Design of Passive Systems of Indian AHWR and CHTR by DEPLOYMENT OF SEVERAL PASSIVE SAFETY SYSTEMS...

BARC

BARC

INPRO Consultancy Meeting JUNE 16-17, 2008, Cadarache, France 1

PASSIVE SYSTEMS RELIABILITY ANALYSIS USING THE METHODOLOGY APSRA

A.K. Nayak, PhD

Reactor Engineering Division

Bhabha Atomic Research Centre

Trombay, Mumbai 400085, India

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India’s Innovative Reactor – The AHWR

• AHWR is a vertical pressure

tube type, boiling light water

cooled and heavy water

moderated reactor using

(233U-Th) O2 and (Pu-Th) O2

fuel.

MAJOR DESIGN OBJECTIVES

1. 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 FUEL

TRANSFER MACHINE

FUELLING

MACHINE

FUEL BUILDING

GRAVITY DRIVEN

WATER POOL (GDWP)

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General Arrangement of AHWR

Core cooling by natural circulation in Main Heat Transport System

Direct steam cycle, Moderator heat recovery

Decay heat Removal by Isolation Condensers

Passive ECCS injection by Accumulators & GDWP; Passive Containment Coolers

Moderator cooling, End Shield Cooling Calandria Vault Cooling Systems

GDWP Recirculation System

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AHWR Reactor Building

Double Containment, Small V1-Volume containing High enthalpy MHT piping

Large inventory of water at higher elevation in Gravity Driven Water Pool

MAIN HEAT TRANSPORT

(MHT) SYSTEM

TAIL PIPES

REACTOR CAVITY

101000 GROUND LEVEL

GRAVITY DRIVEN

WATER POOL (GDWP)

ISOLATION CONDENSER

PRIMARY

CONTAINMENT

SECONDARY

CONTAINMENT

PASSIVE CONCRETE

COOLING SYSTEM

V1 VOLUME

HIGH TEMPERATURE, 285°C

DOWNCOMERS

STEAM DRUM (TYP.)

VENT SHAFT

TAIL PIPE TOWER

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AHWR Reactor Block

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

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Passive 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 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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Use of moderator as heat sink

Water in calandria vault

Flooding of reactor cavity following LOCA


Back up heat sink during low probable event of ECCS failure

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AHWR PHWR

Light water coolant Heavy water coolant

Coolant boils in core No boiling of coolant Core flow maintained by Core flow caused by pump

natural circulation Vertical flow channel Horizontal flow channel

Passive decay heat removal Active decay heat removal

Core coolant transports heat Core coolant transfers heat to directly to condenser secondary coolant which rejects heat in condenser

Main Heat Transport System - AHWR vis-à-vis

PHWR

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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 through

passive systems.

- reliability of

passive systems

must be considered. RADIOLOGICAL CONSEQUENCES

-

-

FR

EQ

UE

NC

Y

(even

ts/y

ea

r)

unallowable

domain

-

Fig 3. Frequency vs. Consequence Safety Goal

Quantitative Probabilistic Safety Goal

allowable

domain

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 OUT

COOLING 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 Parameters Design Pressure : 114 kg/cm2

Design temperature : 315 oC

Maximum Power : 80 kW

Loop Diameter : 50 mm

Elevation : 3000 mm

Heated Section : 1000 mm

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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 bar

Temperature : 285 0 C

Neutron Flux : 106 to 108 n/cm2s

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

instability behaviour of

parallel channels in natural

circulation mode

• Effect of void reactivity

feed back on thermal

hydraulic stability

Geometric Details:

Number of channels : 4

Elevation : 3000 mm

Pipe diameter : 25 mm

Heater diameter : 12 mm

Length of heater : 1000 mm

Operating pressure : 15 bar

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ISOLATION

CONDENSE

R

STEAM

DRUM N2

CYLINDE

R

ADVANCED

ACCUMULATOR

TAIL PIPE

GRAVITY DRIVEN

WATER 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

rro

r

Power (kW)

Apsara

HPNCL

ITL Uncertainties have been

evaluated for

- steady state natural

circulation,

- stability of natural

circulation and limited data

for CHF

Example of error distribution for the test data of ITL,

HPNCL and Apsara natural circulation loops

Ab

solu

te F

req

uen

cy

% Error

Experimental

Loop

Number of

steady state

data points

Uncertainty

Apsara ½” 87

~ 17 % HPNCL 26

ITL 14

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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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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

5.5

Number of grids

in Riser

Ma

ss F

low

Ra

te (

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

Parameter

ParameterParameterError

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Examples of Uncertainties in RELAP5 code for

prediction of CHF induced by flow instability

Tube ID

(mm)

