POLICY ISSUE 

INFORMATION

April 8, 2013 SECY-13-0038

FOR: The Commissioners 

FROM: Eric J. Leeds, Director 

Office of Nuclear Reactor Regulation 

SUBJECT: FISCAL YEAR 2012 RESULTS OF THE INDUSTRY TRENDS 

PROGRAM FOR OPERATING POWER REACTORS 

PURPOSE: 

The purpose of this paper is to inform the Commission of the results of the U.S. Nuclear 

Regulatory Commission’s (NRC’s) Industry Trends Program (ITP) for fiscal year (FY) 2012. 

This paper does not address any new commitments or resource implications. 

BACKGROUND: 

The NRC staff implemented the ITP in 2001 to monitor for adverse trends in safety performance 

based on industry-level indicators. After the NRC assesses adverse trends for safety 

significance, it responds, as necessary, to any identified safety issues, including adjustments to 

the inspection and licensing programs. One important output of the ITP is the annual agency 

performance measures reported to Congress on the number of statistically significant adverse 

industry trends in safety performance. This outcome measure is part of the NRC Performance 

and Accountability Report. In addition, the NRC annually reviews the results of the ITP and any 

actions taken or planned during the Agency Action Review Meeting. The NRC reports the 

findings of this review to the Commission. This paper is the 12th annual report to the 

Commission on the ITP. 

NRC Inspection Manual Chapter (IMC) 0313, “Industry Trends Program,” dated May 29, 2008, 

contains details of the ITP, including definitions of monitored indicators and program 

descriptions. 

CONTACT: Luis A. Cruz, NRR/DIRS 

 301-415-3982
The Commissioners - 2 - 

DISCUSSION: 

Using the ITP, the staff monitors industry safety performance to identify and address adverse 

industry trends. The indicators are comprehensive and based on the best available data. An 

adverse trend exists if the slope of the regression line fitted to the long-term indicator data has a 

positive value. 

The ITP also uses precursor events identified by the Accident Sequence Precursor (ASP) 

Program to assess industry performance. The staff analyzes the occurrence rate of precursors 

to determine if an adverse trend exists. The staff uses results from the ASP program as one of 

the agency’s safety goal performance measures reported in the NRC Performance and 

Accountability Report. 

In addition to the long-term indicators, the ITP uses a statistical approach based on prediction 

limits to identify potential short-term, year-to-year emergent issues before they become longterm trends. The short-term prediction limits are determined from a predictive distribution 

derived using information from an established baseline period. These prediction limits are 

reevaluated each year. 

The ITP complements the Reactor Oversight Process (ROP). The ITP monitors industry-level 

performance, whereas the ROP provides oversight to individual plant conditions and events. 

The Office of Nuclear Regulatory Research (RES) provides indirect support to the ITP in the 

areas of operating experience data and models that are developed and budgeted under other 

RES programs, such as the Standardized Plant Analysis Risk Model Development Program, the 

ASP Program, and the Reactor Operating Experience Data Collection and Analysis Program. 

The ITP uses the results of RES work in the ASP Program to assess industry performance, 

although the funding and performance of RES work are separate from the ITP. 

FY 2012 LONG-TERM INDUSTRY TRENDS: 

Based on the ITP indicators and the ASP Program results, the staff did not identify any 

statistically significant adverse trends in industry safety performance through the end of 

FY 2012 (i.e., until September 30, 2012). The graphs in Enclosure 1 show the long-term ITP 

indicator trends and the ASP data. The staff removed the trendlines from the graphs in 

Enclosure 1 that did not have a statistically significant trend. The staff evaluated both linear and 

exponential trendlines for each set of data, and used the trendline showing the highest degree 

of statistical significance. 

The ASP Program considers an event with a conditional core damage probability (CCDP) or an 

increase in core damage probability (ΔCDP) greater than or equal to 1×10-6 to be a precursor. 

