basic level 1. psa course for analysts · basic level 1. psa course for analysts dependent failure...

21
Basic Level 1. PSA course for analysts Basic Level 1. PSA course for analysts Dependent failure analysis Dependent failure analysis IAEA Training in level 1 PSA and PSA applications

Upload: truongdang

Post on 29-Apr-2018

223 views

Category:

Documents


5 download

TRANSCRIPT

Basic Level 1. PSA course for analystsBasic Level 1. PSA course for analysts

Dependent failure analysisDependent failure analysis

IAEA Training in level 1 PSA and PSA applications

Dependent failure analysis

Slide 2.

ContentContent

Types of dependencies in the PSAPhysical dependenciesFunctional dependencies Location/environmental dependenciesData based dependenciesPlant configuration related dependencies

Common Cause FailuresHuman dependencies

Types of dependencies in the PSATypes of dependencies in the PSAPhysical dependenciesPhysical dependenciesFunctional dependencies Functional dependencies Location/environmental dependenciesLocation/environmental dependenciesData based dependenciesData based dependenciesPlant configuration related dependenciesPlant configuration related dependencies

Common Cause FailuresCommon Cause FailuresHuman dependenciesHuman dependencies

Dependent failure analysis

Slide 3.

PHYSICAL DEPENDENCIESPHYSICAL DEPENDENCIES

EXAMPLES

COMMON SUCTION VALVE FOR TWO PUMPSAC POWER SUPPLYDC POWER SUPPLYINTERLOCKS FOR PUMPS, VALVES, CIRCUIT BREAKERSAUTOMATIC START / ALIGNMENT SIGNALSRESTART SIGNALSCOOLING WATER

EXAMPLESEXAMPLES

COMMON SUCTION VALVE COMMON SUCTION VALVE FOR TWO PUMPSFOR TWO PUMPSAC POWER SUPPLYAC POWER SUPPLYDC POWER SUPPLYDC POWER SUPPLYINTERLOCKS FOR PUMPS, INTERLOCKS FOR PUMPS, VALVES, CIRCUIT BREAKERSVALVES, CIRCUIT BREAKERSAUTOMATIC START / AUTOMATIC START / ALIGNMENT SIGNALSALIGNMENT SIGNALSRESTART SIGNALSRESTART SIGNALSCOOLING WATERCOOLING WATER

TREATMENT

DEPENDENCY MATRICESEVENT TREE / FAULT TREE LOGIC STRUCTUREEVENT TREE / FAULT TREE LINKING

TREATMENTTREATMENT

DEPENDENCY MATRICESDEPENDENCY MATRICESEVENT TREE / FAULT TREE EVENT TREE / FAULT TREE LOGIC STRUCTURELOGIC STRUCTUREEVENT TREE / FAULT TREE EVENT TREE / FAULT TREE LINKINGLINKING

Dependent failure analysis

Slide 4.

FUNCTIONAL DEPENDENCIESFUNCTIONAL DEPENDENCIES

EXAMPLES

INJECTION CRITERIA FOR LOCAsINJECTION REQUIRED FOR RECIRCULATIONMAKEUP AND STEAM RELIEF REQUIRED FOR SECONDARY HEAT REMOVALOPERATOR ACTIONS TO START / ALIGN EQUIPMENTTIMING OF FAILURES AND RECOVERY ACTIONSCOORDINATED OUTAGES AND PLANNED MAINTENANCECOOLING WATERHVAC AND ROOM COOLING

EXAMPLESEXAMPLES

INJECTION CRITERIA FOR INJECTION CRITERIA FOR LOCAsLOCAsINJECTION REQUIRED FOR INJECTION REQUIRED FOR RECIRCULATIONRECIRCULATIONMAKEUP AND STEAM RELIEF MAKEUP AND STEAM RELIEF REQUIRED FOR SECONDARY REQUIRED FOR SECONDARY HEAT REMOVALHEAT REMOVALOPERATOR ACTIONS TO START / OPERATOR ACTIONS TO START / ALIGN EQUIPMENTALIGN EQUIPMENTTIMING OF FAILURES AND TIMING OF FAILURES AND RECOVERY ACTIONSRECOVERY ACTIONSCOORDINATED OUTAGES AND COORDINATED OUTAGES AND PLANNED MAINTENANCEPLANNED MAINTENANCECOOLING WATERCOOLING WATERHVAC AND ROOM COOLINGHVAC AND ROOM COOLING

