NRC INSPECTION MANUAL IPAB

INSPECTION MANUAL CHAPTER 0313

INDUSTRY TRENDS PROGRAM
Issue Date: 01/26/16 i 0313

TABLE OF CONTENTS

0313-01 PURPOSE................................................................................................................ 1

0313-02 OBJECTIVES........................................................................................................... 1

0313-03 RESPONSIBILITIES AND AUTHORITIES ............................................................... 1

03.01 Director, Office of Nuclear Reactor Regulation (NRR) .............................................. 1

03.02 Office of Nuclear Regulatory Research (RES).......................................................... 1

03.03 Director, Division of Inspection and Regional Support (DIRS) .................................. 2

03.04 Chief, Performance Assessment Branch .................................................................. 2

0313-04 BACKGROUND........................................................................................................ 2

0313-05 DISCUSSION........................................................................................................... 3

05.01 Collect Indicator Data ............................................................................................... 3

05.02 Identify Short-Term Issues ....................................................................................... 3

05.03 Identify Adverse Trends............................................................................................ 3

05.04 Analyses of Issues ................................................................................................... 4

05.05 Agency Response .................................................................................................... 5

05.06 Senior Management Review..................................................................................... 5

05.07 Communications with Stakeholders.......................................................................... 5

05.08 Baseline Risk Index for Initiating Events (BRIIE) ...................................................... 6

APPENDIX A INDICATORS QUALIFIED FOR USE IN THE ITP ...........................................A-1

APPENDIX B PREDICTION LIMITS ......................................................................................B-1

APPENDIX C LONG-TERM TRENDING................................................................................C-1

APPENDIX D BASELINE RISK INDEX FOR INITIATING EVENTS (BRIIE) ..........................D-1

Attachment 1 Revision History for IMC 0313.....................................................................Att 1-1
Issue Date: 01/26/16 1 0313

0313-01 PURPOSE

The purpose of the Industry Trends Program (ITP) is to provide a means to assess whether the 

nuclear industry is maintaining the safety performance of operating reactors, and to identify 

significant trends in safety performance.

0313-02 OBJECTIVES

The specific objectives of the ITP are as follows:

02.01 Collect and monitor industry-wide data that can be used to assess whether the nuclear 

industry is maintaining the safety performance of operating plants and to provide the NRC 

feedback to its nuclear reactor safety inspection and licensing programs;

02.02 Assess the safety significance and causes of any statistically significant adverse 

industry trends, determine if the trends represent an actual degradation in overall industry safety 

performance, and respond appropriately to any safety issues that may be identified;

02.03 Communicate industry-level information to stakeholders in an effective and timely 

manner; and 

02.04 Support the NRC’s strategic goals of ensuring safe and secure use of radioactive 

materials, while enhancing openness in the agency’s regulatory processes.

0313-03 RESPONSIBILITIES AND AUTHORITIES

03.01 Director, Office of Nuclear Reactor Regulation (NRR).

a. Provides overall policy direction for the ITP.

b. Directs the development and implementation of policies, programs, and procedures for 

the ITP.

c. Provides oversight of program effectiveness and implementation.

03.02 Office of Nuclear Regulatory Research (RES).

a. Updates and maintains the Accident Sequence Precursor (ASP) database, the 

common-cause failure database, the Licensee Event Report database, and the 

Integrated Data Collection and Coding System for use by NRR, RES, and the Regions.

b. Provides support and data as requested by the Director, NRR.
Issue Date: 01/26/16 2 0313

03.03 Director, Division of Inspection and Regional Support (DIRS).

a. Manages ITP development and implementation within NRR.

b. Oversees program implementation and effectiveness.

03.04 Chief, Performance Assessment Branch.

 a. Develops policy, programs, and procedures for implementation of the ITP.

 

 b. Assesses ITP effectiveness and implementation.

