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ANS PSA 2008 Topical Meeting - Challenges to PSA during the nuclear renaissance , Knoxville, Tennessee, September 6–11, 2008. Implementation of a Concept for a Risk-informed Diagnosis/Prognosis of Plant States through the RISARD System. Kwang-Il Ahn [email protected]

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Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

ANS PSA 2008 Topical Meeting - Challenges to PSA during the nuclear renaissance,

Knoxville, Tennessee, September 6–11, 2008

Implementation of a Concept for a Risk-informed Diagnosis/Prognosis of Plant States through the RISARD System

Kwang-Il Ahn

[email protected]

Integrated Safety Assessment

Korea Atomic Energy Research Institute


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

⊙ Outline

  • Motivation & Objectives

  • The Concept of RI-SAM

  • Computerized Tool SARD

  • Demonstrative Application

  • Concluding Remarks


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

⊙ Motivation

Key Ways for a Successful Implementation of SAM

  • Develop a proper SAM strategy by answering the questions:

    • How to reduce uncertainties in implementing the established SAM strategies? especially when available resources are limited.

    • Which essential safety function was lost at the time of the accident? That is, the root cause of the accident;Which safety systems are currently available for SAM?

    • What will be important future events? and what will be their evolution?

    • What are potential ‘success paths’ for SAM?

  • Utilize the computer-based methods & tools for supporting SAM:

    capable of ① diagnosing the functional states of plant safety systems and ② predicting the future trends of key plant parameters as possible as quickly:

    • The diagnostic capability for plant states at the time of the accident is required to reduce the uncertainties in the current plant system state and to have a good basis for estimating future plant states.

    • Based on the current damage states of the plant, the prognostic capability for the possible evolution of the accident gives time enough to take an action for mitigating the consequence of the accident.


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

Our Approach for supporting SAM:

Utilize a PSA-based and SA phenomenological trends-based database (DB)(e.g., plant-, code-, accident sequence-specific SA analysis results) => SAR DB

Systematic use of SAM-related information

Quick & fast retrieval of the SAM-related information (Quick view)

Provide a computerized platform for a comprehensive use of SAR DB in a simple, fast and risk-informing way => RI-SARD

Proper information about the plant damage statesat the time of the accident: the root cause of the accident (Diagnosis)

Insights on the possible evolution of the accident (critical parameters), based on the current damage states of the plant (Prognosis)

Develop the best strategy for supporting SAM(especially when available plant information is limited)=> RI-SAM

Helpful in finding success paths for intended SAM actions

Helpful in providing appropriate actions to mitigate the accident

⊙ Objectives: RI-SAM Strategy & Tool


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

⊙ RI-SAM: Diagnosis & Prognosis of Plant States

Monitor Plant Data & Signal:

Identify the IE & CD states

Determine the status/availability of

systems needed to mitigate the IE

ReSet

Plant symptoms

& accident time

AS screening (iteration loop)(2)

Yes

Signal Validation

Process

Prioritize

Frequency-based

potential accident

sequences

Determine

Plant symptoms

More

Symptoms

?

Quick view

Future trend

of symptom

parameters

Diagnosis

Symptom-based

SARD module

Plant

symptoms

Plant

Conditions

No

Auto switch to module for Prognosis of Future Plant Status

Performance

1. Key plant safety

parameters for SAM

2. Performance of

key SSCs

Plant

damage states

Determine

Relevant PDS (1)

Decision for

Implementation

of the relevant

SAM strategies

Prognosis

Scenario-based

SARD module

Success Paths

Countermeasures

(dynamic loop)(2)

Modification

Link to SA Simulator

for Interactive Action

Note(1): A prescribed accident sequences by which uncertainty can be reduced in taking an action for SAM.

Note(2): A process by which the prediction can be updated based upon successive data from plant.


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

⊙ A Computerized Tool: RI-SARD


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

SAR Information

- Level 1/2 PSA

- Accident Analysis

- SAM Information

- The other SAR Inform

Formatted SAR Data Sets

SARD System Operation

Data Set Spec. for SARD

- Plant/Code/User ID

- Accident Sequence Inform(1)

- Sensitivity Information (Plant

systems & Model parameters)

- Severe Accident Code Analysis

Results(2) (Code Responses)

- Summary of Key Accident

Progression Events (Code Result)

- Accident Mitigation Options

- Data Set & Databank Index

- Commentary Parts

Data Allocation into

SARDB

Data Search & Retrieval,

Graphical Display

- Scenario-based Plant

Responses & Behavior

- Plant symptom-based

Potential Accident Sequences

- Status of Plant System &

Containment Systems

SARDB: Databank

(MS Access DB)