TREATMENT

EVENT SEQUENCE DIAGRAMSSUCCESS CRITERIA FOR SYSTEMS AND OPERATOR ACTIONSTIME INTEGRALS FOR FAILURES AND RECOVERY ACTIONSPLANNED MAINTENANCE MODELSEVENT TREE / FAULT TREE LOGIC STRUCTUREEVENT TREE / FAULT TREE LINKING

TREATMENTTREATMENT

EVENT SEQUENCE DIAGRAMSEVENT SEQUENCE DIAGRAMSSUCCESS CRITERIA FOR SUCCESS CRITERIA FOR SYSTEMS AND OPERATOR SYSTEMS AND OPERATOR ACTIONSACTIONSTIME INTEGRALS FOR FAILURES TIME INTEGRALS FOR FAILURES AND RECOVERY ACTIONSAND RECOVERY ACTIONSPLANNED MAINTENANCE PLANNED MAINTENANCE MODELSMODELSEVENT TREE / FAULT TREE LOGIC EVENT TREE / FAULT TREE LOGIC STRUCTURESTRUCTUREEVENT TREE / FAULT TREE EVENT TREE / FAULT TREE LINKINGLINKING

Dependent failure analysis

Slide 5.

LOCATION / ENVIRONMENTAL DEPENDENCIESLOCATION / ENVIRONMENTAL DEPENDENCIES

EXAMPLES

STRUCTURAL FAILURES / SEISMIC EVENTSFIRESFLOODINGTURBINE MISSILESWATER SPRAYHVAC AND ROOM COOLINGINTAKE PLUGGING

EXAMPLESEXAMPLES

STRUCTURAL FAILURES / STRUCTURAL FAILURES / SEISMIC EVENTSSEISMIC EVENTSFIRESFIRESFLOODINGFLOODINGTURBINE MISSILESTURBINE MISSILESWATER SPRAYWATER SPRAYHVAC AND ROOM COOLINGHVAC AND ROOM COOLINGINTAKE PLUGGINGINTAKE PLUGGING

TREATMENT

SPATIAL INTERACTIONS ANALYSESEXTERNAL EVENTS ANALYSESEVENT TREE / FAULT TREE LOGIC STRUCTUREEVENT TREE / FAULT TREE LINKING

TREATMENTTREATMENT

SPATIAL INTERACTIONS SPATIAL INTERACTIONS ANALYSESANALYSESEXTERNAL EVENTS EXTERNAL EVENTS ANALYSESANALYSESEVENT TREE / FAULT TREE EVENT TREE / FAULT TREE LOGIC STRUCTURELOGIC STRUCTUREEVENT TREE / FAULT TREE EVENT TREE / FAULT TREE LINKINGLINKING

Dependent failure analysis

Slide 6.

DATADATA--BASED DEPENDENCIESBASED DEPENDENCIES

EXAMPLES

MULTIPLE COMPONENT MAINTENANCECOORDINATED OUTAGES AND PLANNED MAINTENANCEOBSERVED COMBINED FAILURE RATE FOR MULTIPLE SIMILAR COMPONENTS IS HIGHER THAN THE INDEPENDENT PRODUCT OF THE SINGLE COMPONENT FAILURE RATES

EXAMPLESEXAMPLES

MULTIPLE COMPONENT MULTIPLE COMPONENT MAINTENANCEMAINTENANCECOORDINATED OUTAGES AND COORDINATED OUTAGES AND PLANNED MAINTENANCEPLANNED MAINTENANCEOBSERVED COMBINED OBSERVED COMBINED FAILURE RATE FOR MULTIPLE FAILURE RATE FOR MULTIPLE SIMILAR COMPONENTS IS SIMILAR COMPONENTS IS HIGHER THAN THE HIGHER THAN THE INDEPENDENT PRODUCT OF INDEPENDENT PRODUCT OF THE SINGLE COMPONENT THE SINGLE COMPONENT FAILURE RATESFAILURE RATES

