BARC - International Atomic Energy AgencyBARC Safety criteria for advanced reactor systems ... BARC Experimental Facilities for Study of Boiling Two-phase ... using neutron radiography

BARCBARC

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RELABILITY ANALYSIS OF PASSIVE SYSTEMS

A.K. Nayak, PhDReactor Engineering Division

Bhabha Atomic Research CentreTrombay, Mumbai 400085

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Safety criteria for advanced reactor systems

Risk based approach

Accuracy of Current PSA treatment- human reliability?

Advanced systems - operator action

is minimized throughpassive systems.

- reliability of passive systemsmust be considered. RADIOLOGICAL CONSEQUENCES

-

-

FREQ

UEN

CY

(eve

nts/

year

)

unallowabledomain

-

Quantitative Probabilistic Safety Goal

allowabledomain

Residual risk (RR) : no additional public health concerns

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Why Passive Systems Can Fail?

While, Passive systems by definition, should operate only on the basis of fundamental natural physical laws, question arises

Can Such Systems Fail?• Possibly no – for example,

gravity does not fail; buoyancy does not fail or in other words “mechanism does not fail”

• Possibly Yes – for example,mechanism may not fail, but the system may not be able to carry out the required duty or defined objectives whenever called on

This is called as “Functional Failure” of a Passive System, which can happen if the boundary conditions deviate from the specified value on which the performance of the system depends. Mainly because, the driving force of passive systems are small, which can be easily changed even with a small disturbance or change in operating parameters.

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Difficulties in Evaluation of Functional Failure of Passive Systems

Lack of Plant Data and Operational Experience

Lack of sufficient experimental data from Integral Facilities or even from Separate Effect Tests in order to understand their performance characteristics not only at normal operation but also during transients and accidents.

The definition of failure mode of the systems are not well defined.

Difficulty in modeling the physical behaviour of such systems; particularly,• low flow natural circulation; the flow is not fully developed and can be multi-dimensional in

nature• flow instabilities which include flashing, geysering, density-wave, flow pattern transition

instabilities, etc.• critical heat flux under oscillatory condition• flow stratification with kettle type of boiling particularly in large diameter vessel • thermal stratification in large pools such as in GDWP• effect of non-condensable gases on condensation, etc.

Capability of so called “Best Estimate Codes” for such systems- use models applicable for active systems. - applicability for passive systems? Not well known.- Uncertainty of predictions

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Sources of Uncertainties

Uncertainties in the best estimate codes can arise due to• incapable models built-in the codes to represent a specific

phenomena;

• absence of models to represent a particular phenomena;

• deviations of the input parameters due to the uncertainties of the instruments and control systems and that of the geometry of the loop;

• uncertainties in the material properties such as fuel thermal conductivity; fuel-to-clad gap conductance, etc.

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Experimental Programme for Data Generation for Assessment of Code Uncertainties

BARC has built many experimental facilities for study of

• Natural Circulation, Flow Instabilities, CHF Under Oscillatory Condition;

• Condensation in Presence of Non-condensable;

• Behaviour of PCCS and PCIS

BARC will use its best estimate codes (RELAP5 and others) to compare code prediction with test data and evaluate uncertainties.

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Experimental Facilities for Study of Boiling Two-phase Natural Circulation

TEST SECTION

BUS BAR

BUS BAR

VENT LINEBLEED LINE

COOLING WATER OUTCOOLING WATER IN

CONDENSER

FILL LINE

DRAIN LINE

STEAM DRUM

RUPTURE DISCRELIEF VALVE

COOLER

COOLING WATER IN COOLING WATER OUT

Objectives•To generate date for natural circulation steady state and stability behaviour

Major Design ParametersDesign Pressure : 114 kg/cm2

Design temperature : 315 oCMaximum Power : 80 kWLoop Diameter : 50 mmElevation : 3000 mmHeated Section : 1000 mm

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Experimental Facilities for Study of Boiling Two-phase Natural Circulation (Contd.)

