAC No. ME 9727)San Onofre Nuclear Generating Station, Unit 2References: 1. Letter from Mr. Elmo E. Collins (USNRC) to Mr. Peter T. Dietrich (SCE), datedMarch 27, 2012, Confirmatory Action Letter 4-12-001, San Onofre NuclearGenerating Station, Units 2 and 3, Commitments to Address Steam GeneratorTube Degradation2. Letter from Mr. Peter T. Dietrich (SCE) to Mr. Elmo E. Collins (USNRC), datedOctober 3, 2012, Confirmatory Action Letter -Actions to Address SteamGenerator Tube Degradation, San Onofre Nuclear Generating Station, Unit 23. Letter from Mr. James R. Hall (USNRC) to Mr. Peter T. Dietrich (SCE), datedMarch 18, 2013, Second Request for Additional Information (RAI 33-67)Regarding Response to Confirmatory Action Letter, San Onofre NuclearGenerating Station, Unit 24. Letter from Mr. Richard J. St. Onge (SCE) to Document Control Desk(USNRC), dated February 25, 2013, Response to Request for AdditionalInformation (RAIs 2, 3 and 4) Regarding Confirmatory Action Letter Response,San Onofre Nuclear Generating Station, Unit 25. Email from Mr. James R. Hall (USNRC) to Mr. Ryan Treadway (SCE), datedMarch 15, 2013, Request for Additional Information (RAIs 68-72) RegardingResponse to Confirmatory Action Letter, San Onofre Nuclear GeneratingStation, Unit 2Dear Sir or Madam,On March 27, 2012, the Nuclear Regulatory Commission (NRC) issued a Confirmatory ActionLetter (CAL) (Reference 1) to Southern California Edison (SCE) describing actions that the NRCand SCE agreed would be completed to address issues identified in the steam generator tubesof San Onofre Nuclear Generating Station (SONGS) Units 2 and 3. In a letter to the NRC datedOctober 3, 2012 (Reference 2), SCE reported completion of the Unit 2 CAL actions andincluded a Return to Service Report (RTSR) that provided details of their completion.P.O. Box 128 LaSan Clemente, CA 92672 q Document Control Desk-2-April 10, 2013By letter dated March 18, 2013 (Reference 3), the NRC issued Requests for AdditionalInformation (RAls) regarding the CAL response. Enclosure 1 of this letter provides theresponse to RAI 53.SCE provided the response to RAIs 2, 3 and 4 in a letter dated February 25, 2013(Reference 4). By e-mail dated March 15, 2013 (Reference 5), the NRC issued Requests forAdditional Information (RAIs) regarding the response to RAIs 2, 3 and 4. Enclosure 1 of thisletter provides the response to RAI 72.There are no new regulatory commitments contained in this letter. If you have any questions orrequire additional information, please call me at (949) 368-6240.Sincerely,Enclosure:1. Response to RAIs 53 and 72cc:A. T. Howell III, Regional Administrator, NRC Region IVJ. R. Hall, NRC Project Manager, SONGS Units 2 and 3G. G. Warnick, NRC Senior Resident Inspector, SONGS Units 2 and 3R. E. Lantz, Branch Chief, Division of Reactor Projects, NRC Region IV ENCLOSURE 1SOUTHERN CALIFORNIA EDISONRESPONSE TO REQUEST FOR ADDITIONAL INFORMATIONREGARDING RESPONSE TO CONFIRMATORY ACTION LETTERDOCKET NO. 50-361TAC NO. ME 9727Response to RAIs 53 and 72 RAI 53In Reference 9, Section 4.6.2, "[Tube-to-Tube (TTW)] Growth Model," was the regression fitslope and intercept uncertainty modeled (e.g., as was done for the burst pressure versusvoltage model in NRC Generic Letter 95-05)? If not, why is this conservative? Was the datascatter about the regression fit modeled as normally distributed? If so, provide justificationfor the adequacy of this assumption (i.e., normal distribution) to fully capture the upper tail ofthe distribution as shown in Figure 4-12 on page 4-25.RESPONSENote: RAI Reference 9 is the Operational Assessment for SONGS Unit 2 Steam Generatorsfor Upper Bundle Tube-to-Tube Wear Degradation at End of Cycle 16," prepared by IntertekAPTECH for Areva, Report No. AES 12068150-2Q-1, Revision 0, September 2012.The Monte-Carlo simulation which was used to perform the SONGS Unit 2 operationalassessment (OA) for tube-to-tube wear (TTW) relies on a correlation developed usingmeasured Unit 3 TTW depths. The correlating independent variable is the total wear index.This work is described in summary form in Section 4.6.2 of RAI Reference 9. Elements ofthe residual analysis of the TTW growth model development process are shown in Figure4-12 of RAI Reference 9. The two issues identified in RAI 53 are addressed in