Risk Assessment of Operational Events 

Volume 2 – External Events 

Internal Fires – Internal Flooding – Seismic – Other External Events 

Frequencies of Seismically-Induced LOOP Events 

Revision 1.01 

January 2008 

SDP Phase 3 ● ASP ● MD 8.3
Risk Assessment of Operational Events ii 

TABLE OF CONTENTS 

ACRONYMS............................................................................................................................... v

1.0 Introduction..................................................................................................................1-1

1.1 Objectives ................................................................................................................1-1

1.2 Scope of the Handbook............................................................................................1-1

1.3 Audience for the Handbook......................................................................................1-2

1.4 Handbook Content ...................................................................................................1-2

1.5 Companion References to the Handbook.................................................................1-3

1.6 Future Updates to the Handbook .............................................................................1-4

1.7 Questions, Comments, and Suggestions .................................................................1-4

1.8 References...............................................................................................................1-5

2.0 Internal Fire Modeling and Fire Risk Quantification ......................................................2-1

2.1 Objectives and Scope ..............................................................................................2-1

2.2 Fire Scenario Definition and Quantification...............................................................2-2

2.2.1 Define Fire Scenarios...........................................................................................2-2

2.2.2 Quantify Sequence CDFs.....................................................................................2-6

2.3 Examples .................................................................................................................2-6

2.3.1 Example 1 - Event Analysis..................................................................................2-6

2.3.2 Example 2 - Plant Condition Analysis...................................................................2-6

2.3.3 Example 3 - Plant Condition Analysis (Shortcut) ..................................................2-9

2.3.4 Example 4 – Main Control Room (MCR) Fire .....................................................2-13

2.3.5 Other Examples and References........................................................................2-13

2.4 References.............................................................................................................2-13

Appendix 2A. Fire Scenarios/Accident Sequences............................................................2-15

Appendix 2B. Generic Fire Ignition Frequencies ...............................................................2-23

Appendix 2C. Severity Factors Data .................................................................................2-26

Appendix 2D. Detection Failure Data ................................................................................2-26

Appendix 2E. Suppression Failure Data............................................................................2-26

Appendix 2F. Spurious Actuation (due to hot shorts) Probabilities ....................................2-28

Appendix 2G. Operator Actions.........................................................................................2-30

Appendix 2H. Smoke Damage ..........................................................................................2-31

3.0 Internal Flood Modeling and Risk Quantification ..........................................................3-1

3.1 Objectives and Scope ..............................................................................................3-1

3.2 Internal Flooding Scenario Definition and Quantification ..........................................3-2

3.2.1 Define Internal Flooding Scenarios.......................................................................3-2

3.2.2 Quantify Sequence CDFs .......................................................................................3-4

3.3 Examples .................................................................................................................3-5

3.3.1 Example Event Analysis.......................................................................................3-5

3.3.2 Example Condition Analysis ..................................................................................3-5

3.3.3 Example Initiating Event Frequency Calculation...................................................3-6

3.4 References...............................................................................................................3-7

Appendix 3A. Model and Data for Internal Flooding ...........................................................3-8

4.0 Seismic Event Modeling and Seismic Risk Quantification ............................................4-1

4.1 Objectives and Scope ..............................................................................................4-1

4.2 Seismic Event Scenario Definition............................................................................4-1
 iii Handbook Vol. 2 – External Events 

4.2.1 Minimum Input Requirements...............................................................................4-1

4.2.2 Example Seismic Hazard Vector ..........................................................................4-2

4.2.3 Seismic Event Categories ....................................................................................4-2

4.2.4 SSC Seismic Fragilities ........................................................................................4-4

4.2.5 Event Tree Models .........................................................................................4-10

4.2.6 Fault Tree Models ..............................................................................................4-10

4.2.7 New Basic Events ..............................................................................................4-19

4.2.8 Application to SMA Plants ..................................................................................4-19

4.3 Special Modeling Considerations ...........................................................................4-19

4.3.1 Non-safety Systems.............................................................................................4-19

4.3.2 Seismically-induced LOOP ..................................................................................4-19

4.3.3 Operator Actions ................................................................................................4-21

4.3.4 Relay Chatter .....................................................................................................4-21

4.3.5 Seismically-induced Internal Flooding ................................................................4-21

4.3.6 Seismically-induced Fires...................................................................................4-21

4.3.7 Seismically-induced SLOCA and MLOCA ..........................................................4-22

4.4 CDF Quantification for Seismic Events...................................................................4-22

4.5 LERF Quantification for Seismic Events.................................................................4-22

4.6 References.............................................................................................................4-22

Appendix 4A. Generic Seismic Hazard Vectors.................................................................4-40

Appendix 4B. Generic SSC Seismic Fragilities..................................................................4-46

Appendix 4C. Seismic Fragility / pga / HCLPF ..................................................................4-50

Appendix 4D. Correspondence between PGA and Richter Scale......................................4-53

5.0 Other External Events Modeling and Risk Quantification .............................................5-1

5.1 Objectives and Scope ..............................................................................................5-1

5.2 Scenario Definition and Quantification......................................................................5-2

5.2.1 Define Scenarios..................................................................................................5-2

5.2.2 Quantify Sequence CDFs.....................................................................................5-4

5.2.3 Weather-Related LOOP Recovery Distributions ...................................................5-4

5.2.4 Weather-Related LOOP Frequencies...................................................................5-5

5.2.5 Treatment of Hurricane-Related Events ...............................................................5-5

5.3 Examples ......................................................................................................................5-6

5.3.1 Example Condition Analysis ...................................................................................5-6

5.3.2 Example Event Analysis .........................................................................................5-7

5.4 References...............................................................................................................5-8

Appendix 5A. Dam Failure Rates for External Flooding......................................................5-9

Appendix 1. Frequencies of Seismically-Induced LOOP Events for SPAR Models ................ A-1
Risk Assessment of Operational Events iv 

LIST OF FIGURES 

Figure 2-1 An Example New Event Tree Model ......................................................................2-7

Figure 2-2 Fire in DG-08 Base Case (Example 2).................................................................2-11

Figure 2-3 Fire in DG-08 with Plant Condition in Effect (Example 2).....................................2-12

Figure 4-1 Seismic Event BIN-1 Event Tree .........................................................................4-11

Figure 4-2 Seismic Event BIN-2 Event Tree .........................................................................4-12

Figure 4-3 Seismic Event BIN-3 Event Tree .........................................................................4-13

Figure 4-4 RPS Fault Tree (partial top showing introduction of seismic faults)......................4-14

Figure 4-5 RPS-SEISMIC-EQ Fault Tree..............................................................................4-15

Figure 4-6 Adding Seismic Failures to a Support System - Figure 1 of 3 .............................4-16

Figure 4-7 Adding Seismic Failures to a Support System - Figure 2 of 3 .............................4-17

Figure 4-8 Adding Seismic Failures to a Support System - Figure 3 of 3 .............................4-18

Figure 4-9 Estimation of Seismically-induced SLOCA and MLOCA Probabilities..................4-24

LIST OF TABLES 

Table 2-1 Example Summary of Fire Scenarios......................................................................2-5

Table 2-2 An Example Calculation of Sequence CDFs...........................................................2-8

Table 3-1 Example Internal Flooding Results by Scenario......................................................3-4

Table 4-1 Example Seismic Hazard Vector.............................................................................4-2

Table 4-2 Calculation of Bin Accelerations and Frequencies ..................................................4-3

Table 4-3 SSC Fragilities and Their Treatment in SPAR-EE...................................................4-5

Table 4-4 SSC Fragilities and Their Treatment in Plant C SPAR-EE ......................................4-7

Table 4-5 New Basic Events.................................................................................................4-20

Table 4-6 Seismic Event BIN Frequencies............................................................................4-25

Table 4-7 Seismic Event Sequence Frequencies..................................................................4-25

Table 4-8 Seismic Event CDF Cutsets..................................................................................4-27

Table 5-1 Example Matrix Defining Other External Event Scenarios.......................................5-3

Table 5-2 LOOP Recovery Distributions .................................................................................5-4

Table 5-3 LOOP Frequencies.................................................................................................5-5
 v Handbook Vol. 2 – External Events 

ACRONYMS 

ac alternating current 

AFW auxiliary feedwater 

ASME American Society of Mechanical Engineers 

ASP accident sequence precursor 

 

BWR boiling water reactor 

 

CCDP conditional core damage probability 

CCW component cooling water 

CDF core damage frequency 

CDP core damage probability 

 

DBE design basis earthquake 

dc direct current 

 

EDG emergency diesel generator 

EFW emergency feedwater 

ESW emergency service water 

 

FEMA Federal Emergency Management Agency 

FLI internal flooding 

FP fire protection 

FT fault tree 

 

GEM (code) Graphical Evaluation Module (code) 

 

HCLPF high confidence of low probability of failure 

HEP human error probability 

HVAC heating, ventilation and air conditioning 

 

IE initiating event 

IEfreq initiating event frequency 

IMC 0309 Inspection Manual Chapter 0309 

IPEEE Individual Plant Examination of External Events 

 

LER licensee event report 

LERF large early release frequency 

LOCA loss-of-coolant accident 

LOOP loss of offsite power 

LOSWS loss of service water system 

LPSI low-pressure safety injection 

 

MCR main control room 

MD 8.3 Management Directive 8.3 

MFW main feedwater 

MLOCA medium loss-of-coolant accident 

 
Risk Assessment of Operational Events vi 

NOAA National Oceanic and Atmospheric Administration 

NPP nuclear power plant 

NSW nuclear service water 

 

OBE operating-basis earthquake 

 

PCS power conversion system 

pga peak ground acceleration 

PMH probable maximum hurricane 

PMP probable maximum precipitation 

PORV power-operated relief valve 

PWR pressurized water reactor 

 

RASP Risk Assessment of Operational Events Handbook 

RCP reactor coolant pump 

RCS reactor coolant system 

RHR residual heat removal 

RWST refueling water storage tank 

 

SA spectral acceleration 

SAPHIRE Systems Analysis Programs for Hands-on Integrated Reliability Evaluations 

SBO station blackout 

SDP Significance Determination Process 

SG steam generator 

SLOCA small loss-of-coolant accident 

SMA seismic margins analysis 

SPAR (model) Standardized Plant Analysis Risk (model) 

SPRA seismic probabilistic risk analysis (model) 

SRA senior reactor analyst 

SRV solenoid relief valve 

SSC structures, systems and components 

SSE safe shutdown earthquake 

SW service water 

 

USGS U.S. Geological Survey 
 

 1-1 Handbook Vol. 2 – External Events 

External Events: Section 1 

Introduction Rev. 1.01 

1.0 Introduction 

1.1 Objectives 

The first objective of the Risk Assessment of Operational Events Handbook (sometimes known as 

“RASP Handbook” or “handbook”) was to document methods and guidance that NRC staff could 

use to achieve more consistent results when performing risk assessments of operational events 

and licensee performance issues. 

The second objective was to provide analysts and Standardized Plant Analysis Risk (SPAR) 

model developers with additional guidance to ensure that the SPAR models used in the risk analysis 

of operational events represent the as-built, as-operated plant to the extent needed to support the 

analyses. 

This handbook represents best practices based on feedback and experience from the analyses 

of over 600 precursors in the Accident Sequence Precursor (ASP) Program (since 1969) and 

numerous Significance Determination Process (SDP) Phase 3 analyses (since 2000). 

1.2 Scope of the Handbook 

The scope of the handbook is provided below. 

! Applications. The methods and processes described in the handbook can be primarily 

applied to risk assessments for Phase 3 of the SDP, the ASP Program, and event 

assessments under the NRC=s Incident Investigation Program (in accordance with 

Management Directive 8.3). The guidance for the use of SPAR models and Systems 

Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) software 

package can be applied in the risk analyses for other regulatory applications, such as 

the Generic Safety Issues Program and special risk studies of operational experience. 

! Relationships to program requirements. This handbook is intended to provide 

guidance for implementing requirements contained in program-specific procedures, such 

as Inspection Manual Chapter (IMC) 0609, “Significance Determination Process,” and 

IMC 0309, “Reactive Inspection Decision Basis for Reactors.” It is not the scope of this 

handbook to repeat program-specific requirements in the handbook, since these 

requirements may differ between applications and may change as programs evolve. 

Program-specific requirements supersede guidance in this handbook.

! Deviations from methods and guidance. Some unique events may require an 

enhancement of an existing method or development of new guidance. Deviations from 

methods and guidance in this handbook may be necessary for the analysis of atypical 

events. However, such deviations should be adequately documented in the analysis to 

allow for the ease of peer review. Changes in methodologies and guidance may be 

reflected in future revisions of this handbook.
1 Introduction 

Risk Assessment of Operational Events 1-2 

1.3 Audience for the Handbook 

The principal users of this handbook are senior reactor analysts (SRAs) and headquarters 

analysts involved with the risk analysis of operational events. It is assumed that the analysts 

using this handbook have received PRA training at the SRA qualification level. The analyst 

using this handbook should be familiar with the risk analysis of operational events, SAPHIRE 

software package, and key SPAR model assumptions and technical issues. Although, this 

handbook could be used as a training guide, it is assumed that the analyst either has completed 

the NRC course “Risk Assessment in Event Evaluation (Course Number P-302) or has related 

experience. 

1.4 Handbook Content 

The revised handbook includes three volumes, designed to address Internal Events (Volume 1), 

External Events (Volume 2), and SPAR Model Reviews (Volume 3). The scope of these volumes 

is as follows: 

! Volume 1, Internal Events. Volume 1, “Internal Events,” provides generic methods and 

processes to estimate the risk significance of initiating events (e.g., reactor trips, losses 

of offsite power) and degraded conditions (e.g., a failed high pressure injection pump, 

failed emergency power system) that have occurred at nuclear power plants.1

 Specifically, this volume provides guidance on the following analysis methods: 

- Exposure Time Determination and Modeling 

- Failure Determination and Modeling 

- Mission Time Modeling 

- Test and Maintenance Outage Modeling 

- Recovery of Failed Equipment Modeling 

- Multi-Unit Considerations Modeling 

 In addition, the appendices provide further guidance on the following analysis topics: 

- Roadmap - Risk Analysis of Operational Events 

- Quick Reference Guide – SAPHIRE Version 7 

Although, the guidance in this volume of the handbook focuses on the analysis of 

internal events during at-power operations, the basic processes for the risk analysis of 

initiating events and degraded conditions can be applied to external events, as well as 

events occurring during low-power and shutdown operations. A future revision of the 

handbook will integrate all volumes of the handbook. 

! Volume 2, External Events. Volume 2, “External Events,” provides methods and 

guidance for the risk analysis of initiating events and conditions associated with external 

events. External events include internal flooding, internal fire, seismic, external flooding, 

 1

 In this handbook, Ainitiating event@ and Adegraded condition@ are used to distinguish an incident involving a 

reactor trip demand from a loss of functionality during which no trip demand occurred. The terms “operational 

event” and Aevent,@ when used, refer to either an initiating event or a degraded condition. 
 1 Introduction 

 1-3 Handbook Vol. 2 – External Events 

external fire, high winds, tornado, hurricane, and others. This volume is intended to 

complement Volume 1 for Internal Events. 

Specifically, this volume provides the following guidance: 

- Internal Flood Modeling and Risk Quantification 

- Internal Fire Modeling and Risk Quantification 

- Seismic Event Modeling and Seismic Risk Quantification 

- Other External Events Modeling and Risk Quantification 

Volumes 1 and 2 update the staff guidance that was provided for trial use in 2005 and 

2006, respectively. 

! Volume 3, SPAR Model Reviews. Volume 3, “SPAR Model Reviews,” provides analysts 

and SPAR model developers with additional guidance to ensure that the SPAR models used 

in the risk analysis of operational events represent the as-built, as-operated plant to the 

extent needed to support the analyses. This volume provides checklists that can be 

used following modifications to SPAR models that are used to perform risk analysis of 

operational events. These checklists were based on the PRA Review Manual 

(NUREG/CR-3485, Ref. 1-1), the ASME PRA Standard (ASME RA-S-2005, Ref. 1-2), 

Regulatory Guide 1.200 (Ref. 1-3), and experiences and lessons learned from the SDP 

and ASP analyses. 

In addition, this volume summarizes key assumptions in a SPAR model and unresolved 

technical issues that may produce large uncertainties in the analysis results. The 

importance of these assumptions or issues depends on the sequences and cut sets that 

were impacted by the operational event. Additionally, plant-specific assumptions and 

issues may play an even larger role in the analysis uncertainties. 

1.5 Companion References to the Handbook 

Guidance in the three volumes of the handbook often refers to other references, as applicable to 

the application. A bibliography of current technical references used in the risk analysis of 

operational events is provided in Volume 3, in which most of the documents are referenced in 

individual sections throughout the handbook. 

Key companion references that are an extension to this handbook include: 

- NUREG/CR-6268, Rev. 1, “Common-Cause Failure Database and Analysis 

System: Event Data Collection, Classification, and Coding” (Ref. 1-4) 

- NUREG/CR-6850, “EPRI/NRC-RES Fire PRA Methodology for Nuclear Power 

Facilities, Volume 2: Detailed Methodology” (Ref. 1-5) 

- NUREG/CR-6883, “SPAR-H Human Reliability Analysis Method” (Ref. 1-6) 

- Handbook for Phase 3 Fire Protection (FP) Significance Determination Process 

(SDP) Analysis (Ref. 1-7) 

- Basic SAPHIRE training manual (Ref. 1-8) 

- Advanced SAPHIRE training manual (Ref. 1-9) 

- Plant-specific SPAR model manual 
1 Introduction 

Risk Assessment of Operational Events 1-4 

1.6 Future Updates to the Handbook 

It is intended that this handbook will be updated on a periodic and as-needed basis, based on 

user comments and insights gained from “field application” of the document. New topics will 

also be added as needed, and the handbook can also be re-configured and/or reformatted 

based on user suggestions. 

! Revision 2 plans. Current plans for Revision 2 of the handbook will include the 

following additional method guides and tutorials: 

Methods 

- Common-Cause Failure Determination and Modeling

- SPAR-H Human Reliability Analysis Method 

- Parameter Estimation and Update Methods

- Convolution of Failure to Run Parameters Method 

- Uncertainty Analysis Method 

- Simplified Expert Elicitation Method 

 Tutorials and examples 

- Internal Events Modeling of Conditions and Initiating Events – Examples

- Quick Reference Manual – SPAR Models 

- Tutorial - Common-Cause Failure Modeling 

- Tutorial - NRC's Risk Databases and Calculators 

! Future volumes. Two additional volumes are planned in the near future: 

- Risk Analysis of Low-Power and Shutdown Events 

- Risk Analysis of Events Involving Containment-Related Events (LERF) 

1.7 Questions, Comments, and Suggestions 

Questions, comments, and suggestions should be directed to the following: 

Internal NRC staff and NRC contractors: 

! Volume 1, Internal Events – Don Marksberry, 301-415-6378, dgm2@nrc.gov 

! Volume 2, External Events – Selim Sancaktar, 301-415-8184, sxs9@nrc.gov 

! Volume 3, SPAR Model Reviews – Peter Appignani, 301-415-6857, pla@nrc.gov 

External NRC (e.g., public, licensees): 

! All handbook volumes; Significant Determination Process – Paul Bonnett, 301-415-4107, 

fpb@nrc.gov 
 1 Introduction 

 1-5 Handbook Vol. 2 – External Events 

1.8 References 

1-1. U.S. Nuclear Regulatory Commission, “PRA Review Manual,” NUREG/CR-3485, 

September 1985. 

1-2. American Society of Mechanical Engineers, “Standard for Probabilistic Risk Assessment 

for Nuclear Power Plant Applications,” ASME RA-S-2005, 2005. 

1-3. U.S. Nuclear Regulatory Commission, Regulatory Guide 1.200, “An Approach for 

Determining the Technical Adequacy of Probabilistic Risk Assessment Results for RiskInformed Activities,” Revision 1, January 2007. http://www.nrc.gov/reading-rm/doccollections/reg-guides/power-reactors/active/01-200/01-200r1.pdf 

1-4. U.S. Nuclear Regulatory Commission, “Common-Cause Failure Database and Analysis 

System: Event Data Collection, Classification, and Coding,” NUREG/CR-6268, Rev. 1, 

September 2007. http://www.nrc.gov/reading-rm/doc-collections/nuregs/contract/cr6268/ 

1-5. U.S. Nuclear Regulatory Commission, “EPRI/NRC-RES Fire PRA Methodology for 

Nuclear Power Facilities, Volume 2: Detailed Methodology,” NUREG/CR-6850, 

September 2005. http://www.nrc.gov/reading-rm/doc-collections/nuregs/contract/cr6850/ 

1-6. U.S. Nuclear Regulatory Commission, “The SPAR-H Human Reliability Analysis 

Method,” NUREG/CR-6883, August 2005. 

1-7. U.S. Nuclear Regulatory Commission, “Handbook for Phase 3 Fire Protection (FP) 

Significance Determination Process (SDP) Analysis,” December 2005. (ADAMS 

Accession Number ML053620267) 

1-8. Idaho National Laboratory, “SAPHIRE Basics - An Introduction to Probabilistic Risk 

Assessment via the Systems Analysis Program for Hands-On Integrated Reliability 

Evaluations (SAPHIRE) Software,” January 2005 or current revision. 

1-9. Idaho National Laboratory, “Advanced SAPHIRE - Modeling Methods for Probabilistic 

Risk Assessment via the Systems Analysis Program for Hands-On Integrated Reliability 

Evaluations (SAPHIRE) Software,” March 2005 or current revision. 

 

 2-1 Handbook Vol. 2 – External Events 

External Events: Section 2 

Internal Fire Modeling and Fire Risk Quantification Rev. 1.01 

2.0 Internal Fire Modeling and Fire Risk Quantification 

2.1 Objectives and Scope 

! Objectives. This document provides methods and guidance for risk analysis of initiating 

events and conditions associated with internal plant fire scenarios. In addition, this 

handbook provides guidance for modeling scenarios related potential internal plant fire 

event initiators, and quantifying their sequence frequency estimates using SPAR models 

and SAPHIRE software. This volume of the handbook complements Volume 1 for 

internal events (Ref. 2-1). 

! Scope. This handbook provides guidance for the analysis of the following types of 

operational events: 

" Conditions related to degraded fire protection structures, systems, and 

components (SSC) (e.g., fire suppression system, fire-rated barrier, smoke 

detection system). 

" Conditions related to degraded SSC other than fire protection SSCs in which 

associated baseline accident sequence frequencies are heavily influenced by 

postulated fire scenarios (e.g., risk-important cables running through the room of 

a redundant train). 

" Fire initiators where a reactor trip may or may not have been caused by the fire. 

Note that fire-induced initiating events may be best modeled using an internal events 

SPAR model in which an appropriate internal event initiator is set to TRUE (e.g., loss of 

offsite power, loss of main feedwater). Also, for those conditions related to degraded fire 

protection structures, systems, and components, an analysis using the fire protection 

SDP, as documented in IMC 0609 Appendix F (Ref. 2-5), would aid in the identification 

of fire scenario characteristics and fire effects. 

! Alternative guidance. The following additional guides may be used in SDP Phase 3 

and ASP analyses as an alternative to the guidance presented in this volume of the 

RASP Handbook: 

" NUREG/CR-6850. This volume of the RASP Handbook simplifies the detailed 

guidance provided in NUREG/CR-6850, “EPRI/NRC-RES Fire PRA Methodology 

for Nuclear Power Facilities, Volume 2: Detailed Methodology,” (Ref. 2-2) for 

performing a fire risk analysis. In certain cases, a more detailed analysis as 

provided in NUREG/CR-6850 may be better suited for modeling fire scenarios in 

risk-important areas in the plant. 

" Handbook for Phase 3 Fire Protection SDP Analysis. Guidance provided in 

“Handbook for Phase 3 Fire Protection SDP Analysis” (Ref. 2-3) may be used as 

an alternative to this volume of the RASP Handbook. Reference 2-3 also 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-2 

simplifies the detailed guidance in NUREG/CR-6850. The analysis process in 

Ref. 2-3 essentially follows a back-end approach (i.e., analysis starts with the 

mitigation process and works through the detection process and fire frequency 

estimation).2

 This approach may be better suited when uncertainties associated 

with the fire source and frequencies may be larger than those associated with 

detection and mitigation probabilities. The need to justify a fire frequency in this 

case with its uncertainty may be reduced. 

This handbook attempts to avoid repeating guidance in that reference for the front end 

fire analyses that are used to define fire scenarios. However, for convenience of the 

reader, some of the data from NUREG/CR-6850 (Ref. 2-2) is duplicated in this 

handbook. 

2.2 Fire Scenario Definition and Quantification 

A two-step process is discussed to model fire scenarios and quantify their core damage 

frequencies (CDFs): 

1. Define fire scenarios that could lead to core damage, using applicable cases in 

Appendix 2A; calculate scenario frequencies. Definition of a fire scenario is discussed in 

Section 2.2.1. 

2. Quantify the CDF of sequences resulting from these scenarios using a SPAR model and 

the SAPHIRE software. For this purpose, first the scenario-induced conditional core 

damage probability (CCDP) is calculated. Then this CCDP is multiplied by the scenario 

frequency calculated in Step 1 to obtain a fire sequence CDF. From a single fire ignition 

source or a single fire area fire, multiple scenarios may be derived, leading to multiple 

fire sequences whose CDFs need to be summed. Quantification of sequence CDF is 

discussed in Section 2.2.2. 

2.2.1 Define Fire Scenarios 

For the event (or plant condition) in question, one or more fire scenarios must be defined. 

These scenarios would consider ignition frequency, severity, non-suppression, spurious 

actuation, propagation to other fire areas, etc., but will not include plant safety and non-safety 

system responses to a postulated trip: this aspect of the fire-induced CDF sequence will be 

considered in by calculating the CCDP of the plant response to the fire scenario. 

Note that a single ignition source (or a fire in an area) may produce multiple fire scenarios. 

! Fire scenario cases. Depending upon the issue, the following cases are envisioned 

and are included in the scope: 

- Fires limited to one fire area. 

- Fires that can propagate into a second fire area (due to fire barrier failures). 

- Fires that can cause spurious actuations. 

- Main control room fires. 

- Containment fires. 

 2

 The analysis process taken in this volume of the RASP Handbook follows the front-end approach (i.e., analysis 

starts with fire frequency estimation and works through the detection and mitigation processes). 
 2 Internal Fire Modeling and Fire Risk Quantification 

 2-3 Handbook Vol. 2 – External Events 

Fire scenarios for many of these cases assume specific configurations relative to the 

hazards, fire protection features and systems, and spatial considerations such as room 

size. For example, credit for fire suppression systems at the nominal value imply that 

the system is properly designed and installed for the hazard. Credit for separation to 

protect the redundant train in the case where fixed suppression is failed is highly 

dependent on the fire hazard and room size, which determines whether a hot gas layer 

can develop. Some probabilities assigned in the event trees for fire reflect specific 

configurations, which if changed, could affect the assigned probabilities significantly. As 

a result, the analyst should verify if the configuration which is being analyzed reflects the 

likelihood of failure of the fire protection feature and systems which are identified in the 

event trees for these fires. 

A systematic method to define fire scenarios that fit into one of these cases, using 

simple event tree logic is given in Appendix 2A. Those fire scenarios that can lead to 

core damage are selected and their CDFs are quantified, as discussed in this section. 

! Fire scenario frequency. The initiating event frequency (IEfreq) of a fire scenario can 

be simply defined as 

IEfreq = Ffi * SF * Pns, where 

Ffi= fire ignition frequency 

SF = Severity factor 

Pns = Non-suppression probability. 

Other scenario-specific factors can be introduced to the above equation, as warranted 

(e.g., probability of fire propagation to second train). See the example in Section 2.3.3 

for such an additional factor introduced into the equation. 

! Fire scenario summary table. Examine the event/condition characteristics and refer to 

the applicable appendices of this document accordingly. Select the fire scenarios that 

lead to core damage accident sequences and summarize those sequences in terms of a 

table, such as Table 2-1. The columns of this table are discussed below. Note that, 

each fire ignition event is treated as an initiating event that will be assigned an event 

tree. 

1. Scenario name (initiating event ID). This always starts with FRI- and is used 

both for the event tree and the initiating event names. 

2. Scenario description. 

3. Scenario IEfreq. This is calculated using models discussed in Appendices 2A-1 

through 2A-5. 

4. Equipment lost. Equipment credited in the probabilistic risk assessment (PRA) 

that is lost due to fire are listed in this column. 

5. Initiating event caused. This is the initiating event caused by the fire. In most 

cases, it is one of the internal initiating event categories already defined (e.g., 

loss of main feedwater (LOMFW), reactor trip (TRANS), loss of offsite power 

(LOOP), loss-of-coolant accident (LOCA)). In some cases, such as in main 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-4 

control room (MCR) fire, a new event tree model needs to be developed to model 

the operation of the plant from the remote shutdown panel. In that case, put the 

name of the new event tree in this column (scenarios 3 through 8 refer to such 

new event trees in the example below). 

The guidance in the following table can be used to determine the initiating event 

caused by the fire for select cases. 

Initiating Event Caused by the Fire for Select Cases. 

If Fire Causes Initiating Event Caused 

No spurious opening of reactor coolant system (RCS) valves; 

No main control room evacuation; and 

No LOOP.

Transient

Turbine building fire that damages MFW or condenser system 

equipment

Transient with loss of MFW

Spurious opening of RCS system valve(s) (e.g., poweroperated relief valve (PORV), solenoid relief valve)LOCA (LOCA size depend 

on the number and size of 

valves)

Equipment damage (e.g., bus, transformer) leading to LOOP; 

Self induced LOOP by operators by fire procedures

Loss of Offsite Power

Reactor shutdown from remote shutdown panel after main 

control room evacuation

Make special event tree 

model

6. Human error probabilities (HEPs) and other basic events affected. List the basic 

events and operator actions that are affected by the fire (failed, degraded). This 

is in addition to equipment listed in Column 4. Considerations about operator 

actions are provided in Appendix 2G. 

7. New basic events (failures) introduced. List any new basic events introduced 

(such as scenario initiating event frequencies) to model the scenarios. 

Other columns may be introduced as needed. 
 2 Internal Fire Modeling and Fire Risk 

 2-5 Handbook Vol. 2 – External Events 

Table 2-1 Example Summary of Fire Scenarios 

Name Description IE Frequency Equipment Lost Initiating Event Caused HEPs / Other BEs Affected 

 1 2 3 4 5 6 

1 FRI-FI1 Auxiliary Building MCC 1-62J Room 2.63E-4 

Valve BT 2B Valve MS 100B MCC 62J (all three affecting AFW) 

TRANS None / None 

3 FRI-FI3 

4.16KV SWGR Room 16 buses 1 and 2, beneath cable tray 1AT9N 

9.5E-05 MFW pumps A & B LOMFW None / None 

4 FRI-FI4 Diesel B Oil Fire 8.9E-3 

RAT EDG B BUS 6 

FRI-MCRE-0-07 None / None ** 

5 FRI-FI5 Fire in Relay room 6.78E-7 

BUS 6 TAT Valve BT3A (AFW) 

FRI-DSP *** 

6 FRI-FI6 

Turbine Building AFW Pump A oil fire 

6.45E-4 AFW MDP A BUS 5 FRI-MCR- E-0-07 

8 FRI-FI8 Fire Near buses 51 and 52 4.65E-05 BUS 5 FRI-MCR- E-0-07 None/ None 9 FRI-FI10 Fire in MCR Bus 5 Switches Occurs 2.02E-04 Bus 5 FRI-MCR- E-0-07 None/ None 

10 FRI-FI11 Fire in MCR Bus 6 Switches Occurs 2.20E-04 Bus 6 FRI-MCR- E-0-07 None/ None 12 FRI-FI13 Fire in Pressurizer PORV Switches 1.39E-04 Valve PR-2B and 1B are stuck open SLOCA * 

Notes: 

 * = New FTs: FAB-PR-2B-SO and BLEED-PR-2B-SO  ** = New ET: FRI-MCR-E-0-07  *** = New ET: FRI-DSP  Scenarios 2, 7 and 11 are omitted from this table for presentation purposes. 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-6 

2.2.2 Quantify Sequence CDFs 

The CDF of each sequence can be calculated as a product of the scenario frequency and the 

CCDP given the scenario has occurred: 

CDF = IEfreq * CCDP. 

