QUANTIFYING LOW PROBABILITY 

HUMAN FAILURE EVENTS 

Prepared for 

U.S. Nuclear Regulatory Commission 

Contract NRC–02–07–006 

Prepared by 

George Adams 

Center for Nuclear Waste Regulatory Analyses 

San Antonio, Texas 

September 2011 
ii 

ABSTRACT 

This report, which has been prepared as a knowledge capture report for the U.S. Nuclear 

Regulatory Commission, Division of High-Level Waste Repository Safety, documents an 

approach that can be used to systematically examine and identify, in a risk-informed manner, 

dominant contributors to human failure event modeling. For an example set consisting of seven 

low probability human failure events, the report (i) identifies the extent to which various human 

reliability analysis methods included human (and hardware) factors and (ii) uses sensitivity 

analysis to examine how ranges of potential uncertainty in the human factors affect the 

calculated human error probabilities. The sensitivity analysis identified several potentially 

significant contributors to the human error probabilities for these seven examples; namely, 

working conditions, the availability of time to perform an activity, and dependency between 

operator actions. The overall result of the approach documented here is to afford a 

risk-informed estimate of the importance of individual human factor uncertainties on human 

error probabilities. This approach has a potential application in identifying which technical 

bases for human factors are the most significant on which to focus during a review of low 

probability human failure events. 
iii 

CONTENTS 

Section Page 

ABSTRACT ................................................................................................................................... ii 

FIGURES ..................................................................................................................................... iv 

TABLES ........................................................................................................................................ v 

ACKNOWLEDGMENTS .............................................................................................................. vi 

ACRONYMS/ABBREVIATIONS .................................................................................................. vii 

1 INTRODUCTION ............................................................................................................ 1-1

2 QUANTIFICATION OF THE HUMAN FAILURE EVENT EXAMPLES ........................... 2-1

2.1 Description of Examples ..................................................................................... 2-2

2.2 Summary of Methods and Factors Applied in the Human Reliability Analysis ... 2-5

3 SENSITIVITY ANALYSIS OF FACTORS AFFECTING HUMAN FAILURE 

EVENT PROBABILITIES ............................................................................................... 3-1

3.1 Examples A and G: Exposure During Transport and Emplacement Vehicle 

Loading (060–OPDIREXPOSE3–HFI–NOD and 51A–OPDIREXPOSE3 

–HFI–NOD) ........................................................................................................ 3-2

3.2 Example B: Operator Failure During Canister Staging 

(060–OPSTAGERACK1–HFI–NOD) .................................................................. 3-3

3.3 Example C and Example F: Direct Exposure in Canister Transfer Room 

(060–OPCTMDIREXP1–HFI–NOD and 200–OPCTMDIREXP1–HFI–NOD) ..... 3-4

3.4 Example E: Operator Fails To Install Shielded Transfer Cask Shield Ring 

Properly (050–OPSTCSHIELD1–HFI–COD) ...................................................... 3-5

3.5 Example D: Operator Fails To Install Waste Package Inner Lid 

(060–OPWPINNERLID–HFI–NOD).................................................................... 3-6

3.6 Significant Contributors to Human Error Probability ........................................... 3-6

4 SUMMARY ..................................................................................................................... 4-1

5 REFERENCES ............................................................................................................... 5-1
iv 

FIGURES 

Figure Page 

3-1 Examples A and G: 060/51A–OPDIREXPOSE3–HFI–NOD Sensitivity Analysis ......... 3-2 

3-2 Example B: 060–OPSTAGERACK1–HFI–NOD Sensitivity Analysis ............................ 3-4 

3-3 Examples C and F: 060/200–OPCTMDIREXP1–HFI–NOD Sensitivity Analysis .......... 3-5 

3-4 Example E: 050–OPSTCHIELD1–HFI–COD Sensitivity Analysis ................................. 3-6 
v 

TABLES 

Table Page 

2-1 Low Probability Human Failure Events That Are Dominant Contributors to Event 

Sequence Frequency ..................................................................................................... 2-3 

2-2 Summary of Methods and Factors Used in Human Failure Analyses ............................ 2-6 
vi 

ACKNOWLEDGMENTS 

This report was prepared to document work performed by the Center for Nuclear Waste 

Regulatory Analyses (CNWRA®) and its contractors for the U.S. Nuclear Regulatory 

Commission (NRC) under Contract No. NRC–02–07–006. The activities reported here were 

performed on behalf of the NRC Office of Nuclear Material Safety and Safeguards, Division of 

High-Level Waste Repository Safety. This report is an independent product of CNWRA and 

does not necessarily reflect the views or regulatory position of NRC. 

The author thanks A. Ghosh for technical review, O. Pensado, D. Pickett, and J. Winterle for 

programmatic review, and J. McMurry and K. Compton for feedback and support to revise this 

report. The author also appreciates A. Ramos for providing word processing support and 

L. Mulverhill for editorial support in the preparation of this document. 

QUALITY OF DATA, ANALYSES, AND CODE DEVELOPMENT 

DATA: CNWRA data summarized in this report meet quality assurance requirements described 

in the CNWRA Quality Assurance Manual. Calculations have been recorded in CNWRA 

Scientific Notebook Number 1073E (Adams, 2011). Data used to support descriptions in this 

report are also taken from documents published by U.S. Department of Energy contractors and 

supporting organizations; the respective sources of these non-CNWRA data should be 

consulted for determining the level of quality assurance. 

ANALYSES AND CODES: Microsoft® Excel® 2007 (Microsoft, 2006) was used to organize the 

data and produce graphs. SAPHIRE 7 (Idaho National Engineering and Environmental 

Laboratory, 2011) was used to generate event sequence results. 

REFERENCES 

Adams, G. “Quantifying Low Probability Human Failure Events.” Scientific Notebook 1073E. 

San Antonio, Texas: CNWRA. pp. 1–2. 2011. 

Idaho National Engineering and Environmental Laboratory. “SAPHIRE 7 (Version 7.27.0.41).” 

<https://saphire.inel.gov/> (8 February 2011). 

Microsoft. “Microsoft Office Excel 2007.” Redmond, Washington: Microsoft Corporation. 2006. 

 
vii 

ACRONYMS/ABBREVIATIONS 

APOA Assessed Proportion of Affects 

ATHEANA A Technique for Human Event Analysis 

BSC Bechtel SAIC Company, LLC 

CFF Cognitive Function Failure 

CNWRA Center for Nuclear Waste Regulatory Analyses 

CPC Common Performance Condition 

CRCF Canister Receipt and Closure Facility 

CREAM Cognitive Reliability and Error Analysis Method 

CTM Canister Transfer Machine 

DOE 

EPC 

U.S. Department of Energy 

Error-Producing Condition 

ESD Event Sequence Diagram 

GTT Generic Task Type 

HEART Human Error Assessment and Reduction Technique 

IHF Initial Handling Facility 

NARA Nuclear Action Reliability Assessment 

NRC U.S. Nuclear Regulatory Commission 

RF Receipt Facility 

TAD Transportation, Aging, and Disposal 

THERP Technique for Human Error Rate Prediction 

WHF Wet Handling Facility 
1-1 

1 INTRODUCTION 

This report, which has been prepared as a knowledge capture report for the U.S. Nuclear 

Regulatory Commission, Division of High-Level Waste Repository Safety, documents an 

approach that can be used to systematically examine and identify, in a risk-informed manner, 

dominant contributors to human failure event modeling. For an example set of low probability 

human failure events, the report (i) identifies the extent to which various human reliability 

analysis methods included human (and hardware) factors and (ii) uses sensitivity analysis to 

examine how ranges of potential uncertainty in the human factors affect the calculated human 

error probabilities. The overall result of the approach is to provide a risk-informed estimate of 

the importance of individual human factor uncertainties on human error probabilities. This 

approach has a potential application in identifying which technical bases for human factors are 

the most significant to focus on during a review of low probability human failure events. 