STEAM DRUM

APSARA REACTOR

Test Section

NEUTRON BEAM

CONDENSER

Flow pattern transition studies using neutron radiography

OBJECTIVES:

• Develop flow pattern transition criteria

• To understand the low power (Type I) and high power (type II) instabilities in natural circulation

• Measurement of CHF, pressure drop, void fraction and its distribution using NRG

• Evolution of Start-up procedure

Operating Parameters:Pressure : 70 barTemperature : 285 0 CNeutron Flux : 106 to 108 n/cm2s

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Objectives:• In-phase and out-of-phase

instability behaviour of parallel channels in naturalcirculation mode

• Effect of void reactivity feed back on thermalhydraulic stability

Geometric Details:Number of channels : 4Elevation : 3000 mmPipe diameter : 25 mmHeater diameter : 12 mmLength of heater : 1000 mmOperating pressure : 15 bar

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ISOLATIONCONDENSER

STEAM DRUM N2

CYLINDER

ADVANCEDACCUMULATOR

TAIL PIPE

GRAVITY DRIVENWATER POOL

RUPTURE DISC

HEADER

FEEDER

ECCS HEADER

FUEL CHANNEL

SIMULATOR

INTEGRAL TEST LOOP

Generation of database for performance evaluation of following

Steady state performance of natural circulation in MHTS- Mass flow rate- Pressure drop - void fraction- CHF- Gravity separation of Steam-water mixture in SD

Stability performance of natural circulation in MHTS- Static instability- Dynamic instability

Safety systems- Passive decay heat removal system (ICS)- ECCS

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Scaling Philosophy for Design

A three level approach is followed

(a) GLOBAL SCALING

Power – to – Volume scaling philosophy adopted

• Pressure, temperature and elevation : 1:1• Volume scaling ratio : 452

(b) BOUNDARY FLOW SCALING

• Feed water and steam flow simulation• Pressure, temperature and enthalpy : 1:1

(c ) LOCAL PHENOMENA SCALED ARE• CHF• Geysering, flashing, Carry-over and carry-under in steam drum, etc.

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Examples of Uncertainties of RELAP5/MOD3.2 with the in-house natural circulation data

-50 0 50 100 150 200 250 300 350-30

-20

-10

0

10

20

30

% E

rror

Power (kW)

Apsara HPNCL ITL Uncertainties have been

evaluated for

- steady state naturalcirculation,

- stability of naturalcirculation and limited datafor CHF

Example of error distribution for the test data of ITL, HPNCL and Apsara natural circulation loops

Abs

olut

e Fr

eque

ncy

% Error

Experimental Loop

Number of steady state data points

Uncertainty

Apsara ½” 87

~ 17 %HPNCL 26

ITL 14

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Examples of Uncertainties of RELAP5/MOD3.2 with the in-house natural circulation data (Contd.)

Uncertainties in code prediction for flow instabilities

State or condition of flow- Stable - Unstable - Threshold of Instability

Characteristics of Instabilities - Amplitude and frequency of oscillations including flow reversals- Important for simulation of CHF

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Examples of Uncertainties of RELAP5/MOD3.2 with the in-house natural circulation data (Contd.)

How to Evaluate Uncertainties for Flow Instabilities Prediction?

Current Numerical Codes are formulated based on First-Order-Numerical Discretization.

They have inherent numerical problems due to- ill-posedness of basic equations- numerical diffusion- instability whether physical or numerical???- sensitive to nodalization, etc.

Capability of Best-Estimate Codes to flow instabilities are not proven even for the condition or state of instability.Characteristics of Instability????

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Example of Nodalization Sensitivity of RELAP5 code for Simulation of Flow Instability

220 230 240 250 2604.9

5.0

5.1

5.2

5.3

5.4

5.5Number of grids

in Riser

Mas

s Fl

ow R

ate

(kg/

s)

Time (s)

4 grids 8 grids 12 grids 36 grids 40 grids 44 grids 48 grids 52 grids

Inlet Feeder pipes

Down Comers Ring Header

Steam

Steam drums

Tail pipes

Fuel bundles

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Characterization of Uncertainty for Flow Instability Prediction

Quantification of Uncertainties in Code Prediction for Instabilities is not possible with the current knowledge.