The scenario IEfreq is already calculated in the earlier step, using Appendices 2A-1 through 2A5. The CCDP can be calculated by using the SAPHIRE code and the SPAR models, which 

already model plant response to many types of trips. For this purpose, either a change set or 

the Graphical Evaluation Module (GEM) software can be used to model the components failed 

due to fire. The scenario may cause multiple SSCs to fail, even redundant trains of a mitigating 

system. 

New event and fault trees may need to be created, if the scenario does not lead to (i.e., transfer 

to) an already existing event tree (typically one for the existing internal events model). Figure 2-

1 shows a new event tree model that is made for the example calculations. 

 

After the CCDPs have been determined, the sequence CDFs can be calculated. Table 2-2 

shows an example set of sequence CDF calculations. The overall CDF estimate is the sum of 

all sequence CDF estimates. 

Once the CDF is known, it can be used to estimate event/condition importance. 

2.3 Examples 

This section discusses examples for illustrative purposes; the values used in the examples are 

for illustration only. 

2.3.1 Example 1 - Event Analysis 

A fire initiating event occurs in plant X. A 4160 VAC bus is damaged (any suppression attempt prior to damage 

would have to be assumed to have been unsuccessful). This is assumed to be the only equipment damaged by the 

fire. The reactor is manually tripped. 

Use the existing Loss of a 4160 VAC bus initiating event model in SPAR, with an initiating event frequency of 1.0 

(GEM or SAPHIRE can be used). Calculate event CCDP as 

CCDP = 4.3E-04. 

This is the fire initiating event importance, conditional to fire severity factor and non-suppression. 

2.3.2 Example 2 - Plant Condition Analysis 

In 480 volt switchgear room E7 (Fire Area DG-8), Division II (Train B) circuits in two conduits were routed closer than 

20 feet from the redundant Division I (Train A) circuits in the designated separation zone without being protected by a 

one-hour fire rated barrier, as required. A fire in this area could damage the unprotected cables to components 

required to achieve and maintain safe shutdown. 
2 Internal Fire Modeling and F

 2-7 Handbook Vo

LOSC-L

RCP SEAL

COOLING

MAINTAINED

PORV-L

PORVs

ARE

CLOSED

AFW-DSP

AUXILIARY

FEEDWATER

EPS-DSP

EMERGENCY

POWER

RPS

REACTOR

SHUTDOWN

FRI-DSP

SHUTDOWN

FROM

DEDICATED

SHUTDOWN

#  1  2T  3  4  5  6 

 FRI-DSP - Shutdown Plant from the Dedicated Shutdown panel 

Figure 2-1 An Example New Event Tree Model 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-8 

Table 2-2 An Example Calculation of Sequence CDFs 

Event Description 

Initiating 

Event 

Frequency 

Type of Trip CCDP 

1 FRI-FI1 Auxiliary Building MCC 1-62J Room 2.63E-04 TRANS 5.96E-07 2 FRI-FI2 MCC 62A Scenario 1.34E-03 TRANS 2.84E-03 3 FRI-FI3 4.16KV SWGR Room 16 buses 1 and 2, beneath cable tray 1AT9N 9.50E-05 LOMFW 1.21E-05 4 FRI-FI4 Diesel B Oil Fire 8.90E-03 FRI-MCR-E-0-07 2.28E-03 5 FRI-FI5 Fire in Relay room 6.78E-07 FRI-DSP 1.86E-01 6 FRI-FI6 Turbine Building AFW Pump A oil fire 6.45E-04 FRI-MCR-E-0-07 8.68E-02 7 FRI-FI7 AFW Pump B Oil Fire 6.20E-05 FRI-DSP 1.86E-01 8 FRI-FI8 Fire Near buses 51 and 52 4.65E-05 FRI-MCR-E-0-07 8.67E-02 9 FRI-FI1 Fire in MCR Bus 5 Switches Occurs 2.02E-04 FRI-MCR-E-0-07 8.44E-02 

10 FRI-FI11 Fire in MCR Bus 6 Switches Occurs 2.20E-04 FRI-MCR-E-0-07 4.55E-02 11 FRI-FI12 Fire in SG PORV Switches 1.76E-05 LOMFW 1.21E-05 12 FRI-FI13 Fire in Pressurizer PORV Switches 1.39E-04 SLOCA 3.03E-04 

 SUM = 1.19E-02 
 2 Internal Fire Modeling and Fire Risk Quantification 

 2-9 Handbook Vol. 2 – External Events 

Define base and condition case fire scenarios as in Figures 2-2 and 2-3 (note that Ffi = 3.25E-3/yr and SF =1). 

Use SAPHIRE and SPAR to calculate the CCDPs for plant trips with loss of either one or two 4160 buses as 4E-04 

and 0.05, respectively. 

The following probabilities are introduced in Figures 2-2 and 2-3 to calculate fire scenario frequencies: 

DET: Detection. 0.05 failure probability (NUREG/CR-6850, Ref. 2-2) 

SUP: Suppression. 0.05 failure probability (NUREG/CR-6850, Ref. 2-2) 

If the event tree nodes DET and SUP are successful, only the affected component is assumed damaged (and the 

CCDP = 4.0E-4 applies). However, if either DET or SUP is unsuccessful, fire propagation from one division to the 

other is credible and is so modeled (i.e., the CCDP = 0.05 potentially applies), depending upon the conditional 

probability as calculated. 

2ndTR: Fire engulfs second train (conditional upon unsuccessful detection or suppression). Effectively zero for the 

base case (0.00001 is assigned for this assumed configuration. Note that the potential for fire damage with no fixed 

suppression system may be high for rooms where the fire can produce a hot gas layer. For this particular example, 

assuming that separation alone protects this redundant train is conservative, since a low CDF for the base case 

increases the delta CDF due to the presence of transients in the exclusion zone). 

For the condition, 0.01 is assigned, corresponding to 87 hours/year of presence of transient combustibles in the fire 

area and probability of 1.0 of fire propagating to the opposing division if the fire occurs while the transient 

combustibles are present. Without the presence of transient combustibles, the fire in one train affecting the second 

train is assumed to be not credible. 

CCDP: Conditional core damage probability, given a fire scenario occurs. 

For the base case fire scenario, with one 480V bus assumed unavailable, the CCDP is 4E-04 (GEM output). 

For the condition with both 480V buses unavailable, CCDP is calculated to be 4.8E-2 (GEM output). 0.05 is used for 

calculations. 

Base case CDF is calculated as shown in Figure 2-2 as 1.3E-06/yr, as a sum of five fire sequences defined by the 

same figure. 

The condition CDF is calculated as shown in Figure 2-3 as 1.46E-06/yr. 

The condition importance, defined as the difference between CDFs for the plant condition case and the base case, is 

calculated for a one-year exposure time as 

Condition Importance = (1.46E-06 - 1.3E-06) * 1yr = 1.6E-07.

2.3.3 Example 3 - Plant Condition Analysis (Shortcut) 

The example in Section 2.3.2 can also be treated in a shortcut manner as follows: 

The scenario of concern is the failure of both trains due to fire engulfing the second train. The probability of fire 

propagating to second train is 0.01 (P2ndtr). The scenario frequency is: 

IEfreq = Ffi * SF * Pns * P2ndTR 

With SF = 1 and Pns = 0.1 (approximate Boolean sum for failure of detection or suppression), the scenario frequency 

is 

IEfreq = 3.25E-03 * 1 * 0.1 * 0.01 = 3.25E-06 /yr. 

CCDP with loss of two trains is 0.05. Thus the scenario CDF is 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-10 

CDF = IEfreq * CCDP = 3.25E-06 * 0.05 

CDF = 1.6E-07/yr 

This result matches that of the example in Section 2.3.2. 
2 Internal Fire Modeling and F

 2-11 Handbook Vo

Fire Occurs 

in FA DG-08 Detection Suppression Fire Engulfs 2nd Train 

IE-FIRE-DG-08 DET SUP 2ndTR 

CCDP Sequence End State 

 1 OK  0.95 2 CD 1 4.0E-04  0.95 3 OK  0.99999 4 CD 6 4.0E-04  0.05 5 OK 

3.25E-03 0.00001 6 CD 7

 0.05  7 OK  0.99999 8 CD 6 4.0E-04  0.05 9 OK  0.00001 10 CD 8 0.05 

Total = 1

Figure 2-2 Fire in DG-08 Base Case (Example 2) 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-12 

Fire Occurs in 

FA DG-08 Detection Suppression Fire Engulfs 2nd Train 

IE-FIRE-DG-08 DET SUP 2ndTR 

CCDP Sequence End State 

 1 OK  0.95 2 CD 1 4.0E-04  0.95 3 OK  0.99 4 CD 6 4.0E-04  0.05 5 OK 

3.25E-03 0.01 6 CD 7

 0.05  7 OK  0.99 8 CD 6 4.0E-04  0.05 9 OK  0.01 10 CD 8 0.05 

Total = 1

Figure 2-3 Fire in DG-08 with Plant Condition in Effect (Example 2) 
 2 Internal Fire Modeling and Fire Risk Quantification 

 2-13 Handbook Vol. 2 – External Events 

2.3.4 Example 4 – Main Control Room (MCR) Fire 

In the absence of more detailed MCR fire modeling, the following model with three scenarios can be used for MCR 

fire CDF estimation, with adjustment of the number of electrical cabinets for a specific plant. 

The three MCR scenarios are: 

FRI-MCR-NS = Fire in non-safety cabinets in MCR. Loss of all non-safety systems and a transient event is 

assumed. 

FRI-MCR-S = Fire in safety cabinets in MCR. Loss of all trains of one of two safety-related equipment and transient 

is assumed. 

FRI-MCR-EVAC = MCR evacuation with shutdown from remote shutdown panel. 

For a MCR fire, with 103 electrical cabinets (each with a fire ignition frequency of 9.45E-5/yr/cabinet) in the MCR, the 

following limiting fire scenarios are modeled for a plant: 

Scenario Ignition Frequency Ignition Frequency Reactor Trip 

Fire in non-safety 

electrical cabinets 73* 9.45E-05 [1] 6.9E-03 Transient without non-safety systems 

Fire in safety-related 

electrical cabinets 30* 9.45E-05 [1] 2.83E-03 Transient without one safety 

train 

MCR evacuation [2] [2] Shutdown from remote 

shutdown panel 

 Notes: 

 [1] 73 non-safety- related and 30 safety-related cabinets. 

 [2] MCR evacuation analysis is complex. A specialist should be consulted for guidance. 

An illustrative set of ignition frequencies, CCDPs, and CDFs for these scenarios is given below: 

Scenario Ignition Frequency CCDP CDF 

FRI-MCR-NS 6.90E-03 1.77E-07 1.22E-09 

FRI-MCR-S 2.83E-03 2.06E-03 5.82E-06 

FRI-MCR-EVAC [See Note] [See Note] [See Note] 

Note: FRI-MCR-EVAC sequence may have a significant contribution to the total CDF. A specialist should be 

consulted for guidance to perform an MCR evacuation analysis. 

2.3.5 Other Examples and References 

Other examples can be found in NUREG/CR-6850 (Ref. 2-2) and the Handbook for Phase 3 

Fire Detection SDP (Ref. 2-3). Ref. 2-3 also contains information about methods that can be 

used to perform Phase 3 SDP analysis of a sample of fire protection issues. Ref. 2-3 is a 

specific application of those methods detailed in NUREG/CR-6850. 

2.4 References 

2-1. U.S. Nuclear Regulatory Commission, “Risk Assessment of Operational Events 

Handbook: Volume 1 - Internal Events,” Revision 1, September 2007. 

2-2. U.S. Nuclear Regulatory Commission, “EPRI/NRC-RES Fire PRA Methodology for 

Nuclear Power Facilities, Volume 2: Detailed Methodology,” NUREG/CR-6850, 

September 2005. http://www.nrc.gov/reading-rm/doc-collections/nuregs/contract/cr6850/ 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-14 

2-3. U.S. Nuclear Regulatory Commission, “Handbook for Phase 3 Fire Protection (FP) 

Significance Determination Process (SDP) Analysis,” December 2005. (ADAMS 

Accession Number ML053620267) 

2-4. U.S. Nuclear Regulatory Commission, “Fire Events – Update of U.S. Operating 

Experience, 1986-1999,” RES/OERAB/S01-01, December 2001. 

http://nrcoe.inel.gov/results/index.cfm?fuseaction=Fire.showMenu 

2-5 U.S. Nuclear Regulatory Commission, “Fire Protection Significance Determination 

Process,” Inspection Manual Chapter 0609, Appendix F, February 28, 2005 or current 

revision. http://www.nrc.gov/reading-rm/doc-collections/insp-manual/manualchapter/index.html 
 2 Internal Fire Modeling and Fire Risk Quantification 

 2-15 Handbook Vol. 2 – External Events 

Appendix 2A. Fire Scenarios/Accident Sequences 

Fire scenarios may be defined either with respect to a location in the plant, or with respect to 

specific ignition sources in an area. Location-based scenario definition is easier to model and 

requires less detailed layout information, but would be more conservative. Ignition-sourcebased scenario definition would allow more realistic modeling but would require more 

information, resources, and expertise. The first method is favored in this handbook for first-cut 

modeling for an event analysis. The second method may require the assistance of a fire PRA 

analyst. 

2A-1 Fire Sequences for a Single Fire Area – No propagation to another area (boundary 

intact) 

When a fire ignition in a given fire area (or compartment) is postulated, at least the following 

need to be considered to define fire scenarios and calculate scenario frequencies: 

- Fire ignition frequency 

- Fire severity level 

- Fire detection 

- Fire suppression 

Other special considerations, such as spurious actuations due to hot shorts and operator 

actions introduced by the scenario, can be added, as needed. These considerations are 

discussed in the next Appendices. 

The above considerations can be quantitatively factored into the scenario logic to define one or 

more potential core damage sequences. An event tree model can be used to formally define 

sequences based on various developments following a fire. Figure 2A-1-1 depicts such an 

event tree, where potential core damage sequences SC-1 and SC-2 are defined. Such an 

event tree can be simply made by hand, using MS EXCEL, or using SAPHIRE software. Also 

see the example in Section 2.3.3 where a shortcut is used in lieu of developing an event tree. 

! Summary of fire scenarios. To each core damage sequence, attributes can be 

assigned such as 

- Fire ignition frequency 

- Damaged equipment 

- Type of plant trip (initiating event) caused by the scenario 

- Effect of scenario on existing operator actions, success criteria, etc. 

- New operator actions introduced by the scenario, etc. 

Each sequence frequency should be calculated and a summary should be generated, as 

shown in Table 2-1. This information is then used to calculate the CCDP by using the 

SPAR model and the SAPHIRE software. 

Appendices 2B through 2E provide some data for the various event tree nodes that can 

be considered in fire sequence definition. These appendices are 

- 2B – Generic Fire Ignition Frequencies 

- 2C – Severity Factors Data 

- 2D – Detection Failure Data 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-16 

- 2E – Suppression Failure Data 

- 2F – Spurious Actuations (due to hot shorts) Probabilities 

- 2G – Operator Actions 

- 2H – Smoke Damage 

! Fire ignition frequency. For fire ignition frequency, two methods are available and may 

be used: component-based ignition frequencies or plant area-based ignition frequencies. 

Details are provided in Appendix 2B. 

! Damaged equipment. In defining the effect of the fire on the equipment in the area, as 

a first approximation, all PRA relevant equipment in the area may be assumed damaged 

by the fire. If the sequence CDF becomes unduly conservative, further fire 

growth/development modeling, PRA analysis, and walkdowns to credit the actual layout 

and combustible materials may be needed. 

2A-2 Multiple Fire Areas – Propagation to adjacent area possible (boundary 

compromised) 

In some fire scenarios, the fire area X boundary may be compromised and the possibility of a 

fire initiating in X propagating into an adjacent area Y (also a fire originating in Y propagating 

into X) may arise. Such fire scenarios can be modeled in various ways; one way based on 

expanding the formal logic of Figure 2A-1-1 is shown in Figure 2A-2-1. The reverse propagation 

from Y into X must also be modeled in a similar manner. 

! Example 1. From the example depicted in Figure 2A-2-1, the top events in the event 

tree and branch point probabilities may be defined as follows: 

A. Fire Occurs in Fire Area X. This is the fire ignition frequency from Appendix 2B. 

B. Severity Level. From Appendix 2C, a value of 1 was chosen for this example. 

C. Fire Detected in Fire Area X. The automatic fire detection system in this example 

meets all applicable codes, and are designed and installed for the hazard – thus 

they are effective. From Appendix 2D, the unavailability of an automatic 

detection system in this example is 0.05. 

D. Fire Suppressed in Fire Area X. The sprinkler suppression system in this 

example meets all applicable codes, and are designed and installed for the 

hazard – thus they are effective. From Appendix 2E, the unavailability of the 

sprinkler system in this example is 0.05. 

E. Fire Propagates into Fire Area Y. For this example, the combustible loading is 

high for fire area X, and is capable of failing the fire barrier between fire areas X 

and Y. This particular 3-hour fire rated barrier is degraded. 

For the sequences where automatic detection system fails randomly (0.05) in the 

area of fire origin, the fire brigade response in the example is delayed and the 

barrier to the adjoining area fails, despite the fact that the brigade performs 

remedial efforts to prevent barrier failure after arrival. For this particular barrier 

and set of combustibles, failure of the fire brigade to suppress the fire prior to the 

barrier failure is assumed to be 0.5 (for illustrative purposes). 
 2 Internal Fire Modeling and Fire Risk Quantification 

 2-17 Handbook Vol. 2 – External Events 

Success of manual suppression is likely to be greater for the case where 

detection is not delayed in Fire Area X ; however, for illustrative purposes the 

same failure probability (0.5) is assumed. 

Guidance for estimating the failure probability of manual suppression based on 

available time is provided in Appendix 2E. 

F. Fire Detected in Fire Area Y. For sequences where the fire propagates into Fire 

Area Y due to failure to manually suppress the fire before fire barrier breach, two 

branch point paths are provided for this top event. The first branch point (F1) 

assumes higher success of detection from the combination of automatic and 

manual detection. Due to plant practice to check neighboring areas upon such a 

fire, it is very likely that the spread of this fire into the adjoining area will be 

detected. In this example, manual detection is assumed to be likely due to early 

detection of the fire in Fire Area X (i.e., successful detection). The failure 

probability (0.05 x 0.1 = 0.005 ~ 0.01) is the product of random unavailability of 

the automatic fire detection system for Fire Area Y (0.05) and failure to manually 

detect the fire (assumed to be a probability of 0.1 in this example). 

The second branch point (F2) conservatively assumes no credit for manual fire 

detection given failure of the automatic fire detection in Fire Area X. 

Guidance for estimating the failure probability of manual detection based on 

available time is provided in Appendix 2D. 

G. Fire Suppressed in Fire Area Y. For the sequences where detection in Fire Area 

Y succeeds, two branch point paths are provided for this top event. The first 

branch point (G1) assumes higher success of suppression due to the 

combination of the fixed suppression system and manual suppression. 

Further, the overall top event assumes that the successful actuation of the 

detection and fixed sprinkler systems, with or without manual suppression, is 

likely to be adequate to control the fire after it has breached the barrier and prior 

to damage of the redundant train in Fire Area Y. This assumption implies that 

the equipment in Fire Area Y is adequately separated from the failed barrier. In 

this example, the fixed sprinkler system and/or manual suppression in Fire Area 

Y was determined to be effective in preventing fire to the redundant train since 

some separation exists between the failed barrier and raceway containing that 

train. This assumption may not be applicable for cases where cables related to 

trains contained in raceways border the fire barrier, even in the presence of a 

sprinkler system up to code. A fire protection specialist should be consulted to 

determine the effectiveness of a fire suppression system with degraded fire 

barriers. 

The second branch point (G2) assumes no credit for manual suppression given 

failure of the automatic fire detection in Fire Area X. 

Guidance for estimating the failure probability of manual suppression based on 

available time is provided in Appendix 2E. As indicated earlier, the analyst is 

responsible for determining that probabilities associated with the scenarios are 

appropriate for the analysis. 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-18 

! Example 2. Figure 2-2 can be interpreted as another instance of fire propagation from 

one fire compartment to another if the two redundant trains are in separate fire 

compartments (not necessarily reflected in the original development of this scenariosequence). In such a case, the distance between the two fire compartments (where a 

physical boundary other than distance is not present between the compartments) is 

observed to be shorter than the design condition of 20 ft with no intervening 

combustibles, allowing potential fire propagation from train A to train B electrical buses 

of a redundant safety system. 

Generic fire barrier failure probabilities by barrier type from NUREG/CR-6850 (Ref. 2-2, 

Table 11-3) are given in Table 2A-2-1. Note that these probabilities do not represent the 

failure of a barrier given a challenge by a particular fire hazard. 

Table 2A-2-1 Random Barrier Failure Probabilities from NUREG/CR-6850 

Barrier Type Barrier Failure Probability/Demand 

Fire, security, and water tight doors 7.4E-03 

Fire and ventilation dampers 2.7E-03 

Penetration seals, fire walls 1.2E-03 

2A-3 Spurious Actuation (hot-shorts) 

Spurious actuation of components due to hot shorts due to fire in or between cable trays and 

conduits is a concern that is given attention in fire PRAs. An accurate treatment of such 

concerns in a given scenario requires intimate knowledge of the cable types, specific cable 

tray/conduit layouts, their relative locations to ignition sources, and the relative locations of 

multiple trays. Appendix 2F provides spurious actuation probabilities for various characteristics 

of cables. 

In general, estimation of spurious actuation probabilities must be left to fire PRA experts and 

should include detailed fire modeling and walkdowns. In some cases, bounding or simple 

estimates may be useful to assess the risk. An actual example of scenario definitions which 

included potential spurious actuation concerns for three types of failures is shown in 

Figure 2A-3-1. The specific concerns were: 

- Spurious opening of pressurizer power-operated relief valves (PORVs) causes small 

LOCA, 

- Spurious opening of one or more valves transfers inventory from the refueling water 

storage tank (RWST) to sump, 

- Spurious closure of intake valves can fail charging/safety injection pumps, and 

component cooling water leading to potential reactor coolant pump seal failure (small 

LOCA). 

These concerns were modeled by a bounding analysis; by assigning 0.30 probability of failure to 

a specific set of hot-short failures (see Appendix 2F). If two such set of failures occurred, then 

the third set is assigned a probability of 1.0 for hot-shorts. A detailed modeling would reduce 

these probabilities and also take into account the various fire ignition sources that would only 

challenge certain cable trays. 
 2 Internal Fire Modeling and Fire Risk Quantification 

 2-19 Handbook Vol. 2 – External Events 

2A-4 Main Control Room Fires 

Fires that require evacuation of the MCR need to be modeled using a custom made event tree 

capturing the plant-specific procedures and equipment available for this case. Figure 2-1 shows 

such a custom-made event tree for plant shutdown from the dedicated shutdown panel (remote 

shutdown panel). The equipment that are available on this panel for shutdown are usually more 

limited than those available in the MCR. This needs to be reflected in the fault tree models 

supporting this event tree. Crediting of local recovery actions by operators (such as local valve 

manipulation) must be done judiciously to avoid non-conservative modeling. 

In these scenarios, the CCDP, given fire occurs, tends to be dominated by human error, rather 

than equipment failure. 

See Example 2.3.4 for a limiting set of MCR fire scenarios that capture the essence of MCR fire 

scenario concerns. 

2A-5 Containment Fires 

Containment fire scenarios have been generally considered as low contributors to plant risk due 

to their low frequencies. However, if such a scenario needs to be modeled to study a specific 

plant condition or event, modeling may pose at least two difficulties: 

- Assigning the proper ignition frequency to the model; 

- Since containment generally does not have formally defined fire areas and can be 

loosely viewed as a single fire area, it may be difficult to limit the fire scenario to a 

compartment of the containment. Establishing a basis for limiting the fire targets to a 

compartment of the containment may require detailed fire analysis and knowledge of 

layout details. 

If the event/condition involves one of the following two issues, containment fire modeling may be 

further pursued with a qualitative or a quantitative assessment; otherwise it may be screened 

out: 

- There are more combustible materials allowed by the design in a part of the 

containment; 

- Ignition sources are present in a close proximity of a cable or equipment configuration 

that can render inoperable multiple redundant safety-related trains of equipment. 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-20 

Fire Occurs 

in Fire Area 

X 

Severity 

Level 

Fire 

Detected

Fire 

Suppressed

Scenario Scenario 

Name 

Scenario 

Frequency 

IE-FRI-X 

 1 OK 

 

 2 OK 

 0.95 

1.00E-03 0.95 3 FI-X-1 4.8E-05 

 0.05 

1 4 FI-X-2 5.0E-05 

 0.05 

Figure 2A-1-1 Example Event Tree Model Showing Fire Scenario Definitions 

Note: 

In scenario #2, the fire, although detected and suppressed, may still manage to have damaged some equipment 

which contributes to core damage prior to being suppressed. In that case, this scenario can also be added to the 

list of fire scenarios for which CDF is to be quantified. 
2 Internal Fire Modeling and F

 2-21 Handbook Vo

Fire Occurs 

in Fire Area 

X 

Severity 

Level 

Fire 

Detected 

in X 

Fire 

Suppressed 

in X 

Fire 

Propagates 

into Y 

Fire 

Detected in 

Y 

Fire 

Suppressed 

in Y 

A B C D E F G 

Sequence E

S

1 

 2 

IE-FRI-X 

1.00E-03 3 S

 0.95 0.9  0.05 4 S

1 0.99 

 0.99 G1 5 S

F1 0.01 

 0.1 6 S

 0.01 

7 S

 0.5  8 S 0.05 0.95  0.95 G2 9 S

F2 0.05 

 0.5 10 S 0.05 

Figure 2A-2-1 An Example Event Tree Model with Possible Propagation 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-22 

Fire 

Occurs in 

1-A-BALB 

Past 

Incipient 

Stage 

Early 

Suppression 

PORV 

LOCA 

due to 

SA 

CSIP 

Failure due 

to SA 

RCP Seal 

LOCA 

RWST Leak 

due to SA 

Scena

rio 

Initiating 

Event 

Addition

Equipment D

Due to S

 1 OK  Yes 2 TRANS NO SA  0.95 

2.60E-03 NO FAILURE 3 TRANS NO SA 

 NO FAILURE 0.7  0.7 FAILURE 4 TRANS RWST Leak  Yes 0.3  1 NO LOCA NO FAILURE 5 TRANS CSIP A  0.7 NO LOCA 0.7  0.937 FAILURE 6 TRANS RWST Leak, C FAILURE 0.3  0.3 NO FAILURE 7 SLOCA CSIP A  LOCA 0  No 0.063 FAILURE 8 SLOCA RWST Leak, C 0.05 1  NO FAILURE 9 SLOCA  NO FAILURE 0.7  0.7 FAILURE 10 SLOCA RWST Leak  LOCA 0.3  0.3 NO FAILURE 11 SLOCA CSIP A  FAILURE 0  0.3 FAILURE 12 SLOCA RWST Leak, C 1 SA = Spurious actuation due to hot shorts Sum = 

Figure 2A-3-1 An Example Event Tree Model with Possible Spurious Actuations Due to Hot 
 2 Internal Fire Modeling and Fire Risk Quantification 

 2-23 Handbook Vol. 2 – External Events 

Appendix 2B. Generic Fire Ignition Frequencies 

For fire ignition frequency, two methods are available: component-based ignition frequencies or 

plant area-based ignition frequencies. 

! Component-based ignition frequencies. Assemble a fire ignition frequency from 

plant-wide components in the fire area, based on the information presented in 

NUREG/CR-6850 (Ref. 2-2), Table 6-1 or Table C-3. However, this can be done only if 

the number of components in the plant for the plant-wide components are already known 

or can be reliably estimated; otherwise, a determination of this data may be resource 

intensive. 

A reduced version of this table is given as Table 2B-1. 

! Plant area-based ignition frequencies. Use generic fire area frequencies as provided 

in Table 2B-2. This method is useful for screening purposes, and if area fire ignition 

source details are not readily available. The fire area frequencies in Table 2B-2 are 

based on the information presented in the NRC study: “Fire Events – Update of U.S. 

Operating Experience, 1986-1999,” (Ref. 2-4). 