The RES staff evaluated precursor data from FY 2002 through FY 2011 and identified no 

statistically significant trends for the occurrence rate of all precursors during that period 

(Figure 14 of Enclosure 1). Additional information can be found in Section 4.1 of Enclosure 1 of 

SECY-12-0133, “Status of the Accident Sequence Precursor Program and the Standardized 

Plant Analysis Risk Models,” dated October 4, 2012 (Agencywide Documents Access and 

Management System (ADAMS) Accession No. ML12220A608). 
The Commissioners - 3 - 

The ASP Program also provides the basis for the safety performance measure of zero 

significant precursors of a nuclear reactor accident. This is one measure that is associated with 

the safety goal that the NRC established in its strategic plan. A significant precursor is an event 

that has a probability of at least 1 in 1,000 (i.e., CCDP or ΔCDP greater than or equal to 1x10-3) 

of leading to a reactor accident. 

Since the issuance of SECY-12-0056, “Fiscal Year 2011 Results of the Industry Trends 

Program for Operating Power Reactors,” on April 9, 2012, the RES staff completed the ASP 

analysis for FY 2011 and identified seven events as significant events (i.e., CCDP or ΔCDP 

greater than or equal to 1×10-5). These seven events were related to natural phenomena 

occurring at Surry, Units 1 and 2; Browns Ferry, Units 1, 2 and 3; and North Anna, Units 1 

and 2. None of these events were a significant precursor. Figure 3 of Enclosure 1 has been 

revised to incorporate these significant events. 

The RES staff completed preliminary analyses and identified no significant precursors in FY 

2012. However, the staff identified one event as a potential significant precursor, a reactor trip 

and loss of offsite power that occurred on January 13, 2012, at Wolf Creek because of a 

switchyard breaker failure. Based on preliminary analysis, RES staff does not anticipate that 

this event will constitute a significant precursor. The RES staff will complete its evaluation of 

FY 2012 precursors to obtain final results. The staff will update the FY 2012 precursor data and 

will report any changes to the ITP analysis in a memorandum to the Commission after receiving 

the final ASP results from RES. 

FY 2012 SHORT-TERM INDUSTRY PERFORMANCE: 

The staff uses a statistical approach based on prediction limits to identify potential short-term, 

year-to-year emergent issues before they become long-term trends. Enclosure 2 shows the 

short-term results and the prediction limits for each of the ITP indicators. None of the indicators 

exceeded its prediction limit in FY 2012. Short-term FY 2012 data did not reveal any emerging 

trends that warranted additional analysis or significant adjustments to the nuclear reactor safety 

inspection or licensing programs. 

In SECY-12-0056, the staff identified the potential for a high number of significant events for 

FY 2011. On February 4, 2013, the staff issued a memorandum to the Commission (ADAMS 

Accession No. ML12347A034) reporting that this indicator was exceeded. The staff noted that 

the significant events prediction limit was exceeded because of natural phenomena occurring at 

three multi-unit sites (Surry, Browns Ferry, and North Anna) and concluded that these events do 

not represent degradation in overall industry safety performance mainly because the reliability 

and avilability of safety systems, along with operator response, minimized the overall risk 

significance of each event. As indicated in the memorandum, the staff in the Operating 

Experience Branch of the Office of Nuclear Reactor Regulation performed an independent 

evaluation of significant reactor events for calendar year (CY) 2006 through CY 2012, using 

modified criteria, to examine the underlying causes of the events and recommend potential 

changes to agency programs. The modified criteria used to determine a significant event for 

this study were: an Augmented Inspection Team was chartered, a Yellow or Red inspection 

finding was issued under the ROP, or a CCDP of 1×10-5 or higher was calculated by the ASP 

program. The study revealed that the number of events meeting at least one of these criteria 

has increased since 2009. In addition, the number of these events involving an initiator and 
The Commissioners - 4 - 

subsequent complications has increased since 2010. The staff found that nonsafety-related 

system failures and corrective action program weaknesses contributed to most of those 

significant events involving an initiator and complications. The staff’s insights are being 

considered as part of the ongoing ROP enhancement effort discussed in the “Reactor Oversight 

Process Self-Assessment for Calendar Year 2012,” SECY paper.