A Qualitative Treatment Can be Given

Error Uncertainty

< 10% Low

10%<Error<30% Medium

30%<Error<50% High

>50% Severe

.

5.%EXPT

RELAPEXPT

ParameterParameterParameter

Error

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Examples of Uncertainties in RELAP5 code for prediction of CHF induced by flow instability

Tube ID (m m)

Pressure (bar)

Expt. CHF(kW /m2)

Predicted CHF

% Error Uncertainty

13.5 209.68 212.70 1.44 LO W

5.1 196.12 196.56 0.20 LO W

7.0

2.35 118.82 102.68 13.60 M EDIUM

8.11 356.61 310.30 12.99 M EDIUM

6.25 335.00 366.72 9.47 LO W

9.1

4.6 335.00 169.25 49.47 H IGH

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Assessment of Passive Systems ReliAbility (APSRA)

BARC has developed a methodology for Assessment of Passive Systems ReliAbility known as APSRA.

It mainly considers the functional failure of the system to carry out the desired function as the basis of the failure of the passive systems.

The functional failure due to deviation of parameters are correlated with the failure of actual components through root diagnosis.

The methodology relies on in-house experimental data from simulated facilities in addition to best estimate codes for evaluation of reliability.

The method has been evaluated to evaluate the reliability of various Passive Systems of the AHWR.

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APSRA - How it works ?

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Applications

• AHWR is a vertical pressure tube type, boiling light water cooled and heavy water moderated reactor using (233U-Th) O2 and (Pu-Th) O2fuel.

MAJOR DESIGN OBJECTIVES1. A LARGE FRACTION OF POWER FROM THORIUM. 2. DEPLOYMENT OF SEVERAL PASSIVE SAFETY SYSTEMS – 3 DAYS

GRACE PERIOD.3. NO NEED FOR EMERGENCY PLANNING IN PUBLIC DOMAIN.4. POWER OUTPUT – 300 MWe.

CALANDRIA

STEAM DRUM

REACTOR BUILDING

INCLINED FUELTRANSFER MACHINE

FUELLING MACHINE

FUEL BUILDING

GRAVITY DRIVENWATER POOL (GDWP)

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Passive Safety Feature Heat removal from core by natural circulation of coolant in Main Heat Transport System

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Passive Safety FeaturePassive core decay heat removal by Isolation Condensers immersed in Gravity Driven Water Pool

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Passive Safety FeaturePassive injection of ECC water during LOCA, initially from accumulators and later from the overhead GDWP, directly into fuel cluster.Passive Containment Isolation & Passive Containment Cooling

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Passive Safety Feature

Passive Poison Injection System actuates during very low probability event of failure of wired shutdown systems (SDS#1 & SDS#2) and non-availability of Main condenser

Passive Poison Injection in moderator during overpressure transient

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Reliability Evaluation of Natural Circulation Using APSRA

Step IPassive System – For example,

Natural Circulation in the MHT System of the AHWR

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Reliability Evaluation of Natural Circulation Using APSRA (Contd.)

Step IIIdentification of its operational mechanisms:

Natural circulation operates by difference in density in hot and cold legs (known as buoyancy force) balanced by flow resistances.