Component-based frequencies should be used in the evaluation of fire protection structures, 

systems, and components (e.g., fire suppression system, fire-related barrier, smoke detection 

system). For these issues, which affect the risk from fire primarily, key insights from fire 

scenarios based upon components are important to understand and communicate the risk 

significance.
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-24 

Table 2B-1 Fire Frequency Bins and Generic Frequencies 

from NUREG/CR-6850, Table 6-1 (Ref. 2-2) 

ID Location Ignition Source (Equipment Type) Mode 

Generic 

Frequency 

(per reactor-yr) 

I Battery Room Batteries All 7.50E-04 

2 Containment (PWR) Reactor Coolant Pump Power 6.10E-03 

3 Containment (PWR) Transient Combustibles and Hotwork Power 2.00E-03 

4 Control Room Main Control Board All 2.50E-03 

5 Control/Aux/Reactor Building Cable fires caused by welding and cutting Power 1.60E-03 

6 Control/Aux/Reactor Building Transient fires caused by welding and 

cutting Power 9.70E-03 

7 Control/Aux/Reactor Building Transient Combustibles Power 3.90E-03 

8 Diesel Generator Room Diesel Generators All 2.10E-02 

9 Plant-Wide Components Air Compressors All 2.40E-03 

10 Plant-Wide Components Battery Chargers All 1.80E-03 

11 Plant-Wide Components Cable fires caused by welding and cutting Power 2.00E-03 

12 Plant-Wide Components Cable Run (Self-ignited cable fires) All 4.40E-03 

13 Plant-Wide Components Dryers All 2.60E-03 

14 Plant-Wide Components Electric Motors All 4.60E-03 

15 Plant-Wide Components Electrical Cabinets All 4.50E-02 

16 Plant-Wide Components High Energy Arcing Faults All 1.50E-03 

17 Plant-Wide Components Hydrogen Tanks All 1.70E-03 

18 Plant-Wide Components Junction Boxes All 1.90E-03 

19 Plant-Wide Components Misc. Hydrogen Fires All 2.50E-03 

20 Plant-Wide Components Off-gas/H2 Recombiner (BWR) Power 4.40E-02 

21 Plant-Wide Components Pumps All 2.10E-02 

22 Plant-Wide Components RPS MG Sets Power 1.60E-03 

23a Plant-Wide Components Transformers (Oil filled) All 9.90E-03 

23b Plant-Wide Components Transformers (Dry) All 9.90E-03 

24 Plant-Wide Components Transient fires caused by welding and 

cutting Power 4.90E-03 

25 Plant-Wide Components Transient Combustibles Power 9.90E-03 

26 Plant-Wide Components Ventilation Subsystems All 7.40E-03 

27 Transformer Yard Transformer -Catastrophic 2 Power 6.00E-03 

28 Transformer Yard Transformer -Non Catastrophic Power 1.20E-02 

29 Transformer Yard Yard transformers (Others) Power 2.20E-03 

30 Turbine Building Boiler All 1.10E-03 

31 Turbine Building Cable fires caused by welding and cutting Power 1.60E-03 

32 Turbine Building Main Feedwater Pumps Power 1.30E-02 

33 Turbine Building Turbine Generator Excitor Power 3.90E-03 

34 Turbine Building Turbine Generator Hydrogen Power 6.50E-03 

35 Turbine Building Turbine Generator Oil Power 9.50E-03 

36 Turbine Building Transient fires caused by welding and 

cutting Power 8.20E-03 

37 Turbine Building Transient Combustibles Power 8.50E-03 

Notes (Refer to NUREG/CR-6850): 

1. See Appendix M for a description of high-energy arcing fault (HEAF) fires. 

2. See Section 6.5.6 . 

3. The event should be considered either as an electrical or oil fire, whichever yields the worst consequences.
 2 Internal Fire Modeling and Fire Risk Quantification 

 2-25 Handbook Vol. 2 – External Events 

Table 2B-2 Fire Ignition Frequencies for Power Operation 

by Plant Location from NRC Fire Study 1986-1999 (Ref. 2-4) 

Plant Location 

No. of 

Fires 

(Note 3) 

No. of 

Reactor 

Critical 

Years 

Ignition Frequency 

(Mean) 

Auxiliary Building (PWR) 10.07 398.0 2.7E-02 

Battery Room 0 596.5 8.4E-04 

Cable Spreading Room 0 596.5 8.4E-04 

Containment 1.26 596.5 3.0E-03 

Control Room 3.78 596.5 7.2E-03 

Diesel Generator Building 7.56 596.5 1.4E-02 

Reactor Building (BWR) 5.04 198.5 2.8E-02 

Service Water Pump-house 3.78 596.5 7.2E-03 

Switchgear Room 2.52 596.5 5.1E-03 

Switch Yard 10.07 596.5 1.8E-02 

Turbine Building 23.93 596.5 4.1E-02 

Notes: The following explanations apply only if Table 2B-2 is used: 

1. Only, “severe” fires are considered with duration greater than five minutes and not self 

extinguished. These fire area frequencies should only be used in analyses of temporary conditions 

when fire contributes to the risk from other hazard groups, e.g. internal events. As such, these fire area 

frequencies should not be used to evaluate findings from degraded fire protection structures, systems, 

and components (e.g., fire suppression system, fire-related barrier, smoke detection system). An all 

encompassing fire, in the location of interest, should accompany the use of these fire area frequencies 

2. For a severe fire in switchgear, switch yard electrical transformers, diesel generators, and 

cables/cable trays, the initiating fire frequency is developed from the number of power operation fires in 

the plant location (i.e., Switchgear Room, Switch Yard, Cable Spreading Room, Diesel Generator 

Building, etc.) based on the NRC proprietary fire event database with updated fire event data through 

1999. Table 2B-2 provides “severe” fire frequencies for most plant location areas, from the updated fire 

event database. 

3. The distribution of the NEIL fire events in the 68 plants were extrapolated to include the 41 plants 

that did not report to NEIL. Refer to Section A-1.2 in the fire study (Ref. 2-4) for details of the 

extrapolation. 

4. A Jeffrey’s prior (0.5 failures) is added to the number of severe fire events occurring during the 

1986-1999 period and then divided by the number of power operation reactor years for the 1986–1999 

period. For multiple rooms/fire zones within a plant location, the denominator is increased 

proportionately. For durations less than one year the frequency will be multiplied by the fractional year. 

Example : Potential fire in Switchgear Room B (two Switchgear Rooms, A and B): 

Switchgear Room Fire Frequency (Fi ) = (2.51 + 0.5 power operation fires) ÷ (596.5 power operation reactor-years ) x 

1 year (duration) = 5.0 x 10-3

Switchgear Room B Fire Frequency (FiB) = Fi ÷ 2 = 2.5 x 10-3.
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-26 

Note: A “severity factor” has been directly included in the fire frequency by limiting fires to those greater than five 

minutes and were not self-extinguished. (This, too, must be consistent with Ref. 2-2.) 

Appendix 2C. Severity Factors Data 

Be cautious in assigning severity factors other than 1, unless one is already calculated for a 

scenario. Otherwise, inadvertent double-counting with ignition frequency assumptions is 

possible (non-conservative). 

See Table 11-1 of NUREG/CR-6850 (Ref. 2-2) for recommended types of severity factors for 

ignition sources and locations. Then see Appendix E Tables E-2 through E-9 of NUREG/CR6850 (Ref. 2-2) for severity factor values for different ignition sources. If severity credit is 

needed, seek expert help. 

Note: one cannot mix the fire severity factors developed in of NUREG/CR-6850 (Ref. 2-2) with a 

fire ignition database that is developed from a different reference unless the same assumptions 

were consistently employed. This needs to be checked. 

Appendix 2D. Detection Failure Data 

Generic probability of failure of auto detection = 0.05 

Source: NUREG/CR-6850, Appendix P (Ref. 2-2) 

See also Figure P-4 of NUREG/CR-6850 (Ref. 2-2) for a complicated calculation of detectionsuppression by using an event tree model and crediting prompt /automatic /manual detection 

and suppression means. 

Appendix 2E. Suppression Failure Data 

! Fixed suppression systems. Unreliability values for fixed suppression systems from 

NUREG/CR-6850 are given in Table 2E-1, below. 

Table 2E-1 Generic Failure Probabilities of Suppression Systems 

from NUREG/CR-6850, Appendix P (Ref. 2-2) 

Fixed Suppression System Unavailability 

Carbon dioxide 0.04 

Halon system 0.05 

Wet pipe sprinkler systems 0.02 

Deluge or preaction sprinkler systems 0.05 

! Manual suppression (fire brigade). The manual suppression failure probability, Pms, 

can be calculated using the following equation: 

Pms = EXP(-LAMDA * delta T), where 
 2 Internal Fire Modeling and Fire Risk Quantification 

 2-27 Handbook Vol. 2 – External Events 

Delta T (minutes) = (Time to target damage) - (Response time of the brigade) – (Time 

to detection) 

Appendix P of NUREG/CR-6850 (Ref. 2-2) contains suppression probability curves as a 

function of time for various types of fires. Table P-2 contains a summary of all available 

curves. This table is given in Table 2E-2 in reduced form. 

Should an all consuming fire be postulated to fail all equipment in a fire area, a choice 

must be made for which suppression curve to use in the analysis. For fire areas which 

contain two fixed ignition sources, the more conservative suppression curve (Lambda) 

should be utilized. For fire areas which contain many ignition sources, the “all fires” 

suppression curve (LAMDA) should be utilized. The control room type of fire should be 

applied to evaluate the control room. Exceptions should be justified. 

Table 2E-2 Manual Suppression Probability per Unit Time (Lambda) and Failure 

Probability at Delta Time (Minutes) from NUREG/CR-6850, Table P-2 (Ref. 2-2) 

ΔT 

1 

min 

ΔT 

5 

min 

ΔT 

10 

min 

ΔT 

15 

min 

ΔT 

20 

min 

ΔT 

25 

min 

ΔT 

30 

min 

ΔT 

45 

min 

ΔT 

60 

min Type of Fire Lambda 

(/minute) 

Manual Suppression Failure Probability (Pms) 

T/G fires 0.03 0.970 0.861 0.741 0.638 0.549 0.472 0.407 0.259 0.165 

Control room 0.33 0.719 0.192 0.037 0.007 0.001 0.000 0.000 0.000 0.000 

PWR containment 0.13 0.878 0.522 0.273 0.142 0.074 0.039 0.020 0.003 0.000 

Outdoor transformers 0.04 0.961 0.819 0.670 0.549 0.449 0.368 0.301 0.165 0.091 

Flammable gas 0.03 0.970 0.861 0.741 0.638 0.549 0.472 0.407 0.259 0.165 

Oil fires 0.09 0.914 0.638 0.407 0.259 0.165 0.105 0.067 0.017 0.005 

Cable fires 0.36 0.698 0.165 0.027 0.005 0.001 0.000 0.000 0.000 0.000 

Electrical fires 0.12 0.887 0.549 0.301 0.165 0.091 0.050 0.027 0.005 0.001 

Welding fires 0.19 0.827 0.387 0.150 0.058 0.022 0.009 0.003 0.000 0.000 

Transient fires 0.12 0.887 0.549 0.301 0.165 0.091 0.050 0.027 0.005 0.001 

High energy arcing faults 0.04 0.961 0.819 0.670 0.549 0.449 0.368 0.301 0.165 0.091 

All fires 0.08 0.923 0.670 0.449 0.301 0.202 0.135 0.091 0.027 0.008 

Notes: 

1. Minimum Pms = 0.001. 

2. Pms = EXP (-Lambda * ΔT), where ΔT in minutes = (Time to target damage) - (Response time of the brigade) - 

(Time to detection) 

Example: If 30 minutes is available from start of fire to target damage, the detection occurs in 3 minutes, and the fire 

brigade response time is 7 minutes based on fire drills, then 

Delta T = 30 – 7 – 3 = 20 minutes. 

Then, the probability of manual suppression failure before the target is damaged is 0.09. 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-28 

Appendix 2F. Spurious Actuation (due to hot shorts) Probabilities 

For probabilities of spurious actuations due to hot shorts, refer to Section 10 of NUREG/CR6850 (Ref. 2-2). Tables 10-1 through 10-5 from of NUREG/CR-6850 are given below for 

convenience. See table notes following the last table. 

Caution: If detailed circuit analysis calculations need to be done, seek expert help.

NUREG/CR-6850, Table 10-1 Failure Mode Probability Estimates Given 

 Cable Damage Thermoset Cable with Control Power Transformer (CPT) 

Raceway 

Type

Description of Hot 

Short

Best Estimate High Confidence 

Range

Tray M/C Intra-cable 

1/C Inter-cable 

M/C → 1/C Inter-cable 

M/C → M/C Inter-cable 

0.30 

0.20 

0.10 

0.01 – 0.05 

0.10 – 0.50 

0.05 – 0.30 

0.05 – 0.20 

Conduit M/C Intra-cable 

1/C Inter-cable 

M/C → 1/C Inter-cable 

M/C → M/C Inter-cable 

0.075 

0.05 

0.025 

0.005 – 0.01 

0.025 – 0.125 

0.0125 – 0.075 

0.0125 – 0.05 

M/C: Multi-conductor cable 

1/C: Single conductor cable 

Intra-cable: An internally generated hot short. The source conductor is part of the cable of interest 

Inter-cable: An externally generated hot short. The source conductor is from a separate cable. 

NUREG/CR-6850, Table 10-2 Failure Mode Probability 

Estimates Given Cable Damage Thermoset Cable without CPT 

Raceway 

Type

Description of Hot 

Short

Best Estimate High Confidence 

Range

Tray M/C Intra-cable 

1/C Inter-cable 

M/C → 1/C Inter-cable 

M/C → M/C Inter-cable 

0.60 

0.40 

0.20 

0.02 – 0.1 

0.20 – 1.0 

0.1 – 0.60 

0.1 – 0.40 

Conduit M/C Intra-cable 

1/C Inter-cable 

M/C → 1/C Inter-cable 

M/C → M/C Inter-cable 

0.15 

0.1 

0.05 

0.01 – 0.02 

0.05 – 0.25 

0.025 – 0.15 

0.025 – 0.1 

M/C: Multi-conductor cable 

1/C: Single conductor cable 

Intra-cable: An internally generated hot short. The source conductor is part of the cable of interest 

Inter-cable: An externally generated hot short. The source conductor is from a separate cable. 
 2 Internal Fire Modeling and Fire Risk Quantification 

 2-29 Handbook Vol. 2 – External Events 

NUREG/CR-6850, Table 10-3 Failure Mode Probability 

Estimates Given Cable Damage Thermoplastic Cable with CPT 

Raceway 

Type

Description of Hot 

Short

Best Estimate High Confidence 

Range

Tray M/C Intra-cable 

1/C Inter-cable 

M/C → 1/C Inter-cable 

M/C → M/C Inter-cable 

0.30 

0.20 

0.10 

0.01 – 0.05 

0.10 – 0.50 

0.05 – 0.30 

0.05 – 0.20 

Conduit M/C Intra-cable 

1/C Inter-cable 

M/C → 1/C Inter-cable 

M/C → M/C Inter-cable 

0.075 

0.05 

0.025 

0.005 – 0.01 

0.025 – 0.125 

0.0125 – 0.075 

0.0125 – 0.05 

M/C: Multi-conductor cable 

1/C: Single conductor cable 

Intra-cable: An internally generated hot short. The source conductor is part of the cable of interest 

Inter-cable: An externally generated hot short. The source conductor is from a separate cable. 

NUREG/CR-6850, Table 10-4 Failure Mode Probability 

Estimates Given Cable Damage Thermoplastic Cable without CPT 

Raceway 

Type

Description of Hot 

Short

Best Estimate High Confidence 

Range

Tray M/C Intra-cable 

1/C Inter-cable 

M/C → 1/C Inter-cable 

M/C → M/C Inter-cable 

0.60 

0.40 

0.20 

0.02 – 0.1 

0.20 – 1.0 

0.1 – 0.60 

0.1 – 0.40 

Conduit M/C Intra-cable 

1/C Inter-cable 

M/C → 1/C Inter-cable 

M/C → M/C Inter-cable 

0.15 

0.1 

0.05 

0.01 – 0.02 

0.05 – 0.25 

0.025 – 0.15 

0.025 – 0.1 

M/C: Multi-conductor cable 

1/C: Single conductor cable 

Intra-cable: An internally generated hot short. The source conductor is part of the cable of interest 

Inter-cable: An externally generated hot short. The source conductor is from a separate cable. 
2 Internal Fire Modeling and Fire Risk Quantification 

Risk Assessment of Operational Events 2-30 

NUREG/CR-6850, Table 10-5 Failure Mode Probability 

Estimates Given Cable Damage Armored or Shielded Cable 

Raceway 

Type

Description of Hot 

Short Best Estimate High Confidence Range

With CPT M/C Intra-cable 0.075 0.02 – 0.15 

Without 

CPT 

M/C Intra-cable 0.15 0.04 – 0.30 

M/C: Multi-conductor cable 

1/C: Single conductor cable 

Intra-cable: An internally generated hot short. The source conductor is part of the cable of interest 

Inter-cable: An externally generated hot short. The source conductor is from a separate cable. 

NUREG/CR-6850, Table 8-2 Screening Criteria to 

Assess the Ignition and Damage Potential of Electrical Cables 

Cable Type Radiant Heating Criteria Temperature Criteria 

Thermoplastic 6 kW/m2 (0.5 BTU/ft2s) 205°C (400°F)

Thermoset 11 kW/m2 (1.0 BTU/ft2s) 330°C (625°F)

Notes for Failure Mode Probability Estimate Tables. 

1. Categorize the circuit of interest based on the configuration attributes collected in Step 1. 

2. From the appropriate table (Table 10-1 to 10-5), select the probability estimates for the 

failure modes of concern. 

3. If the cable failure mode can occur due to different cable interactions, the probability 

estimate is taken as the simple sum of both estimates. For example, if a particular 

thermoset cable failure mode can be induced either by an intra-cable shorting event (P = 

0.30) or by an inter-cable shorting event (P = 0.03; mid-range of 0.01–0.05), the overall 

probability of that failure mode is estimated to be 0.33. 

4. When more than one cable can cause the component failure mode of concern, and 

those cables are within the boundary of influence for the scenario under investigation, 

the probability estimates associated with all affected cables should be considered when 

deriving a failure estimate for the component. In general, the probabilities should be 

combined as an “Exclusive Or” function, as shown: 

PComponent failure = (PFailure Cable A) + (PFailure Cable B) - (PFailure Cable A) 

(PFailure Cable B) 

Appendix 2G. Operator Actions 

In calculating scenario frequency and sequence CCDP, the following considerations about 

operator actions must be taken into account: 

1. The scenario may affect some mitigative or recovery operator actions that are defined in 

the base internal events PRA. An operator action may either become impossible to 

perform, or its human error probability may increase. Especially, local operator actions 
 2 Internal Fire Modeling and Fire Risk Quantification 

 2-31 Handbook Vol. 2 – External Events 

(outside the main control room) already credited in the PRA need to be considered: such 

actions may require the operator to go to the fire area in question or go through the 

same area to perform the action in another area. The fire may prohibit the operator 

action in both cases. This would affect the CCDP calculation. 

2. New recovery actions may be introduced in defining the sequence, for suppression, 

component recovery, etc. Some new operator actions may also be introduced in the 

system models, which would affect the CCDP calculations. Such new human error 

probabilities must be introduced only when there is supporting basis to do so. 

Manual suppression (fire brigade) is discussed in Appendix 2E. 

Appendix 2H. Smoke Damage 

Appendix T of NUREG/CR-6850 (Ref. 2-2) discusses the smoke damage due to a fire event. It 

concludes that the current state of knowledge can not support detailed quantitative assessment. 

3-1 Handbook Vol. 2 – External Events 

External Events: Section 3 

Internal Flood Modeling and Risk Quantification Rev. 1.01 

3.0 Internal Flood Modeling and Risk Quantification 

3.1 Objectives and Scope 

This document is intended to provide a concise and practical handbook to NRC risk analysts 

who routinely use the Systems Analysis Programs for Hands-on Integrated Reliability 

Evaluations (SAPHIRE) software and the Standardized Plant Analysis Risk (SPAR) probabilistic 

risk assessment (PRA) models to quantify event and plant condition importances, and other adhoc risk analyses. It is a complementary document to the handbook cited in Ref. 3-1. 

NRC risk analysts encounter many plant conditions and events reported by such means as 

inspection reports, licensee event reports (LERs), generic risk issues that lend themselves to 

PRA quantification and evaluation, every year. The need for quantification of the event / 

condition importance in terms of the two common risk measures of core damage frequency 

(CDF) and large early release frequency (LERF) arise in many of these cases. 

This handbook provides NRC risk analysts practical guidance for modeling internal flooding 

scenarios and quantifying their CDF using SPAR models and SAPHIRE software. 

The handbook assumes that: 

1. The user has hands-on experience with the SAPHIRE code; 

2. The user has performed and documented event/condition importance analysis or plant 

risk assessment cases for a period of at least three months (this is a suggested period, 

not a firm limit) under the supervision of an experienced (qualified) senior PRA analyst. 

The user is the primary author of documentation packages for such analyses which are 

reviewed and accepted by an NRC program. 

The current scope is limited to internal flooding events during power operation and calculation 

of CDF only.

Mainstream PRA terms and abbreviations that are used in this document are not defined; the 

intended reader is assumed to be familiar with them. 

Both internal flooding and internal fire events are also known as “area events”. They both share 

modeling characteristics such as: 

i). they can fail multiple components in the same area; 

ii). they can propagate from their immediate area to adjacent areas and can potentially 

cause additional failures, despite the existence of “formal barriers” (due to barrier failure 

or design deficiency). 
3 Internal Flood Modeling and Risk Quantification 

Risk Assessment of Operational Events 3-2 

3.2 Internal Flooding Scenario Definition and Quantification 

A two-step process is discussed to model internal flooding (FLI) scenarios and quantify their 

CDFs: 

1. Define flooding scenarios that lead to core damage. For this purpose, an event tree 

logic structure such as the one given in Figure 3A-1-1 may be used. Using such a 

modeling structure, calculate scenario frequencies. Definition of a flooding scenario is 

discussed in Section 3.2.1. 

2. Quantify the CDF of these scenarios using a SPAR model and the SAPHIRE software. 

For this purpose, first the scenario conditional core damage probability (CCDP) is 

calculated. Then this CCDP is multiplied by the scenario frequency calculated in Step 1. 

From a single flooding source, multiple scenarios may be derived, leading to multiple 

flooding sequences whose CDFs need to be summed. Quantification of sequence CDF 

is discussed in Section 3.2.2. 

 

3.2.1 Define Internal Flooding Scenarios 

For the event (or plant condition) in question, one or more flooding scenarios must be defined. 

Depending upon the issue at hand, the following cases are envisioned and are included in the 

scope: 

1. FLIs that can be terminated by operator action before critical flood height for equipment 

damage is reached. 

2. FLIs that are not terminated early, but are limited to a single flood area. 

3. FLIs that are not terminated early and can propagate to additional flood areas. 

A systematic method to define FLI scenarios that fit into one of these cases, using simple event 

tree logic is given in Appendix 3A. After the plant response is incorporated to define a flooding 

sequence, those FLI sequence scenarios that can lead to core damage are selected, and their 

CDFs are quantified. 

The flooding sequences defined can be summarized in terms of a matrix containing the 

minimum amount of information to be able to quantify the scenario frequency, the scenario 

CCDP, and thus the scenario CDF: 

CDF = Scenario Frequency * CCDP. 

Potential sources of flooding events may include failures in hydraulic components, such as 

piping, expansion joints, heat exchangers, valves, tanks, vessels, and flanges, as well as 

inadvertent fire water actuation by steam or fire, in the following systems: 

! Fire water system 

! Emergency service water (ESW)/component cooling water (CCW) system 

! Circulating water/nuclear service water (NSW) system. 
 3 Internal Flood Modeling and Risk Quantification 

3-3 Handbook Vol. 2 – External Events 

Steamline break events, which by themselves may not pose a flooding threat, can actuate fire 

protection sprinklers and cause consequential flooding. 

Potential damage to electrical equipment, such as in emergency diesel generator (EDG) rooms, 

alternating current (AC) switchgear rooms, electrical cabinets in other locations, must be 

considered, since they may have high consequences. 

Damage modes to be considered include: 

- equipment submergence 

- equipment spray 

Potential loss of a system or a train due to the equipment break causing the flood must also be 

considered, in addition to the equipment damage caused by the consequences of the flood. An 

example may be a non-recoverable loss of service water (SW) due to pipe break. 

Initiating event frequencies of pipe breaks and other equipment that can cause flooding can be 

calculated by using failure frequencies available in the literature. Example sets of such data are 

given in Tables 3A-2-1 and 3A-2-3. An example calculation is shown in Section 3.3. 

Operator actions to diagnose and isolate/ terminate the flood can be introduced into a scenario 

as shown in Figure 3A-1-1. This requires determination of the time window available to the 

operators to implement such actions, before the critical flood height is reached and the subject 

equipment is failed. 

Examine the event/condition characteristics and refer to Section 3A-1 to define scenarios that 

lead to core damage. Summarize those scenarios in terms of a table, such as Table 3A-1-1. 

The columns of this table are discussed below. Note that, each of these scenarios is treated as 

an initiating event and will be transferred to an event tree already modeled in the internal events 

SPAR model. In very special cases, a new event tree representing the plant response to the 

flooding may be constructed, if needed. 

1. Scenario name (initiating event ID). This always starts with FLI and is used both for the 

event tree and the initiating event names. 

2. Scenario description 

3. Scenario frequency IEfreq (initiating event frequency). This is calculated using models 

such as the one discussed in Figure 3A-1-1. 

4. Equipment lost. Equipment credited in the PRA that is lost due to flood is listed in this 

column. Include trains/system that caused the flood and is also lost. 

5. Initiating event caused. This is the initiating event caused by the flood. In most cases, it 

is one of the internal initiating event categories already defined (such as loss of main 

feedwater (LOMFW), TRANS, loss of service water system (LOSWS), etc.). 

6. Human error probabilities (HEPs) and other basic events affected. List the basic events 

and operator actions that are affected by the flood (failed, degraded). This is in addition 

to equipment listed in item 5 above. 
3 Internal Flood Modeling and Risk Quantification 

Risk Assessment of Operational Events 3-4 

7. New basic events (failures) introduced. List any new basic events introduced (such as 

scenario initiating event frequencies, operator actions to isolate flood, etc.) to model the 

scenarios. 

Other columns may be introduced as needed. 

3.2.2 Quantify Sequence CDFs 

When plant response is modeled (e.g., by transferring to the appropriate event tree), a scenario 

sequence is defined. The CDF of each sequence can be calculated as a product of the 

scenario frequency and the CCDP given the scenario has occurred: 

CDF = IEfreq * CCDP. 

The scenario frequency IEfreq is already calculated in the earlier step. The CCDP can be 

calculated by using the SAPHIRE code and the SPAR models. For this purpose, either a 

change set or the GEM software can be used. 

 

The scenario may cause multiple structures, systems, and components (SSCs) to fail, even 

redundant trains of a mitigating system. 

New event and fault trees may need to be made, if the scenario does not lead to (transfer to) an 

already existing event tree (typically one for the existing internal events model). 

Table 3-1 shows an example set of scenario CDF calculations. 

Table 3-1 Example Internal Flooding Results by Scenario 

Event Description 

Initiating 

Event 

Frequency 

Type of Trip CCDP CDF 

1 FLI-FL1 

Turbine Building 

Basement Flood - 

Winter Conditions 

8.90E-05 IE-LOMFW 1.21E-05 1.08E-09 

2 FLI--FL2 

Turbine Building 

Basement Flood - 

Summer Conditions 

1.10E-04 IE-LOMFW 1.21E-05 1.33E-09 

3 FLI-FL3 

Diesel Generator Room 

A SW Connection 

Failure Flood 

5.00E-04 IE-TRANS 1.68E-05 8.42E-09 

4 FLI-FL4 

Diesel Generator Room 

B SW Connection 

Failure Flood 

5.00E-04 IE-TRANS 6.57E-06 3.29E-09 

5 FLI-FL5 Relay Room Potable 

Water Flood 1.50E-04 IE-TRANS 5.97E-07 8.95E-11 

6 FLI-FL6 

Control Rod Drive 

Equipment Room 

Service Water Flood 

1.50E-04 IE-TRANS 5.97E-07 8.95E-11 

 Sum = 1.50E-03 1.43E-08 

Once the sequence CDF is known, it can be used to estimate event/condition importance. 
 3 Internal Flood Modeling and Risk Quantification 

3-5 Handbook Vol. 2 – External Events 

3.3 Examples 

This section discusses examples for illustrative purposes; the values used in the examples are 

for illustration only. 

See Ref. 3-3 for additional discussion and examples. 

3.3.1 Example Event Analysis 

An internal flooding initiating event occurs in plant X due to a rupture in one SWS train. Main feedwater (MFW) is lost 

due to flooding. The ruptured SW train had to be isolated to terminate the flooding, leaving only one train of SWS 

support to frontline systems. The plant is automatically tripped due to loss of MFW. Propagation of flood into other 

areas is not a concern. 

The failure of isolation of the flooding source is calculated to be 1.0E-02. If this failure occurs, the AFW pump 

supported by ruptured SWS train will fail. 

The event importance can be calculated as: 

EVENT-IMP = (1-0.01)*CCDP1 + 0.01*CCDP2, 

where CCDP1 and CCDP2 are the conditional core damage probabilities with or without success of isolation, 

respectively. 

If the isolation is successful, use the existing transient event tree model in SPAR, with an initiating event frequency of 

1.0 (GEM or SAPHIRE can be used). Also fail the MFW system and the one train of SWS. Calculate event CCDP1 

as 

CCDP1 = 1.0E-04. 

If the isolation fails, the same CCDP value is calculated, since AFW pump supported by the faulted SW train is not 

credited anyway in the first case. The faulted SW train is still ineffective and MFW is inoperable. Thus, 

CCDP2 = 1.0E-04. 

The event importance is 1.0E-04. (Even with the modification above, this will still be approximately correct since the 

non-isolated case will dominate.) 

Also consider the following variation: if the isolation fails, the flooding will propagate into a switchgear area, 

rendering a 4160 VAC train inoperable (the bus supports the failed SW train), in addition to the already existing 

failures of the MFW and one SW train. In that case, the SPAR model gives a CCDP2 value of 

CCDP2 = 1.0E-03. 

Thus, with the variation, the event importance is calculated as: 

EVENT-IMP = 0.99*1.0E-04 + 0.01*1.0E-03 

EVENT-IMP = 1.1E-04. (Based on the above discussion, with CCDP1 reduced by at least a factor of 100, this value 

will be no greater than 1.1E-5.) 

3.3.2 Example Condition Analysis 

A plant inspection revealed that the flood barrier between flood areas X and Y was compromised for a period of 3 

months, so that a large flood in area X can propagate to area Y and render both 4160 VAC emergency buses 

inoperable (Ppr). There are no flood sources in area Y. Large flood in area X will also render the MFW system in 

operable. Time window to critical height is so short that no credible operator action to isolate large flood sources 

exists (HEPiso). The total initiating event frequency from different potential large flood sources in area X is 

calculated to be 5E-03/year. 
3 Internal Flood Modeling and Risk Quantification 

Risk Assessment of Operational Events 3-6 

Both the plant base and condition cases must be evaluated to calculate condition importance. 

For the base case, a transient with loss of MFW is modeled and the CCDP-base is calculated as 1.0E-06 using 

SPAR. 

For the condition case, the CCDP-cond calculated by using the SPAR model with TRANS event tree without MFW, 

both emergency 4160 AC buses failed, and potential RCP seal LOCA is 0.2. The exposure time to this plant 

condition is 0.25 years. Thus the plant condition importance is calculated as: 

COND-IMP = exposure time * initiating event frequency * (CCDP-cond - CCDP-base) 

COND-IMP = 0.25 * 5.0E-03 * (0.2 – 1.0E-06) 

COND-IMP = 2.5E-04. 

Note that 

HEPiso = 1.0 

Ppr = 1.0 

in this example. Thus, the scenario frequency is equal to flood initiating event frequency and there is only one 

scenario generated from the flood initiating event.

3.3.3 Example Initiating Event Frequency Calculation 

This example calculation is for the initiating event frequency of large flooding (IE-FLI-X) from the circulating water 

system inlet lines in a pressurized water reactor (PWR). 

Three failure modes are considered: 

1. failure of the expansion joints (F1) 

2. rupture of the piping and components in the system (F2) 

3. maintenance errors (F3); 

IE-FLI-X = F1 + F2 + F3. 

The expansion joints would not be subject to water hammer because they are located downstream of the isolation 

valves and the joints are not connected to a common header after the isolation valves until the lines combine in the 

circulating water discharge tunnel, well past the expansion joints. Expansion joint failures are typically caused by 

either misapplication of the expansion joint for the intended service or poor installation. The physical condition of the 

expansion joints has been evaluated by the vendor and the condition of the expansion joints found acceptable for the 

life of the plant with no expected deterioration in performance. With four inlet expansion joints, the total frequency of 

expansion joint failures is calculated to be: 

F1 = 4.5E-5 * 4 = 1.80E-04 per year, 

Where the expansion joint failure is taken from Table 3A-2-1. 