TREATMENT

COMMON MAINTENANCE BASIC EVENTSPLANNED MAINTENANCE MODELSCOMMON CAUSE FAILURE BASIC EVENTSCOMMON CAUSE FAILURE PARAMETERSEVENT TREE / FAULT TREE LOGIC STRUCTUREEVENT TREE / FAULT TREE LINKING

TREATMENTTREATMENT

COMMON MAINTENANCE COMMON MAINTENANCE BASIC EVENTSBASIC EVENTSPLANNED MAINTENANCE PLANNED MAINTENANCE MODELSMODELSCOMMON CAUSE FAILURE COMMON CAUSE FAILURE BASIC EVENTSBASIC EVENTSCOMMON CAUSE FAILURE COMMON CAUSE FAILURE PARAMETERSPARAMETERSEVENT TREE / FAULT TREE EVENT TREE / FAULT TREE LOGIC STRUCTURELOGIC STRUCTUREEVENT TREE / FAULT TREE EVENT TREE / FAULT TREE LINKINGLINKING

Dependent failure analysis

Slide 7.

HUMAN DEPENDENCIESHUMAN DEPENDENCIES

EXAMPLES

TIME WINDOW FOR OPERATOR RESPONSESIMILAR FUNCTIONSMULTIPLE OPTIONS / PRIORITIESPROCEDURES / TRAININGPERSONNEL / STAFFINGLOCATIONPRECEDING SYSTEM SUCCESSES / FAILURESPRECEDING OPERATOR SUCCESSES / FAILURES

EXAMPLESEXAMPLES

TIME WINDOW FOR TIME WINDOW FOR OPERATOR RESPONSEOPERATOR RESPONSESIMILAR FUNCTIONSSIMILAR FUNCTIONSMULTIPLE OPTIONS / MULTIPLE OPTIONS / PRIORITIESPRIORITIESPROCEDURES / TRAININGPROCEDURES / TRAININGPERSONNEL / STAFFINGPERSONNEL / STAFFINGLOCATIONLOCATIONPRECEDING SYSTEM PRECEDING SYSTEM SUCCESSES / FAILURESSUCCESSES / FAILURESPRECEDING OPERATOR PRECEDING OPERATOR SUCCESSES / FAILURESSUCCESSES / FAILURES

TREATMENT

ORGANIZE MODELS TO DISPLAY OPERATOR ACTIONSTHERMAL / HYDRAULIC ANALYSES FOR TIME WINDOWSCOGNITIVE RESPONSE / IMPLEMENTATION TASKSEVENT TREE / FAULT TREE LOGIC STRUCTUREEVENT TREE / FAULT TREE LINKING

TREATMENTTREATMENT

ORGANIZE MODELS TO ORGANIZE MODELS TO DISPLAY OPERATOR ACTIONSDISPLAY OPERATOR ACTIONSTHERMAL / HYDRAULIC THERMAL / HYDRAULIC ANALYSES FOR TIME ANALYSES FOR TIME WINDOWSWINDOWSCOGNITIVE RESPONSE / COGNITIVE RESPONSE / IMPLEMENTATION TASKSIMPLEMENTATION TASKSEVENT TREE / FAULT TREE EVENT TREE / FAULT TREE LOGIC STRUCTURELOGIC STRUCTUREEVENT TREE / FAULT TREE EVENT TREE / FAULT TREE LINKINGLINKING

Dependent failure analysis

Slide 8.