FY 2012 RESULTS OF BASELINE RISK INDEX FOR INITIATING EVENTS: 

In 2008, the NRC staff implemented the Baseline Risk Index for Initiating Events (BRIIE) as part 

of the ITP. The BRIIE (1) tracks several types of events that could potentially initiate a 

challenge to a plant’s safety systems, (2) assigns a value to each initiating event (IE) according 

to its relative importance to the plant’s overall risk of damage to the reactor core, and 

(3) calculates an overall indicator of industry safety performance. 

The BRIIE concept provides a two-level approach to industry performance monitoring. The first 

level (referred to as Tier 1 performance monitoring) tracks and counts the number of times the 

IEs that have an effect on plant safety occur in nuclear power plants (NPP) during the year. 

Nine IE categories are monitored for boiling-water reactors (BWRs) and 10 for pressurizedwater reactors (PWRs). The number of times that each event occurs is compared to a 

predetermined number of occurrences for that event. The predetermined number of 

occurrences is calculated from a predictive distribution derived using information from an 

established baseline period, and it is reevaluated on a annual basis. If the predetermined 

number is exceeded, one can infer the possible degradation of industry safety performance. 

This annual tracking allows the NRC to intervene and engage the nuclear industry before any 

long-term adverse trends in performance emerge. 

 

The second level (referred to as Tier 2 performance monitoring) addresses the risk to plant 

safety and core damage that each of the initiating events contributes. Each event is assigned 

an importance value, a ranking based on its relative contribution to overall risk to plant safety. 

The greater the contribution of the event to overall risk, the higher the importance value it is 

assigned. Using statistical methods, the importance values are combined with the number of 

times the events occur during the year to calculate a number that indicates how much the 

overall industry risk of damage to the reactor core has changed from a baseline value. If the 

BRIIE-combined industry value reaches or exceeds a threshold value of 1×10-5 per reactor 

critical year, the NRC informs Congress of this performance outcome, along with actions that 

already have been taken or are planned in response, in the NRC Performance and 

Accountability Report. 

Enclosure 3 includes Tier 1 and Tier 2 BRIIE results. None of the IEs tracked in Tier 1 

exceeded its prediction limit in FY 2012. On Tier 2, Figure 15 of Enclosure 3 shows that the 

combined industry BRIIE value for FY 2012 (-9.17×10-7 per reactor critical year) indicates better 

than baseline industry performance. The combined industry BRIIE value is below the 

established reporting threshold of ∆CDF = 1.0×10-5 per reactor critical year. 

In addition to the BRIIE value for FY 2012, the staff also updated the BRIIE value for FY 2011 to 

account for a loss of vital direct current bus event that occurred at Palisades on September 25, 
The Commissioners - 5 - 

2011. The corrected BRIIE value for FY 2011 is 1.56×10-6, which remains below the threshold 

of ∆CDF = 1.0×10-5 per reactor critical year. 

CONCLUSION: 

As discussed in this paper, for FY 2012, the staff identified no statistically significant adverse 

trends in industry safety performance. Specifically, no ITP indicator exceeded its prediction 

limit, and the BRIIE value remained below the threshold for a report to Congress. 

COORDINATION: 

The Office of the Chief Financial Officer has reviewed this paper and concurs. The Office of the 

General Counsel has reviewed this paper and has no legal objection. 

 /RA/

 Eric J. Leeds, Director 

Office of Nuclear Reactor Regulation 

Enclosures: 

1. Fiscal Year 2012 Long-Term Industry 

 Trend Results 

2. Fiscal Year 2012 Short-Term Industry 

 Performance 

3. Summary of Baseline Risk Index for Initiating 

 Events: Annual Graphs through Fiscal Year 2012 

 
The Commissioners - 5 - 

2011. The corrected BRIIE value for FY 2011 is 1.56×10-6, which remains below the threshold 

of ∆CDF = 1.0×10-5 per reactor critical year. 