As described by the Human Factors and Ergonomics Society (2011), “human factors” is a term 

that is concerned with the application of what we know about people; their abilities, 

characteristics, and limitations to the design of equipment they use; environments in which they 

function; and jobs they perform. In the context of this report, the term refers more specifically to 

characteristics of the operators, supervisors, or workers (such as adequate training) and to 

characteristics of the working environment (such as advantageous working conditions). This 

report focuses on low probability human failure events, defined here as those events having 

a probability less than 1 × 10−4

, that are dominant contributors (i.e., contribute more than 

50 percent) to event sequence frequency. 

An event sequence is a schematic representation of the logical progression of an accident 

scenario leading to undesired consequences (Stewart and Melchers, 1997). It describes the 

order in which events occur in time, starting with an initiating event and followed by subsequent 

responses of systems and/or human actions to this initiator. The end state of an event 

sequence is a specific outcome, such as a direct radiation exposure or a particulate release, 

and is expressed in terms of a frequency. This frequency is the expected number of 

occurrences of the event sequence over a specified time period. Low probability human failure 

events, which are the subject of this report, can become dominant contributors to event 

sequence frequency when, for example, they are the only initiator in event sequences with 

no other systems in place to mitigate the consequences or reduce the frequency of the 

event sequence. 

This report examines seven low probability human failure events, taken as examples from 

published human failure event analyses, and develops a sensitivity analysis for the human 

factors that were used to quantify these human failure events. The example human failure 

events and their calculated human error probabilities were taken from descriptions of low 

probability human failure events for hypothetical facilities that receive and handle radioactive 

waste. The U.S. Department of Energy (DOE) originally developed the examples, which involve 

surface facilities only and do not include fire-related event sequences, for various event 

sequences in a Canister Receipt and Closure Facility (CRCF) (BSC, 2009a), a Wet Handling 

Facility (WHF) (BSC, 2009b), a Receipt Facility (RF) (BSC, 2009c), and an Initial Handling 

Facility (IHF) (BSC, 2008). 

The seven examples focus on human error as it relates to operations within surface facilities. In 

some cases, human failure events involve multiple human failure scenarios. For example, a 

human failure scenario might involve a worker receiving a direct exposure because someone 

mistakenly did not install shielding. Another human failure scenario might involve a worker 

receiving a direct exposure because someone installed shielding improperly. The sum of the 
1-2 

failure probabilities from these two scenarios could represent the probability for a human failure 

event in which a worker receives a direct exposure during a cask preparation activity. 

Each identified step in an event sequence can be quantified in terms of success or failure 

probabilities. In assessing the safety of work-related processes, the effect of human failure 

can be considered and quantified by a number of human reliability analysis methods. In 

the selected examples, DOE used a combination of five different human reliability 

analysis methods: 

 Nuclear Action Reliability Assessment (NARA) (Corporate Risk Associates, 2006) 

 Cognitive Reliability and Error Analysis Method (CREAM) (Hollnagel, 1998) 

 Human Error Assessment and Reduction Technique (HEART) (Williams, 1986) 

 The expert elicitation approach from A Technique for Human Event Analysis 

(ATHEANA) (NRC, 2000) 

 Technique for Human Error Rate Prediction (THERP) (Swain and Guttmann, 1983) 

Although DOE did not categorize human factors explicitly in the human reliability analyses, most 

of the examples included the use of the human reliability analysis method CREAM, a method 

that clearly addressed four areas involving human factors: (i) the presence of administrative 

controls or the availability of procedures, (ii) the adequacy of training, (iii) the availability of time 

to perform an activity, and (iv) working conditions. To develop the sensitivity analysis in this 

report, human factors are categorized into these four areas regardless of the human reliability 

analysis method. 
2-1 

2 QUANTIFICATION OF THE HUMAN FAILURE EVENT EXAMPLES 

Ultimately in this report, a sensitivity analysis is used to assess the effect of uncertainty on 

calculated human failure event probabilities. However, when several facilities are considered 

and each facility has multiple potential human failure events, the sensitivity analysis can be 

large. To narrow the sensitivity analysis, a systematic approach is needed to rapidly identify the 

human failure events that are most important from a risk-informed perspective. This proposed 

systematic approach consists of a series of filters that are applied in succession followed by a 

sensitivity analysis as follows: 

1. Filter Event Sequences: For all of the facilities under consideration, identify the higher 

frequency event sequences. In this report, event sequences with a frequency1

 of 

1 × 10−2

 or higher were examined because these event sequences are closer to the 

boundary between Category 1 and Category 2 defined in 10 CFR 63.2. 

2. Filter Human Failure Events: Identify the low probability2

 human failure events in each of 

the higher frequency event sequences. In this report, human failure events with a 

probability less than 1 × 10−4

 were examined because, in general, a detailed 

quantification analysis (as opposed to a screening analysis) is used at probabilities less 

than 1 × 10−4

 and oftentimes in a detailed analysis, more than one human factor is 

needed to obtain the low probability. 

3. Filter Contributors: Identify those human failure events that are dominant contributors to 

event sequence frequency. In this report, human failure events that are dominant 

contribute more than 50 percent to the event sequence frequency. The value of 

50 percent was arbitrarily chosen. The assumption here is that if a single event (in this 

case, human failure event) in an event sequence contributes more than half to the event 

sequence frequency, then uncertainties in its quantification may significantly affect 

uncertainties in the overall event sequence frequency. 

4. Perform a Sensitivity Analysis: For the resulting low probability human failure events 

that are dominant contributors to event sequence frequency, identify the human factors 

with the potential to significantly affect event sequence frequency. For the sensitivity 

analysis in this report, if a human factor can degrade to the point that the overall 

event sequence frequency approaches or crosses a categorization boundary 

(previously discussed in Step 1), then that human factor is considered to have the 

potential to significantly affect event sequence frequency. 

To prepare for the sensitivity analysis, it is necessary to examine the methods used for human 

failure event quantification and to note which human (and hardware) factors were contributors to 

the human error probability. This section of the report describes the seven examples used for 

the subsequent sensitivity analysis and identifies the human reliability analysis methods DOE 

used to quantify the human failure events. 

Table 2-1 lists the seven examples, A through G, of low probability human failure events and 

their associated event sequences. All the human failure events in the table have a probability 

less than 1 × 10−4

 and contribute more than 50 percent to an event sequence frequency. The 

 

1

Event sequence frequency has units of estimated number of occurrences over the operational period. The 

operational period may be several years. 

2

A human error probability is the estimated likelihood that an individual will fail to accomplish the activity identified 

within an event sequence. 
2-2 

table shows cut sets of higher frequency (1 × 10−2

 or higher) event sequences. (A cut set is a 

combination of one or more failure events—that is, human failures, system failures, or 

component failures—that when taken together, specify the accident progression for an event 

sequence.) In the examples, each human failure event was the only basic event 

(i.e., contributor to failure) in its cut set. Therefore, the cut set frequency represents the product 

of the human error probability and the throughput (e.g., number of canisters processed over a 

time period). Table 2-1 shows the percentage contribution of the cut set to the event sequence 

frequency. Because the human failure event is the only event in each cut set, this percentage 

contribution is also the human failure event contribution to the event sequence frequency. 

All event sequences in Table 2-1 are direct exposure event sequences and are part of various 

event sequence diagrams (ESDs) that are detailed in the Table 2-1 supporting references. The 

ESD18 event sequences in the CRCF and the ESD11 event sequences in the RF are direct 

exposures during operations involving the canister transfer machine (CTM). The ESD19 event 

sequences in the CRCF and the ESD12C event sequence in the IHF are direct exposures 

during waste package closure and export. The ESD29 event sequence in the WHF involves 

direct exposure during closure activities for a transportation, aging, and disposal (TAD) canister. 

2.1 Description of Examples 

The seven examples are briefly described here. More detailed information about each 

example is provided in the Appendix, including the human reliability analysis methods, the 

estimated human error probabilities, and the human factors that contribute to the human 

error probabilities. 