Identification of its failure:

Natural circulation failure in AHWR can be identified by

- rise in clad surface temperature above a critical value (400 oC) or/and

- occurrence of CHF by flow induced instability

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Step IIIParameters affecting the

operationNatural Circulation

Performance depends on

- operating pressure- fission heat- level in the steam drum- feed water temperature/ core inlet

subcooling - presence of non-condensable gases- flow resistances in the system

2 4 6 8 10

1200

1400

1600

1800

2000

2200

2400

2600

Flow

rate

- kg

/sec

Pressure - Mpa

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Step IVKey parameters causing the failure

- fission heat generation rate high- level in steam drum low- pressure in the system too low - feed water temperature too low ortoo high

- concentration of non-condensables gases high

Failure can happen if these parameters exceed their limits to cause the failure as discussed in Step II

200 220 240 260 280 300-2

0

2

4

6

8

10

12Tsub=25 KPressure = 70 bar

Mas

s flo

w ra

te (k

g/s)

Time (s)

2.6 MW (100% FP) 3.536 MW (136% FP) 3.614 MW (139% FP)

Flow oscillation induced CHF at high power

200 220 240 260 280 300-1

0

1

2

3

4

5

6

CH

FRTime (s)

100% FP (2.6 MW) 136% FP (3.536 MW) 139% FP (3.614 MW)

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ISOLATIONCONDENSER

STEAM DRUM N2

CYLINDER

ADVANCEDACCUMULATOR

TAIL PIPE

GRAVITY DRIVENWATER POOL

RUPTURE DISC

HEADER

FEEDER

ECCS HEADER

FUEL CHANNEL

SIMULATOR

INTEGRAL TEST LOOP


How to determine the limits of the parameters

- Through use of best estimate codessupplemented by experiments in orderto reduce the uncertainties in the bestestimate codes.

- BARC has a full scaled facility of theAHWR, known as the Integral Test Loop(ITL). This facility operates at the samepressure and temperature conditions ofthe AHWR.

- BARC also has number of experimentalfacilities for study of boiling two-phasenatural circulation.

- Experiments will be conducted in thesefacilities in order to confirm the limits ofthe parameters at which failure ofnatural circulation occurs.

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Step – V : Generation of failure surface

Failure Surface generated by taking into account 3 parameters

010

2030

405050

5560

6570

75100110120130140150160170180190

Subcooling (K

)

% F

ull p

ower

P ressure (bar)

Success

Failure

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Programme for Validation of Failure Surface with Test Data

Range of Key Parameters to cause failure to be determined by Best Estimate Codes

Experimental Facilities

ITL HPNCL

PCL

Set the Key Parameters To the Desired Value as the input for the experiments

Monitor the Failure Variables

Compare code prediction with test data

Determine the Uncertainty and modify the failure data points

Failure data point as input to Mathematical Model to generate failure surface

Failure Surface of Passive System

Input to step V

Benchmarking 2040

60

80

0 5 10 1520

25

0

300

600

900

1200Experimental Data

Unstable data Stable data

Pow

er (k

W)

Pres

sure

(bar

)

Stable

Unstable

Subcooling (K)

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Step VI : Root Diagnosis

After establishing the domain of failure surface, Next task is to Identify the causes for the deviation of key parameters

This must be done carefully through experts’ judgments.

The key parameters’ deviations are either caused by failure of some active components such as

- valves, pumps, instruments, control systems, etc.

Or, due to failure of some passive components such as - rupture disc, check valves, passive valves, etc.

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Step VII Once the causes of failure of key parameters (either due to

active components or passive devices) are known in Step V,the failure probability of the components can be evaluated inthe conventional way.

To evaluate the failure probability of certain components such as aglobe valve at partial open positions, a new methodology is beingdeveloped.

An example of event tree/fault tree for high feed water temperature or low inlet subcooling