CONCLUSION: 

As discussed in this paper, for FY 2012, the staff identified no statistically significant adverse 

trends in industry safety performance. Specifically, no ITP indicator exceeded its prediction 

limit, and the BRIIE value remained below the threshold for a report to Congress. 

COORDINATION: 

The Office of the Chief Financial Officer has reviewed this paper and concurs. The Office of the 

General Counsel has reviewed this paper and has no legal objection. 

 Eric J. Leeds, Director 

Office of Nuclear Reactor Regulation 

Enclosures: 

1. Fiscal Year 2012 Long-Term Industry 

 Trend Results 

2. Fiscal Year 2012 Short-Term Industry 

 Performance 

3. Summary of Baseline Risk Index for Initiating 

 Events: Annual Graphs through Fiscal Year 2012 

WITS 200100034 

ADAMS Accession Number: ML13091A103 *concurred via email 

OFFICE NRR/DIRS/IPAB BC:NRR/DIRS/IPAB Tech Editor* BC:NRR/DIRS/IOEB BC:NRR/PMDA/PFHCB

NAME LCruz RFranovich JDougherty HChernoff CNguyen 

DATE 02/28/2013 03/13/2013 03/08/2013 04/03/2013 03/15/2013 

OFFICE D:NRR/DIRS OCFO* OGC (NLO) RES* D:NRR 

NAME HNieh GPeterson MYoung RCorreia ELeeds 

DATE 03/28/2013 03/28/2013 03/26/2013 03/28/2013 04/08/2013 

OFFICIAL RECORD COPY
Enclosure 1 

FISCAL YEAR 2012 LONG-TERM INDUSTRY TREND RESULTS 

The staff of the U.S. Nuclear Regulatory Commission did not observe any statistically significant 

adverse trends in the Industry Trends Program performance indicator data from the most recent 

10 years (fiscal years 2003–2012), as indicated by the figures below. 

Figure 1. Automatic scrams while critical

0.75

0.56

0.47

0.32

0.48

0.29

0.36

0.44 0.45

0.30

0.00

0.50

1.00

1.50

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Scrams per Unit

Fiscal Year

Industry Average

Industry Average Trend
- 2 - 

Figure 2. Safety system actuations

Figure 3. Significant events

0.42

0.24

0.38

0.22

0.25

0.14

0.23

0.18 0.19

0.17

0

0.2

0.4

0.6

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Actuations per Unit

Fiscal Year

Industry Average

Industry Average Trend

0.07

0.04

0.05

0.03

0.02

0.03

0.02

0.10

0.13

0.08

0

0.04

0.08

0.12

0.16

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per Unit

Fiscal Year

Industry Average
- 3 -

Figure 4. Safety system failures 

Figure 5. Forced outage rate 

As discussed in this paper, Figures 3-5 do not display a trendline because these graphs do not 

have a statistically significant trend. 

0.96

0.78

0.99

0.60

0.68 0.71 0.71

0.96 0.96

0.86

0.0

0.5

1.0

1.5

2.0

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Failures per Unit

Fiscal Year

Industry Average

3.04

1.88

2.34

1.47 1.41 1.34

2.21

1.74 1.80

2.82

0

2

4

6

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Forced Outage Rate (%)

Fiscal Year

Industry Average
- 4 -

Figure 6. Equipment forced outages 

Figure 7. Collective radiation exposure 

0.16

0.15

0.13

0.10

0.11

0.08

0.09

0.10

0.09 0.09

0

0.1

0.2

0.3

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Equipment Forced Outages per 

1,000 Commercial Critical Hours

Fiscal Year

Industry Average

Industry Average Trend

125

100

117

93

109

96

87 91 90

74

0

50

100

150

200

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Average Exposure per Unit

(Person-REM)

