POLICY ISSUE 

(Information)

April 8, 2015 SECY-15-0061

FOR: The Commissioners

FROM: William M. Dean, Director

Office of Nuclear Reactor Regulation

SUBJECT: FISCAL YEAR 2014 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) 2014, and 

updated results from the FY 2013 ITP review. In summary, the staff did not identify any

statistically significant adverse trends in industry safety performance in 2014. For the updated 

FY 2013 results, the staff did identify a statistically significant adverse trend for the Significant 

Events indicator, but it was no longer evident following the 2014 review. This paper does not 

address any new commitments or resource implications.

BACKGROUND:

The staff established the ITP in 2001 to monitor trends in licensee safety performance using

industry-level indicators. Should the staff identify any adverse trends, further analysis would be 

conducted to determine causal factors, and adjustments to the NRC inspection program may 

result. Another 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 reviews the results of the ITP and any actions taken or planned as 

CONTACT: Andrew Waugh, NRR/DIRS

301-415-5601
The Commissioners - 2 -

a result during the annual Agency Action Review Meeting. The NRC reports the findings of this 

review to the Commission during the subsequent Commission meeting. NRC Inspection Manual 

Chapter (IMC) 0313, “Industry Trends Program,” dated May 29, 2008 (Agencywide Documents 

Access and Management System (ADAMS) Accession No. ML080860540), contains details of 

the ITP including definitions of monitored indicators and program descriptions.

Using the ITP, the staff monitors industry-wide safety performance to identify and address any 

statistically significant adverse trends. A statistically significant adverse trend exists if the slope 

of the regression line fitted to the long-term indicator data has a positive value and the fit of the 

regression line is statistically relevant. 

The Significant Events and Accident Sequence Precursors ITP indicators use data from the 

Accident Sequence Precursor (ASP) Program. The Significant Events indicator uses precursors 

with a conditional core damage probability (CCDP) or an increase in core damage probability 

(ΔCDP) greater than or equal to 1×10-5 as one of its inputs. The Accident Sequence Precursors 

indicator is based on precursors with a CCDP or ΔCDP greater than or equal to 1×10-6

. Due to 

the time needed to perform the complex risk analysis required for identifying precursors, these 

two indicators lag behind other ITP indicators.

In addition to the above 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 long-term trends. The short-term prediction limits are determined from an established 

baseline period during which data can be regarded as fairly constant. 

The ITP complements the Reactor Oversight Process (ROP). Specifically, the ITP monitors and 

responds to industry-wide performance, whereas the ROP provides oversight of individual 

reactor sites commensurate with their safety performance.

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

analyzing operating experience data and providing analytical tools, 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.

In 2008, the NRC staff established 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 offers a two-level approach to industry performance monitoring. The first 

level (referred to as Tier 1 performance monitoring) tracks IEs that occur during the year. Nine 

IE categories are monitored for boiling-water reactors and 10 for pressurized-water reactors. 

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 using 

information from an established baseline period. If the predetermined number is exceeded, the 

staff assesses whether there is a possible degradation in overall industry safety performance. 
The Commissioners - 3 -

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 (i.e., Tier 2 performance monitoring) addresses the risk to plant safety and 

core damage that each IE contributes. Each event is assigned an importance value based on

its relative contribution to overall risk of plant safety. The greater the contribution of the event to 

overall risk, the higher the importance value assigned. Using statistical methods, the 

importance values are combined with the number of times the events occur during the year to 

calculate a value 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 have already been taken or are planned in 

response, in the annual NRC Performance and Accountability Report.

DISCUSSION:

Results of FY 2014 Long-Term Industry Trends

For the FY 2014 ITP results, the staff did not identify any statistically significant adverse trends 

in industry-wide safety performance. The graphs in Enclosure 1 show the long-term ITP 

indicator trends. Six indicators showed statistically significant improving trends. Trend lines are 

provided for those indicators with a statistically significant trend. The staff evaluated both linear 

and exponential trend lines for each set of data and used the trend line showing the highest 

degree of statistical significance.

