Transcript Uncertainty and Sensitivity of Accident Consequence

An Approach to Evaluation of
Uncertainties in Level 2 PSAs
T. Ishigami, J. Ishikawa, K. Shintani,
M. Mayumi and K. Muramatsu
Japan Atomic Energy Research Institute
OECD/NEA/CSNI/WGRISK Workshop, Cologne,
March 29 - 31, 2004
Introduction
Background
 PSA application study at JAERI on safety goals,
emergency planning, basic technical study for legal
system for compensation of nuclear damage, and so on
 The first phase PSA at JAERI in 1990 did not address AM,
source terms for energetic events, and uncertainty
 Uncertainty is one of the most important issues in PSA
application
Purpose of This Study
 To develop an uncertainty analysis method for Level 2
PSA
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Type of Uncertainties

Parameter uncertainty

Model uncertainty

Completeness uncertainty
Parameter and model uncertainties are addressed in this
study
Study on Uncertainty Evaluation at JAERI

Development and improvement of computer codes

Assessment of uncertain parameters

Development of uncertainty analysis method for source
terms
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Framework of uncertainty analysis for Level 2 PSA
Analysis step
Uncertain parameters
・Component
failure rates etc.
・Existing PSA
results
・Analysis method
(DET, ROAAM)
SAPHIRE
Accident
progression
analysis
・CET branch
probabilities etc.
・Experiment
- Steam explosion
- Release of fission
products from
fuel
Uncertainty analysis
PREP/SPOP
CET
・Release rates of
fission products
from fuel etc.
Source term
analysis
THALES2
Computer codes
SAPHIRE: System analysis
CET: Containment ET analysis
THALES2: Sever accident analysis
PREP/SPOP:Uncertainty propagation analysis
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Frequency of
exceeding X
Resources
Core damage
frequency
analysis
95%
50%
5%
Source term, X
Conceptual figure of uncertainty
analysis results
JAERI
Computer Codes

SAPHIRE (USNRC)
- Analysis of core damage frequency with ET/FT model
- Capability of uncertainty analysis

CET Analysis Code (JAERI)
- Analysis of containment function failure probability
- Object-oriented programming

THALES2 (JAERI)
-

Integrated severe accident analysis code
Analysis of thermal hydraulics and fission product transport
PREP/SPOP (JRC Ispra)
- Analysis of parameter uncertainty propagation through a model
- Monte Carlo or Latin Hypercube sampling method
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Assessment of Uncertain Parameters
- Core Damage Frequency and Accident Progression Analyses Uncertain Parameters
Approach
Component failure rates
Use of the failure rates evaluated by
Central Research Institute of Electric
Power Industry from operation data of
49 Japanese plants for 16 years (19821997)
CET branch probabilities
for CV failure modes
- Overpressure
- Overtemperature
- Steam explosion
- Direct containment
heating
- Hydrogen burning
Survey of recent experimental and
analytical research results
Use of analytical methods such as DET
and ROAAM
- Probability of containment failure due
to energetic events
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Example of Assessment of Uncertain Parameter
- Probability of Containment Failure due to
Ex-Vessel Steam Explosion at PWR 
Possible phenomena
Steam explosion
at cavity
Loss of containment
integrity at penetration
Load energy brought
into containment
Piping
tenseness
“Load energy > Critical load energy ”

Cavity wall
failure
Movement of
reactor vessel
“Loss of containment integrity”
Preceding analysis for Japanese APWR
(Nuclear Safety Research Association)

Point estimate with DET method
- Survey of research results
- Structural analysis
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Present Analysis for 4-loop PWR

Approach

Use of the DET for APWR
- Similar physical processes at both plants
- Type of containment is PCCV at both plants

Reevaluation of physical quantities depending on plants
- Flow rate of molten core at large scale RV failure
- Critical load energy resulting in containment failure
→ These quantities were scaled according to reactor powers of
the two plants (APWR: 4,451MWt, PWR: 3,411MWt)

New Feature

Evaluation of uncertainty in containment failure
probability caused by uncertainties in
- Branch probabilities of “reactor vessel failure mode
(large/small)” and “Occurrence of triggering (Yes/No)”, and
- Critical load energy resulting in containment failure

Aleatory and epistemic uncertainties were addressed
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Decomposition Event Tree
RV
Failure
Failure
Mode
Small
Scale
Melt
Flow
Rate
Small
Melt
Internal
Energy
Low
Melt
Mass in
Premixture
Triggering
Energy
Conversion
Rate
No
Yes
Low
Medium
High
High
Large
Large
Scale
Load Probability
Energy
E
1
E
2
E
3
・
・
・
・
・
・
・
・
・
・
En
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・
・
・
・
・
・
・
・
・
・
Lower
Energy
Higher
Energy
JAERI
Aleatory and Epistemic Uncertainties
Aleatory uncertainty : Randomness or stochastic properties
Epistemic uncertainty : Lack of our knowledge,
Possible to reduce
Treatment in present analysis

Uncertainties in the branch probabilities : Epistemic
Uncertainty in the critical load energy (capacity) of the
containment: Aleatory and epistemic
Epistemic
PDF