Table 2-1, Examples A and G, Exposure during Transport and Emplacement Vehicle Loading 

(BSC, 2009a, 2008) both represent human failure events that result in exposure while loading a 

waste package onto a transport vehicle. Example A is postulated to occur in the CRCF, and 

Example G is postulated to occur in the IHF. Both human failure events were quantified by the 

same human reliability analysis methods and used the same parameters within these methods 

(Table A–1), so the two examples are treated together for the sensitivity analysis. In Examples 

A and G, three scenarios with individual probabilities (Table A–1) were added together to 

estimate the overall human error probability for the human failure event. In the first scenario, a 

crew member remains in the Waste Package Loadout Room (possibly due to an operator failing 

to order an evacuation) and fails to exit, and a radiation protection worker fails to check or 

recognize that someone has remained in the room. Note the first scenario dominates the 

human error probability; therefore, it is described here and the other two scenarios are detailed 

in the Appendix. 

Table 2-1, Example B, Operator Failure during Canister Staging (BSC, 2009a), has only one 

scenario (Table A–2) and is postulated to occur in the CRCF. In this scenario, an operator 

working from the CRCF control room fails to close the staging rack port gate before raising the 

CTM shield skirt and a supervisor fails to check that the port gate is closed at the end of 

operations (e.g., at the end of a shift). 

Table 2-1, Examples C and F, Direct Exposure in Canister Transfer Room (BSC, 2009a,c), both 

involve a direct exposure during canister transfer. Example C is postulated to occur in the 

CRCF, and Example F is postulated to occur in the RF. Both human failure events were 

quantified using the same human reliability analysis methods and used the same parameters 

within these methods (Table A–3), so they are treated together in the sensitivity analysis. 

These human failure events consist of a scenario in which a worker violates an administrative 
2-3 

Table 2-1. Low Probability Human Failure Events That Are Dominant Contributors to Event Seque

Human Failure Event Description 

Human 

Error 

Probability

Event Sequence 

Identifier* 

Cut Set 

Frequency/Ev

Sequence 

Frequency 

Canister Receipt and Closure Facility (CRCF)† 

Example A: 060–OPDIREXPOSE3–HFI–NOD 

Exposure During Transport and Emplacement Vehicle Loading 

3 × 10−5 CRCF–ESD19–WP–TAD,3 0.244/0.244 

CRCF–ESD19–WP–H&D,3 0.099/0.099 

Example B: 060–OPSTAGERACK1–HFI–NOD 

Operator Failure During Canister Staging 

3 × 10−5 CRCF–ESD18–DSTD,2 0.186/0.302 

Example C: 060–OPCTMDIREXP1–HFI–NOD 

Direct Exposure in Canister Transfer Room 

8 × 10−6 CRCF–ESD18–TAD,2 0.121/0.130 

CRCF–ESD18–HLW,2 0.078/0.085 

CRCF–ESD18–DSTD,2 0.050/0.302 

Example D: 060–OPWPINNERLID–HFI–NOD 

Operator Fails To Install Waste Package Inner Lid 

6 × 10−6 CRCF–ESD19–WP–TAD,2 0.049/0.057 

CRCF–ESD19–WP–H&D,2 0.020/0.023 

Wet Handling Facility (WHF)

‡

Example E: 050–OPSTCSHIELD1–HFI–COD 

Operator Fails To Install Shielded Transfer Cask Shield Ring Properly 

6 × 10−5 WHF–ESD29–TAD,2 0.070/0.070 

Receipt Facility (RF)

§

Example F: 200–OPCTMDIREXP–HFI–NOD 

Direct Exposure in Canister Transfer Room 

8 × 10−6 RF–ESD11,2 0.059/0.067 
2-4 

Table 2-1. Low Probability Human Failure Events That Are Dominant Contributors to Event S

Frequency (continued) 

Human Failure Event Description 

Human 

Error 

Probability

Event Sequence 

Identifier* 

Cut Set 

Frequency/Ev

Sequence 

Frequency 

Initial Handling Facility (IHF)║

Example G: 51A–OPDIREXPOSE3–HFI–NOD 

Exposure During Transport and Emplacement Vehicle Loading 

3 × 10−5 IHF–ESD–12C–NVL,2 0.012/0.012 

*The event sequence identifier contains two main parts and several subparts. For example, event sequence identifier “CRCF–ESD19–W

event sequence 3 in event tree “CRCF–ESD19–WP–TAD” where the event tree graphically depicts a group of event sequences (in this cwaste package closure activities). For this event tree, “CRCF” specifies event sequences in the CRCF, “ESD19” refers to event sequen

TAD” identifies that the event sequence is associated with a waste package containing a transportation, aging, and disposal canister. 

†BSC. “CRCF Reliability and Event Sequence Categorization Analysis.” 060–PSA–CR00–00200–000. Rev. 00B. Las Vegas, Nevada

LLC. 2009. 

‡_____. “WHF Reliability and Event Sequence Categorization Analysis.” 050–PSA–WH00–00200–000. Rev. 00B. Las Vegas, Nevada: Bechtel SAIC Company, LLC. 2009. §_____. “RF Reliability and Event Sequence Categorization Analysis.” 200–PSA–RF00–00200–000. Rev. 00B. Las Vegas, Nevada: Bechtel SAIC Company, LLC. 2009. ║____. “IHF Reliability and Event Sequence Categorization Analysis.” 

51A–PSA–IH0–00200–000. Rev. 00A, CACN 001. Las Vegas, Nevada: Bechtel SAIC Company, LLC. 2008. 
 2-5

control and enters the Canister Transfer Room during a transfer, combined with the failure of 

the control room operator to close the port gate before raising the CTM shield skirt. 

Table 2-1, Example D, Operator Fails to Install Waste Package Inner Lid (BSC, 2009a), has the 

lowest human error probability (6 × 10−6

) of the seven low probability human failure events. It is 

postulated to occur in the CRCF. This human failure event consists of a single scenario 

(Table A–4), in which an operator fails to install the waste package inner shield lid, and a 

worker, violating an administrative control, enters the Waste Package Closure Room prior to the 

start of welding. 

Table 2-1, Example E, Operator Fails to Install Shielded Transfer Cask Shield Ring Properly 

(BSC, 2009b), has the highest human error probability (6  10−5

) of the seven low probability 

human failure events. It is postulated to occur in the WHF and consists of two scenarios with 

individual probabilities that are added to estimate the human error probability (Table A–5). Prior 

to draining the TAD canister in preparation for closure, a shield ring must be installed. In the 

first scenario, the crane operator fails to install the shield ring; crew members do not realize this 

step in the process was missed, and before approaching the TAD canister, they fail to notice the 

shield ring is not in place. Note the first scenario dominates the human error probability; 

therefore, it is described here and the second scenario is detailed in the Appendix. 

Most of the human failure events listed in Table 2-1 contribute more than 85 percent to their 

event sequence frequency. For the two human failure events with lower contributions, both 

occur in Event Sequence 2 of CRCF–ESD18–DSTD; taken together, they account for 

79 percent (i.e., the sum of 62 percent and 17 percent) of the event sequence frequency. 

2.2 Summary of Methods and Factors Applied in the Human 

Reliability Analysis 

Table 2-2 identifies the human reliability analysis methods and the human and hardware factors 

that DOE used to determine the human error probability for the seven example human failure 

events. The human reliability analysis methods and factors applied for the specific examples 

are detailed in the Appendix. For all but one of the human failure events, DOE developed the 

human error probability using more than one human reliability analysis method. As shown in 

Table 2-2, NARA is common to all seven examples and CREAM is common to all of the 

examples except Example D. In addition to NARA and CREAM, HEART and THERP were 

used for Examples A and G and ATHEANA and THERP were used in addition to NARA and 

CREAM for Example E. Example D was the only human failure event of the seven to use just 

one human reliability analysis method (i.e., NARA). 