PLANT CONFIGURATIONSPLANT CONFIGURATIONSPLANT OPERATING ALIGNMENTSPLANT OPERATING ALIGNMENTS

VERY IMPORTANT FOR SHUTDOWN PSA

OPERATIONAL CONSIDERATIONSPRESSURE, TEMPERATURE, COOLING MODERCS AND CONTAINMENT STATUSSYSTEM ALIGNMENTS / SIGNALS / ISOLATION

TESTING / MAINTENANCE CONSIDERATIONSPLANNED MAINTENANCETESTING PROGRAMS

PLANNED MAINTENANCE ALIGNMENTS MAY ALSO APPLY FOR FULL-POWER PSA

VERY IMPORTANT FOR SHUTDOWN PSAVERY IMPORTANT FOR SHUTDOWN PSA

OPERATIONAL CONSIDERATIONSOPERATIONAL CONSIDERATIONSPRESSURE, TEMPERATURE, COOLING MODEPRESSURE, TEMPERATURE, COOLING MODERCS AND CONTAINMENT STATUSRCS AND CONTAINMENT STATUSSYSTEM ALIGNMENTS / SIGNALS / ISOLATIONSYSTEM ALIGNMENTS / SIGNALS / ISOLATION

TESTING / MAINTENANCE CONSIDERATIONSTESTING / MAINTENANCE CONSIDERATIONSPLANNED MAINTENANCEPLANNED MAINTENANCETESTING PROGRAMSTESTING PROGRAMS

PLANNED MAINTENANCE ALIGNMENTS MAY ALSO APPLY FOR PLANNED MAINTENANCE ALIGNMENTS MAY ALSO APPLY FOR FULLFULL--POWER PSAPOWER PSA

Dependent failure analysis

Slide 9.

COMMON CAUSE FAILURESCOMMON CAUSE FAILURESCOMMON CAUSE FAILURE GROUPSCOMMON CAUSE FAILURE GROUPS

SIMILAR COMPONENTS

SAME FAILURE MODES

SIMILAR OPERATING DUTY CYCLES

SIMILAR TESTING, INSPECTION, MAINTENANCE

MAY APPLY ACROSS DIFFERENT SYSTEMS

SIMILAR COMPONENTSSIMILAR COMPONENTS

SAME FAILURE MODESSAME FAILURE MODES

SIMILAR OPERATING DUTY CYCLESSIMILAR OPERATING DUTY CYCLES

SIMILAR TESTING, INSPECTION, MAINTENANCESIMILAR TESTING, INSPECTION, MAINTENANCE

MAY APPLY ACROSS DIFFERENT SYSTEMSMAY APPLY ACROSS DIFFERENT SYSTEMS

Dependent failure analysis

Slide 10.

COMMON CAUSE FAILURESCOMMON CAUSE FAILURESLEVEL OF DETAILLEVEL OF DETAIL

BETA-FACTOR MODELSIMPLENUMERICALLY CONSERVATIVEREASONABLE DATA FOR MANY COMPONENTS AND FAILURE MODES

MULTIPLE GREEK LETTER (MGL) MODELMORE COMPLEX FAULT TREES / CUTSETSLOGICALLY MORE CORRECTNUMERICALLY MORE REALISTICVERY SPARSE DATA FOR MORE THAN 3 FAILURES

BETABETA--FACTOR MODELFACTOR MODELSIMPLESIMPLENUMERICALLY CONSERVATIVENUMERICALLY CONSERVATIVEREASONABLE DATA FOR MANY COMPONENTS AND REASONABLE DATA FOR MANY COMPONENTS AND FAILURE MODESFAILURE MODES

MULTIPLE GREEK LETTER (MGL) MODELMULTIPLE GREEK LETTER (MGL) MODELMORE COMPLEX FAULT TREES / CUTSETSMORE COMPLEX FAULT TREES / CUTSETSLOGICALLY MORE CORRECTLOGICALLY MORE CORRECTNUMERICALLY MORE REALISTICNUMERICALLY MORE REALISTICVERY SPARSE DATA FOR MORE THAN 3 FAILURESVERY SPARSE DATA FOR MORE THAN 3 FAILURES

Dependent failure analysis

Slide 11.

COMMON CAUSE FAILURESCOMMON CAUSE FAILURESLEVEL OF DETAIL (cont.)LEVEL OF DETAIL (cont.)