Fiscal Year

Industry Average

Industry Average Trend
- 5 -

Figure 8. Unplanned power changes

Figure 9. Reactor coolant system activity

1.15

1.00 0.97 0.91 0.91 0.92

0.56

0.86 0.88

0.73

0.0

0.5

1.0

1.5

2.0

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Power Changes per 7,000 Critical Hours

Fiscal Year

Industry Average

Industry Average Trend

0.40 0.42 0.41

0.60

0.45

0.48

0.32

0.19

0.13 0.09

0.0

0.5

1.0

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Maximum Percentage of Technical

Specification Limits

Fiscal Year

Industry Average

Industry Average Trend
- 6 -

Figure 10. Reactor coolant system leakage

Figure 11. Drill and exercise performance 

4.82 4.64 4.45 4.08 4.35 4.25

3.97 4.14 4.06 4.09

0

2

4

6

8

10

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Maximum Percentage of

Technical Specification Limits

Fiscal Year

Industry Average

Industry Average Trend

95.73 95.64 95.85 96.03 96.17 96.25

97.06 96.85

97.29

97.54

92

94

96

98

100

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Percentage Timely and Accurate

Fiscal Year

Industry Average

Industry Average Trend
- 7 -

Figure 12. Emergency response organization drill participation

Figure 13. Alert and notification system reliability

97.74 97.87

98.19

97.96

97.58

98.14

98.64 98.77

99.42 99.38

94

96

98

100

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Percentage of Key Personnel

Fiscal Year

Industry Average

Industry Average Trend

98.92

99.24

99.34

99.48 99.45

99.52 99.57 99.59

99.67

99.77

98

99

100

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Percentage of Tests Successful

Fiscal Year

Industry Average

Industry Average Trend
- 8 -

Figure 14. Accident sequence precursors

Precursors Occurrence per Unit 

Fiscal Year 
Enclosure 3 

FISCAL YEAR 2012 SHORT-TERM INDUSTRY PERFORMANCE

The annual industry trend analysis compares data for the most recent year to established 

short-term “prediction limits.” The prediction limits are 95th percentiles of predictive distributions 

for the data. The predictive distributions are statistical probability distributions that describe 

expected future performance. They are derived from performance during “baseline” periods for 

each performance indicator (PI). Baseline periods are periods for each PI during which the data 

can be regarded as fairly constant and indicative of “current” performance. 

The results of the evaluation of the fiscal year (FY) 2012 Industry Trends Program PIs, using the 

established prediction limits, indicate that no PI exceeded its associated prediction limit in 

FY 2012, as shown in the following figures for each PI with its FY 2012 data and associated 

prediction limit. 

In SECY-12-0056, “Fiscal Year 2011 Results of the Industry Trends Program for Operating 

Power Reactors,” the staff identified the potential for a high number of significant events for 

FY 2011. After completing the accident sequence precursor (ASP) evaluation for seven 

FY 2011 events and including this data, the significant events indicator exceeded its prediction 

limit. On February 4, 2013, the staff issued a memorandum to the Commission (Agencywide 

Documents Access and Management System Accession No. ML12347A034) reporting that this 

indicator was exceeded. The staff noted that the significant events prediction limit was 

exceeded because of natural phenomena occurring at three multi-unit sites (Surry, Browns 

Ferry, and North Anna) and concluded that these events do not represent degradation in overall 

industry safety performance. 

Figure 1. Automatic scrams while critical

0.00

0.25

0.50

0.75

1.00

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Scrams per Unit

Fiscal Year

Industry Average

Prediction Limit (0.673)

Baseline Industry Average (0.534), 1997-2002
- 2 - 

Figure 2. Safety system actuations 

Note that the 2003 blackout event was not included in the short-term data for determining 

prediction limits in Figure 2. It was excluded from the development of the prediction limit models 

because they are considered outlier events that overly influenced the statistical analysis of the 

industrywide data. This treatment results in a more conservative prediction limit. 

