A Pilot Study on The Best-Estimate Thermal-Hydraulic Analysis Methodology

Applied For a Probabilistic Safety Assessment

PSAM9

Integrated Safety Assessment Division, KAERI

Ho-Gon LIM/Joon-Eon YANG

KAERIKAERI 2

Contents

Introduction

OECD/NEA Safety Margin Action Plan

Procedure For Uncertainty Quantification – Accident Sequence Selection

– Identification Of Important Parameters

– Calculation for Nominal Plant Condition

– Calculation to Get the Distribution of The Event Sequence

– Quantification of Failure Probability of The Event Sequence

Conclusion And Future Works

KAERIKAERI 3

Introduction

A thermal/hydraulic (T/H) calculation and an expert judgement are used to develop event trees (ET).

Conservative approach was implemented to compensate the uncertainty.

– The conservative approach can distort the results of PSA (shadoweffect).

Recently, the use of best-estimate T/H code is emphasized

– ASME PRA Standard

There is a concern about hot to deal with the uncertainty caused by to the best-estimate analysis

– We proposed a procedure to quantify the uncertainty due to the best-estimate analysis

KAERIKAERI 4

OECD/NEA Safety Margin Action Plan

STATESmallLOCA

GSLOCA

Long TermCooling

LTC

Feed andBleed

Operation

FB

SecondaryHeat

Removal

SHR

LPSI

LPSI

OperatorAction for

LPSIInjection

O/A

HPSI

HPSI

ReactorSub-

Criticality

RT

OK

ToATWS

CD

CD

OK

CD

CD

OK

CD

CD

Conditionalsuccess/

failure

CSF

Calculate the distribution of safety criteria (PCT, RCS pressure)Compare to Safety Limit (ex. 2200 oF) and calculate exceeding probabilityAssign success/failure probability of a event scenario using new event tree heading

KAERIKAERI 5

Procedure for Uncertainty Quantification

Construct the ET based on the Nominal Plant Data

– Eliminate conservative bias

Screening– Fatal failure or obvious success

• Failure of RHR

• Normal shutdown procedure in ET

– Insignificant accident scenario• F(ETi)< ε

Identification of Parameters – Important parameters affecting

accident progression• Code and plant specific parameters

Calculation based on Random Sampling

– 10CFR50.46 alternative• Response surface construction

– 100 random sampling in the present study• Sampling method is not fixed yet.

Feedback to existing ETs or conditional failure probability quantification

KAERIKAERI 6

Accident sequence Selection(1/2)

Anticipated Transient Without Scram (ATWS)

Characteristics of a selected scenario– Composed of successful turbine trip, favourable exposure

time, PSV reseat, and so on

– An event sequence with the largest frequency

– Large uncertainty exist due to reactivity feedback and the pressure relieving characteristics

– The unfavourable exposure time (UET) is determined based on the nominal plant data

KAERIKAERI 7

Accident sequence Selection(2)

ATWS first scenario #1 in Ulchin 3&4 in Korea

GATWS

AnticipatedTransients

WithoutScram

T_TRIP

Turbine Trip

MTC

FavorableModerate

Temp.Coefficient

PSV

PressurizerSafety Valve

Reseat

CSGTR

ConsequentialSGTR

AFW

DeliverAuxiliary

Feedwater

SR1

SteamRemovalvia TBVsor ADVs

SR2

SteamRemoval

via MSSVs

EBOR

EmergencyBoration

SDC

EstablishShutdown

Cooling

MSHR

MaintainSecondary

HeatRemoval

BD

BleedRCS

HPI

HPSISInjection

HPR

HPSISRecirculation

CSR

RecirculationCooling

SSDC

Switch toShutdown

Cooling

G-U3-IE-ATWS

GSCGTOP

GMHTOP-N

GCSRCTOPGHSRGTOP

GHSIGTOPGSDOL

GMXEBOR

GMSADV1OF4

GMHTOP-N

GCSRCTOPGMXSSDC

GHSRGTOPGHSIGTOP

GSDOLGMXEBOR

GMSMSSVALLO

GCSRCTOPGMXSSDC

GHSRGTOPGHSIGTOP

GSDOE

GAFTOP-N

GCSRCTOP GMXSSDCGHSRGTOP

GHSIGTOPGSDOE

sgi

PSVGCSRCTOP

GHSRGTOP-LMLGHSIHTOP-ML

G-U3-AT-SQ34

GSCGTOP

GMHTOP-N

GCSRCTOPGHSRGTOP

GHSIGTOPGSDOL

GMXEBOR

GMSADV1OF4

GMHTOP-N

GCSRCTOPGMXSSDC

GHSRGTOPGHSIGTOP

GSDOLGMXEBOR

GMSMSSVALLO

GCSRCTOPGMXSSDC

GHSRGTOPGHSIGTOP

GSDOE

GAFTOP-N

GCSRCTOP GMXSSDCGHSRGTOP

GHSIGTOPGSDOE

sgi

PSVGCSRCTOP

GHSRGTOP-LMLGHSIHTOP-ML

G-U3-AT-SQ34

SEQ#

STATE

STATE

FREQ

1 OK 2 OK 3 OK 4 CD 5 CD 6 CD 7 CD 8 CD 1.092E-07 9 OK 10 OK 11 OK 12 CD 13 CD 14 CD 15 CD 16 CD 17 OK 18 OK 19 CD 20 CD 21 CD 22 CD 23 OK 24 OK 25 CD 26 CD 27 CD 28 CD 29 to CSGTR 30 OK 31 CD 2.489E-10 32 CD 1.962E-10 33 CD 1.704E-10 34 CD 2.24E-07 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68