Circulating water inlet piping contains ten pipe segments and four valves. Therefore, the frequency of large (D >= 6”) 

circulating water inlet-initiated pipe rupture events was calculated to be: 

F2 = F(piping) + F (valves) 

F2 = 8760 hours/year *((10 pipe segments) * (1.39E-10 / pipe segment-hour) + (4 valves) * (4.0E-10 / valve-hour)) * 

0.5 

F(piping) = 1.31E-05 per year, 

where data is taken from Tables 3A-2-3 (Generic PWR Pipe Rupture in “Other Safety-Related Systems” for D >= 6’), 

3A-2-1 (Valve non-PCS Rupture) and 3A-2-2 (0.5 for large failure given a break in large piping (D >= 6’)). 
 3 Internal Flood Modeling and Risk Quantification 

3-7 Handbook Vol. 2 – External Events 

Flooding events initiated by maintenance on the circulating water system are considered negligible contributors to the 

overall initiating event frequency (assume an upper bound F3 for completeness): 

F3 = 1.0E-06/yr. 

Thus, the total frequency of large breaks in the circulating system inlet piping is 

IE-FLI-X = 1.8E-04 + 1.31E-05 + 1.0E-06 

IE-FLI-X = 1.9E-04 /year. 

3.4 References 

3-1. U.S. Nuclear Regulatory Commission, “Risk Assessment of Operational Events 

Handbook: Volume 1 - Internal Events,” Revision 1.01. December 2007. 

3-2. Electric Power Research Institute, “Pipe Failure Study Update,” EPRI TR-102266, April 

1993. 

3-3. Idaho National Laboratory, “A Feasibility and Demonstration Study – Incorporating 

External Events into SPAR Models,” February 2005. 

3-4. Reserved. 

3-5. Idaho National Engineering Laboratory, Component External Leakage and Rupture 

Frequency Estimates,” EGG-SSRE-9639, November 1991. 

3-6. U.S. Nuclear Regulatory Commission, “Rates of Initiating Events at U.S. Nuclear Power 

Plants: 1987-1995,” NUREG/CR-5750, February 1999. 
3 Internal Flood Modeling and Risk Quantification 

Risk Assessment of Operational Events 3-8 

Appendix 3A. Model and Data for Internal Flooding 

3A-1 Scenario Definition 

An event tree model that defines a set of generic internal flooding scenario sequences is illustrated 

in Figure 3A-1-1. The end states are transferred to existing event trees (already made for internal 

events), with additional equipment damage due to the scenario. The event tree model considers at 

least the following aspects of an FLI scenario: 

1. Definition of the FLI source in flood area X, its flow rate, critical flood height for equipment 

damage, and time window for reaching the critical height. The frequency of the initiating 

event is also calculated. 

2. Credible detection/isolation by operators to terminate IF to either prevent equipment 

damage or limit the extent of equipment damage. 

3. Potential for propagation from flood area X to another flood area Y due to barrier failure or 

design deficiency. 

Additional event tree nodes to better define scenario-specific issues can also be introduced into the 

event tree to better define FLI scenarios. 

The frequency IEfreq of a limiting FLI scenario can be defined as 

IEfreq = Fif * HEPiso * Ppr, where 

Fif = FLI frequency 

HEPiso = Failure to terminate the flood source 

Ppr = Probability of propagation to another flood area. 

Other scenario-specific factors can be introduced to the above equation, as warranted. 

An example of such a matrix for multiple FLI scenarios is given in Table 3A-1-1. This matrix must 

contain enough information for a PRA analyst to calculate the scenario CCDPs, using existing 

event trees in the internal events PRA. Very special scenarios may require construction of new 

custom-made event/fault trees to address a specific issue. 

Table 3A-1-2 shows another table where the scenario information is tabulated for CCDP 

calculation. 

3A-2 Initiating Event Frequency Data 

Table 3A-2-1 provides pipe and other equipment rupture frequencies assembled from different 

sources. 

In medium and large diameter pipes, the breaks of smaller equivalent sizes can occur. The 

fraction of smaller sizes of breaks, given a failure in a larger pipe, can be calculated by using data 

in Table 3A-2-2. 
 3 Internal Flood Modeling and Risk Quantification 

3-9 Handbook Vol. 2 – External Events 

A more recent data set for pipe failures by system and reactor type is also given in Table 3A-2-3 in 

units of per hr-per segment. Use of this data requires knowing the number of segments in 

question. 

Finally, the initiating event frequencies of steam and feedline breaks are given in Table 3A-2-4. 

3A-3 Quantification of Internal Flooding Initiating Event Frequencies 

To calculate flooding initiating event frequencies, data from Tables 3A-2-1 through 3A-2-4 may be 

used. This requires knowing the number of segments or ft of piping involved. An example 

calculation is given in Section 3.3. 
3 Internal Flood Modeling and Risk Quantification 

Risk Assessment of Operational Events 3-10 

 

FLI in Area X 

Occurs 

Detect / 

Isolate 

Propagation 

to Area Y 

 Transfer 

to IE 

 

 Yes 1 TRANS 

with equipment damage in Area 

X and possibly in Area Y 

 

IE-FLI-X No 2 TRANS 

with more equipment damage in 

Area X, but none in Area Y 

Fif No 

HEPiso 

Yes 3 TRANS 

with equipment damage in Area 

X as for Branch 2 and likely more 

in Area Y than for Branch 1 

 Ppr 

 

Additional event tree nodes may be added to introduce scenario-specific issues. 

Transfers to other event trees are for illustration purposes only; others may be substituted, as needed. 

For example: 

 

FLI in Area X 

Occurs 

Detect / 

Isolate 

Propagation 

to Area Y 

 Transfer 

to IE 

 

 Yes 1 TRANS 

with equipment damage inducing 

a Transient 

 

IE-FLI-X No 2 LOSWS 

with more equipment damage in 

Area X than above, but none in 

Area Y; and, inducing a loss of 

SW, for which the effect of 

equipment damage likely will 

differ from above 

 No 

 Yes 3 LOSWS 

with equipment damage in Area 

X as for Branch 2 and likely more 

in Area Y than for Branch 1, 

although the effect in Area Y 

may differ since a different 

transfer is involved (LOSWS 

instead of TRANS) 

 

Frequency of Scenario 1 = Fif * (1-HEPiso) 

Frequency of Scenario 2 = Fif * HEPiso* (1-Ppr) 

Frequency of Scenario 3 = Fif * HEPiso* Ppr 

Figure 3A-1-1 Event Tree Model for Internal Flooding Scenario 
3 Internal Flood Modeling a

 3-11 Handbook Vo

Table 3A-1-1 Example Matrix Defining Internal Flooding Scenarios 

Name Description IE Frequency Equipment Lost IE Caused 

HE

Ba

Eve

Affe

1 FLI-FL1 Turbine Building Basement Flood - Winter Conditions 8.90E-05 

Non-vital air compressors; MCCs for non-vital air compressors and other components 

IE-LOMFW No

No

2 FLI-FL2 Turbine Building Basement Flood - Summer Conditions 1.10E-04 

Non-vital air compressors; MCCs for non-vital air compressors and other components 

IE-LOMFW No

No

3 FLI-FL3 Diesel Generator Room A SW Connection Failure Flood 5.00E-04 4.16KV Bus 5; EDG A IE-TRANS No

No

4 FLI-FL4 Diesel Generator Room B SW Connection Failure Flood 5.00E-04 4.16KV Bus 6; EDG B IE-TRANS No

No

5 FLI-FL5 Relay Room Potable Water Flood 1.50E-04 None IE-TRANS No

No

6 FLI-FL6 Control Rod Drive Equipment Room Service Water Flood 1.50E-04 None IE-TRANS No

No

Sum = 1.50E-03 
3 Internal Flood Modeling and Risk Quantification 

Risk Assessment of Operational Events 3-12 

Table 3A-1-2 Example Summary of A Plant X Turbine Building Flood Scenario 

IE Name Description Flood Damage Detection/ Isolation Means Failed Gate or CoCI06B Rupture of an Inlet 

Condenser Expansion Joint in TU-22-1 

Propagate: 

TU-94 TU-95B-1 Damage: 

Air Compressor 1F Air Compressor 1G Condensate Pump 1A Condensate Pump 1B Feedwater Pump 1A Feedwater Pump 1B Rx Makeup Pump 1A Rx Makeup Pump 1B Plt Equip Wtr Pump 1A Plt Equip Wtr Pump 1B MCC-32D MCC-42B MCC-42D AOV PW-52 

Detect: Reactor Trip due to 

Loss of Condenser Vacuum Isolate: Trip both Circulating 

Water Pumps 

Initiating Event:

IE-CI06B Failed BEs:01-CM-SIAC1F-PR 01-CM-SIAC1G-PR 03-PM--CDP1A-PR 03-PM--CDP1B-PR 05APM--FWP1A-P05APM--FWP1B-P27APM--RMP1A-P27APM--RMP1B-P27BPM-PEWPA—27BPM-PEWPB—40-BS-MCC32D-S40-BS-MCC42B-SG 40-BS-MCC42D-S26-AV-PW52---OC 
 3 Internal Flood Modeling and Risk Quantification 

 3-13 Handbook Vol. 2 – External Events 

Table 3A-2-1 Data for Calculating Internal Flooding Initiating Event Frequencies 

Component Type Rupture/Leakage 

(Note 4) Rate (/hr) Error Factor (Note 2) 

Leakage 3.0E-09 /hr-ft 10 

Non-PCS Rupture 1.2.0E-10 /hr-ft 30 Generic Piping (including 

elbows) PCS Rupture 3.0E-11 /hr-ft 30 

Leakage 1.0E-08 10 

Valve Non-PCS Rupture 4.0E-10 30 

PCS Rupture 1.0E-10 30 

Leakage 3.0E-08 10 

Pump Non-PCS Rupture 1.2E-09 30 

PCS Rupture 3.0E-10 30 

Leakage 1.0E-08 10 Flange Rupture (all) 1.0E-10 10 

Leakage 1.0E-07 10 

Heat Exchanger Tube Side Non-PCS Rupture 4.0E-09 30 

PCS Rupture 1.0E-09 30 

Leakage 1.0E-08 10 

Heat Exchanger Shell Side Non-PCS Rupture 4.0E-10 30 

PCS Rupture 1.0E-10 30 

Leakage 1.0E-08 10 

Tank Non-PCS Rupture 4.0E-10 30 

PCS Rupture 1.0E-10 30 

Circulating Water Expansion 

Joint (Note 1) Rupture 4.5E-05 /yr 

Notes: 

1. Taken from Internal Flooding Analysis Supplemental Report for the Surry Nuclear Power Plant 

Individual Plant Examination, VEPCO/NUS, November 1991 (ADAMS microfiche no. 9112060076). All 

other data in the table are taken from Ref. 3-5. 

2. Lognormal distribution is postulated. 

3. It was assumed that the rupture of valves, pump casings, and other components have the same 

conditional probability of small, medium, large ruptures as for piping, as given in Table 3A-2-2.

4. Leakage <50 gpm; rupture >= 50gpm. 
3 Internal Flood Modeling and Risk Quantification 

Risk Assessment of Operational Events 3-14 

Table 3A-2-2 Conditional Probability of Small, 

Medium, Large Ruptures for Piping 

Given Break in Medium Size Pipe (2”<=D<6”)

Probability of Small Failure (D<2”) 0.5 

Probability of Medium Failure 0.5 

Given Break in Large Size Pipe (D>=6”)

Probability of Small or Medium Failure (D<6”) 0.25 

Probability of Large Failure 0.5 

Data from Ref. 3-2. Breaks include all ruptures.

Table 3A-2-3 Rupture Failure Rates for Generic System Groups for Piping (1) 

Failure rate (per Section-hour) for Pipe Size 

System Groups (2) 

.5” <= ID < 2” 2” <= ID < 6” 6” <= ID 

BWR – Reactor Coolant System 7.54E-11 1.05E-10 1.06E-10 

BWR – Safety Injection and Recirculation 1.47E-9 2.02E-9 2.06E-9 

BWR - Other Safety-related Systems 8.65E-10 2.12E-10 6.62E-10 

BWR – Main and Auxiliary Emergency Feedwater 

dC d t S t

2.30E-9 1.17E-9 3.4E-10 

BWR - Main and Auxiliary and Extraction Steam 

and Turbine Systems 7.62E-11 2.72E-10 9.63E-10 

Generic BWR 8.54E-10 4.66E-10 8.26E-10 

PWR – Reactor Coolant System 2.13E-10 1.70E-11 2.87E-11 

PWR – Safety Injection and Recirculation 1.42E-9 1.13E-10 1.92E-10 

PWR - Other Safety-related Systems 7.09E-10 7.03E-11 1.39E-10 

PWR – Main and Auxiliary Emergency Feedwater 

and Condensate Systems 7.39E-10 1.17E-9 6.4E-10 

PWR - Main and Auxiliary and Extraction Steam 

and Turbine Systems 3.5E-10 9.77E-10 8.9E-10 

Generic PWR 6.01E-10 3.98E-10 5.64E-10 

Generic Plant 7.05E-10 4.16E-10 6.53E-10 

Notes: 

1. Rupture >50gpm. Use together with Table 3A-2-2 to calculate small, medium and large failures. 

2. A pipe section is a segment of piping between major discontinuities such as valves, pumps, reducers, 

trees, etc. A pipe section is typically 10 to 100 feet long, and contains four to eight welds. Each pipe 

section can also contain several elbows and flanges. Instrumentation connections are not considered 

as major discontinuities. 

3. Data from Ref. 3-2. 
 3 Internal Flood Modeling and Risk Quantification 

 3-15 Handbook Vol. 2 – External Events 

Table 3A-2-4 Generic Frequencies of Steam and Feedline Break Initiating Events 

Event Category Mean 

Frequency 

95th

percentile 

High Energy Line Steam Breaks/Leaks (combined) K 1.3e-02 2.1e-02 

 Steam Line Break/leak Outside Containment K1 1.0e-02 1.7e-02 

 Steam Line Break/leak Inside Containment – PWR only K3 1.0e-03 3.9e-03 

 Feedwater Line Break/leak K2 3.4e-03 7.6e-03 

Notes: 

K: High energy line break 

K1: Steam line break outside containment: is a break of one inch equivalent diameter or more in a steam line 

located outside the primary containment that contains main turbine working fluid at or above atmospheric 

saturation conditions. 

K2: Feedwater line break is a break of one inch equivalent diameter or more in a feedwater or condensate line that 

contains main turbine working fluid at or above atmospheric saturation conditions. 

K3: Steam line break inside containment: is a break of one inch equivalent diameter or more in a steam line 

located inside the primary containment that contains main turbine working fluid at or above atmospheric 

saturation conditions. 

See Ref. 3-6 for the Categories. 

 4-1 Handbook Vol. 2 – External Events

External Events: Section 4 

Seismic Event Modeling and Seismic Risk Quantification Rev. 1.01 

4.0 Seismic Event Modeling and Seismic Risk Quantification 

4.1 Objectives and Scope 

This document is intended to provide a concise and practical handbook to NRC risk analysts 

who routinely use the Systems Analysis Programs for Hands-on Integrated Reliability 

(SAPHIRE) software and the Standardized Plant Analysis Risk (SPAR) probabilistic risk 

assessment (PRA) models to quantify event and plant condition importances, and other ad-hoc 

risk analyses. It is a complementary document to the handbook cited in Ref. 4-1. 

NRC risk analysts encounter many plant conditions and events reported by such means as 

inspection reports, licensee event reports (LERs), generic risk issues that lend themselves to 

PRA quantification and evaluation, every year. The need for quantification of the event / 

condition importance in terms of the two common risk measures of core damage frequency 

(CDF) and large early release frequency (LERF) arise in many of these cases. 

This handbook provides NRC risk analysts practical guidance for modeling seismic event 

scenarios and quantifying their CDF using SPAR models and SAPHIRE software. 

The handbook assumes that: 

1. The user has hands-on experience with the SAPHIRE code; 

2. The user has performed and documented event/condition importance analysis or plant risk 

assessment cases for a period of at least three months (this is a suggested period, not a 

firm limit) under the supervision of an experienced (qualified) senior PRA analyst. The user 

is the primary author of documentation packages for such analyses which are reviewed and 

accepted by an NRC program. 

The current scope is limited to seismic events during power operation and calculation of CDF 

only.

Mainstream PRA terms and abbreviations that are used in this document are not defined; the 

intended reader is assumed to be familiar with them. 

The seismic PRA (SPRA) model described in this handbook can be used for plants with SMA. 

See Section 4.2.8. 

4.2 Seismic Event Scenario Definition 

4.2.1 Minimum Input Requirements 

The minimum input requirements for the seismic SPAR PRA model are as follows: 

1. Seismic Hazard Vector (frequencies of seismic events)
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-2 

2. Seismic fragilities of major structures, systems, and components (SSCs). 

Both of these inputs can be found in plants with SPRAs, and some of this information 

may be available for plants with seismic margins analyses. If not, generic hazard curves 

given in Appendix 4A, and SSC fragilities given in Appendix 4B may be used. 

3. An event tree model representing the seismic sequences. 

Such an event tree model is provided as a default in a later section. 

Those plants with existing SPRAs would also have dominant seismic sequences that can be 

used to validate the SPAR-EE model. 

4.2.2 Example Seismic Hazard Vector 

The seismic hazard vectors for 69 sites to the East of Rocky Mountains are given in Ref. 4-2. 

The default seismic hazard vectors for 72 SPAR model plants are given in Appendix 4A. 

The seismic hazard vector for the example is taken from Ref. 4-2: 

Table 4-1 Example Seismic Hazard Vector 

(cumulative frequency of exceedance of a g value) 

g value mean f per year 

0.05 3.040E-04 

0.08 1.777E-04 

0.15 6.422E-05 

0.25 2.748E-05 

0.30 1.979E-05 

0.40 1.141E-05 

0.50 7.212E-06 

0.65 4.043E-06 

0.80 2.474E-06 

1.00 1.409E-06 

This vector provides the seismic initiating event frequencies (seismic hazard distribution) as a 

function of seismic g level. The frequency of a seismic event of magnitude 0.05g or higher is 

given as 3.04E-04/year. 

The plant is designed to withstand a design basis earthquake (DBE) (also known as safe 

shutdown earthquake (SSE)) of 0.12g peak ground acceleration (PGA). The operating-basis 

earthquake (OBE) is 0.06g. 

4.2.3 Seismic Event Categories 

The seismic acceleration range can be partitioned into N categories (bins) to define N discrete 

seismic event scenarios with increasing intensity. This handbook recommends using three 

seismic bins as defined below, unless plant-specific considerations require more bins. A larger 

number bins can be readily introduced into the SPAR models without taxing their running times. 
 4 Seismic Event Modeling and Seismic Risk Quantification

 4-3 Handbook Vol. 2 – External Events

A larger number of bins may be appropriate for the four sites to the West of the Rocky 

Mountains. 

For the example case above, three seismic event categories are defined as follows: 

 IE Frequency 

IE-EQK-BIN-1 SEISMIC INITIATOR 

(0.05 - 0.3 g) 

2.84E-04 

IE-EQK-BIN-2 SEISMIC INITIATOR 

(0.3 - 0.5 g) 

1.26E-05 

IE-EQK-BIN-3 SEISMIC INITIATOR 

(> 0.5 g) 

7.21E-06 

The frequencies are calculated as shown in Table 4-2. Any reasonable number of seismic bins 

may be defined, as needed. The need may be based on two factors: 

1. Seismicity of the site (seismically more active sites may require more bins); 

2. Fragility grouping of major SSCs (one or more key SSCs with a fragility in a seismic 

range may warrant a bin in that range to make the model more realistic). 

The three seismic bins chosen here follow the Limerick external events feasibility study (Ref. 4-

3). The first bin is driven by seismically induced loss-of-offsite power (LOOP) events; the third 

bin is driven by the seismic failure of major structures, leading to direct core damage. The 

second bin captures other modeled events (small loss-of-coolant accident (SLOCA), large lossof-coolant accident (LLOCA), LOOP, structural failures). 

Table 4-2 Calculation of Bin Accelerations and Frequencies 

Ground 

Acceleration 

(g) 

Exceedance 

Frequency Seismic Bin Bin Acceleration 

Bin 

Frequency 

0.05 3.040E-04 1 (0.05-0.3g) 0.122474 2.842E-04 

0.08 1.777E-04 

0.15 6.422E-05 

0.25 2.748E-05 

0.30 1.979E-05 2 (0.3-0.5g) 0.387298 1.258E-05 

0.40 1.141E-05 

0.50 7.212E-06 3 (>0.5g) 0.707107 7.212E-06 

0.65 4.043E-06 

0.80 2.474E-06 

1.00 1.409E-06 

Sum = 3.040E-04 

Bin acceleration is calculated as a geometric average of two bin range limits. 

Bin frequency is calculated as the difference of the frequencies of two bin range 

limits. 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-4 

To each bin, a mean acceleration is assigned in terms of the geometric average of the bin end 

points. For the three bins in question, the bin accelerations are: 

Seismic Bin Bin Acceleration 

BIN-1 (0.05-0.3g) 0.122 

BIN-2 (0.3-0.5g) 0.387 

BIN-3 (>0.5g) 0.707 

The seismic failure probabilities of SSCs are calculated at these bin acceleration levels, in the 

next task. 

After the next step (4.2.4) is completed, redefinition of the seismic event categories (number of 

bins, or the bin ranges) may be required if plant-specific low fragility SSCs are identified. 

4.2.4 SSC Seismic Fragilities 

The fragilities of the major SSCs must be obtained (or assigned from generic sources) to 

calculate mean seismic failure probabilities, which then are added to the existing random failure 

probabilities. The example SPRA provides various SSC probabilities; it also defines a surrogate 

SSC, whose fragility is used in a conservative, generic manner for some key SSCs. Table 4-3 

shows an example of the fragilities considered and how they are treated for SPAR-EE 

purposes. The list of key SSCs are taken from the Example SPRA. 

The fragility information needed for a SSC is either, 

Median capacity am and βc OR 

Median capacity am, βr and βu. 

βc = (βr

2

 + βu

2

)

1/2 

The mean seismic failure probability Pfail(a) at a bin acceleration level can be calculated by 

using the following equation: 

Pfail(a) = Φ [ ln(a/am) / (βr

2

 + βu

2

)

1/2] 

Where Φ is the standard normal cumulative distribution function and 

a = median acceleration level of the seismic event; 

am = median of the component fragility (or median capacity); 

βr = logarithmic standard deviation representing random uncertainty; 

βu = logarithmic standard deviation representing systematic or modeling uncertainty. 

The SSC high confidence of low probability of failure (HCLPF) value is calculated by the 

equation: 

HCLPF = am exp(1.645(βr+ βu)
4 Seismic Event Modeling and Seism

 4-5 Handbook Vo

Table 4-3 SSC Fragilities and Their Treatment in SPAR-EE 

SSC Description Median Capacity (g) 

βc OR 

βr βu SSC Failure probability Co

0.35 0.55 2.77E-02 LO

Offsite Power 0.35 0.55 5.72E-01 LO

0.35 0.55 8.99E-01 LO

0.63 0.46 1.79E-04 RHR

RHR Heat Exchanger 0.63 0.46 1.45E-01 RHR

0.63 0.46 5.99E-01 RHR

0.64 0.3 1.65E-08 

Surrogate Element 0.64 0.3 4.68E-02 

0.64 0.3 6.30E-01 

Reactor Pressure Vessel 2 0.3 0.35 6.53E-10 

2 0.3 0.35 1.83E-04 

Reactor Pressure Vessel Supports 2 0.3 0.35 1.20E-02 Steam Generators 2.5 0.3 0.4 7.73E-10 

2.5 0.3 0.4 9.53E-05 

Steam Generator Supports 2.5 0.3 0.4 5.77E-03 Pressurizer 2.5 0.3 0.4 7.73E-10 L

2.5 0.3 0.4 9.53E-05 L

Pressurizer Supports 2.5 0.3 0.4 5.77E-03 LReactor Coolant Pumps 2.5 0.3 0.4 7.73E-10 L

2.5 0.3 0.4 9.53E-05 L

Reactor Coolant Pump Supports 2.5 0.3 0.4 5.77E-03 LControl Rod Drive Mechanism 2.5 0.3 0.4 7.73E-10 

2.5 0.3 0.4 9.53E-05 

Reactor Core Upper Internals 2.5 0.3 0.4 5.77E-03 

3.8 0.35 0.5 8.82E-09 

Reactor Coolant System Piping 3.8 0.35 0.5 9.10E-05 

3.8 0.35 0.5 2.93E-03 

Containment Building 1.1 0.3 3.50E-01 9.20E-07 Auxiliary Building 1.1 0.3 3.50E-01 1.17E-02 Turbine Building 1.1 0.3 3.50E-01 1.69E-01 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-6 

SSC Description Median Capacity (g) 

βc OR 

βr βu SSC Failure probability Co

Reactor Coolant Pump Seals not modeled SSecondary Side Piping and Supports not modeled Switchyard Ceramic Insulators modeled above Screenhouse surrogate element is used in SWS FT Instrument Air Assumed failed in SPRA due to low fragility. Feed and bleed not credited in SPR. Feed and 

in SPAR-EE either. 

CST Assumed failed due to low fragility in SPRA. SWS is credited as alternate. However, could 

SPAR since SPAR success criteria requires both. 

RPS Failure to scram is modeled in the RPS fault tree; surrogate element is used. 

g SLOCA MLOCA LLOCA ATWS LOOP C

0.122 1.50E-05 1.00E-07 1.23E-08 7.73E-10 2.77E-02 2.70.387 4.50E-02 4.00E-03 5.91E-04 9.53E-05 5.72E-01 3.50.707 2.50E-01 4.00E-02 1.55E-02 5.77E-03 8.99E-01 5.2

SLOCA and MLOCA IE frequencies are taken from NURE/CR-4840, Figure 3-6, as in SPRA. LLOCA sum of SG, RCP, PRESURIZER, and .1 times MLOCA. ATWS from RPS LOOP From Offsite Power CD-EQ Sum of RVF,SG,RCS piping, and 3 buildings (Containment, Aux., Turbine) Plant-specific SPRA assignments are used when available 
4 Seismic Event Modeling and Seism

 4-7 Handbook Vo

Table 4-4 SSC Fragilities and Their Treatment in Plant C SPAR-EE 

SSC Description Median Capacity (g) 

βr βu SSC Failure probability Comment 

Reactor Pressure Vessel 2 0.3 0.35 6.53E-10 CD 

1 2 0.3 0.35 1.83E-04 CD Reactor Pressure Vessel Supports 2 0.3 0.35 1.20E-02 CD 

Steam Generators 2.5 0.3 0.40 7.73E-10 CD 

2 2.5 0.3 0.40 9.53E-05 CD Steam Generator Supports 2.5 0.3 0.40 5.77E-03 CD 

3.8 0.35 0.50 8.82E-09 CD 

3 3.8 0.3 0.35 3.61E-07 CD Reactor Coolant System Piping 

3.8 0.3 0.35 1.32E-04 CD 

1.1 0.2 0.35 2.45E-08 CD 

4 1.1 0.2 0.35 4.78E-03 CD Buildings (including containment, turbine and auxiliary buildings) 1.1 0.2 0.35 1.36E-01 CD 

CD-EQ1 sum of 1,2,3,4 3.48E-08 CD 

5 CD-EQ2 5.06E-03 CD 

CD-EQ3 1.54E-01 CD Reactor Coolant Pumps 2.5 0.3 0.40 7.73E-10 LLOCA 

6 2.5 0.3 0.40 9.53E-05 LLOCA Reactor Coolant Pump Supports 2.5 0.3 0.40 5.77E-03 LLOCA 

Pressurizer 2.5 0.3 0.40 7.73E-10 LLOCA 

7 2.5 0.3 0.40 9.53E-05 LLOCA Pressurizer Supports 2.5 0.3 0.40 5.77E-03 LLOCA 

** 1.00E-08 LLOCA 

8 10% of MLOCA ** 4.00E-04 LLOCA 

** 4.00E-03 LLOCA 

LLOCA-EQ1 sum of 6,7,8 1.15E-08 LLOCA 

9 LLOCA-EQ2 5.91E-04 LLOCA 

LLOCA-EQ3 1.55E-02 LLOCA SLOCA-EQ1 ** 1.50E-05 SLOCA 

10 SLOCA-EQ2 ** 4.50E-02 SLOCA 

SLOCA-EQ3 ** 2.50E-01 SLOCA 

11 Offsite Power 0.3 0.3 0.35 2.55E-02 LOOP-EQ-1 

0.3 0.3 0.35 7.10E-01 LOOP-EQ-1 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-8 

SSC Description Median Capacity (g) 

βr βu SSC Failure probability Comment 

0.3 0.3 0.35 9.69E-01 LOOP-EQ-3 

Control Rod Drive Mechanism 1.8 0.3 0.40 3.67E-08 RPS-EQ-1 

12 1.8 0.3 0.40 1.06E-03 RPS-EQ-2 Reactor Core Upper Internals 1.8 0.3 0.40 3.08E-02 RPS-EQ-3 

1.45 0.3 0.35 3.95E-08 EDG-EQ-1 

13 EDGs 1.45 0.3 0.35 2.08E-03 EDG-EQ-2 

1.45 0.3 0.35 5.96E-02 EDG-EQ-3 

CST 1.1 0.3 0.35 9.20E-07 AFW-EQ-1 

14 1.1 0.3 0.35 1.17E-02 AFW-EQ-2 

 1.1 0.3 0.35 1.69E-01 AFW-EQ-3 CCW 1.45 0.3 0.35 3.95E-08 CCW-EQ-1 

15 1.45 0.3 0.35 2.08E-03 CCW-EQ-2 

 1.45 0.3 0.35 5.96E-02 CCW-EQ-3 RWST 1.1 0.3 0.35 9.20E-07 HPI-EQ-1 * 

16 1.1 0.3 0.35 1.17E-02 HPI-EQ-2 * 

 1.1 0.3 0.35 1.69E-01 HPI-EQ-3 * 

1.1 0.3 0.35 9.20E-07 SWS-EQ-1 

17 1.1 0.3 0.35 1.17E-02 SWS-EQ-2 

Screenhouse 

1.1 0.3 0.35 1.69E-01 SWS-EQ-2 

1.6 0.3 0.35 1.18E-08 DC-EQ-1 

18 1.6 0.3 0.35 1.04E-03 DC-EQ-2 

Battery Chargers 

1.6 0.3 0.35 3.82E-02 DC-EQ-3 

Notes: 

* also use in LPI-EQ1 

 LPI-EQ2  LPI-EQ3 

** SLOCA and MLOCA IE frequencies are taken from NURE/CR-4840, Figure 3-6. 

g level SLOCA MLOCA 

 0.122 1.50E-05 1.00E-07  0.387 4.50E-02 4.00E-03  0.707 2.50E-01 4.00E-02 
 4 Seismic Event Modeling and Seismic Risk Quantification 

 4-9 Handbook Vol. 2 – External Events

Generally, the ceramic insulators with the lowest fragilities among the SSCs modeled in the 

PRAs govern the occurrence of LOOP following a seismic event in many plants. The generic 

fragility data for ceramic insulators may be taken from Ref. 4-4, if not already available in the 

plant-specific documentation. Appendix 4B provides a convenient table for generic seismic 

fragilities of commonly considered SSCs. 

The fragilities of the key SSCs can be ordered from lowest to highest in a table; the lower 

fragilities will determine the number of bins and their ranges; the lowest of the critical SSC 

fragilities would help determine the highest bin. A critical SSC is one if failed would lead to core 

damage: examples include containment, fuel, reactor pressure vessel, Steam generators 

including their supports, etc. 

Bin definitions may be revisited/revised after SSC fragilities are modeled. 