0313-04 BACKGROUND

The NRC provides oversight of plant safety performance on a plant-specific basis using both 

inspection findings and plant-level performance indicators (PIs) as part of its Reactor Oversight 

Process (ROP). Individual issues that are identified as having generic safety significance are 

addressed using a number of NRC processes, including the generic communications process 

and the generic safety issue process. The NRC staff developed the ITP to complement these 

processes by monitoring and assessing industry-level trends in safety performance.

In developing the ITP, the staff used the following general concepts for its approach:

• The indicators were developed using information available from current NRC programs. 

• Industry trend information is derived from quantitative, industry-wide data.

• Trends are identified on the basis of long-term (i.e., four or more years) data, rather than 

short-term data. This minimizes the impact of short-term variations in data, which may be 

attributable to such factors as operating cycle phase, seasonal variations, and random 

fluctuations.

• Trends and contributing factors are assessed for safety significance. The results of 

inspections, analyses of significant events and abnormal occurrences, and other analyses 

may be used to facilitate an evaluation of the trends. The agency’s response is 

commensurate with the safety significance.
Issue Date: 01/26/16 3 0313

• The current ITP indicators are identified in Appendix A. New ITP indicators should be 

qualified for use and have enough data to perform long-term trending prior to being 

implemented.

The ITP indicators have been revised since the initial implementation of the ITP to be more riskinformed, to make data collection less burdensome, and to better align with all seven ROP

cornerstones. As a further enhancement for the ITP, the staff developed a risk-informed

indicator for initiating events. The indicator, the Baseline Risk Index for Initiating Events 

(BRIIE), was added to the ITP in 2007.

An NRC contractor collects and trends a portion of the ITP data and provides analysis on an as 

needed basis for the NRC.

0313-05 DISCUSSION

The process for collecting, analyzing, reporting, and responding to the industry trend indicators 

is discussed below.

05.01 Collect Indicator Data.

Data for the ITP is collected from a variety of sources, including the ROP PI program, Licensee 

Event Reports, and Event Notifications. Each indicator currently qualified for use in the ITP is 

described in Appendix A.

05.02 Identify Short-Term Issues.

NRR adopted a statistical approach using “prediction limits” to provide a consistent method to 

identify potential short-term emergent issues before they manifest themselves as long-term 

trends. The prediction limits are values established at the beginning of a fiscal year (FY) that 

set an upper bound on expected performance for that FY for each indicator. Actual indicator 

values during the FY can then be monitored and compared to the prediction limits. Indicators 

that cross the prediction limits are investigated to determine the factors contributing to the data. 

These factors are assessed for their safety significance and used to determine an appropriate 

agency response. Should obvious adverse trends emerge in the short-term data during the 

middle of the FY, the staff should initiate a review to determine if agency action is necessary.

A more detailed description of prediction limits is provided in Appendix B.

05.03 Identify Adverse Trends.

For purposes of assessing whether there are any statistically significant adverse industry trends, 

only long-term data is used. The trending of long-term data minimizes reacting to potential 

“false positive” indications that may emerge in short-term data. “Long-term” was defined to be 

greater than or equal to four years to ensure that sufficient data (i.e., data for at least two typical 

nuclear plant operating cycles) is available and valid trends can be distinguished from operating 

cycle effects such as refueling outages and from random fluctuations in the data.
Issue Date: 01/26/16 4 0313 

The staff applies statistical techniques to the long-term indicator data to identify trends. These 

techniques have been previously adapted and used extensively by the NRC in reactor operating 

experience analyses. In general terms, a trendline is fit to each indicator using appropriate 

regression techniques. Once a statistically significant fit of a trendline is made to each indicator, 

the slope of the trendline is examined. Improving or flat trendlines are not considered adverse 

and need not be investigated further. Degrading trendlines are considered adverse. A more 

detailed discussion of long-term trending and the determination of a statistically significant 

adverse trend is discussed in Appendix C.