KAERIKAERI 8

IDENTIFICATION OF THE IMPORTANT PARAMETERS (1/2)

It is necessary to know the parent distribution effectively under the given calculation resources

General Procedure for Parameter Selection– Identification of important phenomena in the accident

scenario

– Identification of parameters in code describing the important phenomena

– Ranking their importance in terms of ΔPCT or Δpop

In the Present analysis– Simplified phenomena identification and parameter selection

procedures

– No ranking process

KAERIKAERI 9

IDENTIFICATION OF THE IMPORTANT PARAMETERS (2/2)

phenomena parameter variable distribution Selection

Dist. 2σ min max Nominal(mean)

opening set pressure(bar) Normal 2.76 171.03 175.17 172.41 O

PSV discharge rate(kg/s) Normal 10.79 57.96 79.55 68.75 O

Fuel-Clad conductivity XClad-coolant conductivity Xinitial coolant temperature X

Pressurizer solid state pressurizer water level (meter) 0.67 -0.381 0.9652 0(50%) OAux. capacity 500 gpm bound X

delay time 45 second bound XAux. temp.(K) 22.22 277.44 321.89 293 O

Convective heat transfer coeff. Xturbine trip time XMSSV flow rate 134.61 722.75 991.97 857.34 X

MSSV set pressure 1.03 85.52 87.59 86.21 OMSIV closing

Time 5 x

Heat transfer to secondary side

Reactivity feedback

RCS pressure relieving valve

capacity

KAERIKAERI 10

Nominal Event Calculation (1/3)

Event history for nominal plant stateTime (sec) Event

0.0 Loss of main feedwater (representative ATWS IE)

42.8 RCS trip set point by PZR high pressure(164 bar)

53.5 Auxiliary Feed water actuation set point by S/G low level

63.8 S/G dryout

72.01 PZR Safety valve opening set pressure

81.9 First PZR blowdown pressure

83.72Main steam line isolation valve (MSIV) closing set point by low

pressure

86.0 Second opening of PZR safety valve

88.72 Complete closing of MSIV

95.1 PZR solid state

98.5 AFW start

~100 Hot leg saturation pressure

115.1 RCS peak pressure

159. MSSV set point by S/G high pressure

1000.0 Calculation terminated

KAERIKAERI 11

Nominal Event Calculation (2/3)

Temporal Behavior of plant main parameter

0 200 400 600 800 10000

500

1000

1500

2000

2500

3000

Rea

ctor

Pow

er(M

W)

T ime(second)

Thermal Power

0 200 400 600 800 1000

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

Rea

ctiv

ity(d

ollo

r)

T ime(second)

Reactivity total doppler moderator

0 200 400 600 800 100040

80

120

160

200

240

280

Pre

ssur

e(X

0.1

Mpa

)

Time(second)

Pressure Pressurizer S/G

0 200 400 600 800 10000.0

0.2

0.4

0.6

0.8

1.0

Nor

mal

ized

PZR

Lev

el

Time(second)

pressurizer Level

• Reactor Power • Reactivity

• RCS & S/G pressure • PZR level

KAERIKAERI 12

Nominal Event Calculation (3/3)

Determination of UET (Unfavorable Exposure Time) according to the fuel burn-up

0 100 200 300 400

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

Pre

ssur

e

Time(second)

a pcm/oF b pcm/oF c pcm/oF

Pressure Limit(3200 psi)

KAERIKAERI 13

Calculation to Get the Distribution of The Event Sequence (1/2)

100 sampling calculation for the selected parameters based on their probability density function)

95/95 approach based on Wilk’s formula is not applied

The calculation by the nominal data is covered well by the sampling calculation results

There is a bifurcation in the calculation, which has frequently appeared in a BE T/H calculation

0 20 40 60 80 100 120 140

14

16

18

20

22

24

26

28

Pressure by Norm inal Data

Pre

ssur

e (M

pa)

T im e(second)

KAERIKAERI 14

Calculation to Get the Distribution of The Event Sequence (1/2)

The distribution has a camelback shape due to a bifurcation of the calculation

The failure probability of the event sequence is given as 0.55 approximately

22 23 24 25 260

5

10

15

20

25

30

Rel

ativ

e Fr

eque

ncy

Pressure(Mpa)

RCS pressure distribution (Number of run = 93)

21 22 23 24 25 260.0

0.2

0.4

0.6

0.8

1.0

Cum

ulat

ive

Prob

abili

ty

Pressure(Mpa)

RCS Pressure Limit

KAERIKAERI 15

Quantification of the Event Sequence Failure Probability

In a PSA, the frequency of success scenario is not quantified – Conservativeness of success scenario

Event Scenario frequency

The frequency of success sequence is 6.183E-6– The failure frequency is 3.4E-6

⎟⎟⎠

⎞⎜⎜⎝

⎛⋅⋅= ∏ ∏

−

= −−

mn

j

n

mnkkjESES

SSpffi

1

iESf

jS

ESf

: Frequency of the event sequence, i

: The failure event of system, j : Initiating event frequency

KAERIKAERI 16

Conclusion & future work

Conclusion– Best-estimate thermal-hydraulic approach to calculate the

uncertainty of an event sequence is implemented

– ATWS was selected as a pilot study

– The RCS pressure was used for the core damage criterion

– Although all the important parameters was not identified and used in the calculation, we demonstrated the possibility that the conditional failure probability can be calculated through the best-estimate T/H calculation

Future Work– Determination of sampling method and number of sampling

– Application for whole event trees considered in a PSA model