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FEEDTEMPw=1.150e-1

HIGH FEEDWATER

TEMPERATURE

LOWFEEDFLOWw=1.150e-1

LOW FEEDWAT ERFLOW

FEED VALVES MALFUNCTI ONI NG

w=2.064e-10

VALVESFEED&STEAM

SIDE

CHECK VALVEw=1.240e-2

Check Valves inthe feed water line

Malfuction

SD-LEVEL-CNTRL- FAIL1

w=2.018e-7

2

Steam DrumLevel controllermalfuctioning

LEVELCNTRL VAL

Malfuctioningof level control

Valves

w=4.31102e-005*

CEP-MKV

Condensateextration pump

malfuction

w=0.0530312*

FWP-MKV

Feed waterPump

malfuction

w=0.0530312*

VAL-ST EAMw=2.694e-2

Inadvertantopening ofVALVES

VAL-FEEDw=2.656e-7

IsolationvalveS feedwater side

SD-LVL-CNTRL1

Steam DrumLevel controller-1

malfuctioning

r=0.003504

SD-LVL-CNTRL2

Steam DrumLevel controller -2

malfuctioning

r=0.003504

SD-LVL-CNTRL3

Steam DrumLevel controller-3

malfuctioning

r=0.003504

LVL-CHV1

before levelcontrol valves -Check Valve 1

stuck close

r=0.0062

LVL-CHV2

After level controlvalves - CheckValve2 stuck

close

r=0.0062

CV-STEAM

Inadvertant openingof C/V in the steam

side of temp controlheater

r=0.0245

MANUAL VALVE-STEAM

Parallel MANUALvalve fails toremain closed

r=0.00245

ISOVAL1-FEED

Isolation valve-1 inthe temp control

heater feed waters ide fails to remain

closed

r=0.002628

ISOVAL2-FEED

Isolation valve-2 inthe temp control

heater feed waterside fails to remain

closed

r=0.002628

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Step VIII

Evaluation of Reliability Of NC System

160.0

150.0

170.0

140.0

130.0

180.0

180.0

50 55 60 65 70 755

10

15

20

25

30

35

40

45

50

120.0

Failure frequency

-5E-10

0

5E-10

1E-9

1.5E-9

2E-9

2.5E-9

3E-9

3.5E-9

Pressure (bar)

Subc

oolin

g (K

)Constant % full power lines

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APSRA applications: other examples

Isolation Condenser

0 20 40 60 80 100

0

1

2

3

4

5

6

7

40

5060708 090

Fa ilu re reg io n

S u ccess reg io n

% o

f Non

-con

dens

able

s

GD

WP

wat

er

tem

pera

ture

(o C)

% H e igh t E x pos ure o f IC Tu be s

Failure probability for IC to maintain Hot-SD ~ 8x1e-7/ yr

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RMPS vs. APSRA

There are certain points which are common in both the methodologies; for example,

• treatment of the functional failure as the failure of the system • identification of functional failure criteria • evaluation of uncertainties in code prediction • Consideration of uncertainties in prediction of functional failure

of system. However, there are differences; for example,

• treatment of deviation of key parameters causing the failure • generation of failure data/surface • consideration of test data/code-to-code differences for

calculation of uncertainties.

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Application of APSRA to DHR of GFR

RELAP5/MOD3.2 code will be used for failure surface generation, assuming code can predict the system behaviour accurately.

For application of APSRA methodology, it is essential to know

• Mission specific Failure criteria of DHR system, mission time• Identification and range of variation of physical parameters which

have significant influence on system behaviour• Flow sheet showing how these parameters are controlled by

mechanical components such as valves, control systems, etc.• Primary side of GFR has a few valves; it is essential to know the

valve characteristics, i.e. resistance vs. opening area.

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Application of APSRA to DHR of GFR

Some of the physical parameters which are anticipated to have significant influence on system behaviour

• DHR primary side initial pressure;• DHR water side initial temperature and pressure• DHR pool side temperature and level• DHR water side (is there possibility of presence of non-

condensables???)

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Application of APSRA to DHR of GFR – Sensitivity analysis may be performed to evaluate model and geometric uncertainties

Uncertainty in models Heat transfer coefficient Friction factor Gap conductance Material properties particularly for heat transfer surfaces

Uncertainty in geometry Tube diameter and length (water side) Pipe diameter and length (primary side)

• Partial blockage of some of tubes in water side

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BARC - International Atomic Energy AgencyBARC Safety criteria for advanced reactor systems ... BARC Experimental Facilities for Study of Boiling Two-phase ... using neutron radiography