05.04 Analyses of Issues.

Once a statistically significant adverse trend is identified, the staff conducts an initial analysis of 

information readily available in the databases used to compile the indicator data to determine 

whether the trend is unduly influenced by a small number of outliers and to identify any 

contributing factors. If the trend is the result of outliers, then it is not considered a trend 

requiring generic actions, and the agency will consider any appropriate plant-specific actions 

using the ROP. For example, the affected plants unduly influencing the adverse trend may 

have already exceeded plant-level thresholds under the ROP, and the NRC regional offices 

would conduct supplemental inspections at these plants to ensure the appropriate corrective 

actions have been taken. If the plants did not exceed any thresholds, the NRC would not take 

regulatory actions beyond the ROP, however, the NRC may gather additional information 

regarding the issue within the scope of the ROP using risk-informed baseline inspections. The 

results of these inspections would be examined to determine if a generic issue existed requiring 

additional NRC review or generic inspections.

If no outliers are identified, the staff conducts a broader review to assess whether larger groups 

of facilities are contributing to the decline and to assess any contributing factors and causes. 

For example, the data review is expanded to include a review of various plant comparison 

groups, contributing factors such as the operational cycle stage of the facilities (shutdown, atpower, startup from refueling, etc.), and the apparent causes for the data (equipment failures, 

procedure problems, etc.). Should a group of plants be identified, the staff will examine the 

results of previously conducted inspections at these plants, including any root causes and the 

extent of the conditions.

Once this information is reviewed, the staff assesses the safety significance of the underlying 

issues. The staff is mindful that trends in individual indicators must be considered in the larger 

context of their overall risk significance. For example, a hypothetical increase in Unplanned 

Scrams from 0.4 to 0.7 per plant per year over several years may be a statistically significant 

trend in an adverse direction. However, it may not represent a significant increase in overall risk 

since the contribution of a small number of scrams is relatively low, and it is possible that overall 

risk may actually have declined if there were reductions in the frequency of more risk-significant 

initiating events or the reliability and availability of safety systems had improved. Depending on 

the issues, the staff may perform an additional evaluation using the most current risk analysis 

tools or an evaluation by the ASP Program.
Issue Date: 01/26/16 5 0313 

05.05 Agency Response.

Should a statistically significant adverse trend in safety performance be identified or an indicator 

exceed a prediction limit, the staff will determine the appropriate response using the processes 

described above and the NRC's established processes for addressing and communicating 

generic issues. The generic issue process is described in Management Directive (MD) 6.4, 

“Generic Issues Program.”

In general, the issues will be assigned to the appropriate branch of NRR for initial review. The 

branch will engage NRC senior management and initiate early interaction with the nuclear 

power industry. Depending on the issue, the process could include requesting industry groups 

such as the Nuclear Energy Institute (NEI) or various owners groups to provide utility 

information. As discussed in SECY-00-0116, “Industry Initiatives in the Regulatory Process,” 

industry initiatives, such as the formation of specialized working groups to address technical 

issues, may be used instead of, or to complement, regulatory actions. This can benefit both the 

NRC and the industry by identifying mutually satisfactory resolution approaches and reducing 

resource burdens.

Depending on the issues, the NRC may consider generic safety inspections at plants. In 

addition, the issues underlying the statistically significant adverse trend may also be addressed 

as part of the generic safety issue process by RES. The NRC may consider additional 

regulatory actions as appropriate, such as issuing generic correspondence to disseminate or 

gather information, or conducting inspections for generic issues using a Temporary Instruction. 

The process also includes consideration of whether any actions proposed by the NRC to 

address the issues constitute a backfit per MD 8.4, “Management of Facility-Specific Backfitting 

and Information Collection.”

05.06 Senior Management Review.

The ITP results and agency response are reviewed annually during the Agency Action Review 

Meeting (AARM). In general, the AARM is intended to review the appropriateness and 

effectiveness of staff actions already taken, rather than to make decisions on agency actions. 