Three of the human failure events (Examples A, G, and E) include a hardware failure (e.g., the 

failure of an interlock, pressure sensor, or radiation sensor) in addition to human failures. 

However, for Examples A and G, the hardware failure occurs only in the third scenario and 

results in only a minor contribution to event sequence frequency (Table A–1). For Example E, 

the probability of the hardware failure (a radiation sensor failure) is at least an order of 

magnitude lower than the human errors associated with the radiation protection worker and 

therefore has little effect on the results. 

 
 2-6

Table 2-2. Summary of Methods and Factors Used in Human Failure Analyses 

Human Reliability 

Analysis Method 

Human Failure Event or Scenario 

(Human Error Probability) 

Factors DOE Described in 

Human Failure Analysis 

NAR

A* 

CRE

AM† 

HEART‡ 

ATHEAN

A§ 

THERP║Hardware 

Administrative 

Controls or 

Available 

Procedures 

Adequate 

Training 

Adequate Time Advantageous 

Working Conditions 

    Example A (060–OPDIREXPOSE3–HFI–

NOD) 

Example G (51A–OPDIREXPOSE3–HFI–

NOD) 

(3  10−5

) 

    

  Example B (060–OPSTAGERACK1–HFI–

NOD) 

(3  10−5

) 

   

  Example C (060–OPCTMDIREXP1–HFI–

NOD) 

Example F (200–OPCTMDIREXP1–HFI–

NOD) 

(8  10−6

) 

   

 Example D (060–OPWPINNERLID–HFI–

NOD) 

(6  10−6

) 

  

    Example E (050–OPSTCSHIELD1–HFI–

COD) 

(6  10−5

) 

  

*NARA = Nuclear Action Reliability Assessment 

†CREAM = Cognitive Reliability and Error Analysis Method 

‡HEART = Human Error Assessment and Reduction Technique 

§ATHEANA = A Technique for Human Event Analysis 

║THERP = Technique for Human Error Rate Prediction
 3-1

3 SENSITIVITY ANALYSIS OF FACTORS AFFECTING HUMAN FAILURE 

EVENT PROBABILITIES 

As shown in Table 2-2, the human reliability analysis methods NARA and CREAM were used 

more frequently to quantify the human failure events in the seven example cases than any of 

the other human reliability analysis methods. In addition, the human factors that were described 

in the human reliability analyses were primarily associated with NARA and CREAM. 

Consequently, the sensitivity analysis focuses primarily on these two methods and their 

application to the seven examples. 

For CREAM, the human factors (administrative controls or availability of procedures, adequate 

training, adequate time, advantageous working conditions) and their effects on common 

performance conditions (CPCs) are assessed by a sensitivity analysis in the sections that 

follow. Similarly, for NARA, the human factors and their effects on assessed proportion of 

affects (APOA) for error-producing conditions (EPCs) are described and assessed in the 

sections that follow. Note that for CREAM and for NARA, the human factors shown in Table 2-2 

may also have been associated with generic task types (GTTs) in NARA or cognitive function 

failures (CFFs) in CREAM. Rather than focusing specifically on uncertainties associated with 

GTTs or CFFs, the sensitivity analysis focuses on ranges of potential uncertainty once the 

generic failure type pertaining to a GTT or CFF is identified. This approach assumes the type of 

human error is adequately reflected by the GTTs or CFFs that DOE assigned, and the 

uncertainty lies in context-specific human factors reflected by EPCs, APOAs, and CPCs. The 

following equations show these quantification parameters for human error probabilities 

calculated using NARA [Eq. (3-1)] and CREAM [Eq. (3-2)]. 

NARA: Probability = GTT  [(EPC1–1)  APOA1 + 1]  ...  [(EPCn–1)  APOAn + 1], 

for n EPCs (3-1)

CREAM: Probability = CFF  CPC1  CPC2  ...  CPCn, for n CPCs (3-2)

For further descriptions of these parameters and how they are applied in the individual human 

reliability analysis methods, see the supporting references for NARA (Corporate Risk 

Associates, 2006) and CREAM (Hollnagel, 1998). 

If the same human reliability analysis method was used multiple times to quantify a human 

failure event and it used the same factor every time, then this factor was changed in all 

instances of the sensitivity analysis. This was done to reflect the effect of this factor on a 

specific human reliability analysis method and to show a potential worst case for one human 

factor in a particular method. 

The figures in the sections that follow show the effects individual factors within a human 

reliability analysis method may have on a human error probability. Each figure has a baseline 

curve (represented by a dotted line) that corresponds to the human error probability for that 

example in Table 2-1 . The value DOE specified for a human factor is indicated by the point 

along the x-axis (Range of Factors) where the curve for one of the four human factors 

categories (i.e., administrative controls or availability of procedures, adequate training, adequate 

time, advantageous working conditions) crosses the baseline. The upper ends of the probability 

curves are truncated by the maximum end of the range for a particular factor (which differs 

depending on the factor and the human reliability analysis method used). Factors with a 

potential to have a significant effect on human error probability are summarized in Section 3.6. 

The figures also display (as horizontal dashed lines) one or more categorization boundaries, in 
 3-2

terms of probability, for specific event sequences identified for that example in Table 2-1. If the 

human error probability curve for a sensitivity analysis factor falls below the dashed line, then 

the associated cut set frequency for that event sequence is in the Category 2 range, as defined 

in 10 CFR 63.2. Above the dashed line, the cut set frequency and therefore the associated 

event sequence frequency fall in the Category 1 range. 

3.1 Examples A and G: Exposure During Transport and 

Emplacement Vehicle Loading (060–OPDIREXPOSE3–HFI–NOD 

and 51A–OPDIREXPOSE3–HFI–NOD) 

Figure 3-1 shows that the probability for the human failure events in Examples A and G 

(060–OPDIREXPOSE3–HFI–NOD and 51A–OPDIREXPOSE3–HFI–NOD) increases as 

parameters associated with the four human factors categories (e.g., CPCs for CREAM or 

APOAs for NARA) are increased individually. The baseline curve shows DOE’s human error 

probability of 3 × 10−5

. The leftmost curve shows the effect of one factor (i.e., working 

conditions) associated with NARA, and the remaining curves show the effect of each of the four 

human factors on the quantification associated with CREAM. As described in Table 2-1, human 

failure events 060–OPDIREXPOSE3–HFI–NOD and 51A–OPDIREXPOSE3–HFI–NOD are 

dominant contributors in three event sequences (two event sequences in the CRCF and one 

event sequence in the IHF). The dashed lines in Figure 3-1 are the points where the human 

error probabilities would be sufficiently high such that the cut set frequency and therefore the 

event sequence frequency would cross a categorization boundary from Category 2 to 

Category 1. The dashed lines are calculated as one divided by the throughput to reflect at least 

one occurrence of the human failure event. 

Figure 3-1. Examples A and G: 060/51A–OPDIREXPOSE3–HFI–NOD Sensitivity Analysis 

1.00E-05

1.00E-04

1.00E-03

1.00E-02

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0

Human Error Probability

Range of Factors

(1) NARA: Working Conditions

(2) CREAM: Available Time

(3) CREAM: Adequacy of Training

(4) CREAM: Availability of Procedures IHF-ESD12C-NVL, 2

CRCF-ESD19-WP-H&D, 3

CRCF-ESD19-WP-TAD, 3

Baseline

(2)

(3)

(4)

(5)
 3-3

Because DOE identified a small level of distraction for a crew member hearing an 

announcement to evacuate, this part of the NARA quantification is categorized 

under “working conditions” in this report. The original DOE analysis also described 

training and procedures in its NARA quantification and allowed some credit for available time for 

a crew member to exit the Waste Package Loadout Room. The factor having the greatest 

influence on human error probability in the NARA quantification involves working conditions, and 

therefore it is shown in the figure. Figure 3-1 shows that as the working conditions degrade for 

a crew member (possibly from increasing machine noise), the human error probability and 

resulting event sequence frequency may increase significantly. For Event Sequence 3 of 

CRCF–ESD19–WP–TAD, at the hypothetical upper extreme involving working conditions, the 

human error probability is high enough that the resulting event sequence frequency approaches 

the categorization boundary (i.e., Curve 1 in Figure 3-1). 