Figure 3. Significant events

0.00

0.20

0.40

0.60

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Actuations per Unit

Fiscal Year

Industry Average

Excluded August 2003 Blackout Event

Prediction Limit (0.375)

Baseline Industry Average (0.275), 1998-2005

0.00

0.05

0.10

0.15

0.20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per Unit

Fiscal Year

Industry Average

Prediction Limit (0.106)

Baseline Industry Average (0.524), 2000-2004
- 3 - 

Figure 4. Safety system failures 

Figure 5. Forced outage rate 

0.00

0.50

1.00

1.50

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Failures per Unit

Fiscal Year

Industry Average

Prediction Limit (1.04)

Baseline Industry Average (0.859), 2001-2004

0

2

4

6

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Forced Outage Rate %

Fiscal Year

Industry Average

Prediction Limit (4.28)

Baseline Industry Average (2.40), 2001-2004
- 4 - 

Figure 6. Equipment forced outages 

Figure 7. Collective radiation exposure

0.00

0.05

0.10

0.15

0.20

0.25

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Equipment Forced Outage Rate per 1,000 

Commercfial Critical Hours 

Fiscal Year

Industry Average

Prediction Limit (0.180)

Baseline Industry Average (0.142), 1998-2004

0

50

100

150

200

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Average Exposure per Unit (Person-REM)

Fiscal Year

Industry Average

Prediction Limit (139)

Baseline Industry Average (119), 1999-2002
- 5 - 

Figure 8. Unplanned power changes per 7,000 critical hours 

Figure 9. Reactor coolant system activity 

Note that Figures 8 and 9 are different from the figures included in SECY-12-0056. The graphs 

were not portrayed correctly in SECY-12-0056 and are corrected in this paper; however, 

revision of these graphs does not change the conclusions presented in SECY-12-0056. 

0.0

0.5

1.0

1.5

2.0

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Unplanned Power Changes per 7,000 

Critical Hours

Fiscal Year

Industry Average

Prediction Limit 1.30

Baseline Industry Average (1.11), 2001-2004

0.00

0.25

0.50

0.75

1.00

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Maximum Percentage of Techincal 

Specification Limits

Fiscal Year

Industry Average

Prediction Limit (0.646)

Baseline Industry Average (0.462), 2001-2004
- 6 - 

Figure 10. Reactor coolant system leakage 

Note that the 2000 steam generator tube rupture event at Indian Point Nuclear Generating 

Unit 2 was not included in the short-term data for determining prediction limits in Figure 10. It 

was excluded from the development of the prediction limit models because they are considered 

outlier events that overly influenced the statistical analysis of the industrywide data. This 

treatment results in a more conservative prediction limit. 

Figure 11. Drill and exercise performance

0

2

4

6

8

10

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Maximum Percentage of Techincal 

Specification Limits

Fiscal Year

Industry Average

Prediction Limit (6.32)

Baseline Industry Average (5.14), 2000-2004

92

94

96

98

100

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Percentage Timely and Accurate

Fiscal Year

Industry Average

Prediction Limit (95.21)

Baseline Industry Average (95.62), 2000-2004
- 7 - 

Figure 12. Emergency response organization drill participation

Figure 13. Alert and notification system reliability 

94

96

98

100

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Percentage of Key Personnel

Fiscal Year

Industry Average

Prediction Limit (97.50)

Baseline Industry Average (97.87), 2003-2007

97

98

99

100

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Percentage of Successful Tests 

Fiscal Year

Industry Average

Prediction Limit (98.35)

Baseline Industry Average (98.87), 2001-2004
Enclosure 3 

SUMMARY OF BASELINE RISK INDEX FOR INITIATING EVENTS: 

ANNUAL GRAPHS THROUGH FISCAL YEAR 2012 

The Baseline Risk Index for Initiating Events (BRIIE) addresses the initiating event (IE) 

cornerstone in the U.S. Nuclear Regulatory Commission’s (NRC’s) Reactor Oversight Process 

(ROP) for monitoring commercial nuclear power plants. It is based on plant performance for the 

10 initiator events listed in the table below. 