NRC senior managers review the industry trends information and, if appropriate, recommend 

any additional actions beyond those implemented by the staff. Additional information 

concerning the AARM can be found in MD 8.14, “Agency Action Review Meeting.”

05.07 Communications with Stakeholders.

The NRC communicates overall industry performance to stakeholders by publishing the ITP 

indicators on the Nuclear Reactors portion of the agency’s public Web site at 

http://www.nrc.gov/reactors/operating/oversight/industry-trends.html. Communication of the 

industry-level indicators, when added to the information on individual plants from the ROP, 

should enhance stakeholder confidence in the efficacy of the NRC’s oversight of the nuclear 

industry.
Issue Date: 01/26/16 6 0313 

The staff informs the Commission of the results of the ITP in an annual report prior to the 

AARM. Some of the indicators are also published annually in the NRC’s “Information Digest 

20XX” (NUREG-1350 series). In addition, NRC managers have historically presented industry 

indicators and trends at major conferences with industry and other external stakeholders.

In addition, the Commission has historically used the ITP indicators when presenting the status 

of industry performance to the NRC’s congressional oversight committees.

05.08 Baseline Risk Index for Initiating Events (BRIIE).

The BRIIE provides a short-term trending mechanism for determining the risk significance of 

changes in performance at the individual initiating event level.

Short-term monitoring is accomplished by monitoring yearly industry performance for 9 risksignificant initiating events for boiling-water reactors (BWRs) and 10 events for pressurizedwater reactors (PWRs) (the additional event category is steam generator tube rupture) against 

performance-based predictions limits. These activities, similar to the process described in 

Appendix B for the ITP indicators, help the NRC identify degrading industry performance before 

the emergence of any long-term adverse trends.

The BRIIE is intended to enhance and complement the ITP and not as a replacement. 

Appendix D to this IMC contains a detailed discussion of the BRIIE and its function within the 

ITP. Historical results and the technical basis for BRIIE are provided in NUREG/CR-6932 

(INLEXT-06-11950), “Baseline Risk Index for Initiating Events (BRIIE).”

END

Appendices:

A. Indicators Qualified for Use in the ITP

B. Prediction Limits

C. Long-Term Trending

D. Baseline Risk Index for Initiating Events (BRIIE)

Attachment:

1. Revision History for IMC 0313
Issue Date: 01/26/16 App A-1 0313

APPENDIX A

INDICATORS QUALIFIED FOR USE IN THE ITP

UNPLANNED SCRAMS

Definition: Total unplanned scrams at all plants each year multiplied by 7000 hrs, and then 

divided by the total critical hours for all plants each year. 

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

definition of an unplanned scram is contained in the latest version of NEI 99-02, “Regulatory 

Assessment Performance Indicator Guideline.”

UNPLANNED POWER CHANGES

Definition: Total unplanned power changes at all plants each year multiplied by 7000 hrs, and 

then divided by the total critical hours for all plants each year.

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

definition of an unplanned power change is contained in the latest version of NEI 99-02, 

“Regulatory Assessment Performance Indicator Guideline.”

UNPLANNED SCRAMS WITH COMPLICATIONS

Definition: Sum of unplanned scrams with complications within each year at all plants.

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

definition of an unplanned scram with complications is contained in the latest version of NEI 99-

02, “Regulatory Assessment Performance Indicator Guideline.”

SAFETY SYSTEM FUNCTIONAL FAILURES (SSFFs)

Definition: Sum of all SSFFs within each year at all plants, divided by the total number of plants. 
Issue Date: 01/26/16 App A-2 0313

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

definition of a SSFF is contained in the latest version of NEI 99-02, “Regulatory Assessment 

Performance Indicator Guideline.”

MITIGATING SYSTEMS PERFORMANCE INDEX (MSPI) FOR EMERGENCY AC POWER 

SYSTEMS 

Definition: Sum of all greater than green MSPI results calculated for emergency AC power 

systems within each year at all plants. 