Database Update &

Modification

Accident Sequence Types

- PSA code-specific plant damage

event trees for graphical use

- User-specified events sequence

SAR-informed Decision-making

⊙ SARD: Data Sets Operation

(1)Severe Accident Initiators:LOCA (Large, Medium, Small), Loss of Off-site Power (LOOP), Station Blackout (SBO), Loss of Feed Water (LOFW), Interfacing System LOCA, Steam Generate Tube Rupture (SGTR), Anticipated Transient w/o Scram (ATWS), Loss of AC Bus (125V, 4.16KV), Large Secondary Side Break, General Transient

(2)Number of Categorized MAAP Response Parameters (Total 883):RCS/SG/ESF Information (134); Behavior of Core and Fuel (152); Lower Plenum Debris Behavior (77); Lower Head Failure Information (85); Containment Information (196); Source Term Information (229); Hydrogen Generation (10)


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

⊙ SARD: SARDB Generation (1)

Identify the initiating event & the status and availability of systems

and equipment needed to avoid or mitigate the severe accident

Plant-specific PDS ET

PDS sequence: plant damage state + frequency

SA phenomenological trends with time

Developing trends of key events during accident

SARDB

Typical Form of SARDB

Allocation of Plant-, Code-specific SA Analysis Results into SARDB


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

Key Role of the PDS ET-based Diagnosis & Prognosis

Provide the status of plant and cont. systems at the time of core damage

All potential ASs for an IE can be shown at a glance with its graphical form

Occurrence probability (or frequency) be systematically derived from PSA

The graphical form of PDS ET can be very useful in specifying a particular AS during the data loading and information retrieval process

Probability can be utilized as a criterion for screening the risk-significant ASs

⊙ SARD: SARDB Generation (2)

Risk-informed SA Analysis


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

LLOCA PDS ET

⊙ SARD: SARDB Generation (3)

Dominant accident initiators:

Frequency-based screening of PDS sequences


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

SAMPLE: Key Events Summary for LF115 (MAAP)

Time Events Code Functional Status

0.000 157:T MAIN FW OFF

0.000 224:T MOTOR-DRIVEN AUX FEED WATER FORCED OFF

0.000 232:T CHARGING PUMPS FORCED OFF

17.836 31:T PZR SPRAYS ON

37.431 13:T REACTOR SCRAM

37.431 156:T MSIV CLOSED

42.578 153:T SEC SV(S) FIRST OPEN BROKEN S/G

42.578 163:T SEC SV(S) FIRST OPEN UNBROKEN S/G'S

867.556 161:T UNBKN S/G DRY

870.375 151:T BROKEN S/G DRY

1109.376 3:TH VALVE FIRST OPENED

1109.376 4:TH VALVE FIRST OPENED

1109.376 5:TH VALVE FIRST OPENED

1113.182 35:T VOID FRACTION IN PZR < 0.1

1728.464 4:T MAIN COOLANT PUMPS OFF

2584.444 691:T TRUE: CORE HAS UNCOVERED

4888.784 509:T TRUE: MAX. CORE TEMP EXCEEDS 2200. F

5084.019 690:T TRUE: MAXIMUM CORE TEMPERATURE HAS EXCEEDED 2499 K

5188.688 508:T TRUE: MAX. CORE EXIT TEMP EXCEEDS 1200. F

5962.269 2:T RELOCATION OF CORE MATERIALS TO

LOWER HEAD STARTED

5987.935 103:T UPPER COMPT. SPRAYS ON

6778.318 3:T RV FAILED

6794.329 5:T HPI ON

6794.329 6:T LPI ON

6857.934 188:T ACCUMULATOR WATER DEPLETED

8142.179 1003:T TRUE: 1 TH COMPT BURNING IN PROGRESS

8142.179 1048:T TRUE: 4 TH COMPT BURNING IN PROGRESS

8142.179 1063:T TRUE: 5 TH COMPT BURNING IN PROGRESS

8142.492 1033:T TRUE: 3 TH COMPT BURNING IN PROGRESS

9897.961 5:F HPI OFF

9897.961 181:T RECIRC SYSTEM IN OPERATION

….

⊙ SARD: SARDB Generation (5)

Events history:

Plant system

status with time

PDS

sequence-

specific SA

code

analysis

Parameters history:

SA code parameter

behavior with time


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

Specification of Code Data (Multiple)

Specification of Databank Index

Specification of Code Data (Single)

Specification of the Target Scenario

SAR Data

ASQ data

Plant Data

Specification of Sensitivity Information

Check of the Allocated Information

SA Code data

Code results

AMP & Summary Data

SARDB

MS Access DB

⊙ SARD: SARDB Generation Module


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

⊙ SARD: Two-way information Retrieval

Set target

Plant ID & Code ID

Scenario Base (1)

Symptom Base (2)

PSA Information:

IE & Target Sequence

Plant Symptoms:

- Code Parameters

- Time windows

More symptoms? AS Screening

Data Search:

Plant-/Code-/AS sequence-specific Responses

Prioritize Accident Scenarios (i = 1, n), in a risk-informing way

Auto Switch

Display

- Plant states

- Base response

- Sensitivity case

- SAMG parameters

- SSC performance

- Events History

Target Sequence

End of Search

(1) Retrieval of the specified- accident sequence-based plant/code behavior (Accident Diagnosis)

(2) Retrieval of plant symptoms-based potential accident sequences (Accident Prognosis)


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

PDS ET Events Functional Status

Set Plant & Code information

The most probable

The most probable

plant system state

plant system state

List of potential

List of potential

Switch to

the Scenario-based Module

plant damage

plant damage

Switch to

the Scenario-based Module

states

states

Progression

Progression

Future trend of

Future trend of

of key events

of key events

plant parameters

plant parameters

User

User

-

-

specified

specified

plant symptoms

plant symptoms

⊙ SARD:Plant Symptom-based Diagnosis


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

Display of the Corresponding PDS ET

PDS ET Events Functional Status

Set Plant & Code information

User

User

-

-

specified

specified

accident conditions

accident conditions

User

User

-

-

specified

specified

code/plant

code/plant

parameters

parameters

Future history key events

Future history key events

&

&

plant parameters

plant parameters

⊙ SARD: PDS sequence-based Prognosis


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

⊙ Demo Application: Diagnosis of PDS sequences

Target: OPR1000-/MAAP-specific SARDB for 6 Initiating Events

(Large/Medium/Small LOCAs, LOOP, SBO, SGTR)


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

⊙ Demo Application: Prognosis of Future Trend

Future Trends of ‘TWCR’ for the Predicted 11 PDS Sequences

Diagnostic result: future trend of ‘TWCR’ for ‘SBLOCA_S012’

After Screening

SBLOCA_S012:SLOCA*/RT*/HPI*/AFW*/SR1*HPR*/DPR*LPR*CSR

TWCR: temperature of water in core (K)

SBLOCA_S012: TWCR


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

SAMG Entry Time !

⊙ SAM-Decision Flow Chart (DFC)-SAMG entry time

Making predictions about future trend of the 7 plant safety parameters to trigger the relevant SAMG and their entry times, based on the user-specified thresholds

LBLOCA-S03

S/G Water Level

Entry time: 6.85 sec.

Entry time:10.4 sec.

RCS Pressure

Entry time: 30.32 sec.

Containment Pressure


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

⊙ SAM-SSC Performance-failure time & probability

Making predictions about when core damage, core support plate failure, induced RCS & SG creep failure, reactor vessel failure, and containment failure will occur

SBLOCA-S26

Water level in RPV

Core uncover at 19876 sec.

RCS HL: unbroken

RCS HL: broken

No induced creep failure

S/G: unbroken

S/G: broken

RPV LH Creep at 37355 sec.

PRV LH creep

P-tube ejection

P-tube heatup

Debris jet impingement


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

⊙ Concluding Remarks

  • Summary

    • Based on a concept of a RI-SAM, the present RI-SARD system explores

      • a symptom-based diagnosis of potential PDS sequences in a risk-informing way &

      • a plant damage sequence-based prognosis of key plant parameter behavior, in a simple, fast, and efficient way.

    • The replicated use of both processes makes it possible to extract information required for taking the intended SAM actions,consequently leading to an answer about what is the best strategy for SAM.

    • An example application through the OPR1000- and MAAP code-specific SAR DB has shown that the present approach can

      • enhance a diagnostic capability for anticipated plant states,

      • give the SAM practitioners more time to take actions for mitigating the accident,

      • reduce the still relatively large uncertainty in the field of SAM, and

      • consequently, help guide the TSC staffs through a severe accident.


Ans psa 2008 topical meeting challenges to psa during the nuclear renaissance

⊙ Concluding Remarks

  • Future Plan for Improvement

    • Will involve the ability to link decisions made by RISARD with the SAM procedure and SA simulator, so that the impact of the SAM actions on an accident progression can be feedback to in an interactive way to a user.

    • Will involve the use of a more structured approach capable of ①diagnosing the current plant system state, ② predicting the most probable accident pathway during the progress of an accident, and ③ taking the best strategy to terminate its progression into an undesirable consequence, including a linking with

      • a diagnostic logic tree to diagnose effectively potential plant damage states,

      • a simplified APET capable of predicting the progress of accidents accurately, and

      • a more sophisticated logical rule capable of extracting appropriate SAM strategies for a given plant damage state

    • In addition, we will explore increasing the number of accident types recognized by RI-SARD (e.g., various spectrum of break sizes for LOCA & SGTR)


Thank you for your attention

Thank you for your attention !!!


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