OTHER PARAMETRIC MODELS LIMITED BY SAME DATA

“LETHAL SHOCKS”AFFECT ALL COMPONENTS IN A GROUPVERY LIKELY TO BE CAUSE FOR MORE THAN 3 OR 4 CORRELATED FAILURES

MODELS FOR LARGE NUMBERS OF COMPONENTSLARGE NUMBER OF COMBINATIONS IN POPULATIONBEWARE OF FUNCTIONAL IMPACTS FROM SPECIFIC COMBINATIONS

OTHER PARAMETRIC MODELS LIMITED BY SAME DATAOTHER PARAMETRIC MODELS LIMITED BY SAME DATA

““LETHAL SHOCKSLETHAL SHOCKS””AFFECT ALL COMPONENTS IN A GROUPAFFECT ALL COMPONENTS IN A GROUPVERY LIKELY TO BE CAUSE FOR MORE THAN 3 OR 4 VERY LIKELY TO BE CAUSE FOR MORE THAN 3 OR 4 CORRELATED FAILURESCORRELATED FAILURES

MODELS FOR LARGE NUMBERS OF COMPONENTSMODELS FOR LARGE NUMBERS OF COMPONENTSLARGE NUMBER OF COMBINATIONS IN POPULATIONLARGE NUMBER OF COMBINATIONS IN POPULATIONBEWARE OF FUNCTIONAL IMPACTS FROM SPECIFIC BEWARE OF FUNCTIONAL IMPACTS FROM SPECIFIC COMBINATIONSCOMBINATIONS

Dependent failure analysis

Slide 12.

COMMON CAUSE FAILURESCOMMON CAUSE FAILURESEXAMPLE EXAMPLE -- 10 RELAYS10 RELAYS

RELAY FAILURE IMPACTSTRAIN A: RELAYS RA1 * RA2TRAIN B: RELAYS RB1 * RB2TRAINS A * B:RELAYS RA1 * RB1 * RXX

COMBINATIONS IN POPULATION2 RELAYS: (10!) / (8!*2!) = 453 RELAYS: (10!) / (7!*3!) = 1204 RELAYS: (10!) / (6!*4!) = 210

RELAY FAILURE IMPACTSRELAY FAILURE IMPACTSTRAIN A:TRAIN A: RELAYS RA1 * RA2RELAYS RA1 * RA2TRAIN B:TRAIN B: RELAYS RB1 * RB2RELAYS RB1 * RB2TRAINS A * B:TRAINS A * B:RELAYS RA1 * RB1 * RXXRELAYS RA1 * RB1 * RXX

COMBINATIONS IN POPULATIONCOMBINATIONS IN POPULATION2 RELAYS:2 RELAYS: (10!) / (8!*2!) = 45(10!) / (8!*2!) = 453 RELAYS:3 RELAYS: (10!) / (7!*3!) = 120(10!) / (7!*3!) = 1204 RELAYS:4 RELAYS: (10!) / (6!*4!) = 210(10!) / (6!*4!) = 210

Dependent failure analysis

Slide 13.

COMMON CAUSE FAILURESCOMMON CAUSE FAILURESEXAMPLE EXAMPLE -- 10 RELAYS (cont.)10 RELAYS (cont.)

TRAIN A: 1 / 45 OF DOUBLE FAILURES +8 / 120 OF TRIPLE FAILURES

TRAIN B: 1 / 45 OF DOUBLE FAILURES +8 / 120 OF TRIPLE FAILURES

TRAINS A * B: 1 / 120 OF TRIPLE FAILURES

COMPLETE MGL EXPANSIONMORE REALISTIC MODELS AND RESULTSMAY BE WORTHWHILE EVEN IF FAILURE OF 4 OR MORE RELAYS CAUSES SEVERE CONSEQUENCES

TRAIN A:TRAIN A: 1 / 451 / 45 OF DOUBLE FAILURES +OF DOUBLE FAILURES +8 / 1208 / 120 OF TRIPLE FAILURESOF TRIPLE FAILURES

TRAIN B:TRAIN B: 1 / 451 / 45 OF DOUBLE FAILURES +OF DOUBLE FAILURES +8 / 1208 / 120 OF TRIPLE FAILURESOF TRIPLE FAILURES