More significant effects are shown in the quantifications associated with CREAM. Within the 

060–OPDIREXPOSE3–HFI–NOD and 51A–OPDIREXPOSE3–HFI–NOD human failure event 

quantification, DOE credited adequate available time (i.e., CPC = 0.5) in one case and also 

identified some time pressure (i.e., CPC = 1.0) in other cases. As shown in Figure 2-1, as the 

adequacy of available time lessens from adequate available time (i.e., CPC = 0.5) to 

continuously inadequate available time at the hypothetical upper extreme (i.e., CPC = 5.0), the 

human error probability increases significantly, resulting in the cut set frequency and therefore 

also the event sequence frequency crossing a categorization boundary for two of the event 

sequences in the CRCF. Additionally, for adequacy of training (although the human error 

probability would not be high enough to result in an event sequence frequency that would cross 

a categorization boundary), Figure 3-1 shows that the frequency would approach the boundary 

for one event sequence in the CRCF as the adequacy of training moves from adequate and is 

associated with high experience (i.e., CPC = 0.8) to a value of inadequate (i.e., CPC = 2.0). 

3.2 Example B: Operator Failure During Canister Staging 

(060–OPSTAGERACK1–HFI–NOD) 

The human error probability for Example B (060–OPSTAGERACK1–HFI–NOD) is based on the 

failure of both an operator and a supervisor in a control room. DOE credited a supervisor 

(who is in the control room with the operator) for understanding the consequences of not closing 

a port gate and understanding his or her value within the organization and in the task being 

undertaken. Therefore, this part of the NARA quantification is categorized under working 

conditions in this report and is shown as a small curve in Figure 3-2. To quantify the supervisor 

failure, DOE accounted for some complacency on the part of the supervisor who trusts the 

operator. Figure 3-2 shows the effect of increasing an APOA from 0.5 to 1.0 for an EPC 

involving low workforce morale or adverse organizational environment. The EPC has a value of 

2, which results in a factor of about 1.3 increase in the supervisor’s failure probability (i.e., Curve 

2 in Figure 3-2). This is in contrast to the result shown for Examples A and G in Section 3.1 

where the EPC had a value of 10 and the crew member’s individual failure probability increased 

by a factor of about 5 as the associated APOA was changed from 0.1 to 1.0. 

The portion of the human failure event quantification involving CREAM (i.e., the operator failure) 

shows more significant increases in human error probability. As shown in Figure 3-2, as human 

factors such as working conditions, availability of procedures, or adequacy of training worsen, 

the human error probability increases significantly. For these factors, the resulting human error 

probability is not high enough to result in a cut set frequency that crosses a categorization 

boundary. However, this is not the case for availability of time. As shown in Figure 3-2, as the 
 3-4

Figure 3-2. Example B: 060–OPSTAGERACK1–HFI–NOD Sensitivity Analysis

adequacy of available time lessens from adequate available time (i.e., CPC = 0.5) to a 

hypothetical extreme condition of continuously inadequate available time (i.e., CPC = 5.0), the 

cut set frequency and therefore the event sequence frequency cross a categorization boundary 

from Category 2 to Category 1. 

3.3 Example C and Example F: Direct Exposure in Canister 

Transfer Room (060–OPCTMDIREXP1–HFI–NOD and 

200–OPCTMDIREXP1–HFI–NOD) 

Figure 3-3 shows the increase in probability for Examples C and F, human failure events 

060–OPCTMDIREXP1–HFI–NOD and 200–OPCTMDIREXP1–HFI–NOD, as parameters 

associated with the human factors categories are increased individually. Although DOE used 

both NARA and CREAM, Figure 3-3 shows only the sensitivity analysis for CREAM. For the 

worker violating an administrative control and entering the Canister Transfer Room, DOE used 

the full effect of an EPC in its NARA analysis by assigning a value of 1 to the APOA. Therefore, 

no additional sensitivity analysis was performed for worker failure, because the maximum value 

was already assigned and the condition could be no worse. The results shown in Figure 3-3 are 

similar to the results for CREAM described in Section 3.2 because the operator’s failure to close 

a port gate is quantified in the same way. The factor shown in Figure 3-3 that has the 

greatest effect is the availability of time. As conditions worsen from adequate available time 

(i.e., CPC = 0.5) to a hypothetical extreme condition of continuously inadequate available time 

(i.e., CPC = 5.0), the cut set frequency crosses a categorization boundary for one event 

sequence (Table 2-1) in the CRCF. 

1.00E-05

1.00E-04

1.00E-03

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0

Human Error Probability

Range of Factors

(2)

(1) CREAM: Available Time

(2) NARA: Working Conditions

(3) CREAM: Working Conditions, Availability of Procedures, or Adequacy of Training

CRCF-ESD18-DSTD, 2

Baseline

(3)

(1)
 3-5

Figure 3-3. Examples C and F: 060/200–OPCTMDIREXP1–HFI–NOD Sensitivity Analysis 

3.4 Example E: Operator Fails To Install Shielded Transfer Cask 

Shield Ring Properly (050–OPSTCSHIELD1–HFI–COD) 

Figure 3-4 shows the increase in probability for Example E (human failure event 

050–OPSTCSHIELD1–HFI–COD) as parameters associated with two of the four human factors 

categories are increased individually. Using CREAM in this example, DOE described adequate 

time available to perform the tasks (i.e., CPC = 0.5) and adequate training (i.e., CPC = 0.8). As 

shown in Figure 3-4, variation in the conditions of available time and adequacy of training with 

respect to CREAM have significant effects on the human error probability, resulting in values in 

these categories that are significantly higher than the specified baseline values. However, in 

neither case would a cut set frequency cross a categorization boundary (i.e., Curves 2 and 3 in 

Figure 3-4). The result is different, however, if the level of dependence between the crew 

members and the crane operator is considered. 

DOE used THERP to quantify the failure of crew members to realize that a shield ring has not 

been installed. As part of this quantification, DOE accounted for dependency between the crew 

members and the crane operator. As shown in Figure 3-4 at the intersection of curve 1 with the 

baseline, DOE assigned a value of 0.05 to the crew members’ failure, and this value reflects a 

low level of dependence with the crane operator. As the level of dependence is increased to a 

hypothetical extreme of complete dependence (i.e., a value of 1.0), the human error probability 

increases rapidly, and the cut set frequency and therefore the event sequence frequency cross 

the Category 1 boundary. Figure 3-4 shows that the level of dependence between the crane 

operator and the crew members has a significant effect on human error probability and the 

resulting event sequence frequency. 

1.00E-06

1.00E-05

1.00E-04

1.00E-03

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0

Human Error Probability

Range of Factors

CRCF-ESD18-DSTD, 2

CRCF-ESD18-TAD, 2

RF-ESD11, 2

CRCF-ESD18-HLW, 2

(1) CREAM: Available Time

(2) CREAM: Working Conditions, Availability of Procedures, or Adequacy of Training

(1)

(2)

Baseline
 3-6

Figure 3-4. Example E: 050–OPSTCSHIELD1–HFI–COD Sensitivity Analysis

3.5 Example D: Operator Fails To Install Waste Package Inner Lid 

(060–OPWPINNERLID–HFI–NOD) 

No sensitivity analysis was conducted for Example D (060–OPWPINNERLID–HFI–NOD). In 

developing the human error probability for this example, DOE used NARA to quantify both an 

operator failure and a worker failure. For the operator failure, DOE did not assign an EPC, and 

for the worker failure, DOE used the full effect of an EPC by assigning the maximum value of 1 

to the APOA. Except for identifying administrative controls and training as part of the generic 

tasks (i.e., GTTs), DOE did not reflect any additional credit in its quantification of this example. 