thisresponse.1. Regression Model UncertaintyIn NRC Generic Letter 95-05 (Reference R1), the implementation consisted of developing asampling method discussed in References R2 and R3. This approach samples from aprediction interval equation which accounts for several components of uncertainty includingthose involving the slope of the regression line, the intercept, and the basic error-of-estimatefrom the data set. The form of the sampling equation is given by:Ys = YCor +/- ta/2,N-2 Sy/x[ 1 + 1/N + (X-x')2 /((N-1)Sx2 ) 0.5where:Y= Sampled value of YYCor = Value computed from regression lineta/2,N-2 = t-distribution with N-2 degrees of freedomSy/x = Standard error of estimate from the correlationN = Number of data pointsX = Value of independent variablex' = Mean of independent variable valuesSx2 = Sample variance of independent variable valuesExamination of the above equation shows that the most important component is the size ofthe data set (N) from which the correlation was developed. In this case, over 320 datapoints were used. A simplified estimate of the effect of neglecting these terms yields amultiplier of 1.0031 on the standard error of estimate. The other affected componentinvolves the use of the t-distribution rather than the normal distribution for the probabilisticsampling component. In general for sample sizes greater than approximately 30, thePage 2 of 12 difference is considered negligible for use in simulation. In the case of the Unit 3 data, thedifference at the 95th percentile is negligible being approximately 0.3% (1.6497 vs. 1.645). Itwas not necessary to explicitly address the uncertainties in slope and intercept variablesfrom the regression analysis since it is inconsequential to the simulation results.2. Statistical Treatment of the Regression ModelIn Figure 4-12 of RAI Reference 9, the distribution of the residuals is well represented by anormal cumulative distribution function. Deviations from normality are observed only at thelower and upper extremes (outside the 95th percentile bounds). For the lower tail, thedeviation is conservative. For the upper tail, the deviation can become non-conservativewhen sampling beyond the upper 97th percentile level (e.g., when the number of TTWinitiations is large so that there is a greater chance in having an extreme value for TTWgrowth as a sample outcome).To validate that any deviation from normality from the upper tail does not significantly impactthe OA results, the TTW growth model was modified. This was accomplished by separatelyfitting the upper tail of the residuals with a Beta distribution to give a more precise fit to theresiduals above the 95th percentile. This modification was done for the 70% power modeland involved changing the logic in the algorithm to select the value for growth rateuncertainty when the standard normal parameter exceeds 1.645 (above the upper 95%).The results from the re-evaluation are given in the table below:Allowable Inspection Interval for Probability of Burst (POB) = 5%(RAI Reference 9, Case I -ETSS Depth Sizing)Normal Distribution of Residuals Normal Distribution of Residuals(Full Sample Range) (Adjusted Above 95th Percentile)1.33(1) (Years at Power) 1.24(2) (Years at Power)Notes:1) Results from RAI Reference 92) Results from modified modelThe above comparison between the two methods of treating the regression error shows asmall difference in the allowable inspection interval calculated from the OA. The change ininspection interval is less than 7%. For the planned inspection interval of 5 months (0.42years at power), the deviation in the upper tail beyond 95% has a negligible effect on theallowable inspection interval for Unit 2 due to the much shorter operating period.Page 3 of 12 | ||
==References:== | |||