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for calculating MSPI are contained in the latest version of NEI 99-02, “Regulatory 

Assessment Performance Indicator Guideline.”

MSPI FOR HIGH PRESSURE INJECTION SYSTEMS 

Definition: Sum of all greater than green MSPI results calculated for high pressure injection 

systems within each year at all plants. 

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for calculating MSPI are contained in the latest version of NEI 99-02, “Regulatory

Assessment Performance Indicator Guideline.”

MSPI FOR HEAT REMOVAL SYSTEMS 

Definition: Sum of all greater than green MSPI results calculated for heat removal systems 

within each year at all plants. 

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for calculating MSPI are contained in the latest version of NEI 99-02, “Regulatory 

Assessment Performance Indicator Guideline.”

MSPI FOR RESIDUAL HEAT REMOVAL SYSTEMS 

Definition: Sum of all greater than green MSPI results calculated for residual heat removal 

systems within each year at all plants. 
Issue Date: 01/26/16 App A-3 0313

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for calculating MSPI are contained in the latest version of NEI 99-02, “Regulatory 

Assessment Performance Indicator Guideline.”

MSPI FOR COOLING WATER SUPPORT SYSTEMS 

Definition: Sum of all greater than green MSPI results calculated for cooling water support 

systems within each year at all plants. 

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for calculating MSPI are contained in the latest version of NEI 99-02, “Regulatory 

Assessment Performance Indicator Guideline.”

REACTOR COOLANT SYSTEM (RCS) SPECIFIC ACTIVITY

Definition: Sum of maximum percentage of Technical Specification RCS specific activity within 

each year at all plants, divided by the total number of plants with data.

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for calculating the maximum percentage of RCS specific activity are contained in 

the latest version of NEI 99-02, “Regulatory Assessment Performance Indicator Guideline.”

REACTOR COOLANT SYSTEM LEAKAGE

Definition: Sum of maximum percentage of Technical Specification RCS leakage within each 

year at all plants, divided by the total number of plants with data.

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for calculating the maximum percentage of RCS leakage are contained in the 

latest version of NEI 99-02, “Regulatory Assessment Performance Indicator Guideline.”

DRILL/EXERCISE PERFORMANCE

Definition: Total number of classifications at all plants each year multiplied by 100, and then 

divided by the total number of classification opportunities at all plants each year.
Issue Date: 01/26/16 App A-4 0313

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for determining the number of classifications and opportunities are contained in 

the latest version of NEI 99-02, “Regulatory Assessment Performance Indicator Guideline.”

EMERGENCY RESPONSE ORGANIZATION (ERO) DRILL PARTICIPATION

Definition: Total number of key ERO members participating in drills at all plants each year 

multiplied by 100, and then divided by the total number of key ERO members at all plants each 

year.

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for determining the number of key ERO members are contained in the latest 

version of NEI 99-02, “Regulatory Assessment Performance Indicator Guideline.”

ALERT AND NOTIFICATION SYSTEM RELIABILITY

Definition: Total number of successful alert and notification system tests at all plants each year 

multiplied by 100, and then divided by the total number of tests at all plants each year.

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for determining the number of tests are contained in the latest version of NEI 99-

02, “Regulatory Assessment Performance Indicator Guideline.”

OCCUPATIONAL EXPOSURE CONTROL EFFECTIVENESS 

Definition: Sum of all technical specification high radiation area (>1 rem per hour) occurrences, 

very high radiation area occurrences, and unintended exposure occurrences within each year at 

all plants. 

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for occupational exposure control effectiveness are contained in the latest version 

of NEI 99-02, “Regulatory Assessment Performance Indicator Guideline.”
Issue Date: 01/26/16 App A-5 0313

RADIOLOGICAL EFFLUENT TECHNICAL SPECIFICATIONS (RETS)/ OFFSITE DOSE 

CALCULATIONS MANUAL (ODCM) RADIOLOGICAL EFFLUENT OCCURRENCES

Definition: Sum of all RETS/ODCM radiological effluent occurrences within each year at all 

plants. 