Therefore, no sensitivity analysis was needed for the human failure event. 

3.6 Significant Contributors to Human Error Probability 

The preceding sensitivity analyses show three potentially significant contributors to human 

error probability that were associated with the seven examples of human failure events 

discussed in this report. As described in Section 3.1, a crew member being able to hear an 

announcement (i.e., a low level of distraction) to evacuate was categorized in this report under 

the “working conditions” human factors category. As illustrated in Figure 3-1, if the working 

conditions in the Waste Package Loadout Room degrade so that the crew member becomes 

less able to hear an announcement (e.g., if machine noise were to increase significantly), then 

the event sequence frequency increases significantly. In addition, as described in Section 3.4, 

the event sequence frequency increases significantly if the level of dependence between 

workers increases significantly. Finally, the availability of time appears to have a significant 

effect on more than one human error probability and resulting event sequence frequency as the 

adequacy of available time lessens. These three results show that characteristics relating to the 

environment, such as background noise or machine noise, relationships between different 

1.00E-05

1.00E-04

1.00E-03

1.00E-02

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0

Human Error Probability

Range of Factors

WHF-ESD29-TAD, 2

(1) THERP: Dependency

(2) CREAM: Available Time

(3) CREAM: Adequacy of Training

Baseline

(1)

(2)

(3)
 3-7

people performing a single activity or process step, or the availability of time to perform an 

activity, can significantly affect the human error probability in these examples. For low 

probability human failure events that are dominant contributors to event sequence frequency, 

the worst case hypothetical result is that the associated event sequence frequency approaches 

or crosses a categorization boundary. Therefore, understanding the significant contributors to 

human error probability can help in determining aspects of human error quantification that are 

important for a risk-informed review. In these three cases, understanding how the environment 

would support a low level of distraction, how operators work together with a low level of 

dependence, or how process steps are accomplished with adequate available time would be 

important aspects of the technical basis for supporting event sequence frequencies where 

human errors are dominant contributors. 
4-1 

4 SUMMARY 

This report illustrates an approach that can be used to systematically examine and identify, in a 

risk-informed manner, dominant contributors to human failure event modeling. This approach 

uses a series of filters to identify a small set of low probability human failure events that are 

dominant contributors to event sequence frequency. Using this approach, seven example 

human failure events were identified. These example human failure events, which DOE 

originally developed, are in event sequences involving direct exposures and occur during CTM 

operations in a CRCF and the RF, during waste package closure and export in a CRCF and 

IHF, and during TAD canister closure activities in a WHF. After identifying the low 

probability human failure events, a sensitivity analysis was performed to identify any human 

factors that may have the potential to significantly affect event sequence frequency. This 

sensitivity analysis was performed rapidly because only seven human failure events needed to 

be analyzed. 

This report quantified human failure events in terms of the human reliability analysis methods 

that DOE used and in terms of the human factors that DOE described for the selected 

examples. In this report, human factors are grouped into four categories: the presence of 

administrative controls or availability of procedures, adequacy of training, available time to 

perform an activity, and working conditions. For all but one of the seven low probability human 

failure events, DOE developed the failure probability using more than one human reliability 

analysis method. However, the human reliability analysis method NARA was used in all the 

examples, and six out of the seven were quantified using CREAM, so much of the quantitative 

analysis in this report focused on factors associated with NARA and CREAM. To prepare for a 

sensitivity analysis, the human factors identified in each example were organized by human 

reliability analysis method for each of the low probability human failure events that are dominant 

contributors to event sequence frequency. 

The sensitivity analysis was based on ranges for these human factors specific to the human 

reliability analysis method. This analysis identified two human factors, in particular, that appear 

to significantly affect human error probability in the examples. One of them involves working 

conditions and relates to the ability of a worker to hear an announcement to evacuate a room. It 

accounts for the worker’s level of distraction, possibly due to machine noise. The other one 

involves the available time for a worker to perform an activity and appears to significantly affect 

the human error probability for six out of the seven low probability human failure events. 

Although not summarized directly in this report as a human factor, dependency between 

operator actions also appears to have a significant effect on the human error probability for one 

of the examples. 

For the examples in this report, these three results show that characteristics relating to the work 

environment, such as background noise or machine noise, relationships between different 

people performing a single activity or process step, or the available time to perform an activity, 

can significantly affect human error probability. For low probability human failure events that are 

dominant contributors to event sequence frequency, the worst case hypothetical result can be 

that the associated event sequence frequency approaches or crosses a categorization 

boundary as defined in 10 CFR 63.2. Therefore, understanding the significant contributors to 

human error probability can help in determining aspects of human error quantification that are 

important for a risk-informed review. In these three cases, understanding how the environment 

would support a low level of distraction, how operators work together with a low level of 

dependence, or how process steps are accomplished with adequate available time would be 
4-2 

important aspects of the technical basis for supporting event sequence frequencies where 

human errors are dominant contributors.
5-1 

5 REFERENCES 

BSC. “CRCF Reliability and Event Sequence Categorization Analysis.” 060–PSA–CR00–

00200–000. Rev. 00B. Las Vegas, Nevada: Bechtel SAIC Company, LLC. 2009a. 

_____. “WHF Reliability and Event Sequence Categorization Analysis.” 

050–PSA–WH00–00200–000. Rev. 00B. Las Vegas, Nevada: Bechtel SAIC 

Company, LLC. 2009b. 

_____. “RF Reliability and Event Sequence Categorization Analysis.” 

200–PSA–RF00–00200–000. Rev. 00B. Las Vegas, Nevada: Bechtel SAIC 

Company, LLC. 2009c. 

_____. “IHF Reliability and Event Sequence Categorization Analysis.” 

51A–PSA–IH0–00200–000. Rev. 00A, CACN 001. Las Vegas, Nevada: Bechtel SAIC 

Company, LLC. 2008. 

Corporate Risk Associates. “A User Manual for the Nuclear Action Reliability Assessment 

(NARA) Human Error Quantification Technique.” CRA–BEGLPOW–J032. Report No.2, 

Issue 5. Leatherhead, England: Corporate Risk Associates. 2006. 

DOE. “Yucca Mountain—Supplemental Response to Request for Additional Information 

Regarding License Application (Safety Analysis Report Sections 1.6 and 1.7), Safety Evaluation 

Report Vol. 2, Chapter 2.1.1.3, Set 3 and Chapter 2.1.1.4, Set 8.” Letter (December 17) 

J.R. Williams to C. Jacobs (NRC). ML093620043. Washington, DC: DOE, Office of Technical 

Management. 2009. 

Hollnagel, E. Cognitive Reliability and Error Analysis Method, CREAM. 1st Edition. New York 

City, New York: Elsevier. 1998. 

Human Factors and Ergonomics Society. “Educational Resources, Definitions of Human 

Factors and Ergonomics.” 

<http://www.hfes.org/Web/EducationalResources/HFEdefinitionsmain.html> (February 8, 2011). 

NRC. NUREG–1624, “Technical Basis and Implementation Guidelines for a Technique for 

Human Event Analysis (ATHEANA).” Rev 1. Washington, DC: U.S. Nuclear Regulatory 

Commission. 2000. 

Stewart, M.G. and R.E. Melchers. Probabilistic Risk Assessment of Engineering Systems. 

New York City, New York: Chapman & Hall. 1997. 

Swain, A.D. and H.E. Guttmann. NUREG/CR–1278, “Handbook of Human Reliability Analysis 

with Emphasis on Nuclear Power Plant Applications Final Report.” Washington, DC: 

U.S. Nuclear Regulatory Commission. 1983. 

Williams, J.C. “HEART—A Proposed Method for Assessing and Reducing Human Error.” 