Table 4B-1 gives the generic SSC seismic fragilities. The table also provides the SSC failure 

probabilities in each bin. 

Tables 4-2 and 4-3 show some examples of how SSC fragilities are used in two plant SPAR-EE 

models. 

The following list illustrates the candidate SSCs for a SPRA (the list is taken from a specific 

SPAR and is not intended to be an exhaustive list). 

Important Structures 

Containment building 

Concrete internal structure 

Auxiliary building 

Turbine building 

Intake structure 

Refueling water and condensate storage tanks 

Diesel Generator fuel oil storage tank (buried) 

Auxiliary saltwater system piping (buried) 

Major Plant System 

Nuclear steam supply system 

Residual heat removal system 

Safety Injection system 

Component cooling water system 

Chemical and volume control system 

Auxiliary saltwater system 

Containment spray system 

Main steam system 

Auxiliary feedwater system 

Diesel generator and auxiliaries 

Containment building ventilation system 

Control room ventilation system 

Vital electrical room ventilation system 

4160 V (vital) electrical system 

480 V (vital) electrical system 

125 V DC electrical system 

Operator instrumentation and control system 

NSSS instrumentation and control system 

Off-site power system 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-10 

Typical Generic Component Categories 

Electrical penetrations 

Balance-of-plant piping and supports 

Air and motor operated valves 

Cable tray, conduits, and supports 

HVAC ducting and supports 

 

4.2.5 Event Tree Models 

The three seismic event tree models developed for the three seismic bins are shown in Figures 

4-1 through 4-3. 

The example SPRA also modeled medium loss-of-coolant accident (MLOCA), but its CDF was 

not dominant. It is left out of the current SPAR-EE model. If necessary, it can be added as a 

transfer into the seismic event trees with minimal additional work. Other events may also be 

considered on a plant-specific basis and may be added to the model as needed. 

4.2.6 Fault Tree Models 

The following new fault trees are introduced to represent the seismic event tree nodes. Each of 

these fault trees contain a single probability and allow transfer into a target event tree, or directly 

go to a CD end state: 

CD-EQ1 

CD-EQ2 

CD-EQ3 

LLOCA-EQ1 

LLOCA-EQ2 

LLOCA-EQ3 

LOOP-EQ1 

LOOP-EQ2 

LOOP-EQ3 

SLOCA-EQ1 

SLOCA-EQ2 

SLOCA-EQ3 

The existing front line and support system fault trees need to be modified to include seismic 

faults. Figure 4-4 shows an example for a front line system. The RPS fault tree top logic is 

revised to include seismic failure basic events. The seismic subtree introduced into the RPS 

fault tree is shown in Figure 4-5. 

Figures 4-6, 4-7, and 4-8 show how seismic subtrees are introduced into a support system. 

Seismic fault trees can be added to as many system models as needed, determined by the 

number of low fragility SSCs. 

The seismic sub trees are only activated when the seismic event bin in question is quantified 

and its flag is set to TRUE.
4 Seismic Event Modeling and Seism

 4-11 Handbook Vo

LOOP-EQ1

LOSS OF

OFFSITE 

POWER

SLOCA-EQ1

SMALL LOCA

EVENT

LLOCA-EQ1

LARGE LOCA 

EVENT

CD-EQ1

DIRECT FUEL

DAMAGE 

EVENTS

IE-EQK-BIN-1

SEISMIC

INITIATOR 

(0.05 - 0.3 g)

# 1 2 3 4 5 

 EQK-BIN-1 - Seismic Event Tree BIN-1 (0.05 - 0.3 g) 

Figure 4-1 Seismic Event BIN-1 Event Tree 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-12 

LOOP-EQ2

LOSS OF

OFFSITE 

POWER

SLOCA-EQ2

SMALL LOCA

EVENT

LLOCA-EQ2

LARGE LOCA 

EVENT

CD-EQ2

DIRECT FUEL

DAMAGE 

EVENTS

IE-EQK-BIN-2

SEISMIC

INITIATOR 

(0.3 - 0.5 g)

# 1 2 3 4 5 

 EQK-BIN-2 - Sesimic Event Tree BIN-2 (0.3 - 0.5 g) 

Figure 4-2 Seismic Event BIN-2 Event Tree 
4 Seismic Event Modeling and Seism

 4-13 Handbook Vo

LOOP-EQ3

LOSS OF

OFFSITE 

POWER

SLOCA-EQ3

SMALL LOCA

EVENT

LLOCA-EQ3

LARGE LOCA 

EVENT

CD-EQ3

DIRECT FUEL

DAMAGE 

EVENTS

IE-EQK-BIN-3

SEISMIC 

INITIATOR 

(> 0.5 g)

# 1 2 3 4 5 

 EQK-BIN-3 - Sesimic Event Tree BIN-3 (> 0.5 g) 

Figure 4-3 Seismic Event BIN-3 Event Tree
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-14 

RPS

1.210E-6

RPS-ROD-CF-RCCAS RPS-1

TRUE

/LOOP RPS-2

158

RPS-SEISMIC-EQ

ELECTRICAL FAILURES

ELECTRICAL FAILURES

REACTOR FAILS

TO TRIP (ANALOG

SERIES)

CCF 10 OR MORE

RCCAS FAIL TO

DROP

Contribution of Seismic

Event to RPS Failure 

 RPS - REACTOR SHUTDOWN 2005/07/06 

Figure 4-4 RPS Fault Tree (partial top showing introduction of seismic faults) 
4 Seismic Event Modeling and Seism

 4-15 Handbook Vo

RPS-SEISMIC-EQ

GATE-158-0 GATE-158-1 GATE-158-2

FALSE

EQ-BIN-1-OCCURS

FALSE

EQ-BIN-2-OCCURS

FALSE

EQ-BIN-3-OCCURS

7.730E-10

EQ-BIN-1-RPS-FA

9.530E-5

EQ-BIN-2-RPS-FA

5

EQ-BIN-3-RPS-F

Seismic Event BIN-1

Occurs

Seismic Event BIN-2

Occurs

Seismic

EventBIN-3

Occurs

Contribution of Seismic

Event to RPS Failure

Contribution of Seismic Events

BIN-1 to RPS Failure 

Contribution of Seismic Event

BIN-2 to RPS Failure 

Contribution of Seismic 

BIN-3 to RPS Failu

 RPS-SEISMIC-EQ - Contribution of Seismic Event to RPS Failure 2005/07/07 Page 

Figure 4-5 RPS-SEISMIC-EQ Fault Tree
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-16 

EPS-DGA

65

EPS-ESW-A

5.865E-4

EPS-DGN-CF-RUN

2.117E-2

EPS-DGN-FR-DGA

9.000E-3

N-TM-DGA

61

EPS-DCP-NK01

8.360E-5

EPS-DGN-CF-START

1

EDG-SEISM

DIESEL

GENERATOR A

IS UNAVAILABLE

ESSENTIAL SERVICE

WATER TO DG A

IS UNAVAILABLE

AVAILABLE

TEST AND

ENANCE

DIESEL

GENERATOR A

FAILS TO RUN

DIVISION 1

DC POWER

IS UNAVAILABLE

COMMON CAUSE

FAILURE OF DIESEL

GENERATORS TO RUN

COMMON CAUSE FAILURE

OF DIESEL GENERATORS

TO START

Contributio

Events to E

 EPS-DGA - CALLAWAY DIESEL GENERATOR A 2005/08/3

Figure 4-6 Adding Seismic Failures to a Support System - Figure 1 of 3 
4 Seismic Event Modeling and Seism

 4-17 Handbook Vo

EPS-DGB

66

EPS-ESW-B

5.865E-4

EPS-DGN-CF-RUN

2.117E-2

EPS-DGN-FR-DGB

9.000E-3

EPS-DGN-TM-DGB

62

EPS-DCP-NK02

8.360E-5

EPS-DGN-CF-START

EDG-SEISM

ESSENTIAL SERVICE

WATER TO DG B

IS UNAVAILABLE

DIESEL

GENERATOR B

IS UNAVAILABLE

G B UNAVAILABLE

DUE TO TEST AND

MAINTENANCE

DIESEL

GENERATOR B

FAILS TO RUN

DIVISION 2

DC POWER

IS UNAVAILABLE

COMMON CAUSE

FAILURE OF DIESEL

GENERATORS TO RUN

COMMON CAUSE FAILURE

OF DIESEL GENERATORS

TO START

Contribut

Events to 

 EPS-DGB - CALLAWAY DIESEL GENERATOR B 2005/08/

Figure 4-7 Adding Seismic Failures to a Support System - Figure 2 of 3 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-18 

EDG-SEISMIC-FAILURES

EDG-BIN-1

FALSE

EQ-BIN-1-OCCURS

3.950E-8

EDG-EQ-1-FA

EDG-BIN-2

FALSE

EQ-BIN-2-OCCURS

2.080E-3

EDG-EQ-2-FA

EDG-BIN-3

FALSE

EQ-BIN-3-OCCURS

Seismic Event

BIN-3 Occurs

Seismic Event

BIN-2 Occurs

Seismic Event

BIN-1 Occurs

Contribution

of Seismic Events

to EDG Failure

Contribution

of Seismic Events

to EDG Failure

BIN-1

Contribution

of Seismic Events

to EDG Failure

BIN-2

 EDG-SEISMIC-FAILURES - Contribution of Seismic Events to EDG Failures 2005/08/30 

Figure 4-8 Adding Seismic Failures to a Support System - Figure 3 of 3 
 4 Seismic Event Modeling and Seismic Risk Quantification 

 4-19 Handbook Vol. 2 – External Events

4.2.7 New Basic Events 

The phrase basic event is used for any record in the SPAR-EE data base, which can be 

accessed with the SAPHIRE menu items MODIFY / BASIC EVENT. Four types of new basic 

events are introduced: 

1. Initiating event frequencies; 

2. basic events; 

3. flags – house events; 

4. Fault tree (FT) names; some FT names can be used as basic events (FT not further 

developed; FT name is used as the basic event). 

Example of basic events introduced in this SPAR-EE are given in Table 4-5. 

For some basic events represented by the FT value, the process flags are set to type W to 

make sure that the success path includes the success probability of the FT. This is done for 

basic events like CD-EQ3 where the seismic failure probability is very high. 

4.2.8 Application to SMA Plants 

The model described above is applicable to plants which have SMA. For an SMA plant, the 

following process applies: 

i). Obtain the seismic hazard vector from Appendix 4A. Calculate BIN frequencies and 

assign bin acceleration levels. 

ii). Examine the SMA documentation to locate any SSC fragilities and/or HCLPFs. 

Supplement that information with generic fragilities from Appendix 4B. 

If a plant-specific HCLPF value is given in SMA, use that value and the corresponding βr and βu

from Table 4B-1 to calculate median acceleration. Then use the median acceleration and the 

betas to calculate SSC failure probabilities for each BIN. 

iii). Once the above data is assembled, proceed with modeling as in SPRA. 

4.3 Special Modeling Considerations 

This section discusses some special issues worth noting for seismic scenario modeling. 

4.3.1 Non-safety Systems 

The non-safety systems credited in the PRA have high likelihood of failure in BINs 2 and 3. As 

a precaution, they should not be credited at least in BINs 2 and 3. Such systems include main 

feedwater, normal service water, and instrument and service air. 

4.3.2 Seismically-induced LOOP 

The frequencies of seismically-induced LOOP events, based on the lowest fragility SSCs (such 

as ceramic insulators) can be calculated with the information available in Appendices 4A and 

4B. Such a calculation is done for all 72 SPAR model plants and is given in Appendix 1 of this 

volume. 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-20 

Table 4-5 New Basic Events 

Name Description Calc. Prob. CD-EQ1 DIRECT FUEL DAMAGE EVENTS 2.77E-06 FT name; also CD-EQ2 DIRECT FUEL DAMAGE EVENTS 3.55E-02 FT name; also CD-EQ3 DIRECT FUEL DAMAGE EVENTS 5.27E-01 FT name; also EQ-BIN-1-OCCURS Seismic Event BIN-1 Occurs 0.00E+00 Flag (housEQ-BIN-1-RHR-FA Contribution of Seismic Event BIN-1 to RHR Failure 1.79E-04 BE EQ-BIN-1-RPS-FA Contribution of Seismic Events BIN-1 to RPS Failure 7.73E-10 BE EQ-BIN-1-SWS-FA Contribution of Seismic BIN-1 to SWS Failure 1.65E-08 BE EQ-BIN-2-OCCURS Seismic Event BIN-2 Occurs 0.00E+00 Flag (housEQ-BIN-2-RHR-FA Contribution of Seismic BIN-2 to RHR Failure 1.45E-01 BE EQ-BIN-2-RPS-FA Contribution of Seismic Event BIN-2 to RPS Failure 9.53E-05 BE EQ-BIN-2-SWS-FA Contribution of Seismic BIN-2 to SWS Failure 4.68E-02 BE EQ-BIN-3-OCCURS Seismic Event BIN-3 Occurs 0.00E+00 Flag (housEQ-BIN-3-RHR-FA Contribution of Seismic Event BIN-3 to RHR Failure 5.99E-01 BE EQ-BIN-3-RPS-FA Contribution of Seismic Event BIN-3 to RPS Failure 5.77E-03 BE EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure 6.30E-01 BE IE-EQK-BIN-1 SEISMIC INITIATOR (0.05 - 0.3 g) 2.84E-04 IE IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 1.26E-05 IE IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 7.21E-06 IE LLOCA-EQ1 LARGE LOCA EVENT 1.23E-08 FT name; also LLOCA-EQ2 LARGE LOCA EVENT 5.91E-04 FT name; also LLOCA-EQ3 LARGE LOCA EVENT 1.55E-02 FT name; also LOOP-EQ1 LOSS OF OFFSITE POWER 2.77E-02 FT name; also LOOP-EQ2 LOSS OF OFFSITE POWER 5.72E-01 FT name; also LOOP-EQ3 LOSS OF OFFSITE POWER 8.99E-01 FT name; also RHR-SEISMIC-EQ Contribution of Seismic Event to RHR Failure 1.00E+00 FT naRPS-SEISMIC-EQ Contribution of Seismic Event to RPS Failure 1.00E+00 FT naSLOCA-EQ1 SMALL LOCA EVENT 1.50E-05 FT name; also SLOCA-EQ2 SMALL LOCA EVENT 4.50E-02 FT name; also SLOCA-EQ3 SMALL LOCA EVENT 2.50E-01 FT name; also SWS-SEISMIC-EQ Contribution of Seismic Events to SWS Failure (Screenhouse) 1.00E+00 FT na
 4 Seismic Event Modeling and Seismic Risk Quantification 

 4-21 Handbook Vol. 2 – External Events

It is recommended that LOOP conditions are postulated without offsite power recovery for 

SLOCA and LLOCA paths (e.g., emergency buses are supported only by the onsite safetyrelated power sources). 

If credit is taken for other AC power sources (other than normal offsite power and onsite 

emergency power) for SBO analysis, these power sources may need to be discredited. 

4.3.3 Operator Actions 

The failure probabilities of some operator actions may increase under high-g seismic event 

conditions. To be prudent the analyst should examine the set of operator actions modeled in 

the PRA and revise their HEPs if needed, for seismic scenarios. Especially, operator actions 

implied in recovery (such as power recovery) must be critically examined and adjusted if 

necessary. 

In the absence of accepted methods, sensitivity analyses may be performed to understand and 

assess risk factors. 

See also relay chatter section below. 

4.3.4 Relay Chatter 

The relay chatter evaluation addresses the questions of 

a. whether the overall plant safety system could be adversely affected by relay malfunction 

in a seismic event and 

b. whether the relays for which malfunction is unacceptable have an adequate seismic 

capacity. 

Relay chatter may introduce system actuation failure or spurious actuation. Operator actions 

may be needed for starting otherwise auto-start safety systems. This handbook does not 

address modeling of relay chatter explicitly. However, it should be noted that generic relay 

seismic fragilities may be on the lower side, as shown in Table 4B-1. 

See NUREG/CR-4840, page 3-32 for a discussion. 

Unless the Individual Plant Examination of External Events (IPEEE) or similar reports identified 

relay chatter vulnerabilities, this issue need not be pursued for evaluation purposes. 

4.3.5 Seismically-induced Internal Flooding 

In seismic BINs 2 and 3, non-safety system piping failures in the Turbine building could create 

internal flooding concerns that can potentially fail other components either directly or through 

propagation of the flood into other areas. These issues are not further pursued in this 

handbook. 

4.3.6 Seismically-induced Fires 

The following four seismic-fire interaction issues are identified in the literature: 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-22 

1. Seismically induced fires, 

2. Degradation of fire suppression systems and features, 

3. Spurious actuation of suppression and/or detection systems, and 

4. Degradation of manual firefighting effectiveness. 

It is recommended that a Fire PRA include a qualitative assessment of these issues. 

4.3.7 Seismically-induced SLOCA and MLOCA 

Generic frequencies of seismically induced SLOCA and MLOCA can be calculated from 

Figure 3-6 of NUREG/CR-4840. Figure 4-9 of this handbook shows the calculations for the pga 

values for the three seismic bins discussed in Section 4.2. A curve-fit has been implemented to 

the graph in Figure 3-6 to provide analysts SLOCA and MLOCA probabilities for different pga 

values. An MS EXCEL file containing these values is placed in ADAMS with accession number 

ML071220066. 

4.4 CDF Quantification for Seismic Events 

This section summarizes the CDF quantification for seismic events only. 

Seismic sequences are automatically generated from the three seismic event trees and their 

CDF frequencies are quantified and CDF cutsets are identified using the SAPHIRE software. 

Tables 4-6 through 4-8 provide an illustration of the results and output for a plant-specific 

SPAR-EE seismic PRA model. 

4.5 LERF Quantification for Seismic Events 

LERF modeling and quantification is not currently addressed. 

4.6 References 

4-1. U.S. Nuclear Regulatory Commission, “Risk Assessment of Operational Events 

Handbook: Volume 1 - Internal Events,” Revision 1.01, December 2007. 

4-2. U.S. Nuclear Regulatory Commission, “Revised Livermore Seismic Hazard Estimates for 

Sixty-Nine Nuclear Power Plant Sites East of the Rocky Mountains,” NUREG-1488, April 

1994. 

4-3. Idaho National Laboratory, “A Feasibility and Demonstration Study – Incorporating 

External Events into SPAR Models,” February 2005. 

4-4. U.S. Nuclear Regulatory Commission, “Methodology for Analyzing Precursors to 

Earthquake-Initiated and Fire-Initiated Accident Sequences," NUREG/CR-6544, April 

1998. 
 4 Seismic Event Modeling and Seismic Risk Quantification 

 4-23 Handbook Vol. 2 – External Events

4-5. U.S. Nuclear Regulatory Commission, “Procedures for the External Event Core Damage 

Frequency Analyses for NUREG-1150,” NUREG/CR-4840, November 1990. 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-24 

Figure 4-9 Estimation of Seismically-induced SLOCA and MLOCA Probabilities 

(NUREG/CR-4840. Figure 3-6) 
 4 Seismic Event Modeling and Seismic Risk Quantification 

 4-25 Handbook Vol. 2 – External Events

Table 4-6 Seismic Event BIN Frequencies 

IE Freq. CCDP CDF 

EQK-BIN-1 2.84E-04 2.55E-05 7.26E-09 

EQK-BIN-2 1.26E-05 3.86E-02 4.86E-07 

EQK-BIN-3 7.21E-06 6.13E-01 4.42E-06 

Sum = 3.04E-04 4.91E-06 

Table 4-7 Seismic Event Sequence Frequencies 

Event tree Sequence CDF Cutsets End 

State 

EQK-BIN-3 5 3.80E-06 1 CD-EQK Direct CD 

EQK-BIN-3 3-11 5.37E-07 3 CD-EQK SLOCA 

EQK-BIN-2 5 4.47E-07 1 CD-EQK Direct CD 

EQK-BIN-3 4-3 3.33E-08 2 CD-EQK LLOCA 

EQK-BIN-2 3-11 2.65E-08 2 CD-EQK SLOCA 

EQK-BIN-3 2-17 2.48E-08 32 CD-EQK LOOP 

EQK-BIN-2 2-17 7.17E-09 29 CD-EQK LOOP 

EQK-BIN-3 3-13 5.37E-09 1 CD-EQK SLOCA 

EQK-BIN-3 3-24 4.92E-09 4 CD-EQK SLOCA 

EQK-BIN-3 3-03 3.37E-09 56 CD-EQK SLOCA 

EQK-BIN-1 2-18-03 3.04E-09 32 CD-EQK LOOP 

EQK-BIN-2 2-18-03 2.77E-09 32 CD-EQK LOOP 

EQK-BIN-3 2-19-13 2.01E-09 6 CD-EQK LOOP 

EQK-BIN-3 2-19-04 1.68E-09 6 CD-EQK LOOP 

EQK-BIN-1 2-17 1.67E-09 18 CD-EQK LOOP 

EQK-BIN-1 2-18-06 1.51E-09 26 CD-EQK LOOP 

EQK-BIN-2 2-18-06 1.38E-09 26 CD-EQK LOOP 

EQK-BIN-3 2-18-03 8.83E-10 24 CD-EQK LOOP 

EQK-BIN-1 5 7.87E-10 1 CD-EQK Direct CD 

EQK-BIN-2 3-03 6.15E-10 34 CD-EQK SLOCA 

EQK-BIN-3 3-12 5.37E-10 1 CD-EQK SLOCA 

EQK-BIN-3 2-19-20 4.51E-10 5 CD-EQK LOOP 

EQK-BIN-3 2-18-06 4.38E-10 20 CD-EQK LOOP 

EQK-BIN-2 4-3 3.48E-10 1 CD-EQK LLOCA 

EQK-BIN-3 4-2 3.28E-10 7 CD-EQK LLOCA 

EQK-BIN-3 2-19-09 2.65E-10 1 CD-EQK LOOP 

EQK-BIN-2 3-13 2.65E-10 1 CD-EQK SLOCA 

EQK-BIN-3 2-19-19 2.24E-10 23 CD-EQK LOOP 

EQK-BIN-3 2-19-18 2.20E-10 3 CD-EQK LOOP 

EQK-BIN-1 2-18-45 1.80E-10 32 CD-EQK LOOP 

EQK-BIN-2 2-18-45 1.64E-10 31 CD-EQK LOOP 

EQK-BIN-3 3-23 1.58E-10 14 CD-EQK SLOCA 

EQK-BIN-2 3-24 5.40E-11 1 CD-EQK SLOCA 

EQK-BIN-3 2-12 5.03E-11 8 CD-EQK LOOP 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-26 

Event tree Sequence CDF Cutsets End 

State 

EQK-BIN-3 2-02-05 4.70E-11 10 CD-EQK LOOP 

EQK-BIN-2 4-2 4.46E-11 1 CD-EQK LLOCA 

EQK-BIN-3 3-07 4.44E-11 1 CD-EQK SLOCA 

EQK-BIN-3 2-18-45 4.01E-11 12 CD-EQK LOOP 

EQK-BIN-1 2-18-09 3.28E-11 7 CD-EQK LOOP 

EQK-BIN-2 2-18-09 3.00E-11 7 CD-EQK LOOP 

EQK-BIN-2 3-07 2.94E-11 1 CD-EQK SLOCA 

EQK-BIN-2 3-12 2.65E-11 1 CD-EQK SLOCA 

EQK-BIN-2 2-19-20 2.33E-11 5 CD-EQK LOOP 

EQK-BIN-1 2-18-12 2.32E-11 7 CD-EQK LOOP 

EQK-BIN-2 2-18-12 2.12E-11 7 CD-EQK LOOP 

EQK-BIN-1 2-18-42 2.08E-11 8 CD-EQK LOOP 

EQK-BIN-2 2-18-42 1.90E-11 8 CD-EQK LOOP 

EQK-BIN-2 2-19-09 1.37E-11 1 CD-EQK LOOP 

EQK-BIN-2 3-23 9.83E-12 6 CD-EQK SLOCA 

EQK-BIN-2 2-12 9.76E-12 4 CD-EQK LOOP 

EQK-BIN-3 2-18-09 8.14E-12 4 CD-EQK LOOP 

EQK-BIN-2 2-02-05 7.90E-12 4 CD-EQK LOOP 

EQK-BIN-2 2-19-04 6.42E-12 2 CD-EQK LOOP 

EQK-BIN-2 2-19-13 6.42E-12 4 CD-EQK LOOP 

EQK-BIN-3 2-18-12 4.21E-12 2 CD-EQK LOOP 

EQK-BIN-2 2-19-18 2.74E-12 1 CD-EQK LOOP 

EQK-BIN-3 2-18-42 2.52E-12 2 CD-EQK LOOP 

EQK-BIN-3 3-05 1.71E-12 1 CD-EQK SLOCA 

EQK-BIN-2 3-05 1.13E-12 1 CD-EQK SLOCA 

TOTALS 4.91E-06 591 
4 Seismic Event Modeling and Seism

 4-27 Handbook Vo

Table 4-8 Seismic Event CDF Cutsets 

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

1 82.97 3.80E-6 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 CD-EQ3 DIRECT FUEL DAMAGE EVENTS 

2 11.73 5.37E-7 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  SLOCA-EQ3 SMALL LOCA EVENT 

3 9.75 4.47E-7 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 CD-EQ2 DIRECT FUEL DAMAGE EVENTS 

4 0.73 3.33E-8 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LLOCA-EQ3 LARGE LOCA EVENT 

5 0.58 2.65E-8 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 EQ-BIN-2-SWS-FA Contribution of Seismic BIN-2 to SWS Failure  SLOCA-EQ2 SMALL LOCA EVENT 

6 0.20 8.69E-9 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 AFW-TDP-FS-1C AFW TDP 1C FAILS TO START  /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER  /SLOCA-EQ3 SMALL LOCA EVENT 

7 0.16 7.25E-9 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 AFW-TDP-TM-1C AFW TDP 1C UNAVAILABLE DUE TO TEST AND MAINTENANCE 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-28 

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER  /SLOCA-EQ3 SMALL LOCA EVENT 

8 0.14 6.00E-9 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 AFW-TDP-FR-1C AFW TDP 1C FAILS TO RUN  /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER  /SLOCA-EQ3 SMALL LOCA EVENT 

9 0.12 5.37E-9 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure 

RCS-XHE-XMCDOWN1 OPERATOR FAILS TO INITIATE RAPID COOLDOWN 

 SLOCA-EQ3 SMALL LOCA EVENT 

10 0.11 4.92E-9 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-RPS-FA Contribution of Seismic Event BIN-3 to RPS Failure  SLOCA-EQ3 SMALL LOCA EVENT 

11 0.07 3.07E-9 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-RHR-FA Contribution of Seismic Event BIN-3 to RHR Failure  LPR-XHE-XM OPERATOR FAILS TO INITIATE LPR SYSTEM  SLOCA-EQ3 SMALL LOCA EVENT 
4 Seismic Event Modeling and Seism

 4-29 Handbook Vo

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

12 0.05 2.02E-9 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 AFW-TDP-FS-1C AFW TDP 1C FAILS TO START  EQ-BIN-2-SWS-FA Contribution of Seismic BIN-2 to SWS Failure  LOOP-EQ2 LOSS OF OFFSITE POWER 

13 0.04 1.68E-9 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 AFW-TDP-TM-1C AFW TDP 1C UNAVAILABLE DUE TO TEST AND MAINTENANCE  EQ-BIN-2-SWS-FA Contribution of Seismic BIN-2 to SWS Failure  LOOP-EQ2 LOSS OF OFFSITE POWER 

14 0.04 1.45E-9 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 AFW-MOV-CC-102 AFW TDP 1C MAIN STEAM VALVE 102 FAILS TO OPEN  /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER  /SLOCA-EQ3 SMALL LOCA EVENT 

15 0.04 1.40E-9 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 AFW-TDP-FR-1C AFW TDP 1C FAILS TO RUN  EQ-BIN-2-SWS-FA Contribution of Seismic BIN-2 to SWS Failure  LOOP-EQ2 LOSS OF OFFSITE POWER 

16 0.03 9.23E-10 IE-EQK-BIN-1 SEISMIC INITIATOR (0.05 - 0.3 g) 

 EPS-DGN-CF-RUN COMMON CAUSE FAILURE OF DIESEL GENERATORS TO RUN  EPS-XHE-XL-NR08H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 8 HOURS  LOOP-EQ1 LOSS OF OFFSITE POWER 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-30 

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

 /RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 

17 0.02 8.44E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 EPS-DGN-CF-RUN COMMON CAUSE FAILURE OF DIESEL GENERATORS TO RUN  EPS-XHE-XL-NR08H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 8 HOURS  LOOP-EQ2 LOSS OF OFFSITE POWER  /RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 

18 0.02 8.36E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-RPS-FA Contribution of Seismic Event BIN-3 to RPS Failure  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER 

PPR-SRV-OOSRV3BLIQ SAFETY RELIEF VALVE 3B FAILS TO RECLOSE AFTER PASSING WATER 

 /SLOCA-EQ3 SMALL LOCA EVENT 

19 0.02 8.36E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-RPS-FA Contribution of Seismic Event BIN-3 to RPS Failure  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER 

PPR-SRV-OOSRV3ALIQ SAFETY RELIEF VALVE 3A FAILS TO RECLOSE AFTER PASSING WATER 

 /SLOCA-EQ3 SMALL LOCA EVENT 
4 Seismic Event Modeling and Seism

 4-31 Handbook Vo

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

20 0.02 7.87E-10 IE-EQK-BIN-1 SEISMIC INITIATOR (0.05 - 0.3 g) 

 CD-EQ1 DIRECT FUEL DAMAGE EVENTS 

21 0.02 7.87E-10 IE-EQK-BIN-1 SEISMIC INITIATOR (0.05 - 0.3 g) 

 AFW-CKV-CC-301 CONDENSATE STORAGE TANK DISCHARGE CHECK VALV

FAILS 

 LOOP-EQ1 LOSS OF OFFSITE POWER 

22 0.02 7.87E-10 IE-EQK-BIN-1 SEISMIC INITIATOR (0.05 - 0.3 g) 

 AFW-XHE-XA-SUCT OPERATOR FAILS TO ALIGN SWS/XTIE RMST TO AFW SYSTEM  LOOP-EQ1 LOSS OF OFFSITE POWER 

23 0.02 7.20E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 AFW-CKV-CC-301 CONDENSATE STORAGE TANK DISCHARGE CHECK VALV

FAILS 

 LOOP-EQ2 LOSS OF OFFSITE POWER 

24 0.02 7.20E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 AFW-XHE-XA-SUCT OPERATOR FAILS TO ALIGN SWS/XTIE RMST TO AFW SYSTEM  LOOP-EQ2 LOSS OF OFFSITE POWER 

25 0.02 7.06E-10 IE-EQK-BIN-1 SEISMIC INITIATOR (0.05 - 0.3 g) 

 EPS-DGN-FR-1A DIESEL GENERATOR 1A FAILS TO RUN  EPS-DGN-FR-1B DIESEL GENERATOR 1B FAILS TO RUN  EPS-XHE-XL-NR08H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 8 HOURS  LOOP-EQ1 LOSS OF OFFSITE POWER  /RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-32 

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

26 0.02 6.45E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 EPS-DGN-FR-1A DIESEL GENERATOR 1A FAILS TO RUN  EPS-DGN-FR-1B DIESEL GENERATOR 1B FAILS TO RUN  EPS-XHE-XL-NR08H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 8 HOURS  LOOP-EQ2 LOSS OF OFFSITE POWER  /RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 