RI. Generic Letter 95-05: Voltage-Based Repair Criteria for Westinghouse SteamGenerator Tubes Affected by Outside Diameter Stress Corrosion Cracking,(August 3, 1995).R2. Statistics Manual, Crow, Davis, and Maxfield, Dover Press, New York, Page 163.R3. Applied Regression Analysis, Second Edition, Draper and Smith, John Wiley andSons, New York, Page 30, 1981.Page 4 of 12 RAI 72Reference 1, Response to RAI 3 -This response did not fully address RAI question 3. What isthe sensitivity of the results in Figure 5-4 of Reference 4 to the different formulations of wearindex in Equations 1 through 5?RESPONSENote: RAI Reference 1 is SCE's "Response to Request for Additional Information (RAls 2, 3,and 4) Regarding Confirmatory Action Letter Response," dated February 25, 2013.Note: RAI Reference 4 is the "Operational Assessment for SONGS Unit 2 Steam Generatorsfor Upper Bundle Tube-to-Tube Wear Degradation at End of Cycle 16," prepared by IntertekAPTECH for Areva, Report No. AES 12068150-2Q-1, Revision 0, September 2012.The wear index represents the complete state of wear degradation in a tube due to contact withtube supports. As discussed in the response to RAI 3, the justification of the wear index used inRAI Reference 4 is the ability of the wear index, as a correlating parameter, to describe theSONGS Unit 3 tube-to-tube wear (TTW) in terms TTW depth and maximum depths of TTW after0.926 years at power. This was accomplished by selecting the correlation equation developedby regression analysis of the Unit 3 data that achieved the best fit. A standard approach inengineering modeling is to apply "goodness of fit" criteria in the selection process. Thisapproach provides a basis for selecting the mathematical combination of wear indices to yieldthe best correlation. Statistical regression analysis and goodness-of-fit verification (R2 andstandard deviation of the residuals) are the means by which an empirical correlation can bedeveloped that best explains what is physically observed with minimum uncertainty. From thisapproach, the total wear index based on the summation of anti-vibration bar (AVB) and tubesupport plate (TSP) wear was established.The wear index selection process evaluated several alternative definitions and determined thegoodness-of-fit for each. Of the five model variations discussed in the response to RAI 3, thefirst four have similar properties in terms of the fraction of the data variation explained by theregression model (R2), and the standard deviation of the residuals (proportional to the standarderror of estimate) which is a measure of variance in the prediction ability of the model. Forthese criteria, it was concluded that Alternatives 1 through 4 are essentially equivalent havingsimilar capability in correlating the observed NDE data to each definition of the wear index.The wear index definition from Alternative 4 (the summation of AVB and TSP wear) wasselected as the definition of the wear index. This alternative resulted in the ability to define theTTW depth prediction model in terms of a single wear related quantity with accuracycomparable to a more complex model of the group.Alternative 5 redefined the wear index in terms of AVB wear only. As demonstrated in Table 1of the response to RAI 3, this alternative does not describe wear degradation as well asAlternatives 1 through 4. Because of the greater variance for the AVB wear index model, it wasexpected that this definition for the wear index would give a more limiting result for probability ofburst (POB) than the current total wear index model.To respond to this RAI, a separate and complete operational assessment (OA) model wasdeveloped using a wear index based on AVB wear only, to demonstrate the effect of analternate definition on POB. Comparison of the two wear index models (AVB wear only and thePage 5 of 12 total wear index as the sum of AVB and TSP) is shown in Figure 1 for Unit 2 and Figure 2 forUnit 3. For Unit 2, the change in definition doesn't appear significant but small differences inindices greater than 60% through-wall (TW) will affect the development of the probability ofinitiation (POI) model. For Unit 3, the AVB wear index effectively reduces the range of the indexfrom greater than 300%TW to less than 200%TW. This change in definition compresses thescale of both the initiation and TTW growth rate models and affects the shape of the POI modelfor Unit 2.Figure 3 shows the existence of TTW in Unit 3 plotted as the presence or non-presence of TTWagainst the AVB wear index. Logistic regression analysis was used to produce the Unit 3 curve.Following the same benchmarking procedure in RAI Reference 4, the Unit 3 curve was adjustedto develop the model for Unit 2. The Unit 2 curve transitioned to probability of unity as the AVBwear index approached 200% TW. An acceptable benchmark was achieved when