9th Advances in Reliability Technology Symposium–1986. Bradford, England: University of 

Bradford. 1986. 
APPENDIX A 
A–1 

A DESCRIPTION OF HUMAN FAILURE EVENTS 

The tables in the sections that follow show details of the human reliability analysis methods and 

certain factors the U.S. Department of Energy (DOE) described when determining the human 

error probability for the seven human failure events (BSC, 2009a,b,c; 2008). Although DOE did 

not explicitly categorize human factors in its human reliability analyses, its analyses using the 

Cognitive Reliability and Error Analysis Method (CREAM) explicitly addressed four areas 

involving human factors (i.e., the presence of administrative controls or availability of 

procedures, adequacy of training, available time to perform an activity, and working conditions). 

Because DOE used CREAM several times to quantify the seven human failure events, these 

four areas (i.e., human factors categories) were used in this report to categorize human factors 

regardless of the human reliability analysis method. However, for human reliability analysis 

methods other than CREAM, it is not always clear whether a human factor falls under one of the 

four categories. Therefore, if DOE appeared to credit activities relating to one of the human 

factors categories when using a human reliability analysis method other than CREAM, then 

these activities were included under one of the four human factors categories. Specific 

instances where this occurred for the Nuclear Action Reliability Assessment (NARA) and A 

Technique for Human Event Analysis (ATHEANA) expert elicitation are described in the 

following sections. Note that the tables in the sections that follow also include a hardware 

category because, in some cases, DOE relied on hardware such as an interlock in its human 

failure quantification. 

A.1 Exposure During Transport and Emplacement Vehicle Loading 

 (060–OPDIREXPOSE3–HFI–NOD and 51A–OPDIREXPOSE3–HFI–NOD) 

DOE associated human failure event 060–OPDIREXPOSE3–HFI–NOD with the 

Canister Receipt and Closure Facility (CRCF) (BSC, 2009a) and human failure event 

51A–OPDIREXPOSE3–HFI–NOD with the Initial Handling Facility (IHF) (BSC, 2008). DOE 

quantified these events using the same human reliability analysis methods and the same 

parameters within these methods; therefore, the events are described together in this section. 

These human failure events include three scenarios with individual probabilities that are added 

to estimate the human error probability. The first scenario (i.e., Scenario 1a) consists of a crew 

member remaining in the Waste Package Loadout Room (possibly due to the Waste Package 

Transfer Trolley Operator failing to order an evacuation) and failing to exit and a radiation 

protection worker failing to check or recognize that someone has remained in the room. The 

second scenario (i.e., Scenario 1b) involves a crew member reentering the Waste Package 

Loadout Room after operations have begun with the supervisor allowing access. The third 

scenario (i.e., Scenario 1c) involves a personnel access shield door being left open combined 

with a hardware failure, and the Waste Package Transfer Trolley entering the Waste Package 

Loadout Room. 

For these human failure events, Table A–1 summarizes the factors DOE described in each 

scenario and the human reliability analysis method DOE used in each scenario. This table 

shows that Scenario 1a accounts for the majority of the human error probability. The 

probabilities for the remaining two scenarios are one or more orders of magnitude less than that 

of Scenario 1a. Also, these events are the only low probability human failure events out of the 

seven for which DOE used the Human Error Assessment and Reduction Technique (HEART). 

DOE used HEART in Scenario 1a. In Scenario 1c, when the hardware failure probability of 
A–2 

Table A–1. 060/51A–OPDIREXPOSE3–HFI–NOD Summary 

Human Reliability 

Analysis Method 

Human Failure Event or 

Scenario 

(Human Error Probability) 

Factors DOE Described in 

Human Failure Analysis 

NAR

A* 

CREAM† HEART‡ 

ATHEAN

A§ 

THERP║Hardware 

Administrative 

Controls or 

Available 

Procedures 

Adequate 

Training 

Adequate Time Advantageous 

Working Conditions 

    060–OPDIREXPOSE3–HFI–NOD 

51A–OPDIREXPOSE3–HFI–NOD 

(3 × 10−5)

    

   Scenario 1a 

(3 × 10−5

)

   

 Scenario 1b 

(2 × 10−6

)

  

  Scenario 1c 

(4 × 10−7

)

  

*NARA = Nuclear Action Reliability Assessment 

†CREAM = Cognitive Reliability and Error Analysis Method 

‡HEART = Human Error Assessment and Reduction Technique 

§ATHENA = A Technique for Human Event Analysis 

║THERP = Technique for Human Error Rate Prediction 

4 × 10−3

 is combined with a human error probability of 1 × 10−4, the Scenario 1c probability 

becomes approximately an order of magnitude or more lower than that of the other two 

scenarios involving only human errors and has only a small contribution on the event 

sequence frequency. 

As part of its NARA quantification, DOE identified the level of distraction for a crew member 

hearing an announcement to evacuate was small (i.e., not a significant amount of machine 

noise to mask the announcement). Although DOE did not explicitly characterize the small level 

of distraction as an advantageous working condition, in this report, this environment is assumed 

to provide an advantageous working condition. 

A.2 Operator Failure During Canister Staging 

 (060–OPSTAGERACK1–HFI–NOD) 

DOE associated human failure event 060–OPSTAGERACK1–HFI–NOD with the CRCF 

(BSC, 2009a). This human failure event consists of only one scenario in which an operator 

working from the control room fails to close the staging rack port gate before raising the 

Canister Transfer Machine (CTM) shield skirt combined with the supervisor failing to check that 

the port gate is closed at the end of operations (e.g., at the end of a shift). DOE described 

administrative controls or available procedures, adequate training, adequate time, and 

advantageous working conditions when quantifying the failure of the operator to close the port 

gate. In addition, DOE described administrative controls or available procedures for the 

supervisor failing to check that the port gate was closed. DOE quantified the operator failure 

using CREAM and the supervisor failure using NARA. Table A–2 shows the human reliability 

analysis methods and the factors DOE described in the human failure analysis. 
A–3 

Table A–2. 060–OPSTAGERACK1–HFI–NOD Summary 

Human Reliability 

Analysis Method 

Human Failure Event or Scenario

(Human Error Probability) 

Factors DOE Described in Human 

Failure Analysis 

NAR

A* 

CREAM† HEART‡ 

ATHEANA§ 

THERP║Hardware 

Administrative 

Controls or 

Available 

Procedures 

Adequate 

Training 

Adequate Time Advantageous 

Working Conditions 

  060–OPSTAGERACK1–HFI–NOD 

(3 × 10−5

)

   

*NARA = Nuclear Action Reliability Assessment 

†CREAM = Cognitive Reliability and Error Analysis Method 

‡HEART = Human Error Assessment and Reduction Technique 

§ATHENA = A Technique for Human Event Analysis 

║THERP = Technique for Human Error Rate Prediction 

DOE credited a supervisor (who is also in the control room with the operator) for understanding 

the consequences of not closing the gate. The supervisor has at least some understanding of 

his or her value within the organization and in the task being undertaken. Although DOE did not 

explicitly characterize the supervisor’s actions with advantageous working conditions, in this 

report, this environment is assumed to provide an advantageous working condition. 

A.3 Direct Exposure in Canister Transfer Room 

(060–OPCTMDIREXP1–HFI–NOD and 200–OPCTMDIREXP1–HFI–NOD) 

DOE associated human failure event 060–OPCTMDIREXP1–HFI–NOD with the CRCF 

(BSC, 2009a) and human failure event 200–OPCTMDIREXP–HFI–NOD with the Receipt 

Facility (RF) (BSC, 2009b). DOE quantified these events using the same human reliability 

analysis methods and the same parameters within these methods; therefore, these events are 

described together in this section. 