TRAINS A * B:TRAINS A * B: 1 / 1201 / 120 OF TRIPLE FAILURESOF TRIPLE FAILURES

COMPLETE MGL EXPANSIONCOMPLETE MGL EXPANSIONMORE REALISTIC MODELS AND RESULTSMORE REALISTIC MODELS AND RESULTSMAY BE WORTHWHILE EVEN IF FAILURE OF 4 OR MAY BE WORTHWHILE EVEN IF FAILURE OF 4 OR MORE RELAYS CAUSES SEVERE CONSEQUENCESMORE RELAYS CAUSES SEVERE CONSEQUENCES

Dependent failure analysis

Slide 14.

COMMON CAUSE FAILURESCOMMON CAUSE FAILURESCOMMON CAUSE DATA SCREENINGCOMMON CAUSE DATA SCREENING

TABULATED PARAMETER VALUESBROAD APPLICABILITYAUTHORS’ JUDGMENTMAY NOT BE CONSERVATIVE FOR ALL APPLICATIONS

ACTUAL EVENT SUMMARIES MOST USEFUL

EVENT REVIEW / SCREENINGDO NOT USE “BETTER” TRAINING, PROCEDURES, PEOPLE, ETC. AS BASIS FOR REMOVING EVENTSPOSSIBLE MORE SEVERE PLANT-SPECIFIC IMPACTS THAN AT OCCURRENCE PLANT

TABULATED PARAMETER VALUESTABULATED PARAMETER VALUESBROAD APPLICABILITYBROAD APPLICABILITYAUTHORSAUTHORS’’ JUDGMENTJUDGMENTMAY NOT BE CONSERVATIVE FOR ALL MAY NOT BE CONSERVATIVE FOR ALL APPLICATIONSAPPLICATIONS

ACTUAL EVENT SUMMARIES MOST USEFULACTUAL EVENT SUMMARIES MOST USEFUL

EVENT REVIEW / SCREENINGEVENT REVIEW / SCREENINGDO NOT USE DO NOT USE ““BETTERBETTER”” TRAINING, PROCEDURES, TRAINING, PROCEDURES, PEOPLE, ETC. AS BASIS FOR REMOVING EVENTSPEOPLE, ETC. AS BASIS FOR REMOVING EVENTSPOSSIBLE MORE SEVERE PLANTPOSSIBLE MORE SEVERE PLANT--SPECIFIC IMPACTS SPECIFIC IMPACTS THAN AT OCCURRENCE PLANTTHAN AT OCCURRENCE PLANT

Dependent failure analysis

Slide 15.

HUMAN DEPENDENCIESHUMAN DEPENDENCIESELEMENTS OF A HUMAN ACTIONELEMENTS OF A HUMAN ACTION

IDENTIFICATION

DIAGNOSIS COGNITIVE

DECISION

RESPONSE IMPLEMENTATION

IDENTIFICATIONIDENTIFICATION

DIAGNOSISDIAGNOSIS COGNITIVECOGNITIVE

DECISIONDECISION

RESPONSERESPONSE IMPLEMENTATIONIMPLEMENTATION

}

Dependent failure analysis

Slide 16.

HUMAN DEPENDENCIESHUMAN DEPENDENCIESHUMAN BEINGS ARE NOT HARDWAREHUMAN BEINGS ARE NOT HARDWARE

HUMAN RELIABILITY CANNOT BE EVALUATED OUT OF CONTEXT

HUMAN PERFORMANCE DEPENDS ON THE ENTIRE HISTORY OF ACCUMULATED KNOWLEDGE, EXPERIENCE, TRAINING, GUIDANCE, AND INFORMATION UNTIL THE TIME OF RESPONSE