the modelproduced about two detected indications at the estimated threshold detection level for the+PointTM probe. This process was discussed in the response to RAI 9. The results from thebenchmarking simulation of 1000 trial calculations are shown in the histogram in Figure 4. Thebenchmarking performed produced similar outcomes as the total wear index model.The development of the TTW growth model based on the AVB wear index is discussed in theresponse to RAI 3. The regression line for the TTW maximum depth data is shown in Figure 5having an intercept of 19.638, a slope of 0.2206 and a standard deviation of the residuals of12.63.Figure 6 compares the POB results for the 70% power OA for the two wear index definitions.The 70% OA in RAI Reference 4 established an allowable inspection interval of 1.33 years atpower or 16 months based on the total wear index. For the wear index based on AVB wear, theallowable inspection interval becomes 1.15 years at power or 14 months. The reduction in theinspection interval is about 2 months. This difference is not significant since the moreconservative AVB wear index results confirm that significant margin exist for the planned 5month inspection interval. The more conservative results for the AVB wear index are primarilythe result of greater scatter (regression error) evident in the residuals in the regression process.Based on the goodness-of-fit comparisons discussed in the response to RAI 3, and theresponse of RAI 72, the total wear index (Alternative 4) is the optimum model (of thealternatives evaluated) for this degradation mechanism. It is expected that the more complexAlternatives 1 through 3 will give similar POB results as the total wear index model(Alternative 4), having nearly identical scatter in the residuals.Page 6 of 12 SONGS-2 Wear Index Histogram (after 1.718 Years at Power)220u 1402= 1200S10080Ez 6040200AVB Wear Index, (%TW)SONGS-2 Wear Index Histogram (after 1.718 Years at Power)220200 *2E-088--j180160u 140aU 120U010080z 6040200Total Wear Index, (%TW)Figure 1- Unit 2 Histograms for AVB Wear Index andTotal Wear Index Model DefinitionsPage 7 of 12 SONGS-3 Wear Index Histogram (after 0.926 Years at Power)220200 -3E-088 _N 3E-089180160U 140C" 1200 t6100.80-E2 60-4020AVB Wear Index, (%/TW)SONGS-3 Wear Index Histogram (after 0.926 Years at Power)220200 -3E-088111312-089180 -160 --0U140 -S120 -0100z 604020-Total Wear Index, (%/,TW)Figure 2 -Unit 3 Histograms for AVB Wear Index andTotal Wear Index Model DefinitionsPage 8 of 12 Tube-to-Tube Wear Initiation Model.0170J214-0.0o..0)0/0U1.00.90.80.70.60.50.40.30.20.10.0*SONGS-3Oata-A"B WI---SONGS-3 Regression Fit -AVB WI-A--SONGS-2 Initiation Model -AVB Wl-E-SONGS-2 Initiation Model -Total WI--._ ..... ... ....... .II * -0 20 40 60 80 100 120 140 160 180 200Wear Index, WI (%TW)Figure 3 -Comparison of Initiation Models for the AVB and Total Wear IndexDefinitionsPage 9 of 12 U0Initiation Model Benchmarking Results (1000 Trials)220200 -A E Total Wear Index"AVB Wear Index180160140120100806020-20Number of TTW InitiationsFigure 4 -Unit 2 Benchmarking Results for the AVB and Total Wear Index ModelDefinitionsPage 10 of 12 Tube-to-Tube Wear Depths -ETSS 27902.2 SizedIa.0010090807060504030201000 20 40 60 80 100 120AVB Wear Index, (%TW)140 160 180 20(Figure 5 -Unit 3 Tube-to-Tube Wear Depths versus AVB Wear IndexPage 11 of 12 Operational Assessment for TTW for Mid-Cycle 17 for 70% Power Operation0.160.14-0.12 -00~0.10o 0.08S0.0600.04-0.020.00IfI I I--- ETSS 27902.2 Sizing, Total Wear Index Model---ETSS 27902.2 Sizing, AVB Wear Index Model---Mid-Cycle 17 (5 Months at Power)--Cycle 17 (1.578 Years at Power)-SIPC Margin, P09 <= 0.05--I-S___ i +-----.4 -I- I0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1Inspection Interval, (Years at Power)1.2 1.3 1.4 1.5 1.6Figure 6 -Probability of Burst Results for the AVB and Total Wear Index ModelsPage 12 of 12 | |||
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Revision as of 07:41, 27 March 2018
ML13102A296 | |
Person / Time | |
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Site: | San Onofre ![]() |
Issue date: | 04/10/2013 |
From: | St.Onge R J Edison International Co, Southern California Edison Co |
To: | Document Control Desk, Office of Nuclear Reactor Regulation |
References | |
TAC ME9727 | |