These human failure events consist of one scenario in which a worker violates an administrative 

control and enters the Canister Transfer Room during a transfer combined with the failure of the 

control room operator to close the port gate before raising the CTM shield skirt. DOE used 

NARA to quantify the worker violating administrative controls (e.g., entering at prescheduled 

times and getting permission from the control room prior to entering) and used CREAM to 

quantify the operator failing to close the port gate. Similar to its quantification for the control 

room operator in Section A.2, DOE described administrative controls or available procedures, 

adequate training, adequate available time, and advantageous working conditions for failure of 

the control room operator to close the port gate. Table A–3 shows the human reliability analysis 

methods and the factors DOE described in the human failure analysis. 

A.4 Operator Fails To Install Waste Package Inner Lid 

 (060–OPWPINNERLID–HFI–NOD)

DOE associated human failure event 060–OPWPINNERLID–HFI–NOD with the CRCF 

(BSC, 2009a). This human failure event consists of one scenario in which an operator fails to 
A–4 

Table A–3. 060/200–OPCTMDIREXP1–HFI–NOD Summary 

Human Reliability 

Analysis Method 

Human Failure Event or Scenario 

(Human Error Probability) 

Factors DOE Described in 

Human Failure Analysis 

NAR

A* 

CREAM† HEART‡ 

ATHEAN

A§ 

THERP║Hardware 

Administrative 

Controls or 

Available 

Procedures 

Adequate 

Training 

Adequate Time Advantageous 

Working Conditions 

  060–OPCTMDIREXP1–HFI–NOD 

200–OPCTMDIREXP1–HFI–NOD 

(8 × 10−6

)

   

*NARA = Nuclear Action Reliability Assessment 

†CREAM = Cognitive Reliability and Error Analysis Method 

‡HEART = Human Error Assessment and Reduction Technique 

§ATHEANA = A Technique for Human Event Analysis 

║THERP = Technique for Human Error Rate Prediction 

install the waste package inner shield lid combined with a worker violating an administrative 

control and entering the Waste Package Closure Room prior to the start of welding. The CTM 

operator installs this inner shield lid on waste packages containing unshielded canisters 

(e.g., DOE standardized canisters and high-level waste canisters) in the Canister Transfer 

Room as the last step of CTM operations. Alternatively, it is installed on waste packages 

containing a Transportation, Aging, and Disposal (TAD) canister (i.e., a shielded canister) during 

waste package closure. For the operator, DOE quantified the failure of the operator to install 

the inner shield lid (possibly mistaking the type of container inside the waste package) using 

NARA and identified training as part of this quantification. As was done for the worker in 

Section A.3, DOE used NARA to quantify the worker violating administrative controls (e.g., 

entering at prescheduled times and getting permission from the control room prior to entering) 

for this human failure event. Table A–4 shows the human reliability analysis method and the 

factors DOE described in the human failure analysis. 

Out of the seven low probability human failure events, 060–OPWPINNERLID–HFI–NOD has the 

lowest human error probability. It is an order of magnitude lower than the one having the 

highest human error probability, 050–OPSTCSHIELD1–HFI–COD, described next. 

A.5 Operator Fails To Install Shielded Transfer Cask Shield Ring Properly 

 (050–OPSTCSHIELD1–HFI–COD) 

DOE associated human failure event 050–OPSTCSHIELD1–HFI–COD with the WHF 

(BSC, 2009c). This human failure event consists of two scenarios with individual probabilities 

that are added to estimate the human error probability. A shield ring is required to be 

installed prior to draining the TAD canister in preparation for closure. In the first scenario 

(i.e., Scenario 1a), the crane operator fails to install the shield ring; crew members do not realize 

this step in the process was missed and, before approaching the TAD canister, fail to notice the 

shield ring is not in place. In the second scenario (i.e., Scenario 1b), the crane operator 

improperly installs the shield ring (e.g., the ring is not seated properly); the radiation protection 
A–5 

Table A–4. 060–OPWPINNERLID–HFI–NOD Summary 

Human Reliability 

Analysis Method 

Human Failure Event or Scenario 

(Human Error Probability) 

Factors DOE Described in Human 

Failure Analysis 

NARA* CREAM† HEART‡ ATHEAN

A§ 

THERP║

Hardware 

Administrative 

Controls or 

Available 

Procedures 

Adequate 

Trainin

g

Adequate 

Time 

Advantageou

s Working Conditions 

 060–OPWPINNERLID–HFI–NOD 

(6 × 10−6

)

 

*NARA = Nuclear Action Reliability Assessment 

†CREAM = Cognitive Reliability and Error Analysis Method 

‡HEART = Human Error Assessment and Reduction Technique 

§ATHEANA = A Technique for Human Event Analysis 

║THERP = Technique for Human Error Rate Prediction

 

worker fails to check radiation levels, misreads the meter or the meter itself fails, and the crew 

members fail to notice the ring is out of position before approaching the TAD canister. 

Table A–5 shows the human reliability analysis methods and the factors DOE described in the 

human failure analysis. As shown in this table, Scenario 1a accounts for the majority of the 

human error probability. The probability for the remaining scenario is more than an order of 

magnitude less than that of Scenario 1a. Human failure event 050–OPSTCSHIELD1–HFI–COD 

has the highest human error probability among the seven low probability human failure events, 

and it is the only event out of the seven to use ATHEANA’s expert elicitation approach. 

In terms of ATHEANA’s expert elicitation approach, DOE identified ample opportunity for the 

crew to recognize that the shield ring was not properly in place. Therefore, in this report, 

adequate available time is assumed to be part of the ATHEANA expert elicitation quantification. 

In addition, DOE identified the crew performing the task often. Because DOE frequently 

associated routine operations with training, the consideration of training may also have been a 

factor in its ATHEANA expert elicitation quantification for this human failure event. Therefore, in 

this report, adequate training is assumed to be part of the ATHEANA expert elicitation 

quantification for human failure event 050–OPSTCSHIELD1–HFI–COD. 

 
A–6 

Table A–5. 050–OPSTCSHIELD1–HFI–COD Summary 

Human Reliability 

Analysis Method 

Human Failure Event or Scenario 

(Human Error Probability) 

Factors DOE Described in 

Human Failure Analysis 

NAR

A* 

CREAM† HEART‡ 

ATHEAN

A§ 

THERP║Hardware 

Administrative 

Controls or 

Available 

Procedures 

Adequate 

Training 

Adequate Time Advantageous 

Working Conditions 

    050–OPSTCSHIELD1–HFI–COD 

(6 × 10−5

) 

  

   Scenario 1a¶ 

(6 × 10−5

) 

  

    Scenario 1b 

(1 × 10−6

) 

  

*NARA = Nuclear Action Reliability Assessment 

†CREAM = Cognitive Reliability and Error Analysis Method 

‡HEART = Human Error Assessment and Reduction Technique 

§ATHEANA = A Technique for Human Event Analysis 

║THERP = Technique for Human Error Rate Prediction 

¶For Scenario 1a, due to round-off error, the Scenario 1a probability is listed as 5 × 10−5

 by BSC. “WHF Reliability and 

Event Sequence Categorization Analysis.” 050–PSA–WH00–00200–000. Rev. 00B. Las Vegas, Nevada: Bechtel 

SAIC Company, LLC. 2009. 

A.6 REFERENCES 

BSC. “CRCF Reliability and Event Sequence Categorization Analysis.” 

060–PSA–CR00–00200–000. Rev. 00B. Las Vegas, Nevada: Bechtel SAIC 

Company, LLC. 2009a. 

_____. “RF Reliability and Event Sequence Categorization Analysis.” 

200–PSA–RF00–00200–000. Rev. 00B. Las Vegas, Nevada: Bechtel SAIC Company, LLC. 

2009b. 

_____. “WHF Reliability and Event Sequence Categorization Analysis.” 

050–PSA–WH00–00200–000. Rev. 00B. Las Vegas, Nevada: Bechtel SAIC Company, LLC. 

 2009c. 

_____. “IHF Reliability and Event Sequence Categorization Analysis.” 

51A–PSA–IH0–00200–000. Rev. 00A, CACN 001. Las Vegas, Nevada: Bechtel SAIC 

Company, LLC. 2008.