27 0.02 5.80E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 AFW-PMP-FR-TD1C AFW TURBINE-DRIVEN 1C PUMP UNIT ONLY FAILS TO RUN  /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER  /SLOCA-EQ3 SMALL LOCA EVENT 

28 0.02 5.37E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure 

RCS-XHE-XMRCSDEP OPERATOR FAILS TO DEPRESSURIZE THE RCS 

 SLOCA-EQ3 SMALL LOCA EVENT 

29 0.02 4.93E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 ED-BIN-2-RHR-FA Contribution of Seismic Event BIN-2 to RHR Failure  LPR-XHE-XM OPERATOR FAILS TO INITIATE LPR SYSTEM  SLOCA-EQ2 SMALL LOCA EVENT 

30 0.02 4.62E-10 IE-EQK-BIN-1 SEISMIC INITIATOR (0.05 - 0.3 g) 
4 Seismic Event Modeling and Seism

 4-33 Handbook Vo

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

 EPS-DGN-CF-RUN COMMON CAUSE FAILURE OF DIESEL GENERATORS TO RUN  EPS-XHE-XL-NR04H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 4 HOURS  LOOP-EQ1 LOSS OF OFFSITE POWER  RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 

31 0.01 4.22E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 EPS-DGN-CF-RUN COMMON CAUSE FAILURE OF DIESEL GENERATORS TO RUN  EPS-XHE-XL-NR04H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 4 HOURS  LOOP-EQ2 LOSS OF OFFSITE POWER  RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 

32 0.01 4.18E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-RPS-FA Contribution of Seismic Event BIN-3 to RPS Failure  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER 

PPR-SRV-OOSRV3ALIQ SAFETY RELIEF VALVE 3A FAILS TO RECLOSE AFTER PASSING WATER 

 /SLOCA-EQ3 SMALL LOCA EVENT 

SWS-TRAINAALIGNED SW TRAIN A ALIGNED TO TURBINE BLDG 

33 0.01 4.18E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-34 

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

 EQ-BIN-3-RPS-FA Contribution of Seismic Event BIN-3 to RPS Failure  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER 

PPR-SRV-OOSRV3ALIQ SAFETY RELIEF VALVE 3A FAILS TO RECLOSE AFTER PASSING WATER 

 /SLOCA-EQ3 SMALL LOCA EVENT 

SWS-TRAINBALIGNED SW TRAIN B ALIGNED TO TURBINE BLDG 

34 0.01 4.18E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-RPS-FA Contribution of Seismic Event BIN-3 to RPS Failure  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER 

PPR-SRV-OOSRV3BLIQ SAFETY RELIEF VALVE 3B FAILS TO RECLOSE AFTER PASSING WATER 

 /SLOCA-EQ3 SMALL LOCA EVENT 

SWS-TRAINAALIGNED SW TRAIN A ALIGNED TO TURBINE BLDG 

35 0.01 4.18E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EQ-BIN-3-RPS-FA Contribution of Seismic Event BIN-3 to RPS Failure  EQ-BIN-3-SWS-FA Contribution of Seismic BIN-3 to SWS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER 

PPR-SRV-OOSRV3BLIQ SAFETY RELIEF VALVE 3B FAILS TO RECLOSE AFTER PASSING WATER 

 /SLOCA-EQ3 SMALL LOCA EVENT 
4 Seismic Event Modeling and Seism

 4-35 Handbook Vo

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

SWS-TRAINBALIGNED SW TRAIN B ALIGNED TO TURBINE BLDG 

36 0.01 3.53E-10 IE-EQK-BIN-1 SEISMIC INITIATOR (0.05 - 0.3 g) 

 EPS-DGN-FR-1A DIESEL GENERATOR 1A FAILS TO RUN  EPS-DGN-FR-1B DIESEL GENERATOR 1B FAILS TO RUN  EPS-XHE-XL-NR04H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 4 HOURS  LOOP-EQ1 LOSS OF OFFSITE POWER  RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 

37 0.01 3.48E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 EQ-BIN-2-SWS-FA Contribution of Seismic BIN-2 to SWS Failure  LLOCA-EQ2 LARGE LOCA EVENT 

38 0.01 3.37E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 AFW-MOV-CC-102 AFW TDP 1C MAIN STEAM VALVE 102 FAILS TO OPEN  EQ-BIN-2-SWS-FA Contribution of Seismic BIN-2 to SWS Failure  LOOP-EQ2 LOSS OF OFFSITE POWER 

39 0.01 3.23E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 EPS-DGN-FR-1A DIESEL GENERATOR 1A FAILS TO RUN  EPS-DGN-FR-1B DIESEL GENERATOR 1B FAILS TO RUN  EPS-XHE-XL-NR04H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 4 HOURS  LOOP-EQ2 LOSS OF OFFSITE POWER  RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 

40 0.01 3.17E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-36 

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  LLOCA-EQ3 LARGE LOCA EVENT  LPR-XHE-XM OPERATOR FAILS TO INITIATE LPR SYSTEM 

41 0.01 3.00E-10 IE-EQK-BIN-1 SEISMIC INITIATOR (0.05 - 0.3 g) 

 EPS-DGN-FR-1A DIESEL GENERATOR 1A FAILS TO RUN  EPS-DGN-TM-1B DIESEL GENERATOR 1B UNAVAILABLE DUE TO TEST AND MAINTENANCE  EPS-XHE-XL-NR08H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 8 HOURS  LOOP-EQ1 LOSS OF OFFSITE POWER  /RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 

42 0.01 3.00E-10 IE-EQK-BIN-1 SEISMIC INITIATOR (0.05 - 0.3 g) 

 EPS-DGN-FR-1B DIESEL GENERATOR 1B FAILS TO RUN  EPS-DGN-TM-1A DIESEL GENERATOR 1A UNAVAILABLE DUE TO TEST AND MAINTENANCE  EPS-XHE-XL-NR08H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 8 HOURS  LOOP-EQ1 LOSS OF OFFSITE POWER  /RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 

43 0.01 2.74E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 EPS-DGN-FR-1B DIESEL GENERATOR 1B FAILS TO RUN  EPS-DGN-TM-1A DIESEL GENERATOR 1A UNAVAILABLE DUE TO TEST AND MAINTENANCE  EPS-XHE-XL-NR08H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 8 HOURS 
4 Seismic Event Modeling and Seism

 4-37 Handbook Vo

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

 LOOP-EQ2 LOSS OF OFFSITE POWER  /RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 

44 0.01 2.74E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 EPS-DGN-FR-1A DIESEL GENERATOR 1A FAILS TO RUN  EPS-DGN-TM-1B DIESEL GENERATOR 1B UNAVAILABLE DUE TO TEST AND MAINTENANCE  EPS-XHE-XL-NR08H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 8 HOURS  LOOP-EQ2 LOSS OF OFFSITE POWER  /RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS 

45 0.01 2.70E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EPS-DGN-CF-RUN COMMON CAUSE FAILURE OF DIESEL GENERATORS TO RUN  EPS-XHE-XL-NR08H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 8 HOURS  LOOP-EQ3 LOSS OF OFFSITE POWER  /RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS  /SLOCA-EQ3 SMALL LOCA EVENT 

46 0.01 2.65E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  CVC-XHE-XM-BOR OPERATOR FAILS TO INITIATE EMERGENCY BORATION  EQ-BIN-3-RPS-FA Contribution of Seismic Event BIN-3 to RPS Failure  LOOP-EQ3 LOSS OF OFFSITE POWER 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-38 

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

 /SLOCA-EQ3 SMALL LOCA EVENT 

47 0.01 2.65E-10 IE-EQK-BIN-2 SEISMIC INITIATOR (0.3 - 0.5 g) 

 EQ-BIN-2-SWS-FA Contribution of Seismic BIN-2 to SWS Failure 

RCS-XHE-XMCDOWN1 OPERATOR FAILS TO INITIATE RAPID COOLDOWN 

 SLOCA-EQ2 SMALL LOCA EVENT 

48 0.01 2.30E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 AFW-XHE-XA-SUCT OPERATOR FAILS TO ALIGN SWS/XTIE RMST TO AFW SYSTEM  /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  LOOP-EQ3 LOSS OF OFFSITE POWER  /SLOCA-EQ3 SMALL LOCA EVENT 

49 0.01 2.30E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 AFW-CKV-CC-301 CONDENSATE STORAGE TANK DISCHARGE CHECK VALV

FAILS 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  LOOP-EQ3 LOSS OF OFFSITE POWER  /SLOCA-EQ3 SMALL LOCA EVENT 

50 0.01 2.06E-10 IE-EQK-BIN-3 SEISMIC INITIATOR (> 0.5 g) 

 /CD-EQ3 DIRECT FUEL DAMAGE EVENTS  EPS-DGN-FR-1A DIESEL GENERATOR 1A FAILS TO RUN  EPS-DGN-FR-1B DIESEL GENERATOR 1B FAILS TO RUN  EPS-XHE-XL-NR08H OPERATOR FAILS TO RECOVER EMERGENCY DIESEL IN 8 HOURS  LOOP-EQ3 LOSS OF OFFSITE POWER 
4 Seismic Event Modeling and Seism

 4-39 Handbook Vo

Cut 

No. 

% 

Cut 

Set 

Frequency Basic Event Description 

 /RCS-MDP-LK-BP2 RCP SEAL STAGE 2 INTEGRITY (BINDING/POPPING OPEN) FAILS  /SLOCA-EQ3 SMALL LOCA EVENT 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-40 

Appendix 4A. Generic Seismic Hazard Vectors 

The generic hazard vectors for 69 sites east of the Rocky Mountains are taken from Ref. 4-2. 

The hazard vectors for the remaining 4 sites are taken from their IPEEE submittals to the NRC. 

Table 4A-1 provides the seismic hazard vectors for the 72 SPAR plants. 

G values are in term of peak ground acceleration (pga). 
4 Seismic Event Modeling and Seism

 4-41 Handbook Vo

Table 4A-1 Seismic Hazard Vectors for the 72 SPAR Plants 

mean frequency of exceedance (per year) 

1/2 3/4 5 6/7 8 9 10 11 

ANO Beaver Valley Braidwood Browns Ferry Brunswick Byron Callaway Calvert 

g 

value 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f 

yea

0.05 .1273E-02 .8778E-03 .4297E-03 .9121E-03 .1527E-02 .5091E-03 .1083E-02 .7674E0.08 .6698E-03 .4919E-03 .2313E-03 .4560E-03 .8013E-03 .2864E-03 .4763E-03 .4321E0.15 .2016E-03 .1686E-03 .7032E-04 .1247E-03 .2428E-03 .9093E-04 .9878E-04 .1459E0.25 .7274E-04 .7056E-04 .2448E-04 .4190E-04 .9380E-04 .3227E-04 .2739E-04 .5891E0.30 .4858E-04 .5056E-04 .1595E-04 .2724E-04 .6580E-04 .2116E-04 .1684E-04 .4141E0.40 .2442E-04 .2901E-04 .7622E-05 .1309E-04 .3692E-04 .1021E-04 .7532E-05 .2292E0.50 .1369E-04 .1832E-04 .4067E-05 .7065E-05 .2316E-04 .5489E-05 .3900E-05 .1402E0.65 .6568E-05 .1027E-04 .1825E-05 .3231E-05 .1306E-04 .2488E-05 .1723E-05 .7565E0.80 .3522E-05 .6292E-05 .9232E-06 .1663E-05 .8121E-05 .1269E-05 .8721E-06 .4498E1.00 .1729E-05 .3589E-05 .4239E-06 .7792E-06 .4751E-05 .5885E-06 .4048E-06 .2490E

13 14 15 16 17 18 19 20 

Clinton Columbia Comanche Peak Cook Cooper Crystal River Davis Besse Diablo C

g 

value 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

0.05 .1547E-02 .1410E-03 .5010E-03 .1155E-02 .1482E-03 .1070E-02 0.08 .8083E-03 .6790E-04 .2729E-03 .7283E-03 .8403E-04 .5745E-03 0.15 .2457E-03 .1880E-04 .8900E-04 .2924E-03 .2765E-04 .1631E-03 0.25 .9422E-04 .6420E-05 .3578E-04 .1335E-03 .1039E-04 .5326E-04 0.30 .6543E-04 .4190E-05 .2528E-04 .9828E-04 .7035E-05 .3413E-04 0.40 .3573E-04 .2020E-05 .1421E-04 .5867E-04 .3625E-05 .1604E-04 0.50 .2171E-04 .1100E-05 .8843E-05 .3813E-04 .2083E-05 .8537E-05 0.65 .1165E-04 .5080E-06 .4890E-05 .2211E-04 .1039E-05 .3868E-05 0.80 .6894E-05 .2660E-06 .2969E-05 .1392E-04 .5796E-06 .1990E-05 1.00 .3794E-05 .1280E-06 .1681E-05 .8187E-05 .2992E-06 .9390E-06 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-42 

22 23 24 25 26 27 28 29 

Duane 

Arnold Farley Fermi Fitzpatrick Fort Calhoun Ginna Grand Gulf Hatc

g 

value 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f 

yea

0.05 .1548E-03 .1995E-03 .6010E-03 .7335E-03 .8778E-03 .8483E-03 .3306E-03 .6133E0.08 .8105E-04 .1092E-03 .2980E-03 .3537E-03 .5580E-03 .4657E-03 .1765E-03 .3186E0.15 .2378E-04 .3463E-04 .7740E-04 .8831E-04 .2306E-03 .1457E-03 .5513E-04 .9661E0.25 .8208E-05 .1268E-04 .2493E-04 .2764E-04 .1080E-03 .5283E-04 .2103E-04 .3713E0.30 .5359E-05 .8459E-05 .1603E-04 .1761E-04 .8024E-04 .3516E-04 .1448E-04 .2583E0.40 .2584E-05 .4230E-05 .7622E-05 .8284E-05 .4854E-04 .1742E-04 .7745E-05 .1416E0.50 .1397E-05 .2357E-05 .4108E-05 .4444E-05 .3187E-04 .9558E-05 .4613E-05 .8644E0.65 .6421E-06 .1124E-05 .1894E-05 .2048E-05 .1870E-04 .4403E-05 .2409E-05 .4680E0.80 .3338E-06 .6009E-06 .9902E-06 .1075E-05 .1187E-04 .2255E-05 .1395E-05 .2801E1.00 .1594E-06 .2947E-06 .4769E-06 .5206E-06 .7043E-05 .1041E-05 .7485E-06 .1567E

31/32 33 34 35 36 37/38 39 40/4

Indian 

Point Kewaunee LaSalle Limerick McGuire Millstone 2 & 3 Monticello Nine M

Point 1 

g 

value 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f 

yea

0.05 .1152E-02 .3040E-03 .8251E-03 .1220E-02 .1084E-02 .9965E-03 .3562E-03 .7302E0.08 .6552E-03 .1777E-03 .4633E-03 .6990E-03 .5582E-03 .5635E-03 .2131E-03 .3525E0.15 .2123E-03 .6422E-04 .1616E-03 .2290E-03 .1568E-03 .1823E-03 .7981E-04 .8831E0.25 .7736E-04 .2748E-04 .6797E-04 .8350E-04 .5192E-04 .6635E-04 .3511E-04 .2772E0.30 .5148E-04 .1979E-04 .4859E-04 .5550E-04 .3329E-04 .4410E-04 .2556E-04 .1769E0.40 .2562E-04 .1141E-04 .2765E-04 .2750E-04 .1553E-04 .2189E-04 .1500E-04 .8339E0.50 .1421E-04 .7212E-05 .1728E-04 .1520E-04 .8136E-05 .1211E-04 .9622E-05 .4483E0.65 .6738E-05 .4043E-05 .9548E-05 .7100E-05 .3580E-05 .5713E-05 .5493E-05 .2073E0.80 .3583E-05 .2474E-05 .5773E-05 .3730E-05 .1785E-05 .3025E-05 .3411E-05 .1090E1.00 .1749E-05 .1409E-05 .3244E-05 .1790E-05 .8089E-06 .1469E-05 .1976E-05 .5298E
4 Seismic Event Modeling and Seism

 4-43 Handbook Vo

43 44 45 46 47 48 49 50 

Oconee 1, 

2 & 3 

Oyster 

Creek Palisades Palo Verde 1, 2 & 3 Peach Bottom Perry Pilgrim Point B

g 

value 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f 

yea

0.05 .1280E-02 .8528E-03 .3924E-03 .1058E-02 .4477E-03 .2814E-02 .3125E0.08 .6937E-03 .4839E-03 .2109E-03 .6043E-03 .2466E-03 .1777E-02 .1825E0.15 .2104E-03 .1626E-03 .6870E-04 .1982E-03 .7663E-04 .7154E-03 .6573E0.25 .7353E-04 .6463E-04 .2824E-04 .7229E-04 .2710E-04 .3272E-03 .2804E0.30 .4815E-04 .4510E-04 .2019E-04 .4793E-04 .1780E-04 .2410E-03 .2017E0.40 .2328E-04 .2461E-04 .1159E-04 .2357E-04 .8628E-05 .1441E-03 .1160E0.50 .1257E-04 .1486E-04 .7331E-05 .1288E-04 .4671E-05 .9379E-04 .7319E0.65 .5725E-05 .7875E-05 .4129E-05 .5953E-05 .2142E-05 .5446E-04 .4089E0.80 .2930E-05 .4606E-05 .2540E-05 .3085E-05 .1107E-05 .3430E-04 .2493E1.00 .1360E-05 .2499E-05 .1455E-05 .1454E-05 .5224E-06 .2016E-04 .1414E

52 53 54 55/56 57 58 59 60 

Quad 

Cities 1 & 

2 

River Bend Robinson 

Saint 

Lucie 1 & 

2 

Salem 1 & 

2 

San Onofre 2 

& 3 Seabrook Sequo

g 

value 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f 

yea

0.05 .3658E-03 .1965E-03 .2717E-02 .1470E-03 .9589E-03 2.34E-03 1.33E0.08 .1948E-03 .1072E-03 .1565E-02 .8565E-04 .5429E-03 1.37E-03 7.54E0.15 .5727E-04 .3426E-04 .5469E-03 .3037E-04 .1805E-03 4.62E-04 2.44E0.25 .1965E-04 .1322E-04 .2256E-03 .1263E-04 .7102E-04 1.71E-04 8.80E0.30 .1280E-04 .9138E-05 .1600E-03 .8974E-05 .4940E-04 1.15E-04 5.82E0.40 .6139E-05 .4913E-05 .8990E-04 .5047E-05 .2686E-04 5.74E-05 2.85E0.50 .3295E-05 .2932E-05 .5574E-04 .3125E-05 .1620E-04 3.19E-05 1.55E0.65 .1492E-05 .1531E-05 .3062E-04 .1711E-05 .8599E-05 1.50E-05 7.14E0.80 .7603E-06 .8842E-06 .1849E-04 .1030E-05 .5051E-05 7.92E-06 3.68E1.00 .3519E-06 .4737E-06 .1043E-04 .5790E-06 .2764E-05 3.80E-06 1.72E
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-44 

62 63 64 65 66 67 68 69 

South 

Texas 1 & 

2 

Surry 1 & 

2 

Susqueha

nna 1 & 2 

Three Mile 

Island 

Turkey 

Point 3 & 

4 

V.C. Summer Vermont Yankee Vogt

g 

value 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f per 

year 

mean f 

yea

0.05 1.628E-04 6.033E-04 8.46E-04 .1108E-02 .1227E-03 .1833E-02 .1293E-02 .2500E0.08 9.408E-05 3.363E-04 4.68E-04 .6339E-03 .7052E-04 .9731E-03 .6738E-03 .1356E0.15 3.256E-05 1.104E-04 1.47E-04 .2076E-03 .2361E-04 .2842E-03 .1963E-03 .4152E0.25 1.312E-05 4.322E-05 5.29E-05 .7622E-04 .8904E-05 .9814E-04 .6913E-04 .1546E0.30 9.179E-06 2.998E-05 3.49E-05 .5082E-04 .6013E-05 .6448E-04 .4583E-04 .1060E0.40 5.024E-06 1.621E-05 1.71E-05 .2532E-04 .3074E-05 .3170E-04 .2286E-04 .5677E0.50 3.038E-06 9.713E-06 9.28E-06 .1404E-04 .1750E-05 .1755E-04 .1279E-05 .3415E0.65 1.613E-06 5.097E-06 4.26E-06 .6627E-05 .8616E-06 .8392E-05 .6148E-05 .1830E0.80 9.453E-07 2.955E-06 2.19E-06 .3504E-05 .4751E-06 .4535E-05 .3315E-05 .1094E1.00 5.144E-07 1.586E-06 1.02E-06 .1693E-05 .2425E-06 .2274E-05 .1644E-05 .6181E

71 72 

Watts Bar Wolf Creek 

g 

value 

mean f per 

year 

mean f per 

year 

0.05 .1258E-02 .3290E-03 0.08 .7128E-03 .1664E-03 0.15 .2301E-03 .4581E-04 0.25 .8298E-04 .1526E-04 0.30 .5483E-04 .9857E-05 0.40 .2686E-04 .4666E-05 0.50 .1465E-04 .2480E-05 0.65 .6754E-05 .1110E-05 0.80 .3488E-05 .5607E-06 1.00 .1634E-05 .2569E-06 
4 Seismic Event Modeling and Seism

 4-45 Handbook VoFor 69 NPP sites east of Rocky Mountains, NUREG-1488 provides Seismic IEV frequencies. For the four sites West of Rocky mountains, this information is obtained from IPEEE studies and is given below

14 

Columbia 

20 

Diablo Canyon 

46 

Palo Verde 1, 2 & 3 

58 

San Onofre 2 & 3 

g 

value 

mean f per 

year 

g 

value 

mean f 

per year g value mean f per year g value mean f per year 

0.05 1.30E-03 0.20 1.85E-02 1.00E-02 3.00E-02 0.20 5.20E-03 0.10 1.30E-03 0.50 7.44E-03 2.00E-02 5.70E-03 0.30 2.00E-03 0.20 3.00E-04 0.80 3.56E-03 5.00E-02 9.10E-04 0.40 8.00E-04 0.30 1.10E-04 1.00 2.19E-03 7.00E-02 5.30E-04 0.50 3.38E-04 0.40 5.00E-05 1.20 1.35E-03 1.00E-01 3.00E-04 0.60 2.10E-04 0.50 2.50E-05 1.50 6.26E-04 1.50E-01 1.50E-04 0.70 1.00E-04 0.60 1.30E-05 2.00 1.61E-04 2.00E-01 7.90E-05 0.80 4.80E-05 0.70 7.80E-06 2.50 3.73E-05 3.00E-01 2.20E-05 0.90 2.60E-05 0.80 4.60E-06 3.00 7.89E-06 5.00E-01 1.10E-06 1.00 1.30E-05 0.90 3.00E-06 4.00 2.42E-07 1.00E+00 9.30E-10 2.00 7.80E-08 1.00 1.80E-06 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-46 

Appendix 4B. Generic SSC Seismic Fragilities 

Generic SSC seismic fragilities and the failure probabilities for SSCs in each seismic bin as 

derived from these fragilities are given in Table 4B-1. In the absence of plant-specific fragility 

information for a SSC, the values from this table can be used. 

A seismic fragility library is being constructed from plant-specific SSC fragilities available in 

recent sources, such as IPEEEs. The currently available seismic fragility information in this 

library is placed in ADAMS as an EXCEL file with accession number ML71220070. 
4 Seismic Event Modeling and Seis

 4-47 Handbook VTable 4B-1 Generic SSC Seismic Fragilities 

Failure prob

Component 

Median 

Capacity, 

g 

beta-r beta-u 

HCLPF 

Capacity, 

g 

Failure Mode Source 0.122 0

Offsite power 0.3 0.30 0.45 0.10 Failure of ceramics 1 4.81E-02 6.Electrical equipment - Function during seismic event 

1.0 0.30 0.35 0.34 Chatter functional failure 1 2.52E-06 1.

Large flat-bottom storage tanks 1.1 0.30 0.35 0.37 Buckling or wall failure 1 9.20E-07 1.Battery chargers 1.6 0.30 0.35 0.54 Functional failure 1 1.18E-08 1.Inverters 1.6 0.30 0.35 0.54 Functional failure 1 1.18E-08 1.Cable trays 2.5 0.35 0.50 0.61 Support failure 1 3.75E-07 1.HVAC ducts 2.5 0.35 0.50 0.61 Support failure 1 3.75E-07 1.Heat exchangers and small tanks 1.9 0.30 0.35 0.65 Rupture 1 1.30E-09 2.Recirculation pumps 1.9 0.30 0.35 0.65 Support failure 1 1.30E-09 2.Transformers 1.9 0.30 0.35 0.65 Loss of function /structural failure 1 1.30E-09 2.Motor-driven pumps 2.0 0.30 0.35 0.68 Support failure 1 6.53E-10 1.Air handling units 2.5 0.30 0.40 0.75 Structural failure 1 7.73E-10 9.Pressurizer 2.5 0.30 0.40 0.75 Structural failure of support 1 7.73E-10 9.Control rod drive and hydraulic drive units 

2.5 0.30 0.40 0.76 Functional failure 1 7.73E-10 9.
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-48 

Failure prob

Component 

Median 

Capacity, 

g 

beta-r beta-u 

HCLPF 

Capacity, 

g 

Failure Mode Source 0.122 0

Electrical equipment - Function after seismic event 

2.5 0.30 0.40 0.77 Chatter functional failure 1 7.73E-10 9.

Buried welded steel piping 2.0 0.25 0.30 0.80 Buckling 1 4.00E-13 1.Accumulators 2.5 0.30 0.35 0.85 Structural failure 1 2.87E-11 2.Turbine-driven pumps 2.5 0.30 0.35 0.85 Support failure 1 2.87E-11 2.Air-operated valves 3.8 0.35 0.50 0.93 Loss of function 1 8.82E-09 9.Motor-operated valves 3.8 0.35 0.50 0.93 loss of function 1 8.82E-09 9.Piping 3.8 0.35 0.50 0.93 Loss of support 1 8.82E-09 9.Safety relief, manual and check valves 

3.8 0.35 0.50 0.93 Loss of function 1 8.82E-09 9.

Diesel generator and support systems 

3.1 0.30 0.35 1.06 Functional failure 1 1.13E-12 3.

Switchgear and motor control centers 

3.1 0.30 0.35 1.06 Functional failure 1 1.13E-12 3.

Batteries and battery racks 3.8 0.30 0.35 1.30 Structural failure of supports 1 4.37E-14 3.Panelboards and instrumentation panel 

3.8 0.30 0.35 1.30 Functional failure 1 4.37E-14 3.

Containment, buildings 1.1 0.30 0.35 0.45 Structural failure Kew 9.20E-07 1.
4 Seismic Event Modeling and Seis

 4-49 Handbook V

Failure prob

Component 

Median 

Capacity, 

g 

beta-r beta-u 

HCLPF 

Capacity, 

g 

Failure Mode Source 0.122 0

Reactor internals and core assembly 

1.8 0.30 0.40 0.55 Structural failure 1 3.67E-08 1.

Reactor pressure vessel 2.0 0.30 0.35 0.68 Support failure 1 6.53E-10 1.Steam generators 2.5 0.30 0.40 0.75 Structural failure of support 1 7.73E-10 9.Reactor coolant pump 

2.5 0.30 0.40 0.75 Structural failure of support 1 7.73E-10 9.

Seismically induced small LOCA probability 4840 1.50E-05 4.Seismically induced medium LOCA probability 4840 1.00E-07 4.Sources: 1 NUREG/CR-6544, Table 6-1  KEW Kewaunee SPAR-EE model  4840 Seismically-induced SLOCA and MLOCA probabilities are taken from NURE/CR-484
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-50 

Appendix 4C. Seismic Fragility / pga / HCLPF 

The complete fragility description of any particular SSC includes a representation of both the 

probabilities of failure vs. pga and the uncertainty of the analyst in estimating those probabilities. 

("Failure", in this context, refers to inability to perform the assigned safety function.) 

In the absence of variability and uncertainty, the capacity of an element could be defined by a 

single number, the precise pga at which the element would fail. Because of earthquake-toearthquake variations in the dynamic response and capacity for the same nominal pga, one 

must recognize that the capacity can be represented only by a distribution -- specifically, a 

distribution of failure probability vs. pga. Further, because of incomplete technical knowledge 

(both theoretical and observational) about the probabilistic seismic behavior of elements and 

systems, it is necessary to describe the uncertainty in these fragility distributions. 

Figure 4C-1 (Figure 2-1 of NUREG/CR-4334) presents one way of displaying such a full fragility 

description. The curves on this figure are very stylized and do not represent any particular 

functional form. The solid curve in the middle represents a "best-estimate" curve, the "median 

fragility curve.” Corresponding to an ordinate of 0.50 is the ("best estimate" of the) median 

capacity, Am, Point A. The pga corresponding to Point B is the ("best estimate" of the) pga at 

which there is only a 5% probability of failure. 

The dashed lines in Figure 4C-1 reflect the uncertainty in the analyst's estimation of the 

probability distribution -- the uncertainty in the pga value corresponding to a given probability of 

failure, or conversely, the uncertainty in the probability of failure corresponding to a given pga. 

For example, Point D corresponds to the 95% (lower) confidence estimate of the median 

capacity. Specifically, the analyst is 95% confident that the median capacity exceeds this pga 

level. Similarly, Point C represents the high (95%) confidence estimate of the pga at which 

there is only a small (5%) probability of failure. 

In those situations in which full fragility descriptions have been developed (mainly in full-scope 

seismic PRA studies), we have chosen the HCLPF to be represented by Point C. It is important 

to realize that this choice is only a convention, because the HCLPF point should not connote 

such numerical precision. 

In most PRA practice, it has been conventional to assume a particular model for the fragility 

description. This is the (double) lognormal, in which the fragility can be fully described by only 

three parameters: the "best estimate" of) median capacity (Am); a randomness measure, βR that 

measures the slope or spread of the median fragility curve; and an uncertainty measure, βU that 

is a measure of the separations between the median curve and the 95% and 5% curves in 

Figure 4C-1. Under these circumstances, and assuming that the lognormal model exactly 

characterizes the fragility at issue, it can be shown that Point B is below the median point by a 

factor of exp (-1.65 βR). Also, Point D is below the median by a factor of exp (-1.65 βU), and 

Point C is below the median by exp [-1.65(βR + βU)]. 
 4 Seismic Event Modeling and Seismic Risk Quantification 

 4-51 Handbook Vol. 2 – External Events

Peak ground acceleration (logarithmic scale) 

Figure 4C-1 Fragility Curves. Peak ground acceleration corresponding to Point A 

represents the median capacity. Peak ground acceleration corresponding to Point C 

represents the HCLPF capacity. 

Source: NUREG/CR-4334 (1985), Figure 2-1 

Composite variability (βc): 

The composite variability includes the aleatory (randomness) uncertainty (βR) and the epistemic 

(modeling and data) uncertainty (βU). The logarithmic standard deviation of composite 

variability, (βc), is expressed as (βR

2

 + βU

2

)

1/2. 