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for RETS/ODCM radiological effluent occurrences are contained in the latest 

version of NEI 99-02, “Regulatory Assessment Performance Indicator Guideline.”

PROTECTED AREA SECURITY EQUIPMENT PERFORMANCE INDEX 

Definition: Sum of the protected area security equipment performance index within each year at 

all plants, divided by the total number of plants with data. 

Data Source: ROP PI data submittals from licensees.

Description: This indicator is based on data submitted by licensees to support the ROP. The 

requirements for the protected area security equipment performance index are contained in the 

latest version of NEI 99-02, “Regulatory Assessment Performance Indicator Guideline.”

BASELINE RISK INDEX FOR INITIATING EVENTS (BRIIE)

Definition: A performance indicator that provides a mechanism for determining the risk 

significance of changes in performance at the individual initiating event level.

Data Source: Input for this indicator is derived from LERs and supplemented by 10 CFR 50.72 

reports.

Description: Each BRIIE category is calculated as an average events per reactor critical year. 
Issue Date: 01/26/16 App B-1 0313

APPENDIX B

PREDICTION LIMITS

To develop prediction limits, two steps are required. The first is to establish a baseline period 

for each indicator, during which the data can be regarded as fairly constant.

The second step is to select an appropriate constant model for the data in the baseline period. 

The prediction limit is based on this constant model and corresponds to a selected probability 

that future data points will not exceed the prediction limit.

Baseline Period and Prediction Limits

For each indicator considered, a baseline period must be established. The baseline period data 

are then used as input to the predictive limits analysis.

To guide the determination of the baseline period, the following characteristics were identified:

• The baseline period is representative of current industry performance.

• The baseline period is long enough to give a good estimate of the frequency, and is not 

strongly influenced by random variation.

• The baseline period is limited in length to ensure that the true frequency is approximately 

constant.

Because a long enough period is needed to give a good estimate, it was decided that every 

baseline period should contain at least four years. For each indicator, the history is examined 

back to the earliest year of data. Candidate baseline periods are analyzed for successively 

shorter time periods down to the minimum of four years. For each candidate baseline period, a 

trend model is fit to the data. That is, the slope of the trend model is estimated from the data for 

the corresponding period. A statistical test is then performed to see whether the slope could be 

equal to zero (a slope equal to zero would reflect a frequency that is constant). The statistical 

significance of this test is a probability (called a p-value). If the significance of the test is less 

than 0.05, then the slope is treated as being different from zero. 

In this way, a “significance” value is calculated for each candidate baseline period year. The 

closer the “significance” value is to 1.0, the more assurance one has that the slope is zero. The 

baseline period with the largest significance value and with reasonable mean value is selected 

as the baseline period. The baseline period is selected to balance the other competing criteria 

described above.

Using information from the baseline period (e.g., number of occurrences and reactor operating 

or calendar years) and an estimate of the reactor operating or calendar time for the next year, a 

predictive distribution is determined. This distribution is derived on the assumption that it will 
Issue Date: 01/26/16 App B-2 0313

predict future performance subject only to random fluctuations in the data. The 95% percentile 

of this distribution is the prediction limit. Random fluctuations should only exceed this value 

about 5% of the time based on current conditions. However, if those conditions should degrade, 

then the prediction limit could be exceeded more often. This situation would indicate that further 

investigation is warranted. An example prediction limit chart is presented in Figure 1.

When such a period and its associated statistical model have been established, the prediction 

limit threshold does not change from one year to the next unless a clear change has been noted 

in the performance of an indicator. Such a change would need to be both noticeable and 

persistent. Thus, data from a single year would not be sufficient to change a model and its 

prediction limit.