Aleatory
Critical load energy
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1.0
5%
50%
1.E+00
95%
0.8
1.E-01
0.6
Probability
Cumulative probability of
containment failure
Probability Distribution of Load Energy and
Containment Failure Probability
Aleatory
0.4
Epistemic
1.E-02
1.E-03
1.E-04
1.E-05
0.2
1.E-06
0.0
0
200
400
600
1.E-07
800
0
Load energy (MJ)
200
400
600
800
Load energy
energy (MJ)
Load
(MJ)
Scenarios with higher load energy caused from larger
size of RV failure contribute to containment failure
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Cumulative probability
Uncertainty Analysis Result of Containment
Failure Probability (conditional probability)
1
0.9
Aleatory
0.8
0.7
Aleatory+Epistemic
0.6
(Solid line)
0.5
0.4
0.3
Epistemic
0.2
(Dotted line)
0.1
0
1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00
Containment failure probability
• Uncertainty range : 0 – 0.006 (95th)
• Epistemic uncertainty is dominant
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Uncertainty Analysis Method for Source Terms
Subject
Approach
 A large number of
accident sequences
 Classification of sequences
 Uncertainty propagation
 Direct use of THALES2, instead of
parametric model (XSOR in NUREG-1150),
with Monte Carlo simulation
 Survey of recent experimental and
analytical research results
 Comparison of the model results with
experimental data or different model results
 Parameter uncertainty
 Model uncertainty
Repeated calculation
・・
X1
X2
・
Input Parameters
Code
(THALES2)
Y
Output
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Classification of sequences for uncertainty
analysis (BWR Mark-II)
Sequence group
PRV Pressure
Sequences subgroup
Loss of containment heat removal
function with high pressure
coolant injection available
High ～ Medium
Transient or SB-LOCA
Medium ～ Low
MB- ～ LB-LOCA
Low
Transient with reactor depressurized
by failure of SRV reclose
Loss of containment heat removal
function with low pressure coolant
injection available
Low
Transient or SB- ～ LB-LOCA
Loss of coolant injection
High ～ Medium
Transient or SB-LOCA
Medium ～ Low
MB- ～ LB-LOCA
Low
Transient or SB-LOCA
Low
MB- ～ LB-LOCA
High ～ Medium
Transient or SB-LOCA
Low
Transient with reactor depressurized
by failure of SRV reclose
High ～ Medium
Transient or SB-LOCA
Low
MB- ～ LB-LOCA
Station blackout
Anticipated transient without
scram (ATWS)
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Uncertain Parameters in THALES2 and
Parametric Model
Uncertain parameters is denoted by ＊
THALES2
Input ・・
Heat transfer
coefficient
Model
ThermalHydraulic
behavior
Data
Calculated
Parametric
Model
-Pressure
-Temperature
＊
・・・
＊
＊
Deposition
Release rate
coefficient ・・・ rate
Release from
fuel
FP behavior
in RV
Release
fraction from
fuel
Release
fraction from
RV
Release
fraction from
fuel
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＊
・・・
・・・
Release
＊
fraction
from
×
・・・
RV
-Failure pressure
＊
-Size of rupture
Environmental
release
Release
fraction to the
environment
Release
＝ fraction to the
environment
JAERI
Comparison of the two Methods
Direct Use of Code
Characteristics of
uncertain
parameters
Accident
sequences to be
analyzed
Calculation time
Parametric Model
- Rather fundamental
(Some are related to
experimental data)
- Not fundamental (To
be obtained from a
model)
- Less dependent on
time or sequence
- Dependent on time
and sequence
- Individual representative
sequence in a set of
sequences classified by
state of safety systems
- a set of sequences
classified by physical
state (Zr-oxidation
level, RCS pressure)
- Possible to compare the
results with different
model results
- Difficult to assess the
results
- Long
- Short
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Approach to Assessment of Uncertain
Parameters
Survey preceding PSAs (NUREG-1150) and comparative
study of THALES2 and MELCOR to determine uncertain
parameters
 Select parameters in THALES2 relating to the above
uncertain parameters
- Representative parameters are selected to reduce the
number of uncertain parameters
e.g. One correction factor for deposition rate in RCS for all
the deposition mechanisms
 Determine the uncertainties by surveying recent
experimental and analytical research results as well as
preceding PSA study
- Experiments on FCI (FARO, COTELS, …)
- Experiment on FP release from fuel (VEGA,…) etc.

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An example of uncertain items and associated
parameters in THALES2 (BWR Mark-II)
Uncertain items
Release of FPs from Fuel (in-vessel)
Coolability of molten core (in-vessel)
Deposition of FPs (in-vessel)
Deposition of FPs (ex-vessel)
Release of FPs from molten core (ex-vessel)
Coolability of molten core (ex-vessel)
Integrity of containment
Pool scrubbing
LOCA
Associated parameters
- Release rate of FPs
- Heat transfer coefficient between molten core and
coolant/or lower head wall
- Fraction of fragmented molten core in FCI
- Average particle size of molten core droplets
- Deposition rate of FPs to the wall
- Deposition rate of FPs to the floor
- Deposition rate of FPs to the wall
- Deposition rate of FPs to the floor
- Release rate of FPs
- Heat transfer coefficient between molten core and
coolant
- Failure pressure by overpressure
- Size of rapture
- Size of bubble
- Rising velocity of bubble
- Break size in LOCA
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Summary

Study on developing uncertainty analysis method for Level
2 PSA at JAERI includes
-

Development and improvement of computer codes
Assessment of uncertain parameters
Development of uncertainty analysis method for source terms
To quantify uncertain parameters
- Recent experimental and analytical research results are surveyed
- Analytical method such as DET is used to evaluate uncertainty in
containment failure probability due to steam explosion, where
aleatory and epistemic uncertainties are considered

Uncertainty analysis method for source terms is
- Direct use of THALES2 with Monte Carlo simulation, where
- Uncertain parameters in THLES2 are assessed by surveying recent
research results
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