Updated Results of FY 2013 Long-Term Industry Trends

In SECY-14-0042, “Fiscal Year 2013 Results of the Industry Trends Program for Operating 

Power Reactors,” the staff identified five precursors that could potentially meet the criteria for 

significant events. The staff noted that a statistically significant adverse trend for the Significant 

Events indicator would exist if the final ASP results for all five of these precursor events meet 

the significant events criteria. 

Upon completing the final ASP analysis, all five precursor events did meet the significant events 

criteria which yielded a statistically significant adverse trend for the significant event indicator 

during the FY 2004 to 2013 timeframe (included as Figure 15 of Enclosure 1). Based on 

currently available data, this statistically significant adverse trend did not continue into FY 2014. 

The staff had already been analyzing the increase in significant events that began in FY 2010 

as part of the industry trends, operating experience, and RES programs. A Bulletin and several 

Information Notices were issued based on staff’s review of these significant events. The review 

revealed that the causes of most of these events were related to issues with electrical 

distribution systems. Because of the ASP result, the staff has initiated an in-depth electrical 

distribution system and component reliability study to glean insights from precursors associated 

with issues in plant electrical systems. Other broad issues, such as those initiated by natural 

phenomena, are already being considered using normal agency processes. Any safety concern 

involving an individual plant was addressed already in a timely manner and no changes to 

oversight or licensing were identified as a result. 
The Commissioners - 4 -

Results of FY 2014 Short-Term Industry Performance

As described above, 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 their prediction limits in FY 2014. Short-term FY 2014 data did 

not reveal any emerging trends that warranted additional analysis or significant adjustments to 

the nuclear reactor safety inspection or licensing programs. 

Results of FY 2014 Baseline Risk Index for Initiating Events

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

exceeded their prediction limits in FY 2014. For Tier 2, Figure 15 of Enclosure 3 shows that the 

combined industry BRIIE value for FY 2014, -2.53×10-6 per reactor critical year, is negative, 

which shows that industry performance was in fact better than baseline. The combined industry 

BRIIE value is below the established reporting threshold of ΔCDF = 1.0×10-5 per reactor critical 

year.

Status of Commitments from Program Review

On June 13, 2013, the Commission issued a staff requirements memorandum (SRM) in 

response to the May 29, 2013, “Briefing on the Results of the Agency Action Review Meeting 

(AARM).” In this SRM the Commission directed the staff to review the ITP as follows:

As part of the Reactor Oversight Process (ROP) Self-Assessment for calendar year (CY) 

2013, the staff should review implementation of the Industry Trends Program over its 

history for lessons learned and inform the Commission of any program enhancements 

and/or resource reductions that may be warranted.

After completing the review of the ITP in 2013, the staff made the following commitments in 

SECY-14-0042:

• Consider using the public radiation safety cornerstone ROP performance indicator (i.e., 

radiological effluence occurrence) in the ITP

• Consider using the security cornerstone ROP performance indicator (i.e., protected area 

security equipment performance index) in the ITP

• Evaluate the possibility of supplementing or replacing ITP indicators with ROP 

performance indicators (PIs) where applicable

• Evaluate performance data for new reactors in the ITP, as applicable

The staff continues to evaluate the efficacy of replacing the current ITP indicators with ROP PIs. 

PIs were established to provide a broad sample of data to assess licensee performance in the 

risk-significant areas of each cornerstone. Shifting the ITP focus to an evaluation of trends in 

PIs could provide a complementary approach on an industry-wide basis to what the ROP 
The Commissioners - 5 -

provides on a plant-by-plant basis. The advantages of replacing the current ITP indicators with

ROP PIs are as follows:

• A more holistic view of industry safety performance would be achieved because all 

cornerstones of the ROP would be evaluated

• The significant resource burden (i.e., contract support) related to data collection and 

analysis would be greatly reduced

• The ITP would be more understandable by using the ROP PIs because they are more 

commonly used and widely disseminated

Currently, 6 of the 14 ITP indicators are based upon ROP PIs and several of the other indicators 

have an ROP PI that is very similar in nature, such as the “automatic scrams while critical” ITP 

indicator and the “unplanned scrams” ROP PI. 

The staff plans to solicit internal and external feedback regarding the potential for unintended 

consequences to making the change to ITP indicators based on ROP PIs, determine the 

necessary program revisions to enact this change, and seek to put those changes in place in 

time for the FY 2015 ITP assessment period.