Figure 1. Sample Prediction Limit Chart

1.51

1.39

1.21

1.07

1.15

1.00 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

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Power Changes per 7000 Critical Hours

Fiscal Year

Unplanned Power Changes

Industry Average

Prediction Limit 1.30

Baseline Industry Average (1.11), 2001-

2004
Issue Date: 01/26/16 App C-1 0313

APPENDIX C

LONG-TERM TRENDING

As mentioned in the main body of this Manual Chapter, one objective of the Industry Trends 

Program (ITP) is to determine the number of statistically significant adverse trends in industry 

performance. The ITP uses long-term trending of the data to report against this performance 

measure.

The NRC has been collecting and trending industry level data since at least 1987. The ITP 

previously established long-term trends based on data back through FY 1988. When most 

indicators were continuing to show improving performance, trending from 1988 worked well. 

However, continuing to display trends driven largely by the 1987 to mid-1990s data is no longer 

valid for representing recent industry performance. In order to ensure current performance 

trends are not masked by the use of historical data, the NRC has removed some historical data 

from consideration during the trending analysis. The NRC now uses a 10-year rolling period to 

establish long term trends. A 10-year period was chosen to ensure enough data was available 

for meaningful statistical analysis. An example long-term trending chart is presented in Figure 

2.

Using a 10-year period through the current year’s data, trend lines are developed using 

statistical regression techniques. Statistical “goodness of fit” tests are then conducted to 

determine which trend line model best fits the data. Statistical analysis is performed to 

determine the significance of the trend. Confidence levels are used in a manner very similar to 

that discussed in Appendix B. If the confidence level in a trend is 95% or greater, there is 

strong evidence that the trend is not due to random data fluctuation. At this point, the trend is 

considered “statistically significant.”

In order for a trend to be considered a “statistically significant adverse trend,” the slope of the 

trend line model has to be in the adverse direction (performance degrading) and statistical 

analysis has to determine that the trend is statistically significant.
Issue Date: 01/26/16 App C-2 0313

Figure 2. Sample Long-Term Trending Chart

0.41

0.60

0.45

0.48

0.32

0.19

0.13

0.09

0.08

0.11

y = 0.8121e-0.233x

R2 = 0.8568

0.0

0.5

1.0

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Maximum Percentage of Technical

Specification Limits

Fiscal Year

Reactor Coolant System Activity
Issue Date: 01/26/16 App D-1 0313

APPENDIX D

BASELINE RISK INDEX FOR INITIATING EVENTS (BRIIE)

To enhance the ITP, the staff developed the Baseline Risk Index for Initiating Events (BRIIE), a 

performance indicator that provides a short-term trending mechanism for determining the risk 

significance of changes in performance at the individual initiating event level.

ENHANCEMENT PROCESS FOR INITIATING EVENTS CORNERSTONE OF SAFETY

A two-step process is used to enhance the ITP coverage of the Initiating Events Cornerstone of 

Safety:

Step 1 - identify appropriate risk-significant categories of initiating events

Step 2 - trend and establish performance-based prediction limits for these individual event 

categories 

Step 1 - Identification of Risk-Significant Initiating Events

The list of risk-significant initiating event types consists of 10 initiating event categories 

applicable to pressurized-water reactors (PWRs) and 9 applicable to boiling-water reactors 

(BWRs) as listed below in Table 1:

Table 1. Risk-significant initiating event categories covered by the BRIIE

Pressurized Water Reactors (PWRs) Boiling Water Reactors (BWRs)

1. Loss of offsite power (LOOP) 1. Loss of offsite power (LOOP)

2. Loss of vital AC bus (LOAC) 2. Loss of vital AC bus (LOAC)

3. Loss of vital DC bus (LODC) 3. Loss of vital DC bus (LODC)

4. Loss of main feedwater (LOMFW) 4. Loss of main feedwater (LOMFW)

5. Very small loss of coolant accident 

(VSLOCA)

5. Very small loss of coolant accident 

(VSLOCA)