Download: ML13102A296 (14) | |
Text
SOUTHERN CALIFORNIA Richard 1. St. OngeEDISONmeDirector, Nuclear Regulatory Affairs andED SO " Emergency PlanningAn EDISON INTERNATIONAL CompanyApril 10, 201310 CFR 50.4U.S. Nuclear Regulatory CommissionATTN: Document Control DeskWashington, DC 20555-0001Subject: Docket No. 50-361Response to Request for Additional Information (RAIs 53 and 72) RegardingConfirmatory Action Letter Response(TAC No. ME 9727)San Onofre Nuclear Generating Station, Unit 2References: 1. Letter from Mr. Elmo E. Collins (USNRC) to Mr. Peter T. Dietrich (SCE), datedMarch 27, 2012, Confirmatory Action Letter 4-12-001, San Onofre NuclearGenerating Station, Units 2 and 3, Commitments to Address Steam GeneratorTube Degradation2. Letter from Mr. Peter T. Dietrich (SCE) to Mr. Elmo E. Collins (USNRC), datedOctober 3, 2012, Confirmatory Action Letter -Actions to Address SteamGenerator Tube Degradation, San Onofre Nuclear Generating Station, Unit 23. Letter from Mr. James R. Hall (USNRC) to Mr. Peter T. Dietrich (SCE), datedMarch 18, 2013, Second Request for Additional Information (RAI 33-67)Regarding Response to Confirmatory Action Letter, San Onofre NuclearGenerating Station, Unit 24. Letter from Mr. Richard J. St. Onge (SCE) to Document Control Desk(USNRC), dated February 25, 2013, Response to Request for AdditionalInformation (RAIs 2, 3 and 4) Regarding Confirmatory Action Letter Response,San Onofre Nuclear Generating Station, Unit 25. Email from Mr. James R. Hall (USNRC) to Mr. Ryan Treadway (SCE), datedMarch 15, 2013, Request for Additional Information (RAIs 68-72) RegardingResponse to Confirmatory Action Letter, San Onofre Nuclear GeneratingStation, Unit 2Dear Sir or Madam,On March 27, 2012, the Nuclear Regulatory Commission (NRC) issued a Confirmatory ActionLetter (CAL) (Reference 1) to Southern California Edison (SCE) describing actions that the NRCand SCE agreed would be completed to address issues identified in the steam generator tubesof San Onofre Nuclear Generating Station (SONGS) Units 2 and 3. In a letter to the NRC datedOctober 3, 2012 (Reference 2), SCE reported completion of the Unit 2 CAL actions andincluded a Return to Service Report (RTSR) that provided details of their completion.P.O. Box 128 LaSan Clemente, CA 92672 q Document Control Desk-2-April 10, 2013By letter dated March 18, 2013 (Reference 3), the NRC issued Requests for AdditionalInformation (RAls) regarding the CAL response. Enclosure 1 of this letter provides theresponse to RAI 53.SCE provided the response to RAIs 2, 3 and 4 in a letter dated February 25, 2013(Reference 4). By e-mail dated March 15, 2013 (Reference 5), the NRC issued Requests forAdditional Information (RAIs) regarding the response to RAIs 2, 3 and 4. Enclosure 1 of thisletter provides the response to RAI 72.There are no new regulatory commitments contained in this letter. If you have any questions orrequire additional information, please call me at (949) 368-6240.Sincerely,Enclosure:1. Response to RAIs 53 and 72cc:A. T. Howell III, Regional Administrator, NRC Region IVJ. R. Hall, NRC Project Manager, SONGS Units 2 and 3G. G. Warnick, NRC Senior Resident Inspector, SONGS Units 2 and 3R. E. Lantz, Branch Chief, Division of Reactor Projects, NRC Region IV ENCLOSURE 1SOUTHERN CALIFORNIA EDISONRESPONSE TO REQUEST FOR ADDITIONAL INFORMATIONREGARDING RESPONSE TO CONFIRMATORY ACTION LETTERDOCKET NO. 50-361TAC NO. ME 9727Response to RAIs 53 and 72 RAI 53In Reference 9, Section 4.6.2, "[Tube-to-Tube (TTW)] Growth Model," was the regression fitslope and intercept uncertainty modeled (e.g., as was done for the burst pressure versusvoltage model in NRC Generic Letter 95-05)? If not, why is this conservative? Was the datascatter about the regression fit modeled as normally distributed? If so, provide justificationfor the adequacy of this assumption (i.e., normal distribution) to fully capture the upper tail ofthe distribution as shown in Figure 4-12 on page 4-25.RESPONSENote: RAI Reference 9 is the Operational Assessment for SONGS Unit 2 Steam Generatorsfor Upper Bundle Tube-to-Tube Wear Degradation at End of Cycle 16," prepared by IntertekAPTECH for Areva, Report No. AES 12068150-2Q-1, Revision 0, September 2012.The Monte-Carlo simulation which was used to perform the SONGS Unit 2 operationalassessment (OA) for tube-to-tube wear (TTW) relies on a correlation developed usingmeasured Unit 3 TTW depths. The correlating independent variable is the total wear index.This work is described in summary form in Section 4.6.2 of RAI Reference 9. Elements ofthe residual analysis of the TTW growth model development process are shown in Figure4-12 of RAI Reference 9. The two issues identified in RAI 53 are addressed in thisresponse.1. Regression Model UncertaintyIn NRC Generic Letter 95-05 (Reference R1), the implementation consisted of developing asampling method discussed in References R2 and R3. This approach samples from aprediction interval equation which accounts for several components of uncertainty includingthose involving the slope of the regression line, the intercept, and the basic error-of-estimatefrom the data set. The form of the sampling equation is given by:Ys = YCor +/- ta/2,N-2 Sy/x[ 1 + 1/N + (X-x')2 /((N-1)Sx2 ) 0.5where:Y= Sampled value of YYCor = Value computed from regression lineta/2,N-2 = t-distribution with N-2 degrees of freedomSy/x = Standard error of estimate from the correlationN = Number of data pointsX = Value of independent variablex' = Mean of independent variable valuesSx2 = Sample variance of independent variable valuesExamination of the above equation shows that the most important component is the size ofthe data set (N) from which the correlation was developed. In this case, over 320 datapoints were used. A simplified estimate of the effect of neglecting these terms yields amultiplier of 1.0031 on the standard error of estimate. The other affected componentinvolves the use of the t-distribution rather than the normal distribution for the probabilisticsampling component. In general for sample sizes greater than approximately 30, thePage 2 of 12 difference is considered negligible for use in simulation. In the case of the Unit 3 data, thedifference at the 95th percentile is negligible being approximately 0.3% (1.6497 vs. 1.645). Itwas not necessary to explicitly address the uncertainties in slope and intercept variablesfrom the regression analysis since it is inconsequential to the simulation results.2. Statistical Treatment of the Regression ModelIn Figure 4-12 of RAI Reference 9, the distribution of the residuals is well represented by anormal cumulative distribution function. Deviations from normality are observed only at thelower and upper extremes (outside the 95th percentile bounds). For the lower tail, thedeviation is conservative. For the upper tail, the deviation can become non-conservativewhen sampling beyond the upper 97th percentile level (e.g., when the number of TTWinitiations is large so that there is a greater chance in having an extreme value for TTWgrowth as a sample outcome).To validate that any deviation from normality from the upper tail does not significantly impactthe OA results, the TTW growth model was modified. This was accomplished by separatelyfitting the upper tail of the residuals with a Beta distribution to give a more precise fit to theresiduals above the 95th percentile. This modification was done for the 70% power modeland involved changing the logic in the algorithm to select the value for growth rateuncertainty when the standard normal parameter exceeds 1.645 (above the upper 95%).The results from the re-evaluation are given in the table below:Allowable Inspection Interval for Probability of Burst (POB) = 5%(RAI Reference 9, Case I -ETSS Depth Sizing)Normal Distribution of Residuals Normal Distribution of Residuals(Full Sample Range) (Adjusted Above 95th Percentile)1.33(1) (Years at Power) 1.24(2) (Years at Power)Notes:1) Results from RAI Reference 92) Results from modified modelThe above comparison between the two methods of treating the regression error shows asmall difference in the allowable inspection interval calculated from the OA. The change ininspection interval is less than 7%. For the planned inspection interval of 5 months (0.42years at power), the deviation in the upper tail beyond 95% has a negligible effect on theallowable inspection interval for Unit 2 due to the much shorter operating period.Page 3 of 12
References:
RI. Generic Letter 95-05: Voltage-Based Repair Criteria for Westinghouse SteamGenerator Tubes Affected by Outside Diameter Stress Corrosion Cracking,(August 3, 1995).R2. Statistics Manual, Crow, Davis, and Maxfield, Dover Press, New York, Page 163.R3. Applied Regression Analysis, Second Edition, Draper and Smith, John Wiley andSons, New York, Page 30, 1981.Page 4 of 12 RAI 72Reference 1, Response to RAI 3 -This response did not fully address RAI question 3. What isthe sensitivity of the results in Figure 5-4 of Reference 4 to the different formulations of wearindex in Equations 1 through 5?RESPONSENote: RAI Reference 1 is SCE's "Response to Request for Additional Information (RAls 2, 3,and 4) Regarding Confirmatory Action Letter Response," dated February 25, 2013.Note: RAI Reference 4 is the "Operational Assessment for SONGS Unit 2 Steam Generatorsfor Upper Bundle Tube-to-Tube Wear Degradation at End of Cycle 16," prepared by IntertekAPTECH for Areva, Report No. AES 12068150-2Q-1, Revision 0, September 2012.The wear index represents the complete state of wear degradation in a tube due to contact withtube supports. As discussed in the response to RAI 3, the justification of the wear index used inRAI Reference 4 is the ability of the wear index, as a correlating parameter, to describe theSONGS Unit 3 tube-to-tube wear (TTW) in terms TTW depth and maximum depths of TTW after0.926 years at power. This was accomplished by selecting the correlation equation developedby regression analysis of the Unit 3 data that achieved the best fit. A standard approach inengineering modeling is to apply "goodness of fit" criteria in the selection process. Thisapproach provides a basis for selecting the mathematical combination of wear indices to yieldthe best correlation. Statistical regression analysis and goodness-of-fit verification (R2 andstandard deviation of the residuals) are the means by which an empirical correlation can bedeveloped that best explains what is physically observed with minimum uncertainty. From thisapproach, the total wear index based on the summation of anti-vibration bar (AVB) and tubesupport plate (TSP) wear was established.The wear index selection process evaluated several alternative definitions and determined thegoodness-of-fit for each. Of the five model variations discussed in the response to RAI 3, thefirst four have similar properties in terms of the fraction of the data variation explained by theregression model (R2), and the standard deviation of the residuals (proportional to the standarderror of estimate) which is a measure of variance in the prediction ability of the model. Forthese criteria, it was concluded that Alternatives 1 through 4 are essentially equivalent havingsimilar capability in correlating the observed NDE data to each definition of the wear index.The wear index definition from Alternative 4 (the summation of AVB and TSP wear) wasselected as the definition of the wear index. This alternative resulted in the ability to define theTTW depth prediction model in terms of a single wear related quantity with accuracycomparable to a more complex model of the group.Alternative 5 redefined the wear index in terms of AVB wear only. As demonstrated in Table 1of the response to RAI 3, this alternative does not describe wear degradation as well asAlternatives 1 through 4. Because of the greater variance for the AVB wear index model, it wasexpected that this definition for the wear index would give a more limiting result for probability ofburst (POB) than the current total wear index model.To respond to this RAI, a separate and complete operational assessment (OA) model wasdeveloped using a wear index based on AVB wear only, to demonstrate the effect of analternate definition on POB. Comparison of the two wear index models (AVB wear only and thePage 5 of 12 total wear index as the sum of AVB and TSP) is shown in Figure 1 for Unit 2 and Figure 2 forUnit 3. For Unit 2, the change in definition doesn't appear significant but small differences inindices greater than 60% through-wall (TW) will affect the development of the probability ofinitiation (POI) model. For Unit 3, the AVB wear index effectively reduces the range of the indexfrom greater than 300%TW to less than 200%TW. This change in definition compresses thescale of both the initiation and TTW growth rate models and affects the shape of the POI modelfor Unit 2.Figure 3 shows the existence of TTW