Finally, as a part of the ongoing ROP enhancement effort, the staff continues to examine the 

overall efficacy of this program. Specifically, the staff is evaluating the relative benefits and 

costs of the ITP given that it has not informed any substantive changes to the ROP since its 

inception, and similar insights could potentially be gained by leveraging other NRC programs. 

CONCLUSION:

The results of the FY 2014 ITP did not indicate any statistically significant adverse trends in 

industry safety performance. Also, no ITP indicator exceeded its prediction limit, and the BRIIE 

value remained below the threshold for a report to Congress. 

The updated results for FY 2013 ITP caused a statistically significant adverse trend for the 

Significant Events indicator. The trend was evaluated and no changes to oversight or licensing 

were identified.
The Commissioners - 6 -

RESOURCES:

The resources for ITP activities are included in the FY 2015 Current Estimate (CE) and the FY 

2016 Congressional Budget Justification (CBJ). The total resources that are included in the FY 

2015 CE are 0.5 full-time equivalent (FTE) and $595K; and in the FY 2016 CBJ of 0.5 FTE and 

$595K. No additional resources beyond those already budgeted will be required for the ITP. 

Resources beyond FY 2017 will be addressed during the Planning, Budgeting, and 

Performance Management process. 

COORDINATION:

The Office of the Chief Financial Officer has reviewed this paper for resource implications and 

has no objections. The Office of the General Counsel has reviewed this paper and has no legal 

objection. 

Sincerely,

/RA by Jennifer Uhle for/

William M. Dean, Director

Office of Nuclear Reactor Regulation

Enclosures:

1. Fiscal Year 2014 Long-Term Industry Trend 

Results

2. Fiscal Year 2014 Short-Term Industry

Performance

3. Summary of Baseline Risk Index for 

Initiating Events: Annual Graphs through 

Fiscal Year 2014
Enclosure 1

FISCAL YEAR 2014 LONG-TERM INDUSTRY TREND RESULTS

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

adverse trends in the industry trends program performance indicator data from the most recent 

10 years (fiscal years 2005–2014), as shown by the figures below.

Upon receiving finalized FY 2013 data the staff identified a statistically significant adverse trend 

for the significant event indicator during the FY 2004 to 2013 timeframe as shown in Figure 15.

Figure 1. Automatic scrams while critical

0.47

0.32

0.48

0.29

0.36

0.44 0.45

0.30

0.38 0.39

0.00

0.50

1.00

1.50

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Scrams per Unit

Fiscal Year

Industry Average
- 2 -

Figure 2. Safety-system actuations

Figure 3. Significant events (FY 2014 inputs are not yet complete)

0.38

0.22

0.25

0.14

0.23

0.18 0.19

0.17

0.29

0.20

0

0.2

0.4

0.6

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Actuations per Unit

Fiscal Year

0.05

0.03

0.02

0.03

0.02

0.10

0.13

0.10

0.07

0.01

0.00

0.05

0.10

0.15

0.20

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per Unit

Fiscal Year

Industry Average

Industry Average
- 3 -

Figure 4. Safety-system failures

Figure 5. Forced outage rate

0.98

0.60

0.68 0.71 0.71

0.93 0.94

0.87 0.92 0.87

0.0

0.5

1.0

1.5

2.0

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Failures per Unit

Fiscal Year

2.34

1.47 1.41 1.34

2.21

1.74 1.80

2.77

2.98

1.27

0

2

4

6

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Forced Outage Rate (%)

Fiscal Year

Industry Average

Industry Average
- 4 -

Figure 6. Equipment forced outages

As discussed in this paper, Figures 1 through 6 do not display a trend line because these 

graphs do not have a statistically significant trend.