HUMANS INTERPRET THE INFORMATION THAT THEY RECEIVE, EVALUATE ITS RELEVANCE AND MEANING, FORM A CONCLUSION, AND RESPOND

INFORMATION, INTERPRETATION, AND DECISION DEPEND ON CONTEXT

HUMAN RELIABILITY CANNOT BE EVALUATED OUT OF HUMAN RELIABILITY CANNOT BE EVALUATED OUT OF CONTEXTCONTEXT

HUMAN PERFORMANCE DEPENDS ON THE ENTIRE HUMAN PERFORMANCE DEPENDS ON THE ENTIRE HISTORY OF ACCUMULATED KNOWLEDGE, HISTORY OF ACCUMULATED KNOWLEDGE, EXPERIENCE, TRAINING, GUIDANCE, AND EXPERIENCE, TRAINING, GUIDANCE, AND INFORMATION UNTIL THE TIME OF RESPONSEINFORMATION UNTIL THE TIME OF RESPONSE

HUMANS INTERPRET THE INFORMATION THAT THEY HUMANS INTERPRET THE INFORMATION THAT THEY RECEIVE, EVALUATE ITS RELEVANCE AND MEANING, RECEIVE, EVALUATE ITS RELEVANCE AND MEANING, FORM A CONCLUSION, AND RESPONDFORM A CONCLUSION, AND RESPOND

INFORMATION, INTERPRETATION, AND DECISION INFORMATION, INTERPRETATION, AND DECISION DEPEND ON CONTEXTDEPEND ON CONTEXT

Dependent failure analysis

Slide 17.

HUMAN DEPENDENCIESHUMAN DEPENDENCIESSCENARIOSCENARIO--BASED PERSPECTIVEBASED PERSPECTIVE

PSA MODELS CONTAIN VERY LARGE NUMBERS OF INDIVIDUAL SCENARIOS (“SEQUENCES”, “CUTSETS”, ETC.)

IDENTIFY IMPORTANT DIFFERENCES THAT AFFECT HUMAN RESPONSE

GROUP SCENARIOS AND DEFINE PSA ACTIONS BASED ON SUCCESS CRITERIA AND BOUNDARY CONDITIONS FOR HUMAN PERFORMANCE

MANUAL START OF STANDBY EQUIPMENT IS A SCENARIO-BASED COGNITIVE ACTION

PSA MODELS CONTAIN VERY LARGE NUMBERS OF PSA MODELS CONTAIN VERY LARGE NUMBERS OF INDIVIDUAL SCENARIOS (INDIVIDUAL SCENARIOS (““SEQUENCESSEQUENCES””, , ““CUTSETSCUTSETS””, , ETC.)ETC.)

IDENTIFY IMPORTANT DIFFERENCES THAT AFFECT IDENTIFY IMPORTANT DIFFERENCES THAT AFFECT HUMAN RESPONSEHUMAN RESPONSE

GROUP SCENARIOS AND DEFINE PSA ACTIONS BASED GROUP SCENARIOS AND DEFINE PSA ACTIONS BASED ON SUCCESS CRITERIA AND BOUNDARY CONDITIONS ON SUCCESS CRITERIA AND BOUNDARY CONDITIONS FOR HUMAN PERFORMANCEFOR HUMAN PERFORMANCE

MANUAL START OF STANDBY EQUIPMENT IS A MANUAL START OF STANDBY EQUIPMENT IS A SCENARIOSCENARIO--BASED COGNITIVE ACTIONBASED COGNITIVE ACTION

Dependent failure analysis

Slide 18.

HUMAN DEPENDENCIESHUMAN DEPENDENCIESSCENARIOSCENARIO--BASED CONSIDERATIONSBASED CONSIDERATIONS

INITIATING EVENT

AVAILABLE TIME WINDOW

AVAILABLE EQUIPMENT

CUES, INDICATIONS, AND ALARMS

PROCEDURES, TRAINING, AND EXPERIENCE

COMPETING PRIORITIES

PREVIOUS OPERATOR ACTIONS (SUCCESSES AND FAILURES)

INITIATING EVENTINITIATING EVENT

AVAILABLE TIME WINDOWAVAILABLE TIME WINDOW

AVAILABLE EQUIPMENTAVAILABLE EQUIPMENT

CUES, INDICATIONS, AND ALARMSCUES, INDICATIONS, AND ALARMS

PROCEDURES, TRAINING, AND EXPERIENCEPROCEDURES, TRAINING, AND EXPERIENCE

COMPETING PRIORITIESCOMPETING PRIORITIES

PREVIOUS OPERATOR ACTIONS (SUCCESSES AND PREVIOUS OPERATOR ACTIONS (SUCCESSES AND FAILURES)FAILURES)

Dependent failure analysis

Slide 19.