Pressure

(bar)

Expt. CHF

(kW/m2)

Predicted

CHF

%Error Uncertainty

13.5 209.68 212.70 1.44 LOW

5.1 196.12 196.56 0.20 LOW

7.0

2.35 118.82 102.68 13.60 MEDIUM

8.11 356.61 310.30 12.99 MEDIUM

6.25 335.00 366.72 9.47 LOW

9.1

4.6 335.00 169.25 49.47 HIGH

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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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Reliability Evaluation of Natural Circulation Using

APSRA

Step I

Passive System – For example,

Natural Circulation in the

MHT System of the AHWR

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APSRA (Contd.)

Step II

Identification 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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APSRA (Contd.)

Step III

Parameters affecting the

operation

Natural 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

Fig.6 Effect of pressure on primary system flow rate

Flo

w r

ate

- kg

/sec

Pressure - Mpa

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APSRA (Contd.)

Step IV

Key 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 or

too 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

12

Tsub

=25 K

Pressure = 70 bar

Ma

ss

flo

w r

ate

(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

FR

Time (s)

100% FP (2.6 MW)

136% FP (3.536 MW)

139% FP (3.614 MW)

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ISOLATION

CONDENS

ER

STEAM

DRUM N2

CYLINDE

R

ADVANCED

ACCUMULATOR

TAIL PIPE

GRAVITY DRIVEN

WATER POOL

RUPTURE

DISC

HEADER

FEEDER

ECCS

HEADER

FUEL

CHANNEL

SIMULATOR

INTEGRAL TEST LOOP


APSRA (Contd.)

How to determine the limits of the parameters

- Through use of best estimate codes

supplemented by experiments in order

to reduce the uncertainties in the best

estimate codes.

- BARC has a full scaled facility of the

AHWR, known as the Integral Test Loop

(ITL). This facility operates at the same

pressure and temperature conditions of

the AHWR.

- BARC also has number of experimental

facilities for study of boiling two-phase

natural circulation.

- Experiments will be conducted in these

facilities in order to confirm the limits of

the parameters at which failure of

natural circulation occurs.

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APSRA (Contd.)

Step – V :

Generation of failure surface

Failure Surface generated by

taking into account 3 parameters

010

20

30

40

505055

6065

7075

100

110

120

130

140

150

160

170

180

190

Subcooling (K

)

% F

ull

po

wer

Pressure (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 20

40

60

80

05

1015

2025

0

300

600

900

1200Experimental Data

Unstable data

Stable data

Pow

er

(kW

)

Pre

ssure

(bar)

Stable

Unstable

Subcooling (K)

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APSRA (Contd.)

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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APSRA (Contd.)

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 in

the conventional way.

To evaluate the failure probability of certain components such as a

globe valve at partial open positions, a new methodology is being

developed.

An example of event tree/fault tree for high feed water

temperature or low inlet subcooling

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APSRA (Contd.)

FEEDTEMPw=1.150e-1

HIGH FEEDWATER

TEMPERATURE

LOWFEEDFLOW

w=1.150e-1

LOW FEEDWATERFLOW

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-STEAMw=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 steamside of temp control

heater

r=0.0245

MANUAL VALVE-STEAM

Parallel MANUALvalve fails toremain closed

r=0.00245

ISOVAL1-FEED

Isolation valve-1 inthe temp control

heater feed waterside 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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APSRA (Contd.)

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)

Su

bco

olin

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

50

60

70

80

90

Failure region

Success region

% o

f N

on

-co

nd

en

sab

les

GD

WP

wate

r

tem

pera

ture

(oC

)

% Height Exposure of IC Tubes

Failure probability for IC to maintain

Hot-SD ~ 8x1e-7/ yr

0 20 40 60 80 100 120 140 160 180 2000

10

20

30

40

50

60

70

80

90

100

Failure due to insufficient

V1-V2 pressure differential to

raise water to spill into duct

Failure due to insufficient

inventory in the tank to

form liquid seal

Success region

Failu

re r

eg

ion

Failure region

Wate

r le

vel in

tan

k (

% o

f d

esig

n v

alu

e)

% Break size

Passive Containment Isolation

System (PCIS)

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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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Design of Passive Systems of Indian AHWR and CHTR by DEPLOYMENT OF SEVERAL PASSIVE SAFETY SYSTEMS...

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Transcript of Design of Passive Systems of Indian AHWR and CHTR by DEPLOYMENT OF SEVERAL PASSIVE SAFETY SYSTEMS...