 INITIATOR ACRONYM APPLICABLE PLANTS 

 General transient TRAN Both plant types, separately 

 Loss of condenser heat sink LOCHS Both plant types, separately 

 Loss of main feedwater LOMFW Both plant types 

 Loss of offsite power LOOP Both plant types 

Loss of vital alternating 

current bus LOAC Both plant types 

Loss of vital direct current 

bus LODC Both plant types 

Stuck-open safety or relief 

valve SORV Both plant types, separately 

 Loss of instrument air LOIA Both plant types, separately 

Very small loss-of-coolant 

accident VSLOCA Both plant types 

Steam generator tube 

rupture SGTR Pressurized-water reactors (PWRs) only 

The BRIIE program, described in NUREG/CR-6932, “Baseline Risk Index for Initiating Events 

(BRIIE),” issued June 2007, consists of two levels or tiers. The first tier considers individual IEs 

and evaluates performance based on statistical prediction limits. This evaluation is for the 

ongoing monitoring and early detection of possible industry-level deficiencies. A second tier is a 

risk-based integrated measure evaluated for each plant type. Because four of the initiators 

have separate data for each plant type, there are a total of 14 Tier 1 graphs. 

The units for the Tier 1 IE frequency graphs are event counts for a fiscal year divided by the 

industry critical time for the year. The Tier 1 graphs also show the average frequency for an 

established “baseline period” and 95-percent prediction limits for a future year if occurrences 

continue at the same rate as in the baseline period. If industry data shift as time progresses, 

the baseline periods used to determine the prediction limits may no longer be relevant. The 

periods originally were developed to describe, roughly, calendar years 1998–2002. 

The prediction limits depend on the expected critical years of reactor operation in the upcoming 

year and the baseline occurrence rate for each indicator. A rate can exceed a limit by having 

more events than expected or by having the same number of events and less critical time than 

expected. In recent years, U.S. nuclear power plant availability has been approximately 

90 percent at the industry level. This figure enters into the calculations that determine the 

bounds on the number of events that might be expected. 

None of the fiscal year (FY) 2012 occurrence rates exceeded their prediction limits. 
- 2 - 

The Tier 2 integrated index includes, for each plant type, the relative contribution of each 

initiator to the risk of core damage, based on the events that occurred in each fiscal year. 

The event frequencies are converted to core damage frequency (CDF) estimates by multiplying 

by Birnbaum risk coefficients. These coefficients are industry averages of the contribution to 

core damage from each initiator as reflected in the industry standardized plant analysis risk 

models. 

Figure 15 shows annual differences in estimated industry CDF compared to the established 

baseline levels of these quantities. The combined industry BRIIE value for FY 2012 (-9.17×10-7

per reactor critical year) indicates better than baseline industry performance. The combined 

industry BRIIE value is below the established reporting threshold of ∆CDF = 1.0×10-5 per reactor 

critical year. 

In addition to the BRIIE value for FY 2012, the staff also updated the BRIIE value for FY 2011. 

Figure 8 was corrected to account for a loss of vital direct current bus event that occurred at 

Palisades on September 25, 2011. The staff did not include this event in the BRIIE analysis for 

SECY-12-0056, “Fiscal Year 2011 Results of the Industry Trends Program for Operating Power 

Reactors,” because the licensee event report (LER) was submitted during FY 2012 

(Agencywide Documents Access and Management System Accession No. ML113260522). The 

staff identified this event as applicable to FY 2011 during its analysis of FY 2012 BRIIE data. 

The corrected BRIIE value for FY 2011 is 1.56×10-6, as reflected in Figure 15, which remains 

below the threshold of ∆CDF = 1.0×10-5 per reactor critical year. 