HUMAN DEPENDENCIESHUMAN DEPENDENCIESIDENTIFY / DISPLAY DEPENDENCIESIDENTIFY / DISPLAY DEPENDENCIES

PSA MODELS SHOULD:DISPLAY OPERATOR ACTIONS IN SCENARIO CONTEXTIDENTIFY ALL CONDITIONS WHERE OPERATOR ACTIONS ARE COMBINED THROUGH “AND” LOGIC

DIFFICULT TO IDENTIFY SCENARIO CONTEXT AND COMBINED ACTIONS IN FAULT TREE FORMAT

USUALLY REQUIRES MODEL SOLUTIONNUMERICAL VALUES MAY SUPPRESS CUTSETS“SCREENING VALUES” MAY BE OPTIMISTIC

EVENT TREE FORMAT GENERALLY BETTERDEFINES SCENARIO CONTEXTIDENTIFIES COMBINED ACTIONS

PSA MODELS SHOULD:PSA MODELS SHOULD:DISPLAY OPERATOR ACTIONS IN SCENARIO CONTEXTDISPLAY OPERATOR ACTIONS IN SCENARIO CONTEXTIDENTIFY ALL CONDITIONS WHERE OPERATOR ACTIONS ARE IDENTIFY ALL CONDITIONS WHERE OPERATOR ACTIONS ARE COMBINED THROUGH COMBINED THROUGH ““ANDAND”” LOGICLOGIC

DIFFICULT TO IDENTIFY SCENARIO CONTEXT AND COMBINED DIFFICULT TO IDENTIFY SCENARIO CONTEXT AND COMBINED ACTIONS IN FAULT TREE FORMATACTIONS IN FAULT TREE FORMAT

USUALLY REQUIRES MODEL SOLUTIONUSUALLY REQUIRES MODEL SOLUTIONNUMERICAL VALUES MAY SUPPRESS CUTSETSNUMERICAL VALUES MAY SUPPRESS CUTSETS““SCREENING VALUESSCREENING VALUES”” MAY BE OPTIMISTICMAY BE OPTIMISTIC

EVENT TREE FORMAT GENERALLY BETTEREVENT TREE FORMAT GENERALLY BETTERDEFINES SCENARIO CONTEXTDEFINES SCENARIO CONTEXTIDENTIFIES COMBINED ACTIONSIDENTIFIES COMBINED ACTIONS

Dependent failure analysis

Slide 20.

HUMAN DEPENDENCIESHUMAN DEPENDENCIESFACTORS THAT REDUCE HUMAN DEPENDENCEFACTORS THAT REDUCE HUMAN DEPENDENCE

PRECEDING OPERATOR SUCCESS

LONG TIME WINDOW BETWEEN SUCCESSIVE ACTIONS

DIVERSE FUNCTIONS

DIVERSE PERSONNEL AND LOCATIONS

PRECEDING OPERATOR SUCCESSPRECEDING OPERATOR SUCCESS

LONG TIME WINDOW BETWEEN SUCCESSIVE ACTIONSLONG TIME WINDOW BETWEEN SUCCESSIVE ACTIONS

DIVERSE FUNCTIONSDIVERSE FUNCTIONS

DIVERSE PERSONNEL AND LOCATIONSDIVERSE PERSONNEL AND LOCATIONS

Dependent failure analysis

Slide 21.

ReferencesReferences

IAEA-TECDOC-648 Procedures for conducting common cause failure analysis in probabilistic safety assessment (1992)IAEAIAEA--TECDOCTECDOC--648 Procedures for conducting common cause failure analysis in 648 Procedures for conducting common cause failure analysis in probabilistic safety assessment (1992)probabilistic safety assessment (1992)