HCLPF capacity: 

The high confidence of low probability of failure (HCLPF) capacity is a measure of seismic 

margin. In seismic PRA, this is defined as the earthquake motion level at which there is a high 

(95 percent) confidence of a low (at most 5 percent) probability of failure. Using the lognormal 

fragility model, the HCLPF capacity is expressed as Am [exp(-1.65(βR + βU)]. When the 

logarithmic standard deviation of composite variability βc is used, the HCLPF capacity could be 

approximated as the ground motion level at which the composite probability of failure is at most 

1 percent. In this case, HCLPF capacity is expressed as Am[exp-2.33 βc]. In deterministic 

SMAs, the HCLPF capacity is calculated using the Conservative Deterministic Failure 

Methodology method. 

Peak ground acceleration (PGA): 

Maximum value of acceleration displayed on an accelerogram; the largest ground acceleration 

produced by an earthquake at a site. 

Source: ANSI/ANS-58.21-2007 American National Standard External-Events PRA 

Methodology 

Peak Ground Acceleration (http://earthquake.usgs.gov/faq/meas.html#14) 

Acceleration is the rate of change in velocity of the ground shaking (how much the velocity 

changes in a unit time), just as it is the rate of change in the velocity of your car when you step 

on the accelerator or put on the brakes. Velocity is the measurement of the speed of the ground 

motion. Displacement is the measurement of the actual changing location of the ground due to 

shaking. All three of the values can be measured continuously during an earthquake. The peak 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-52 

ground acceleration (PGA) is the largest acceleration recorded by a particular station during an 

earthquake. 

Spectral Acceleration 

(http://earthquake.usgs.gov/image_glossary/spectral_accel.html) 

PGA (peak acceleration) is what is experienced by a particle on the ground. SA (spectral 

acceleration) is approximately what is experienced by a building, as modeled by a particle on a 

massless vertical rod having the same natural period of vibration as the building. 
 4 Seismic Event Modeling and Seismic Risk Quantification 

 4-53 Handbook Vol. 2 – External Events

Appendix 4D. Correspondence between PGA and Richter Scale 

There are two methods of measurement for describing earthquakes. The Richter Scale 

measures magnitude, or the energy released by an earthquake. The Modified Mercalli Scale 

measures intensity, or an earthquake’s impact or effect as felt at a particular location. 

This section provides some information for the correspondence among Richter scale, PGA and 

modified Mercelli intensity scales for seismic events. The relation between modified Mercelli 

scale and PGA is taken from a paper which is based on regression analysis of eight significant 

California earthquakes. 

Although there are some empirical relationships, no exact correlations of intensity, magnitude, 

and acceleration with damage are possible since many factors contribute to seismic behavior 

and structural performance. 

Table 4D-1 Modified Mercalli Intensity Scale versus PGA 

Mercalli 

Intensity 

Equivalent 

Richter 

Magnitude 

Witness Observations Intensity Peak 

Accel. (% g) 

I 1.0 to 2.0 Felt by very few people; barely noticeable. <0.17 

II 2.0 to 3.0 Felt by a few people, especially on upper floors. 0.17-1.4 

III 3.0 to 4.0 Noticeable indoors, especially on upper floors, but may not be 

recognized as an earthquake. 0.17-1.4 

IV 4 Felt by many indoors, few outdoors. May feel like heavy truck 

passing by. 1.4-3.9 

V 4.0 to 5.0 Felt by almost everyone, some people awakened. Small objects 

moved. trees and poles may shake. 3.9-9.2 

VI 5.0 to 6.0 Felt by everyone. Difficult to stand. Some heavy furniture 

moved, some plaster falls. Chimneys may be slightly damaged. 9.2-18 

VII 6 

Slight to moderate damage in well built, ordinary structures. 

Considerable damage to poorly built structures. Some walls 

may fall. 

18-34 

VIII 6.0 to 7.0 

Little damage in specially built structures. Considerable damage 

to ordinary buildings, severe damage to poorly built structures. 

Some walls collapse. 

34-65 

IX 7 

Considerable damage to specially built structures, buildings 

shifted off foundations. Ground cracked noticeably. Wholesale 

destruction. Landslides. 

65-124 

X 7.0 to 8.0 

Most masonry and frame structures and their foundations 

destroyed. Ground badly cracked. Landslides. Wholesale 

destruction. 

>124 

XI 8 Total damage. Few, if any, structures standing. Bridges 

destroyed. Wide cracks in ground. Waves seen on ground. >124 

XII 8.0 or 

greater 

Total damage. Waves seen on ground. Objects thrown up into 

air. >124 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-54 

Table 4D-2 PGA vs. Richter and Modified Mercalli Scales 

Peak Ground 

Acceleration 

(% g) 

PGA 

(representative) 

Equivalent 

Richter 

Magnitude 

Mercalli 

Intensity Scale 

<0.17 I 

0.17-1.4 II –III 

1.4-3.9 IV 

3.9-9.2 V 

9.2-18 0.15g 5.0 to 6.0 VI 

18-34 0.30g 6 VII 

34-65 0.50g 6.0 to 7.0 VIII 

65-124 1.00g 7 IX 

>124 1.25g 7.0 or greater X+ 

Table gives the peak ground motion ranges that correspond to each unit Modified Mercalli 

intensity value according to regression of the observed peak ground motions and intensities for 

California earthquakes. Equivalent Richter scales are also included. 
 4 Seismic Event Modeling and Seismic Risk Quantification 

 4-55 Handbook Vol. 2 – External Events 

The Modified Mercalli Scale of Earthquake Intensity 

In seismology a scale of seismic intensity is a way of measuring or rating the effects of an 

earthquake at different sites. The Modified Mercalli Intensity Scale is commonly used in the 

United States by seismologists seeking information on the severity of earthquake effects. 

Intensity ratings are expressed as Roman numerals between I at the low end and XII at the high 

end. 

The Intensity Scale differs from the Richter Magnitude Scale in that the effects of any one 

earthquake vary greatly from place to place, so there may be many Intensity values (e.g., IV, 

VII) measured from one earthquake. Each earthquake, on the other hand, should have just one 

Magnitude, although the several methods of estimating it will yield slightly different values (e.g., 

6.1, 6.3). 

Ratings of earthquake effects are based on the following relatively subjective scale of

descriptions: 

Table 4D-3 Modified Mercalli Intensity Scale (from FEMA) 

Mercalli 

Intensity Description

I People do not feel any Earth movement. 

II A few people might notice movement if they are at rest and/or on the upper floors of tall 

buildings. 

III Many people indoors feel movement. Hanging objects swing back and forth. People 

outdoors might not realize that an earthquake is occurring. 

IV 

Most people indoors feel movement. Hanging objects swing. Dishes, windows, and doors 

rattle. The earthquake feels like a heavy truck hitting the walls. A few people outdoors may 

feel movement. Parked cars rock. 

V 

Almost everyone feels movement. Sleeping people are awakened. Doors swing open or 

close. Dishes are broken. Pictures on the wall move. Small objects move or are turned 

over. Trees might shake. Liquids might spill out of open containers. 

VI 

Everyone feels movement. People have trouble walking. Objects fall from shelves. Pictures 

fall off walls. Furniture moves. Plaster in walls might crack. Trees and bushes shake. 

Damage is slight in poorly built buildings. No structural damage. 

VII 

People have difficulty standing. Drivers feel their cars shaking. Some furniture breaks. 

Loose bricks fall from buildings. Damage is slight to moderate in well-built buildings; 

considerable in poorly built buildings. 

VIII 

Drivers have trouble steering. Houses that are not bolted down might shift on their 

foundations. Tall structures such as towers and chimneys might twist and fall. Well-built 

buildings suffer slight damage. Poorly built structures suffer severe damage. Tree branches 

break. Hillsides might crack if the ground is wet. Water levels in wells might change. 

IX 

Well-built buildings suffer considerable damage. Houses that are not bolted down move off 

their foundations. Some underground pipes are broken. The ground cracks. Reservoirs 

suffer serious damage. 

X 

Most buildings and their foundations are destroyed. Some bridges are destroyed. Dams are 

seriously damaged. Large landslides occur. Water is thrown on the banks of canals, rivers, 

lakes. The ground cracks in large areas. Railroad tracks are bent slightly. 

XI Most buildings collapse. Some bridges are destroyed. Large cracks appear in the ground. 

Underground pipelines are destroyed. Railroad tracks are badly bent. 

XII Almost everything is destroyed. Objects are thrown into the air. The ground moves in 

waves or ripples. Large amounts of rock may move. 
4 Seismic Event Modeling and Seismic Risk Quantification 

Risk Assessment of Operational Events 4-56 

As one can see from the list above, rating the Intensity of an earthquake's effects does not 

require any instrumental measurements. Thus seismologists can use newspaper accounts, 

diaries, and other historical records to make intensity ratings of past earthquakes, for which 

there are no instrumental recordings. Such research helps promote understanding of the 

earthquake history of a region, and estimate future hazards. 
 5-1 Handbook Vol. 2 – External Events 

External Events: Section 5 

Other External Events Modeling and Risk Quantification Rev. 1.01 

5.0 Other External Events Modeling and Risk Quantification 

5.1 Objectives and Scope 

This document is intended to provide a concise and practical handbook to NRC risk analysts 

who routinely use the SAPHIRE software and the Standardized Plant Analysis Risk (SPAR) 

probabilistic risk assessment (PRA) models to quantify event and plant condition importances, 

and other ad-hoc risk analyses. It is a complementary document to the handbook cited in 

Ref. 5-1. 

NRC risk analysts encounter many plant conditions and events reported by such means as 

inspection reports, licensee event reports (LERs), generic risk issues that lend themselves to 

PRA quantification and evaluation, every year. The need for quantification of the event / 

condition importance in terms of the two common risk measures of core damage frequency 

(CDF) and large early release frequency (LERF) arise in many of these cases. 

This handbook provides NRC risk analysts practical guidance for modeling “other external 

events” scenarios and quantifying their CDF using SPAR models and SAPHIRE software. 

Other External Events” are defined in Appendix A of Ref. 5-2, excluding internal fires, internal 

flooding, and seismic events. For those events, complementary handbooks are already 

prepared. 

External flooding and extreme winds / tornadoes are the two other external events that most 

likely may appear as scenarios in some PRA studies (non-targeted transportation accidents, 

such as nearby chemical transport explosions or inadvertent on-site air crash, may appear in 

rare instances). This handbook will focus on these two events. 

The handbook assumes that: 

1. The user has hands-on experience with the SAPHIRE code; 

2. The user has performed and documented event/condition importance analysis or plant 

risk assessment cases for a period of at least three months (this is a suggested period, 

not a firm limit) under the supervision of an experienced (qualified) senior PRA analyst. 

The user is the primary author of documentation packages for such analyses which are 

reviewed and accepted by an NRC program. 

The current scope is limited to other external events during power operation and calculation of 

CDF only.

Mainstream PRA terms and abbreviations that are used in this document are not defined; the 

intended reader is assumed to be familiar with them. 
5 Other External Events Modeling and Risk Quantification 

Risk Assessment of Operational Events 5-2 

5.2 Scenario Definition and Quantification 

This handbook focuses on external flooding and extreme winds / tornadoes. These events 

share many common traits with area events (like internal flooding) and loss of offsite power 

(LOOP) events. However, two aspects in which they are distinctly different are (1) they 

originate from outside the facility; and (2) there is little, if any, opportunity for mitigation (e.g., 

one can suppress a fire or terminate an internal event, but one cannot readily block an external 

flooding event or tornado, other than to pre-harden the facility). In fact the initiating event 

frequency of LOOP includes weather related LOOP. Weather-related LOOP events involve 

hurricanes, strong winds greater than 125 miles per hour, tornadoes, thunderstorms, snow, and 

ice storms. 

As in internal flooding and fire scenarios, a two-step process is discussed to model other 

external event scenarios and quantify their CDFs: 

1. Define scenarios that lead to core damage. For this purpose, define initiating event, 

calculate its frequency; identify damaged structures, systems and components (SSCs) 

and evaluate their recovery (or lack of recovery) potential and means. 

Using a structured model, such as a small event tree, define scenarios that stem from 

the initiating event; calculate their scenario frequencies, and transfer each scenario to an 

existing event tree (such as LOOP). 

 See example in the next section for an application of this process. 

2. Quantify the CDF of the sequences stemming from these scenarios. For this purpose, 

first the scenario conditional core damage probability (CCDP) is calculated by using a 

SPAR model and the SAPHIRE software. Then this CCDP is multiplied by the scenario 

frequency calculated in Step 1. 

The sequences defined can be summarized in terms of a matrix containing the minimum 

amount of information to be able to quantify the scenario frequency, the scenario CCDP, and 

thus the sequence CDF: 

CDF = Scenario Frequency * CCDP. 

5.2.1 Define Scenarios 

Examine the event/condition characteristics and define scenarios that lead to core damage. 

Summarize those scenarios in terms of a table, such as Table 5-1. The columns of this table 

are discussed below. Note that, each of these scenarios is treated as an initiating event and will 

be assigned an event tree. 

1. Scenario name (initiating event ID). This always starts with an appropriate prefix such 

as (FLE, HWD, TOR, etc.) and is used both for the event tree and the initiating event 

names. 

2. Scenario description. 

3. Scenario frequency IEfreq (initiating event frequency). 
5 Other External Events Modeling a

 5-3 Handbook Vo

Table 5-1 Example Matrix Defining Other External Event Scenarios 

Name Description IE Frequency Equipment Lost IE Caused 

HEPs / 

Basic 

Events 

Affected 

1 OEX-DAM Dam failure – external flooding event 1.0E-05 LOOP; SWS; no LOOP recovery; no SWS recovery IE-LOOP None / None 

Name Description IE Frequency Equipment Lost IE Caused 

HEPs / 

Basic 

Events 

Affected 

1 OEX-HUR LOOP due to hurricane during Mode 4 operation N/A (1) Offsite AC power IE-LOOP 

No RCP seal LOCA; eventspecific LOOP recovery probabilities 

Notes: (1) = event analysis is made; initiating event frequency is set equal to 1.0 
5 Other External Events Modeling and Risk Quantification 

Risk Assessment of Operational Events 5-4 

4. Equipment lost. Equipment credited in the PRA that is lost due to the external event is 

listed in this column. Include trains/system that caused the external event, if such is 

possible (unlikely for other than internal fires and floods, not being addressed here) and 

is also lost. 

5. Initiating event caused. This is the initiating event caused by the external event. In most 

cases, it is one of the internal initiating event categories already defined (such as loss of 

main feedwater (LOMFW), TRANS, loss of service water system (LOSWS), etc.). 

However, due to the potential for structural damage similar to seismic, e.g., 

tornadoes/high winds or air crash, it may be necessary to consider new or merged event 

trees where multiple internal events initiators could be triggered concurrently. 

6. Human error probabilities (HEPs), recovery actions, and other basic events affected. 

List the basic events and operator actions that are affected by the event (failed, 

degraded). This is in addition to equipment listed in item 5 above. 

7. New basic events (failures) introduced. List any new basic events to model the 

scenarios. 

Other columns may be introduced as needed. 

5.2.2 Quantify Sequence CDFs 

The CDF of each sequence can be calculated as a product of the scenario frequency and the 

CCDP given the scenario has occurred: 

CDF = IEfreq * CCDP. 

The scenario frequency IEfreq is already calculated in the earlier step. The CCDP can be 

calculated by using the SAPHIRE code and the SPAR models. For this purpose, either a 

change set or the Graphical Evaluation Module (GEM) software can be used. 

Once the sequence CDF is known, it can be used to estimate event/condition importance. 

5.2.3 Weather-Related LOOP Recovery Distributions 

LOOP recovery distributions for weather-related events differ from other LOOP events. They 

are given in Table 5-2, as taken from Ref. 5-4, SPAR 3.12 models. 

Table 5-2 LOOP Recovery Distributions 

Failure to Recover Offsite Power in X hours 

X Composite Weather Related 

1 0.53 0.66 

2 0.32 0.52 

2.5 0.26 0.48 

3 0.22 0.44 

4 0.16 0.38 

5 0.12 0.34 
 5 Other External Events Modeling and Risk Quantification 

 5-5 Handbook Vol. 2 – External Events 

Failure to Recover Offsite Power in X hours 

X Composite Weather Related 

6 0.010 0.31 

7 0.08 0.28 

8 0.07 0.26 

Composite = Composite of plant-, switchyard-centered, and grid-, and weather-related LOOP 

categories. 

5.2.4 Weather-Related LOOP Frequencies 

The weather-related LOOP frequencies (per reactor critical year or calendar year at power, and 

units for shutdown) are given in Table 5-3, as taken from Ref. 5-4. 

Table 5-3 LOOP Frequencies 

LOOP Category Mean 95% 

Critical Operation

Plant-centered 2.07E-3 7.96E-3 

Switchyard-centered 1.04E-2 3.98E-2 

Grid-related 1.86E-2 7.16E-2 

Weather-related 4.83E-3 1.86E-2 

 

All 3.59E-2 9.19E-2 

LOOP Category Mean 95% 

Shutdown Operation

Plant-centered 5.09E-02 2.06E-01 

Switchyard-centered 1.00E-01 2.83E-01 

Grid-related 9.13E-03 3.51E-02 

Weather-related 3.52E-02 1.35E-01 

 

All 1.96E-01 4.33E-01 

5.2.5 Treatment of Hurricane-Related Events 

Plants susceptible to hurricane events have procedures to bring plant to a shutdown state prior 

to an expected hurricane event. Thus, a plant is expected to be in a Mode 3 or Mode 4 

shutdown state when the site experiences a hurricane event. The most likely consequence of 

such an event is loss off offsite power, with a plant specific-recovery distribution for that 

particular event. See Example 5.3.2 for treatment of LOOP following a hurricane, while the 

plant is in a shutdown state. 

If a SPAR shutdown model is available for the plant in question, it can be used for estimating 

the importance of the event or plant condition. If the SPAR-SD model does not provide enough 

modeling detail to address specific issues associated with the event, the LOOP/SBO model 

from SPAR internal events may be used, with certain modifications, which can be implemented 

by a change set in SAPHIRE. The following modifications can be considered: 
5 Other External Events Modeling and Risk Quantification 

Risk Assessment of Operational Events 5-6 

i). RPS failure is removed (no ATWS); 

ii). RCP seal LOCA (for PWRs) is most likely not applicable and should be removed; 

iii). PORV LOCA likelihood is considerably reduced; may be removed; 

iv). Availability of AFW and MFW recovery should be established and kept in the model; 

v). Event-specific offsite power recovery distribution may need to be calculated and used; 

as a minimum, generic severe-weather recovery distribution should be used. 

vi). Operator actions outside of the buildings, or those that require travel from one building to 

another via outside should not be modeled, at least for the first 2-4 hours following the 

onsite of the hurricane at the site. 

vii). Introduction of an operator action to start a mitigating system (modeled in the LOOP / 

SBO event trees), which otherwise, would have started automatically. 

viii). Since the plant has been shutdown for a period of 4-8 hours, the time windows available 

for operator actions, and also for time to core melt are expected to be longer (more 

favorable) than those used for at-power operations. Thus, the plant condition/event 

importance estimates using the at-power LOOP event tree are expected to be on the 

conservative side. 

5.3 Examples 

This section discusses examples for illustrative purposes; the values used in the examples are 

for illustration only. 

5.3.1 Example Condition Analysis 

An external flooding event is postulated to occur due to a catastrophic dam failure upstream in a river that provides 

the intake water for the service water system (SWS). Although the main plant buildings are not expected to be 

flooded, a non-recoverable failure of SWS during the first 24-hour mission time is postulated. The initiating event 

frequency is estimated as 1.0E-05/year. The event is postulated to occur only after extreme rains, and the plant has 

a procedure to shutdown under these severe conditions and remain at Mode 2 or lower. For modeling purposes, the 

event occurs during Mode 2 operation. LOOP is also expected and is postulated. No offsite power recovery is 

expected during the mission time. 

This scenario was not considered in the plant PRA. This newly discovered condition importance can be calculated 

for an exposure time of 1 year as 

COND-IMP = 1 year * IE-freq * CCDP 

Where 

IE-Freq = 1.0E-05/year 

and CCDP is calculated as 3.2E-02 by using the SPAR model with LOOP event tree, no SWS, no LOOP recovery 

and no SWS recovery. It is assumed that the LOOP success criteria developed for at-power conditions bound the 

Mode 2 conditions. 

This sequence represents additional risk and there is no need to process base plant risk. Thus the condition 

importance is given by 

COND-IMP = 1.0E-05 * 3.2E-02 = 3.2E-07, 

for a 1-year exposure time.
 5 Other External Events Modeling and Risk Quantification 

 5-7 Handbook Vol. 2 – External Events 

5.3.2 Example Event Analysis 

A dual-unit LOOP occurred at a nuclear power plant (NPP) site. Earlier that day both units commenced an orderly 

shutdown to prepare for the arrival of Category-3 Hurricane J. At the time of the LOOP, the site was experiencing 

hurricane force winds with both units in Mode 4. 

This event is modeled as a loss of alternating current (AC) power event leading to loss of RHR cooling during Mode 4 

with a 24-hour mission time (no structural damage, other than that in the switchyard or offsite which could cause 

LOOP, is postulated). 

 

Assumptions

1. The risk of this event can be estimated by assuming that the success criteria for a LOOP event at power applies. 

This assumption has both conservative and non-conservative aspects that are deemed to be balancing from 

a risk point of view. Namely, 

a) Since the units are already shutdown, the decay heat is lower than at power. This gives a larger time 

window for operator actions, both for starting systems, or recovering power. 

b) Some mitigating safety systems, if needed, may require operator action to start; they may not be available 

for automatic actuation in Mode 4. One example of this is AFW cooling by SGs for unit 1. 

2. For AC recovery time distribution, an event-specific calculation is made using SPAR-H model. 

3. Credit for crosstie to other unit emergency diesel generator (EDG), which is already modeled in SPAR, is 

retained. 

4. Unit 1 is assumed to go to steam generator (SG) cooling by auxiliary feedwater (AFW), if residual heat removal 

(RHR) cooling failed. 

5. Unit 1 SPAR model is used to estimate the event importance. 

6. The reactor coolant system (RCS) temperature and pressure conditions are such that no reactor coolant pump 

(RCP) seal LOCA challenge exists. 

For this category 3 hurricane event, event-specific offsite power non-recovery probabilities are calculated. 

Although no attempt was made to restore offsite power to the startup transformers during the hurricane, if EDG power 

was lost, offsite power could have been restored through Bay 2. However, weather conditions did hamper the 

restoration of offsite power to the units' electrical buses. Therefore, during the hurricane, safe shutdown loads 

remained connected to the EDGs even after power was capable of being restored to the east electrical switchyard 

buses because conditions would not allow personnel to safely inspect the switchyard. AC power recovery was 

feasible during the mission time of interest and credible. It is modeled in the event importance assessment. 

In the actual event, the offsite power was restored to the emergency buses in 11 hours; during that time, EDGs 

powered the buses. 

The following AC power recovery distribution is used: 

 

OPERATOR FAILS TO RECOVER OFFSITE POWER: 

IN 1 HR 1.0 

IN 2 HRS 0.5 

IN 3 HRS 0.05 

IN ≥4 HRS 0.005 

When this AC power recovery distribution is used, the CCDP is calculated as 1.8E-05, which is the event importance. 

Compare this with SPAR severe weather AC power recovery failure distribution. Namely 

 
5 Other External Events Modeling and Risk Quantification 

Risk Assessment of Operational Events 5-8 

OPERATOR FAILS TO RECOVER OFFISTE POWER: 

IN 1 HR 4.6E-001 

IN 2 HRS 3.6E-001 

IN 3 HRS 3.0E-001 

IN 4 HRS 2.5E-001 

IN 5 HRS 2.2E-001 

IN 6 HRS 2.0E-001 

IN 7 HRS 1.8E-001 

With this recovery distribution, the event importance is calculated as CCDP = 3.4E-05. 

5.4 References 

5-1. U.S. Nuclear Regulatory Commission, “Risk Assessment of Operational Events 

Handbook: Volume 1 - Internal Events,” Revision 1.01. December 2007. 

5-2. American National Standard, “External Events PRA Methodology,” ANSI/ANS-58.21-

2003, 2003. 

5-3. Idaho National Laboratory, “A Feasibility and Demonstration Study – Incorporating 

External Events into SPAR Models,” February 2005. 

5-4. U.S. Nuclear Regulatory Commission, “Reevaluation of Station Blackout Risk at Nuclear 

Power Plants - Analysis of Loss of Offsite Power Events: 1986-2004,” NUREG/CR-6890, 

Volume 1, December 2005. 

http://www.nrc.gov/reading-rm/doc-collections/nuregs/contract/cr6890/ 
 5 Other External Events Modeling and Risk Quantification 

 5-9 Handbook Vol. 2 – External Events 

Appendix 5A. Dam Failure Rates for External Flooding 

External flooding is due to precipitation, storm surge, tsunami, or rupture of an impoundment. The 

precipitation can be in the form of extreme rainfall or a rapidly melting snow pack. The dam or dike 

rupture can be due to overtopping by flood or “blue sky” piping and collapse. Storm surge is 

typically a coastal phenomenon. Tsunamis and their fresh water cousins, seiches are seismic and 

shoreline geography phenomena. 

The existing nuclear sites based their flood protection on the recommendations of SRP section 2.4, 

Regulatory Guides (RGs) 1.159 (Rev. 2) and 1.102, with RG 1.159 providing actual data for sites 

east of the Rockies. The accepted analysis methodology is outlined in ANSI/ANS-2.8-1992, 

“Determining Design Basis Flooding at Power Reactor Sites.” 

Tsunamis 

Tsunamis are treated as rare and mild events on eastern coasts and not analyzed. On the West 

coast, California plants claim a less than 10 foot tsunami but agreed to a design basis three times 

higher. There are no plants on the Pacific Northwest coast where there is an active plate boundary 

that can generate local large tsunamis. 

Weather-Related Flood 

Much of the country has already been analyzed by the U.S. Army Corps of Engineers and Federal 

Emergency Management Agency (FEMA) for flood and surge that are based on National Oceanic 

and Atmospheric Administration (NOAA) and U.S. Geological Survey (USGS) data. Virtually all 

licensees used the NRC recommended Refs.5-1 through 5-4 for input in Section 2.4 of their SARs. 

The hurricane and precipitation data record only goes back 100 to 200 years. Probable maximum 

hurricane (PMH) values are developed from storm history over a wide stretch of coast extrapolated 

out about 2000 years. Probable maximum precipitation (PMP) values are developed from the100 

year record maximum for the area. Both PMP and PMH are single value parameters that are 

deterministic and only of limited use for PRA. If more recent data is desired, precipitation 

frequency estimates are available out to 1000 years from NOAA at 

http://hdsc.nws.noaa.gov/hdsc/pfds/index.html and recent storm surge estimates are incomplete but 

available at the National Hurricane Study Program at 

http://chps.sam.usace.army.mil/USHESdata/HESHOME.htm . 

Dam and Dike Failure 

Dam failure is well documented and can be characterized by type of dam. Table 5A-1 is a 

summary of point estimate failure rates for dams that are broken down by large dams (>50 ft) and 

all sized dams. Characteristics of US dams and dam failures are available at the National 

Inventory of Dams, http://crunch.tec.army.mil/nid/webpages/nid.cfm and the National Performance of Dams 

Program, http://npdp.stanford.edu/index.html . 

Of the 79,777 dams in the US, 72% are embankment type and 28% are concrete. Nineteenth 

century dams would fail at 5% in the first five years after construction but would settle out to a 1 to 

4% additional failure by 20 years of life. This was reduced to 2% in the first 5 years for dams built 

after 1930. By 1960, dam failure rates were less than 0.01% due to better engineering. Whatever 

the era, half of all dams that ever fail, do so in the first five years. This high infant mortality is often 

due to piping in the soil around the dam or underneath it. Even concrete dams are not immune. 
5 Other External Events Modeling and Risk Quantification 

Risk Assessment of Operational Events 5-10 

However, dam construction dropped dramatically after 1980 so that nearly all dams are older than 

5 years. 

Dams as far up or downstream as 300 miles should be considered for both flood and loss of heat 

sink. It is noteworthy that all forms of dams have a failure rate between 1E-4 and 4E-4, even for 

blue sky events. Determining flood levels, however, is a complex matter. The USACOE has 

software named HEC that when combined with GIS geographical data will model river flow and 

flooding in great detail. 

Weather based floods remain in the deterministic world because the input conditions are always 

from the same source as was used in the original plant design basis. Besides, the growth of the 

maximum precipitation only increases about 20% when a 100 year interval is compared to a 1000 

year interval. With only 100 years of data available in many locations, projecting beyond a 1E-3/yr 

event is very uncertain anyway. 
5 Other External Events Modeling a

 5-11 Handbook Vo

Table 5A-1 Dam Failure Rates 

(all dams) Failures Dam- years apost bpost Mean 5% 5

1 All Arch Dams 2 9101 2.5 12163.2644 2.055E-04 4.709E-05 1.782 All Buttress Dams 2 9819 2.5 12881.2644 1.941E-04 4.446E-05 1.683 All Concrete Dams 10 110227 10.5 113289.2644 9.268E-05 5.116E-05 8.974 All Earth Dams 366 2240403 366.5 2243465.2644 1.634E-04 1.496E-04 1.635 All Gravity Dams 28 122798 28.5 125860.2644 2.264E-04 1.615E-04 2.236 All Masonry Dams 5 21692 5.5 24754.2644 2.222E-04 9.240E-05 2.087 All Multi-Arch Dams 0 240 0.5 3302.2644 1.514E-04 5.954E-07 6.888 All Rockfill Dams 7 73806 7.5 76868.2644 9.757E-05 4.723E-05 9.329 All Stone Dams 2 11365 2.5 14427.2644 1.733E-04 3.970E-05 1.50

10 All Timber Crib Dams 3 6536 3.5 9598.2644 3.646E-04 1.129E-04 3.30

T Total 425 2605987 0.5 3062.2644 1.633E-04 6.420E-07 7.42

No statistical difference among dam types. P-value = 0.15096. Empirical Bayes distribution does not exit since routine faPrior distribution is obtained using the total values and obtaining using a Jeffreys' prior distribution. Then obtained uncertusing CNIP. 

(dams over 50 feet high) Failures Dam- years apost bpost Mean 5% 

1 Buttress Dams Over 50 Feet High 0 1876 2.4026 11970.7049 2.007E-04 4.410E-02 Arch Dams Over 50 Feet High 2 5667 4.4026 15761.7049 2.793E-04 1.018E-03 Concrete Dams Over 50 Feet High 0 19215 2.4026 29309.7049 8.197E-05 1.801E-04 Earth Dams Over 50 Feet High 56 144810 58.4026 154904.7049 3.770E-04 2.997E-05 Gravity Dams Over 50 Feet High 7 19542 9.4026 29636.7049 3.173E-04 1.683E-06 Masonry Dams Over 50 Feet High 0 1987 2.4026 12081.7049 1.989E-04 4.370E-07 Multi-Arch Dams Over 50 Feet High 0 77 2.4026 10171.7049 2.362E-04 5.190E-08 Rockfill Dams Over 50 Feet High 4 20010 6.4026 30104.7049 2.127E-04 9.568E-0

T Total 69 213184 2.4026 10094.7049 2.380E-04 5.230E-0

Prior distribution obtained using empirical Bayes method in SAS. 

Notes: Dams constructed with mixed materials are not counted; dams with no construction dates available are not counted.