Figure 7. Collective radiation exposure

0.13

0.10

0.11

0.08

0.09

0.10

0.09 0.09

0.08

0.10

0

0.1

0.2

0.3

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Equipment Forced Outages per

1,000 Commercial Critical Hours

Fiscal Year

117

93

109

96

87 91 90

72

77

72

0

50

100

150

200

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Average Exposure per Unit

(Person-REM)

Fiscal Year

Industry Average

Industry Average

Industry Average Trend
- 5 -

Figure 8. Unplanned power changes

Figure 9. Reactor coolant system activity

0.97

0.91 0.91 0.92

0.56

0.86 0.89

0.70

0.76

0.95

0.0

0.5

1.0

1.5

2.0

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Unplanned Power Changes per 

7,000 Critical Hours

Fiscal Year

0.41

0.60

0.45

0.48

0.32

0.19

0.13

0.09

0.08 0.11

0.0

0.5

1.0

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Maximum Percentage of Technical

Specification Limits

Fiscal Year

Industry Average

Industry Average

Industry Average Trend
- 6 -

Figure 10. Reactor coolant system leakage

Figure 11. Drill and exercise performance

4.45 4.08 4.35 4.25

3.97 4.14 4.05 4.08 3.99 4.02

0

2

4

6

8

10

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Maximum Percentage of

Technical Specification Limits

Fiscal Year

95.82

96.06 96.19 96.22

97.06 96.89

97.30

97.51 97.47

97.86

92

94

96

98

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Percentage Timely and Accurate

Fiscal Year

Industry Average

Industry Average Trend

Industry Average

Industry Average Trend
- 7 -

Figure 12. Emergency response organization drill participation

Figure 13. Alert and notification system reliability

98.20

97.89 97.55

98.16

98.65

98.77

99.43

99.33

99.46

99.71

96

98

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Percentage of Key Personnel

Fiscal Year

99.34

99.48 99.45

99.53 99.57 99.59

99.68

99.77 99.77 99.79

98

99

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Percentage of Tests Successful

Fiscal Year

Industry Average

Industry Average Trend

Industry Average

Industry Average Trend
- 8 -

Figure 14. Accident sequence precursors (FY 2004-2013)

Figure 15. Updated Significant events 2004-2013

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Precursors Occurrence per Unit

Fiscal Year

0.04

0.05

0.03

0.02

0.03

0.02

0.10

0.13

0.10

0.07

0.00

0.05

0.10

0.15

0.20

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Events per Unit

Fiscal Year

Industry Average

Industry Average Trend
Enclosure 2

FISCAL YEAR 2014 SHORT-TERM INDUSTRY PERFORMANCE

The annual industry trend analysis compares data for the most recent year with 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 indicator. Baseline periods are periods for each indicator during which the data can be 

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

The results of the evaluation for fiscal year (FY) 2014 Industry Trends Program indicators, using 

the established prediction limits, show that no indicator exceeded its associated prediction limit 

in FY 2014, as shown in the following figures for each indicator with its FY 2014 data and 

associated prediction limit.

Figure 1. Automatic scrams while critical

0.00

0.25

0.50

0.75

1.00

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Scrams per Unit

Fiscal Year

Industry Average

Prediction Limit (0.673)

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

Figure 2. Safety-system actuations

Figure 3. Significant events (FY 2014 inputs are not yet complete)

0.00

0.20

0.40

0.60

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Actuations per Unit

Fiscal Year

Industry Average

Prediction Limit (0.375)

Baseline Industry Average (0.275), 1998-2005

0.00

0.05

0.10

0.15

0.20

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

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

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Failures per Unit

Fiscal Year

Industry Average

Prediction Limit (1.04)

Baseline Industry Average (0.859), 2001-2004

0

2

4

6

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

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

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Equipment Forced Outage per 

1,000 Commercial Critical Hours

Fiscal Year

Industry Average

Prediction Limit (0.180)

Baseline Industry Average (0.142), 1998-2004

0

50

100

150

200

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

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

0.0

0.5

1.0

1.5

2.0

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

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

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Maximum Percentage of Technical

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 steam generator tube rupture event at Indian Point Nuclear Generating Unit 2 in 

2000 was not included in the short-term data for determining prediction limits in Figure 10. This 

event was excluded from the development of the prediction limit models because it was

considered as an outlier that could overly influence 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

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Maximum Percentage of 

Technical Specification Limits

Fiscal Year

Industry Average

Prediction Limit (6.32)

Baseline Industry Average (5.14), 2000-2004

92

94

96

98

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

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

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Percentage of Key Personnel

Fiscal Year

Industry Average

Prediction Limit (97.50)

Baseline Industry Average (97.87), 2003-2007

97

98

99

100

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Percentage of Tests Successful

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 2014

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 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 might 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 about 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) 2014 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 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 2014 (−2.53×10−6

per reactor critical year) shows 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.