6. PWR general transient (TRAN) 6. BWR general transient (TRAN)

7. PWR loss of condenser heat sink 

(LOCHS)

7. BWR loss of condenser heat sink 

(LOCHS)

8. PWR stuck open safety/relief valve 

(SORV)

8. BWR stuck open safety/relief valve 

(SORV)

9. PWR loss of instrument air (LOIA) 9. BWR loss of instrument air (LOIA)

10. Steam generator tube rupture (SGTR) 

In general, these risk-significant initiating event types, cover approximately 60% of the internal 

event core damage risk (excluding internal flooding) from the operating commercial nuclear 

power plants in the United States. Also, these initiating events do not overlap.
Issue Date: 01/26/16 App D-2 0313

Step 2 - Performance Monitoring of Risk-Significant Initiating Event Categories

Performance monitoring activity consists of trending risk-significant initiating event categories 

and monitoring yearly industry performance against prediction limits. To accomplish this, the 

staff established up-to-date baseline frequencies for each of the risk-significant initiating event 

categories, and then determined performance-based prediction limits using these baseline 

frequencies and estimated yearly industry-total critical-reactor years of operation. The process 

is similar to the “prediction limit” process described in Appendix B for the ITP indicators. An 

example is presented in Figure 3.

These activities are intended to help the NRC identify degrading industry performance as an 

adjunct to the plant-specific performance assessment performed as part of the ROP. Potential 

NRC responses if one or more of the prediction limits are reached or exceeded are outlined 

later in this appendix. BRIIE activities and results are used by the NRC as a diagnostic tool to 

identify degrading industry performance before the emergence of any long-term adverse trends.

The BRIIE results will be placed on the NRC Web site for access by interested stakeholders.

POTENTIAL REGULATORY RESPONSES TO BRIIE RESULTS

As an example, suppose four events are observed in one year that are classified as very small 

break LOCAs (VSLOCA), and each event occurred at a different plant. A VSLOCA as an 

initiating event is rare. The 95% prediction limit is two events. Therefore, the 95% prediction 

limit has been exceeded. Because the number of actual events exceeds the prediction limit, 

this initiating event is a candidate for further investigation.

Figure 3

19881989199019911992199319941995199619971998199920002001200220032004

Fiscal Year 0.0

0.8

1.6

2.4

3.2 Events per reactor critical year

Rate for PWR general transients Baseline period maximum likelihood estimate (n/T) 95% prediction limit Baseline period: CY1998-2002

Baseline log model p-value = 0.26 PQ-11-Jan-2006
Issue Date: 01/26/16 App D-3 0313

Because VSLOCAs do not occur very often, the NRC would examine and review each event in 

more detail after it occurred. The ITP would look at these events to see if there were similarities 

among the events and to provide any lessons learned from this evaluation. These lessons 

would be communicated to the industry via appropriate generic communication. Further

regulatory action would be taken as necessary based on the results of a detailed NRC 

inspection of each event.
Issue Date: 01/26/16 Att 1-1 0313

Revision History for IMC 0313

Commitment

Tracking

Number

Accession 

Number 

Issue Date

Change Notice

Description of Change Description 

of Training

Required and 

Completion 

Date

Training

Completed

Comment and 

Feedback

Resolution

Accession Number

(Pre-Decisional, 

Non-Public)

NA 05/29/08

CN 08-016

Added Appendix D and description of 

Baseline Risk Index for Initiating Events 

(BRIIE) throughout text of Manual 

Chapter

Revised Section 06.01 to describe a 

process to ensure that revised and 

updated data (such as data from 

inspection findings and ASP results) are 

included in the count of Significant 

Events

NA NA ML081430600

ML15316A039

01/26/16

CN 16-003

Revised to match the new 

congressional reporting requirements 

that came out of the Congressional 

Budget Justification: Fiscal Year 2016

Revised Appendix A to align the ITP 

indicators with the ROP PIs

NA NA ML15328A037