 

 A1-1 Handbook Vol. 2 – External Events 

External Events: Appendix 1 

Frequencies of Seismically-Induced LOOP Events for 

SPAR Models 

Rev. 1 

Appendix 1. Frequencies of Seismically-Induced LOOP Events for SPAR 

Models 

1. Objective 

This report provides frequencies of seismically-induced loss of offsite power (LOOP) events for 

U.S. nuclear power plants (NPPs). These LOOP frequencies could be used for external events 

scenarios in event importance calculations. The intended user is the U.S. NRC senior reactor 

analysts (SRAs). 

 

2. Input 

The inputs to these calculations are: 

i). seismic initiating event frequencies (seismic hazard distribution) as a function of seismic 

g level (NUREG-1488, April 1994); 

ii). structures, systems and components (SSCs) (for example ceramic insulator) fragilities 

as a function of g level (NUREG-6544, April 1998). 

Attachment A provides the details. 

3. Summary of Results 

The input data is combined as a weighted average over the g levels to obtain mean value 

estimates, as shown in Attachment A. The following information is provided as shown in Table 

1: 

1. Seismic initiating event mean frequency of a 0.05g or higher earthquake per year; 

2. Given an earthquake occurs, the conditional LOOP probability caused by the earthquake 

(based on failure of ceramic insulators); 

3. Frequency of seismically induced LOOP event (per year). 

Tables 2 and 3 compare the seismically induced LOOP frequency with frequencies of other 

“internal LOOP events.” Average durations of the LOOP events are also provided in the same 

tables. 

4. Comments 

i). These results show that the seismically-induced LOOP frequencies are at least two 

orders of magnitude lower than LOOP frequencies calculated for internal events. 

However, the power recovery may not be feasible for an extended time period, following 
Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

Risk Assessment of Operational Events A1-2 

a seismic event. This fact should be factored into the calculation of plant risk due to 

seismically-induced LOOP events. 

ii). A small fraction of these LOOP events (at high seismic g values) will have additional 

SSC failures that would cause other initiating events, such as small loss-of-coolant 

accident (LOCA), large LOCA, etc. 

iii). For the sites to the east of the Rocky Mountains, a calculational tool is set up in terms of 

an MS EXCEL workbook and is used repeatedly to calculate the seismically-induced 

LOOP frequencies for 61 sites. The same generic ceramic insulator seismic fragility 

distribution is used for these calculations. 

iv). For the four sites west of the Rocky Mountains, plant-specific seismic event frequency 

distributions (seismic hazard curves) are obtained from Individual Plant Examination of 

External Events (IPEEE) submittals (they are not given in the reference NUREG). The 

seismic fragility distributions for LOOP are also obtained from the same source. Then, 

the same calculational tool is used for LOOP frequency calculations. 

v). The calculations can be readily customized for plant-specific SSC fragilities (e.g., 

ceramic insulators) and/or hazard curves. The MS EXCEL workbook named 

Seismically-Induced LOOP – Tables.xls is available for this purpose. 
Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

 A1-3 Handbook Vol. 2 – External Events 

Table 1 Frequencies of Seismically-Induced LOOP Events 

Seismic 

IEV 

Frequency 

Cond. 

Prob. of 

LOOP 

Seis. Indu. 

LOOP 

Frequency Plant 

A B A*B 

Plant Type # of 

Units 

1-2 ANO 1 & 2 1.27E-03 6.59E-02 8.39E-05 B&W/CE 2 

3-4 Beaver Valley 1 & 2 8.78E-04 8.52E-02 7.48E-05 W 2 

5 Braidwood 1 & 2 4.30E-04 6.64E-02 2.85E-05 W 2 

6-7 Browns Ferry 2 & 3 9.12E-04 5.63E-02 5.14E-05 BWR 2 

8 Brunswick 1 & 2 1.53E-03 6.95E-02 1.06E-04 BWR 2 

9 Byron 1 & 2 5.09E-04 7.23E-02 3.68E-05 W 2 

10 Callaway 1.08E-03 3.82E-02 4.14E-05 W 1 

11 Calvert Cliffs 1 & 2 7.67E-04 8.24E-02 6.33E-05 CE 2 

12 Catawba 1 & 2 1.20E-03 6.27E-02 7.52E-05 W 2 

13 Clinton 1.55E-03 6.87E-02 1.06E-04 BWR 1 

14 Columbia (ex-WNP-2) 1.30E-03 1.37E-01 1.78E-04 BWR 1 

15 Comanche Peak 1 & 2 1.41E-04 5.52E-02 7.78E-06 W 2 

16 Cook 1 & 2 5.01E-04 7.77E-02 3.89E-05 W 2 

17 Cooper 1.16E-03 1.15E-01 1.33E-04 BWR 1 

18 Crystal River 3 1.48E-04 7.76E-02 1.15E-05 B&W 1 

19 Davis-Besse 1.07E-03 6.12E-02 6.55E-05 B&W 1 

20 Diablo Canyon 1.85E-02 5.71E-02 1.06E-03 W 2 

21 Dresden 4.58E-04 7.23E-02 3.31E-05 BWR 2 

22 Duane Arnold 1.55E-04 6.28E-02 9.72E-06 BWR 1 

23 Farley 1 & 2 2.00E-04 7.17E-02 1.43E-05 W 2 

24 Fermi 2 6.01E-04 5.29E-02 3.18E-05 BWR 1 

25 Fitzpatrick 7.34E-04 4.95E-02 3.63E-05 BWR 1 

26 Fort Calhoun 8.78E-04 1.21E-01 1.06E-04 CE 1 

27 Ginna 8.48E-04 7.07E-02 6.00E-05 W 1 

28 Grand Gulf 3.31E-04 7.12E-02 2.35E-05 BWR 1 

29 Hatch 1 & 2 6.13E-04 6.83E-02 4.19E-05 BWR 2 

30 Hope Creek 9.72E-04 8.09E-02 7.86E-05 BWR 1 

31-32 Indian Point 2 1.15E-03 7.54E-02 8.69E-05 W 2 

33 Kewaunee 3.04E-04 9.38E-02 2.85E-05 W 1 

34 LaSalle 1 & 2 8.25E-04 8.66E-02 7.14E-05 BWR 2 

35 Limerick 1 & 2 1.22E-03 7.66E-02 9.35E-05 BWR 2 

36 McGuire 1 & 2 1.08E-03 5.86E-02 6.35E-05 W 2 

37-38 Millstone 2 & 3 9.97E-04 7.49E-02 7.46E-05 CE/W 2 

39 Monticello 3.56E-04 1.01E-01 3.58E-05 BWR 1 

40-41 Nine Mile Point 1 & 2 7.30E-04 4.98E-02 3.63E-05 BWR 2 

42 North Anna 1 & 2 1.15E-03 7.42E-02 8.55E-05 W 2 

43 Oconee 1, 2, & 3 1.28E-03 6.69E-02 8.57E-05 B&W 3 

44 Oyster Creek 8.53E-04 6.98E-05 6.98E-05 BWR 1 

45 Palisades 3.92E-04 7.78E-02 3.05E-05 CE 1 

46 Palo Verde 1, 2, & 3 3.00E-02 1.79E-03 5.37E-05 CE 3 

47 Peach Bottom 2 & 3 1.06E-03 7.63E-02 8.08E-05 BWR 2 

48 Perry 4.48E-04 6.96E-02 3.12E-05 BWR 1 

49 Pilgrim 2.81E-03 1.16E-01 3.25E-04 BWR 1 
Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

Risk Assessment of Operational Events A1-4 

Seismic 

IEV 

Frequency 

Cond. 

Prob. of 

LOOP 

Seis. Indu. 

LOOP 

Frequency Plant 

A B A*B 

Plant Type # of 

Units 

50 Point Beach 1 & 2 3.13E-04 9.32E-02 2.91E-05 W 2 

51 Prairie Island 1 & 2 3.15E-04 1.04E-01 3.28E-05 W 2 

52 Quad Cities 1 & 2 3.66E-04 6.37E-02 2.33E-05 BWR 2 

53 River Bend 1.97E-04 7.45E-02 1.46E-05 BWR 1 

54 Robinson 2 2.72E-03 8.78E-02 2.39E-04 W 1 

55-56 Saint Lucie 1 & 2 1.47E-04 9.02E-02 1.33E-05 CE 2 

57 Salem 1 & 2 9.59E-04 8.06E-02 7.73E-05 W 2 

58 San Onofre 2 & 3 5.20E-03 4.71E-01 2.45E-03 CE 2 

59 Seabrook 2.34E-03 8.08E-02 1.89E-04 W 1 

60 Sequoyah 1 & 2 1.33E-03 7.46E-02 9.92E-05 W 2 

61 Shearon Harris 5.85E-04 6.25E-02 3.65E-05 W 1 

62 South Texas 1 & 2 1.63E-04 8.59E-02 1.40E-05 W 2 

63 Surry 1 & 2 6.03E-04 7.83E-02 4.72E-05 W 2 

64 Susquehanna 1 & 2 8.46E-04 7.12E-02 6.02E-05 BWR 2 

65 TMI-1 1.11E-03 7.68E-02 8.51E-05 B&W 1 

66 Turkey Point 3 & 4 1.23E-04 7.97E-02 9.78E-06 W 2 

67 V.C. Summer 1.83E-03 6.36E-02 1.17E-04 W 1 

68 Vermont Yankee 1.29E-03 6.20E-02 8.02E-05 BWR 1 

69 Vogtle 1 & 2 2.50E-03 7.05E-02 1.76E-04 W 2 

70 Waterford 2.86E-04 8.56E-02 2.45E-05 CE 1 

71 Watts Bar 1.26E-03 7.44E-02 9.36E-05 W 1 

72 Wolf Creek 3.29E-04 5.70E-02 1.87E-05 W 1 

 Average = 1.20E-04 Sum = 103 

Note: 

Bold numbers in the first column identify the four sites to the West of Rocky Mountains. 
Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

 A1-5 Handbook Vol. 2 – External Events 

Table 2 LOOP Frequency Comparisons - Power Operation 

Mean 

Frequency 95% 

Mean 

Duration 

(hrs) 

95% 

Duration

1 Plant centered 2.38E-03 9.15E-03 0.5 2 

2 Switchyard centered 8.74E-03 3.36E-02 1.3 5 

3 Grid related 1.67E-02 6.41E-02 2.7 9.3 

4 Severe weather related 2.98E-03 1.15E-02 5.4 25.1 

5 Extreme weather related 2.32E-03 8.91E-03 78 187.4 

6 Seismically induced 1.2E-04 78 187.4 

Sum = 3.32E-02 

Table 3 LOOP Frequency Comparisons - Shutdown Operation 

Mean 

Frequency 95% 

Mean 

Duration 

(hrs) 

95% 

Duration

1 Plant centered 5.16E-02 2.03E-01 0.5 2 

2 Switchyard centered 1.02E-01 2.92E-01 1.3 5 

3 Grid related 9.26E-03 3.56E-02 2.7 9.3 

4 Severe weather related 2.51E-02 9.65E-02 5.4 25.1 

5 Extreme weather related 1.32E-03 5.08E-03 78 187.4 

6 Seismically induced 1.2E-04 78 187.4 

Sum = 1.89E-01 

Source = INEEL/EXT-04-02326, October 20004 
Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

Risk Assessment of Operational Events A1-6 

Attachment A - Calculations 

This attachment documents the calculational details of the frequencies of seismically-Induced 

LOOP events given in the main body of the report. 

A-1 Input-1: Seismic Event Frequencies 

The seismic event frequencies for 69 NPP sites east of the Rocky Mountains are given in 

NUREG-1488 (April 1994). Data taken from this source for seven example plants east of the 

Rock Mountains is given in Table AA-1. Similar data for plants to the West of the Rock 

Mountains may be obtained from the utilities, or their IPEEEs. 

A-2 Input-2: SSC Fragilities leading to LOOP 

Generally, the ceramic insulators with the lowest fragilities among the SSCs modeled in the 

PRAs govern the occurrence of LOOP following a seismic event. The generic fragility data for 

ceramic insulators is taken from NUREG-6544 (April 1998) as shown in Table AA-2. The mean 

failure probabilities at different g level earthquakes are calculated by using the equation: 

Pfail(a) = Φ [ ln(a/am) / sqrt(βr

2

 + βu

2

)] 

Where Φ is the standard normal cumulative distribution function and 

a = median acceleration level of the seismic event; 

am = median of the component fragility (or median capacity); 

βr = logarithmic standard deviation representing random uncertainty; 

βu = logarithmic standard deviation representing systematic or modeling uncertainty. 

Fragilities of SSCs that would cause LOOP for the plants west of the Rocky Mountains can also 

be calculated by using the information taken from their IPEEEs. 

Calculations of mean failure probabilities of SSCs as a function of g level for various cases are 

shown in Tables AA-2 and AA-3. 

A-3 Calculation of LOOP Frequency 

Once the initiating event frequencies at different g levels and their corresponding conditional 

LOOP probabilities are known, as given in Tables AA-1 through AA-3, the frequency of 

seismically-induced LOOP event can be calculated as a weighed average of frequencies at 

different g intervals. This is shown for seven plants in Tables A-1 through A-7. The summary 

Table 1 has the seismically induced LOOP frequencies for all SPAR models. 

A-4 Summary of Results 

The summary of results for 

1. Seismic initiating event frequencies 

2. Conditional probability of LOOP given seismic event 

3. Frequency of seismically-induced LOOP event 

for SPAR models is given in Table A-1. 
Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

 A1-7 Handbook Vol. 2 – External Events 

The calculations can be readily customized for plant-specific SSC fragilities and/or hazard 

curves. 

The seismically-induced LOOP frequency calculations for the 72 SPAR model plants are 

performed in a MS EXCEL workbook, which can be found by ADAMS accession number 

ML062540239. 
Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

Risk Assessment of Operational Events A1-8 

Table AA-1 Seismic Initiating Event Frequencies 

mean frequency of exceedance (per year)

g value Clinton Comanche Peak Duane Arnold Limerick Pilgrim Robinson 

0.05 1.55E-03 1.41E-04 1.55E-04 1.22E-03 2.81E-03 2.72E-03 0.08 8.08E-04 6.79E-05 8.11E-05 6.99E-04 1.78E-03 1.57E-03 0.15 2.46E-04 1.88E-05 2.38E-05 2.29E-04 7.15E-04 5.47E-04 0.25 9.42E-05 6.42E-06 8.21E-06 8.35E-05 3.27E-04 2.26E-04 0.30 6.54E-05 4.19E-06 5.36E-06 5.55E-05 2.41E-04 1.60E-04 0.40 3.57E-05 2.02E-06 2.58E-06 2.75E-05 1.44E-04 8.99E-05 0.50 2.17E-05 1.10E-06 1.40E-06 1.52E-05 9.38E-05 5.57E-05 0.65 1.17E-05 5.08E-07 6.42E-07 7.10E-06 5.45E-05 3.06E-05 0.80 6.89E-06 2.66E-07 3.34E-07 3.73E-06 3.43E-05 1.85E-05 1.00 3.79E-06 1.28E-07 1.59E-07 1.79E-06 2.02E-05 1.04E-05 

Seismic IE Freq. = 1.55E-03 1.41E-04 1.55E-04 1.22E-03 2.81E-03 2.72E-03 

For 69 NPP sites east of Rocky Mountains, NUREG-1488 provides Seismic IEV frequencies. For other plants West of Rocky mountains, this information can be obtained either from the plant, or from the literature, as neede
Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

 A1-9 Handbook Vol. 2 – External Events 

Table AA-2 Fragilities of SSCs causing seismically induced LOOP 

median 

capacity βr βu HCLPF 

Generic Ceramic Insulators 0.3 0.3 0.45 0.1 

used for all sites 

except those West of 

the Rocky Mountains 

Switchyard Fragility 0.31 0.25 0.43 0.1 Columbia 

Offsite Power 1.40 0.2200 0.2 0.7 Diablo Canyon 

Ceramic Insulators 0.3 0.3 0.45 0.1 Palo Verde 
Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

Risk Assessment of Operational Events A1-10 

Table AA-3 Calculation of mean failure probability of SSCs 

(causing LOOP) as a function of g level 

Ceramic Insulators

median 

capacity βr βu HCLPF HCLPF (calculated) 

0.3 0.3 0.45 0.1 0.087 

g value pf (median) pf(mean) g value pf(mean) 

0.05 1.17E-09 4.62E-04 0.05 0.0005 

0.08 5.27E-06 7.26E-03 0.1 0.0211 

0.15 1.04E-02 1.00E-01 0.15 0.1000 

0.25 2.72E-01 3.68E-01 0.2 0.2267 

0.3 5.00E-01 5.00E-01 0.25 0.3680 

0.4 8.31E-01 7.03E-01 0.3 0.5000 

0.5 9.56E-01 8.28E-01 0.35 0.6122 

0.65 9.95E-01 9.24E-01 0.4 0.7026 

0.8 9.99E-01 9.65E-01 0.45 0.7733 

1 1.00E+00 9.87E-01 0.5 0.8275 

 0.55 0.8688 

 0.6 0.9000 

pf = probability of failure 0.65 0.9236 

median pf is not used; for comparison only. 0.7 0.9414 

Note that median overshoots mean above 0.3g 0.75 0.9549 

 0.8 0.9651 

 0.85 0.9729 

 0.9 0.9789 

 0.95 0.9835 

 1 0.9870 

For SSC fragilities, a simple generic list is available in NUREG-6544 Table 6-1. 

Columbia Switchyard Fragility 

median 

capacity βr βu HCLPF HCLPF (calculated) 

0.31 0.25 0.43 0.1 0.101 

g value pf 

(median) pf(mean) 

0.05 1.47E-13 1.22E-04 

0.1 1.25E-04 1.15E-02 

0.2 8.83E-02 1.89E-01 

0.3 5.00E-01 4.74E-01 

0.4 8.31E-01 6.96E-01 

0.5 9.56E-01 8.32E-01 

0.6 9.90E-01 9.08E-01 

0.7 9.98E-01 9.49E-01 

0.8 9.99E-01 9.72E-01 

0.9 1.00E+00 9.84E-01 

1 1.00E+00 9.91E-01 
 Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

 A1-11 Handbook Vol. 2 – External Events 

Diablo Canyon Table 3-8 (page 3-53) of IPEEE Submittal 

Offsite Power median 

capacity βr βu HCLPF HCLPF (calculated) 

 1.40 0.2200 0.2 0.7 0.702 

g value pf(mean) 

0.2 2.99E-11 

0.5 2.67E-04 

0.8 2.99E-02 

1 1.29E-01 

1.2 3.02E-01 

1.5 5.92E-01 

2 8.85E-01 

2.5 9.74E-01 

3 9.95E-01 

4 1.00E+00 

San Onofre Table 3.6-1 (page 3.83) of IPEEE Submittal 

Switchyard SA(g) βr βu HCLPF HCLPF 

(calculated) 

 0.74 0.2 0.34 0.304 

IPEEE reports fragility in spectral acceleration; use generic fragility in units of PGA from Table AA-3 for 

failure probability calculations. 

Ceramic Insulators used for Palo Verde 

median 

capacity βr βu HCLPF HCLPF (calculated) 

0.3 0.3 0.45 0.1 0.087 

g value pf 

(median) pf(mean) g value pf(mean) 

0.01 0.00E+00 1.61E-10 0.05 0.0005 

0.02 0.00E+00 2.77E-07 0.1 0.0211 

0.05 1.17E-09 4.62E-04 0.15 0.1000 

0.07 6.15E-07 3.56E-03 0.2 0.2267 

0.1 1.25E-04 2.11E-02 0.25 0.3680 

0.15 1.04E-02 1.00E-01 0.3 0.5000 

0.2 8.83E-02 2.27E-01 0.35 0.6122 

0.3 5.00E-01 5.00E-01 0.4 0.7026 

0.5 9.56E-01 8.28E-01 0.45 0.7733 

1 1.00E+00 9.87E-01 0.5 0.8275 

 0.55 0.8688 

 0.6 0.9000 

pf = probability of failure 0.65 0.9236 

median pf is not used; for comparison only. 0.7 0.9414 

Note that median overshoots mean above 0.3g 0.75 0.9549 

 0.8 0.9651 

 0.85 0.9729 

 0.9 0.9789 

 0.95 0.9835 

 1 0.9870 
Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

Risk Assessment of Operational Events A1-12 

Table A-1 Clinton 

g value mean f 

per year 

LOOP 

Probability 

EQ g 

interval 

Interval 

IEV 

Frequency 

Interval 

Conditional 

LOOP 

Probability 

Weighted 

Average 

0.05 1.55E-03 4.62E-04 .05-.08 7.39E-04 1.83E-03 1.35E-06 

0.08 8.08E-04 7.26E-03 .08-.15 5.63E-04 2.70E-02 1.52E-05 

0.15 2.46E-04 1.00E-01 .15-.25 1.51E-04 1.92E-01 2.91E-05 

0.25 9.42E-05 3.68E-01 .25-.30 2.88E-05 4.29E-01 1.23E-05 

0.30 6.54E-05 5.00E-01 .30-.40 2.97E-05 5.93E-01 1.76E-05 

0.40 3.57E-05 7.03E-01 .40-.50 1.40E-05 7.63E-01 1.07E-05 

0.50 2.17E-05 8.28E-01 .50-.65 1.01E-05 8.74E-01 8.79E-06 

0.65 1.17E-05 9.24E-01 .65-.80 4.76E-06 9.44E-01 4.49E-06 

0.80 6.89E-06 9.65E-01 .80-1 3.10E-06 9.76E-01 3.03E-06 

1.00 3.79E-06 9.87E-01 >1 3.79E-06 1.00E+00 3.79E-06 

 Sum = 1.55E-03 1.06E-04 

SE Initiating Event Frequency = 1.55E-03 CCDP = 6.87E-02 

Seismically induced LOOP probability = 6.87E-02 

Seismically induced LOOP frequency = 1.06E-04 

Table A-2 Comanche Peak 

g value mean f 

per year 

LOOP 

Probability 

EQ g 

interval 

Interval 

IEV 

Frequency 

Interval 

Conditional 

LOOP 

Probability 

Weighted 

Average 

0.05 1.41E-04 4.62E-04 .05-.08 7.31E-05 1.83E-03 1.34E-07 

0.08 6.79E-05 7.26E-03 .08-.15 4.91E-05 2.70E-02 1.32E-06 

0.15 1.88E-05 1.00E-01 .15-.25 1.24E-05 1.92E-01 2.37E-06 

0.25 6.42E-06 3.68E-01 .25-.30 2.23E-06 4.29E-01 9.57E-07 

0.30 4.19E-06 5.00E-01 .30-.40 2.17E-06 5.93E-01 1.29E-06 

0.40 2.02E-06 7.03E-01 .40-.50 9.20E-07 7.63E-01 7.02E-07 

0.50 1.10E-06 8.28E-01 .50-.65 5.92E-07 8.74E-01 5.18E-07 

0.65 5.08E-07 9.24E-01 .65-.80 2.42E-07 9.44E-01 2.28E-07 

0.80 2.66E-07 9.65E-01 .80-1 1.38E-07 9.76E-01 1.35E-07 

1.00 1.28E-07 9.87E-01 >1 1.28E-07 1.00E+00 1.28E-07 

 Sum = 1.41E-04 7.78E-06 

SE Initiating Event Frequency = 1.41E-04 CCDP = 5.52E-02 

Seismically induced LOOP probability = 5.52E-02 

Seismically induced LOOP frequency = 7.78E-06 
 Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

 A1-13 Handbook Vol. 2 – External Events 

Table A-3 Duane Arnold 

g 

value 

mean f 

per year 

LOOP 

Probability 

EQ g 

interval 

Interval 

IEV 

Frequency 

Interval 

Conditional 

LOOP 

Probability 

Weighted 

Average 

0.05 1.55E-04 4.62E-04 .05-.08 7.38E-05 1.83E-03 1.35E-07 

0.08 8.11E-05 7.26E-03 .08-.15 5.73E-05 2.70E-02 1.54E-06 

0.15 2.38E-05 1.00E-01 .15-.25 1.56E-05 1.92E-01 2.99E-06 

0.25 8.21E-06 3.68E-01 .25-.30 2.85E-06 4.29E-01 1.22E-06 

0.30 5.36E-06 5.00E-01 .30-.40 2.78E-06 5.93E-01 1.64E-06 

0.40 2.58E-06 7.03E-01 .40-.50 1.19E-06 7.63E-01 9.05E-07 

0.50 1.40E-06 8.28E-01 .50-.65 7.55E-07 8.74E-01 6.60E-07 

0.65 6.42E-07 9.24E-01 .65-.80 3.08E-07 9.44E-01 2.91E-07 

0.80 3.34E-07 9.65E-01 .80-1 1.74E-07 9.76E-01 1.70E-07 

1.00 1.59E-07 9.87E-01 >1 1.59E-07 1.00E+00 1.59E-07 

 Sum = 1.55E-04 9.72E-06 

SE Initiating Event Frequency = 1.55E-04 CCDP = 6.28E-02 

Seismically induced LOOP probability 

= 

6.28E-02 

Seismically induced LOOP frequency = 9.72E-06 

Table A-4 Limerick 

g 

value 

mean f per 

year 

LOOP 

Probability 

EQ g 

interval 

Interval 

IEV Frequency

Interval 

Conditional 

LOOP 

Probability 

Weighted 

Average 

0.05 1.22E-03 4.62E-04 .05-.08 5.21E-04 1.83E-03 9.54E-07 

0.08 6.99E-04 7.26E-03 .08-.15 4.70E-04 2.70E-02 1.27E-05 

0.15 2.29E-04 1.00E-01 .15-.25 1.46E-04 1.92E-01 2.79E-05 

0.25 8.35E-05 3.68E-01 .25-.30 2.80E-05 4.29E-01 1.20E-05 

0.30 5.55E-05 5.00E-01 .30-.40 2.80E-05 5.93E-01 1.66E-05 

0.40 2.75E-05 7.03E-01 .40-.50 1.23E-05 7.63E-01 9.38E-06 

0.50 1.52E-05 8.28E-01 .50-.65 8.10E-06 8.74E-01 7.08E-06 

0.65 7.10E-06 9.24E-01 .65-.80 3.37E-06 9.44E-01 3.18E-06 

0.80 3.73E-06 9.65E-01 .80-1 1.94E-06 9.76E-01 1.89E-06 

1.00 1.79E-06 9.87E-01 >1 1.79E-06 1.00E+00 1.79E-06 

 Sum = 1.22E-03 9.35E-05 

SE Initiating Event Frequency = 1.22E-03 CCDP = 7.66E-02 

Seismically induced LOOP probability 

= 

7.66E-02 

Seismically induced LOOP frequency 

= 

9.35E-05 
Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

Risk Assessment of Operational Events A1-14 

Table A-5 Pilgrim 

g value mean f 

per year 

LOOP 

Probability 

EQ g 

interval 

Interval 

IEV 

Frequency 

Interval 

Conditional 

LOOP 

Probability 

Weighted 

Average 

0.05 2.81E-03 4.62E-04 .05-.08 1.04E-03 1.83E-03 1.90E-06 

0.08 1.78E-03 7.26E-03 .08-.15 1.06E-03 2.70E-02 2.86E-05 

0.15 7.15E-04 1.00E-01 .15-.25 3.88E-04 1.92E-01 7.45E-05 

0.25 3.27E-04 3.68E-01 .25-.30 8.62E-05 4.29E-01 3.70E-05 

0.30 2.41E-04 5.00E-01 .30-.40 9.69E-05 5.93E-01 5.74E-05 

0.40 1.44E-04 7.03E-01 .40-.50 5.03E-05 7.63E-01 3.84E-05 

0.50 9.38E-05 8.28E-01 .50-.65 3.93E-05 8.74E-01 3.44E-05 

0.65 5.45E-05 9.24E-01 .65-.80 2.02E-05 9.44E-01 1.90E-05 

0.80 3.43E-05 9.65E-01 .80-1 1.41E-05 9.76E-01 1.38E-05 

1.00 2.02E-05 9.87E-01 >1 2.02E-05 1.00E+00 2.02E-05 

 Sum = 2.81E-03 3.25E-04 

SE Initiating Event Frequency = 2.81E-03 CCDP= 1.16E-01 

Seismically induced LOOP probability = 1.16E-01 

Seismically induced LOOP frequency = 3.25E-04 

Table A-6 Robinson 

g value mean f 

per year 

LOOP 

Probability 

EQ g 

interval 

Interval 

IEV 

Frequency 

Interval 

Conditional 

LOOP 

Probability 

Weighted 

Average 

0.05 2.72E-03 4.62E-04 .05-.08 1.15E-03 1.83E-03 2.11E-06 

0.08 1.57E-03 7.26E-03 .08-.15 1.02E-03 2.70E-02 2.74E-05 

0.15 5.47E-04 1.00E-01 .15-.25 3.21E-04 1.92E-01 6.16E-05 

0.25 2.26E-04 3.68E-01 .25-.30 6.56E-05 4.29E-01 2.81E-05 

0.30 1.60E-04 5.00E-01 .30-.40 7.01E-05 5.93E-01 4.15E-05 

0.40 8.99E-05 7.03E-01 .40-.50 3.42E-05 7.63E-01 2.60E-05 

0.50 5.57E-05 8.28E-01 .50-.65 2.51E-05 8.74E-01 2.20E-05 

0.65 3.06E-05 9.24E-01 .65-.80 1.21E-05 9.44E-01 1.15E-05 

0.80 1.85E-05 9.65E-01 .80-1 8.06E-06 9.76E-01 7.87E-06 

1.00 1.04E-05 9.87E-01 >1 1.04E-05 1.00E+00 1.04E-05 

 Sum = 2.72E-03 2.39E-04 

SE Initiating Event Frequency = 2.72E-03 CCDP= 8.78E-02 

Seismically induced LOOP probability = 8.78E-02 

Seismically induced LOOP frequency = 2.39E-04 
 Appendix 1 Frequencies of Seismically-Induced LOOP Events for SPAR Models 

 A1-15 Handbook Vol. 2 – External Events 

Table A-7 Vogtle 

g value mean f 

per year 

LOOP 

Probability 

EQ g 

interval 

Interval 

IEV 

Frequency

Interval 

Conditional 

LOOP 

Probability 

Weighted 

Average 

0.05 2.50E-03 4.62E-04 .05-.08 1.14E-03 1.83E-03 2.09E-06 

0.08 1.36E-03 7.26E-03 .08-.15 9.41E-04 2.70E-02 2.54E-05 

0.15 4.15E-04 1.00E-01 .15-.25 2.61E-04 1.92E-01 5.00E-05 

0.25 1.55E-04 3.68E-01 .25-.30 4.86E-05 4.29E-01 2.08E-05 

0.30 1.06E-04 5.00E-01 .30-.40 4.92E-05 5.93E-01 2.92E-05 

0.40 5.68E-05 7.03E-01 .40-.50 2.26E-05 7.63E-01 1.72E-05 

0.50 3.42E-05 8.28E-01 .50-.65 1.59E-05 8.74E-01 1.39E-05 

0.65 1.83E-05 9.24E-01 .65-.80 7.36E-06 9.44E-01 6.95E-06 

0.80 1.09E-05 9.65E-01 .80-1 4.76E-06 9.76E-01 4.64E-06 

1.00 6.18E-06 9.87E-01 >1 6.18E-06 1.00E+00 6.18E-06 

 Sum = 2.50E-03 1.76E-04 

SE Initiating Event Frequency = 2.50E-03 CCDP = 7.05E-02 

Seismically induced LOOP probability = 7.05E-02 

Seismically induced LOOP frequency = 1.76E-04