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

0.515 0.524

0.649

0.559 0.568

0.866

0.655

0.439

0.566

0.644

0.0

0.5

1.0

1.5

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1998 - 2002 Fiscal Year

 Baseline industry average

 95% prediction limit for one year
- 3 -

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

Figure 3. PWR loss of condenser heat sink

0.837

0.558

0.971

0.546

0.839

0.634

0.472

0.646 0.665 0.634

0.0

0.5

1.0

1.5

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1997 Fiscal Year - 2002

 Baseline industry average

 95% prediction limit for one year

0.064 0.064

0.032

0.016

0.047

0.082

0.033 0.034 0.034

0

0.00

0.05

0.10

0.15

0.20

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Fiscal Year Baseline period: 1995 - 2002

 Baseline industry average

 95% prediction limit for one year 
- 4 -

Figure 4. BWR loss of condenser heat sink

Figure 5. Loss of main feedwater

0.161

0.031

0.157

0.091 0.093

0.060 0.063 0.062 0.063

0

0.0

0.1

0.2

0.3

0.4

0.5

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1996 - 2002 Fiscal Year

 Baseline industry average

 95% prediction limit for one year 

0.086

0.042

0.063

0.042 0.042

0

0.022

0.011

0.033

0.011

0.00

0.05

0.10

0.15

0.20

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1993 - 2002 Fiscal Year

 Baseline industry average

 95% prediction limit for one 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

0.021

0.011

0

0.031

0

0.075

0.055

0.044

0.033

0.00

0.05

0.10

0.15

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1997 - 2004 Fiscal Year

 Baseline industry average

 95% prediction limit for one year 

0 0 0 0 0

0.021

0

0.011

0 0

0.00

0.02

0.04

0.06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1992 - 2002 Fiscal Year

 Baseline industry average

 95% prediction limit for one year
- 6 -

Figure 8. Loss of vital direct-current bus

Figure 9. PWR stuck-open safety or relief valve

0 0 0 0 0 0

0.011

0 0 0

0.00

0.01

0.02

0.03

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1988 - 2002 Fiscal Year

 Baseline industry average

 95% prediction limit for one year

0 0 0 0 0 0 0 0 0 0

0.00

0.01

0.02

0.03

0.04

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Fiscal Year Baseline period: 1988 - 2002

 Baseline industry average

 95% prediction limit for one year
- 7 -

Figure 10. BWR stuck-open safety or relief valve

Figure 11. PWR loss of instrument air

0 0 0 0

0.031

0 0 0 0 0

0.00

0.03

0.06

0.09

0.12

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1993 - 2002 Fiscal Year

 Baseline industry average

 95% prediction limit for one year

0

0.016 0.016

0 0

0.016

0 0

0.017 0.017

0.00

0.02

0.04

0.06

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1997 Fiscal Year - 2002

 Baseline industry average

 95% prediction limit for one year
- 8 -

Figure 12. BWR loss of instrument air

Figure 13. Very small loss-of-coolant accident

0

0.031

0 0 0 0 0 0 0

0.030

0.00

0.02

0.04

0.06

0.08

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1991 - 2002 Fiscal Year

 Baseline industry average

 95% prediction limit for one year

0.011

0 0 0 0 0 0 0 0 0

0.00

0.01

0.02

0.03

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1992 - 2002 Fiscal Year

 Baseline industry average

 95% prediction limit for one year
- 9 -

Figure 14. PWR steam generator tube rupture

Figure 15. BRIIE Tier 2 (ΔCDF)

0 0 0 0 0 0 0 0 0 0

0.00

0.01

0.02

0.03

0.04

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Events per reactor critical year

Baseline period: 1991 - 2002 Fiscal Year

 Baseline industry average

 95% prediction limit for one year

-1.0E-05

-5.0E-06

0.0E+00

5.0E-06

1.0E-05

1.5E-05

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Delta CDF (1/rcry)

Fiscal Year

PWR BWR Industry Using Bayesian updates of annual frequencies

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