Figure 1. Pressurized-water reactor (PWR) general transients

1.166

0.717

0.515 0.524

0.649

0.559 0.568

0.883

0.655

0.422

0.0

0.5

1.0

1.5

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1998 - 2002

Baseline industry average

95% prediction limit for 1 year
- 3 - 

Figure 2. Boiling-water reactor (BWR) general transients 

Figure 3. PWR loss of condenser heat sink

0.991

0.808 0.837

0.558

0.971

0.546

0.839

0.634

0.472

0.554

0.0

0.5

1.0

1.5

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1997 - 2002

Baseline industry average

95% prediction limit for one year

0.065

0.112

0.064 0.064

0.032

0.016

0.047

0.082

0.033 0.034

0.00

0.05

0.10

0.15

0.20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1995 - 2002

Baseline industry average

95% prediction limit for 1 year 
- 4 - 

Figure 4. BWR loss of condenser heat sink 

Figure 5. Loss of main feedwater

0.256

0.155 0.161

0.031

0.157

0.091 0.093

0.060 0.063 0.062

0.0

0.1

0.2

0.3

0.4

0.5

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1996 - 2002

Baseline industry average

95% prediction limit for 1 year 

0.075

0.084 0.086

0.042

0.063

0.042 0.042

0

0.022

0.011

0.00

0.05

0.10

0.15

0.20

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Baseline period: 1993 - 2002 Fiscal Year

Baseline industry average

95% prediction limit for 1 year 
- 5 - 

Figure 6. Loss of offsite power 

The prediction limit for loss of offsite power was calculated under the assumption that the eight 

at power events that occurred during the 2003 blackout were a single event. This treatment 

results in a more conservative prediction limit.

Figure 7. Loss of vital alternating current bus

0.129

0.053

0

0.021

0.011

0

0.031

0

0.075

0.055

0.00

0.05

0.10

0.15

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1997 - 2004

Baseline industry average

95% prediction limit for 1 year 

0.011

000000

0.021

0

0.011

0.00

0.02

0.04

0.06

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1992 - 2002

Baseline industry average

95% prediction limit for 1 year

Events 

per Reactor Critical Year
- 6 - 

Figure 8. Loss of vital direct current bus

Figure 9. PWR stuck-open safety or relief valve

00000000

0.011

0

0.00

0.01

0.02

0.03

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1988 - 2002

Baseline industry average

95% prediction limit for 1 year

0000000000

0.00

0.01

0.02

0.03

0.04

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1988 - 2002

Baseline industry average

95% prediction limit for 1 year
- 7 - 

Figure 10. BWR stuck-open safety or relief valve

Figure 11. PWR loss of instrument air 

Note that Figure 11 is different from the figure included in SECY-12-0056. The graph was not 

portrayed correctly in SECY-12-0056 and is corrected in this paper; however, revision of this 

graph does not change the conclusions presented in SECY-12-0056. 

0.032 0.031

0000

0.031

000

0.00

0.03

0.06

0.09

0.12

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1993 - 2002

Baseline industry average

95% prediction limit for 1 year

0.016

0 0

0.016 0.016

0 0

0.016

0 0

0.00

0.02

0.04

0.06

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year

Baseline period: 1997 - 2002

Baseline industry average

95% prediction limit for 1 year
- 8 - 

Figure 12. BWR loss of instrument air

Figure 13. Very small loss-of-coolant accident

000

0.031

000000

0.00

0.02

0.04

0.06

0.08

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1991 - 2002

Baseline industry average

95% prediction limit for one year

0 0

0.011

0000000

0.00

0.01

0.02

0.03

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1992 - 2002

Baseline industry average

95% prediction limit for 1 year
- 9 - 

Figure 14. PWR steam generator tube rupture

Figure 15. BRIIE Tier 2 (ΔCDF)

0000000000

0.00

0.01

0.02

0.03

0.04

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Events per reactor critical year

Fiscal Year Baseline period: 1991 - 2002

Baseline industry average

95% prediction limit for 1 year

-1.0E-05

-5.0E-06

1.0E-20

5.0E-06

1.0E-05

1.5E-05

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

ΔCDF per Reactor Critical Year

Fiscal Year

PWR BWR Industry Using Bayesian updates of annual frequencies

Industry BRIIE threshold for 1 year of data: 1.E-5