in Unit 3 plotted as the presence or non-presence of TTWagainst the AVB wear index. Logistic regression analysis was used to produce the Unit 3 curve.Following the same benchmarking procedure in RAI Reference 4, the Unit 3 curve was adjustedto develop the model for Unit 2. The Unit 2 curve transitioned to probability of unity as the AVBwear index approached 200% TW. An acceptable benchmark was achieved when the modelproduced about two detected indications at the estimated threshold detection level for the+PointTM probe. This process was discussed in the response to RAI 9. The results from thebenchmarking simulation of 1000 trial calculations are shown in the histogram in Figure 4. Thebenchmarking performed produced similar outcomes as the total wear index model.The development of the TTW growth model based on the AVB wear index is discussed in theresponse to RAI 3. The regression line for the TTW maximum depth data is shown in Figure 5having an intercept of 19.638, a slope of 0.2206 and a standard deviation of the residuals of12.63.Figure 6 compares the POB results for the 70% power OA for the two wear index definitions.The 70% OA in RAI Reference 4 established an allowable inspection interval of 1.33 years atpower or 16 months based on the total wear index. For the wear index based on AVB wear, theallowable inspection interval becomes 1.15 years at power or 14 months. The reduction in theinspection interval is about 2 months. This difference is not significant since the moreconservative AVB wear index results confirm that significant margin exist for the planned 5month inspection interval. The more conservative results for the AVB wear index are primarilythe result of greater scatter (regression error) evident in the residuals in the regression process.Based on the goodness-of-fit comparisons discussed in the response to RAI 3, and theresponse of RAI 72, the total wear index (Alternative 4) is the optimum model (of thealternatives evaluated) for this degradation mechanism. It is expected that the more complexAlternatives 1 through 3 will give similar POB results as the total wear index model(Alternative 4), having nearly identical scatter in the residuals.Page 6 of 12 SONGS-2 Wear Index Histogram (after 1.718 Years at Power)220u 1402= 1200S10080Ez 6040200AVB Wear Index, (%TW)SONGS-2 Wear Index Histogram (after 1.718 Years at Power)220200 *2E-088--j180160u 140aU 120U010080z 6040200Total Wear Index, (%TW)Figure 1- Unit 2 Histograms for AVB Wear Index andTotal Wear Index Model DefinitionsPage 7 of 12 SONGS-3 Wear Index Histogram (after 0.926 Years at Power)220200 -3E-088 _N 3E-089180160U 140C" 1200 t6100.80-E2 60-4020AVB Wear Index, (%/TW)SONGS-3 Wear Index Histogram (after 0.926 Years at Power)220200 -3E-088111312-089180 -160 --0U140 -S120 -0100z 604020-Total Wear Index, (%/,TW)Figure 2 -Unit 3 Histograms for AVB Wear Index andTotal Wear Index Model DefinitionsPage 8 of 12 Tube-to-Tube Wear Initiation Model.0170J214-0.0o..0)0/0U1.00.90.80.70.60.50.40.30.20.10.0*SONGS-3Oata-A"B WI---SONGS-3 Regression Fit -AVB WI-A--SONGS-2 Initiation Model -AVB Wl-E-SONGS-2 Initiation Model -Total WI--._ ..... ... ....... .II * -0 20 40 60 80 100 120 140 160 180 200Wear Index, WI (%TW)Figure 3 -Comparison of Initiation Models for the AVB and Total Wear IndexDefinitionsPage 9 of 12 U0Initiation Model Benchmarking Results (1000 Trials)220200 -A E Total Wear Index"AVB Wear Index180160140120100806020-20Number of TTW InitiationsFigure 4 -Unit 2 Benchmarking Results for the AVB and Total Wear Index ModelDefinitionsPage 10 of 12 Tube-to-Tube Wear Depths -ETSS 27902.2 SizedIa.0010090807060504030201000 20 40 60 80 100 120AVB Wear Index, (%TW)140 160 180 20(Figure 5 -Unit 3 Tube-to-Tube Wear Depths versus AVB Wear IndexPage 11 of 12 Operational Assessment for TTW for Mid-Cycle 17 for 70% Power Operation0.160.14-0.12 -00~0.10o 0.08S0.0600.04-0.020.00IfI I I--- ETSS 27902.2 Sizing, Total Wear Index Model---ETSS 27902.2 Sizing, AVB Wear Index Model---Mid-Cycle 17 (5 Months at Power)--Cycle 17 (1.578 Years at Power)-SIPC Margin, P09 <= 0.05--I-S___ i +-----.4 -I- I0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1Inspection Interval, (Years at Power)1.2 1.3 1.4 1.5 1.6Figure 6 -Probability of Burst Results for the AVB and Total Wear Index ModelsPage 12 of 12