1
October 17, 2008
"PSA AS A TOOL FOR EVALUATION OF AGEING EFFECTS ON THE
SAFETY OF NPPs"
Andrei Rodionov
October 17, 2008
1. INTRODUCTION :
PSA Application in the Long-Term Operation of NPPs
Rationale of the Ageing PSA Network
2. SELECTION OF SYSTEMS, STRUCTURES AND COMPONENTS SENSITIVE TO AGEING
Proposed Approach
Related Uncertainties and Limitations
3. ACTIVE COMPONENTS RELIABILITY ASSESSMENT
Task Specification: Incorporation of Ageing Effects into the PSA Model
Time-Dependent Reliability Models
Data issues
4. IMPACT OF AGEING EFFECTS ON THE SYSTEM AND PLANT LEVELS
Approach Proposed for Demonstration
System Level Effect
Plant Level Effect
5. CONCLUSIONS. (+Summary of activities and future planning)
2
INTRODUCTION
October 17, 2008
Motivations :
• NPPs are getting older
• Probabilistic safety goals have to be maintained for the LTO
• Application of Risk Informed Regulation
Questions :
• Could PSA be applied to ageing assessments?
• How realistically do PSA models reflect important ageing issues?
• Are any modifications or revisions of PSA assumptions needed to apply
a PSA approach to risk-informed decision-making with regard to ageing
evaluation?
• What data are available and how representative are they with regard to
important ageing issues?
3
Background and motivations
4
October 17, 2008
Actual situation worldwide:
•
•
213 (49%) are between 20 and 30 years old,
115 (26%) units are between 30 and 40 years
old,
In total : about 3/4 of the 438 reactors
Long-term operation : on July 2006, 1/2 of the
licensed NPPs in US had received or were
under review for license renewal
Situation in Europe (EU):
• 88 (60%) reactors from 146 are in the age
of 20-30 years old
• 24 (16%) between 30 and 40 years old
Europe - # of reactors per age. March 1, 2008.
18
16
14
12
10
8
6
4
2
0
1 2 3
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 38 40
Age of reactors
Background and motivations
5
October 17, 2008
VVER reactors in EU MS (19 reactors) :
 about the same ages distribution.
* RF -15 and UA – 15 reactors in operation
# of VVER in Europe (total 19)
12
10
8
6
 EU MS - Prevision for 2018
 19 (14%) reactors from 139 need to be
licensed for life extension (LTO) or
shutdown,
 94 (67%) have to be under evaluation for
life extension or definitive shutdown.
Series1
4
2
0
0-5
5-10
10-15
15-20
20-25
25-30 30-35
35-40
Age of reactor
Europe - Prevision for 2018
new reactors
presently in operation
LTO desision ?
16
8
6
4
2
Age of reactors
49
46
43
40
37
34
31
28
25
22
19
16
13
10
0
7
commissioned.
10
4
NPPs operation only up to the end of design
lifetime (40 years) and 4 new reactors will be
12
1
**supposing that Sweden and Germany will continuer
14
background and motivations
6
October 17, 2008
 Probabilistic Safety Goal (INSAG-12) :
“The target for existing nuclear power plants consistent with the technical safety
objective is a frequency of occurrence of severe core damage that is below about
10–4 events per plant operating year. Severe accident management and mitigation
measures could reduce by a factor of at least ten the probability of large off-site
releases requiring short term off-site response.”
 Risk Informed Regulation
Traditional
analysis
1. Define
change
2. Perform
engineering
analysis
PSA
3. Define implementation /
monitoring program
4. Submit a
proposal
Background and motivations
7
October 17, 2008
RISK
BARRIER
TARGET
Design
Operating loads
+
Environmental stressors
SSC
degradation
due to the
ageing
Qualification
Test/Monitoring
SSC
Reliability/availability
Risk to overal plant
safety
Maintenance
Operating Feedback
Ageing effect on unit/SSC reliability and safety
Main activities related to the ageing management :
• Ageing management
• Life time extension
• Surveillance and Maintenance optimisation
Background and motivations
October 17, 2008
Current situation
 Standard PSA tools do not adequately address important ageing issues as :
– assumption on component reliability model l=const,
– reliability data may not adequately represent the current status of the plants,
– existing PSAs overlook some components (e.g. cables, structures, etc.) as
having a very low failure probability, but they may have increasing weight due to
ageing effects
 Limited experience with applying of PSA approach to evaluate ageing effects :
– no commonly accepted methods,
– all the studies are performed by relatively isolated organisations,
– and publications on the subject are scarce
8
Needs for Advances Time-Dependent Reliability Analysis
9
October 17, 2008
 Possible impact to PSA results
 Passive components
 IE frequencies and definitions (high Risk Importance)
 Safety Systems unavailability due to the failures of non-redundant parts
 Active components




Safety Systems unavailability due to the ageing failures,
Safety Systems unavailability due to the unplanned maintenance,
IE frequencies (when modeled with a FT),
Intersystem CCF
 Practical implications
Risk Profile and RI factors used as decision criteria in many
applications could be changed in time. These changes have to be
considered in decision making process.
EC JRC Network on Aging PSA : goals, tasks, working
approach
October 17, 2008
10
JRC Ageing PSA Network Objectives :
Using common resources of Network participants to identify, develop and
demonstrate methods and approaches which could help PSA developers and users
– to promote the use of PSA for ageing management and risk-informed
applications of Nuclear Power Plants in LTO,
– to incorporate the effects of equipment ageing into current PSA models to
perform engineering analysis,
– in case where age-dependent PSA couldn’t be applied (absence or nonadequacy of ageing probabilistic model, lack of data, etc.), to specify and
prioritize reliability monitoring actions/approach to assure that potential
decreasing of reliability of SSC would be identified and corrected in time
EC JRC Network on Aging PSA : goals, tasks,
working approach
October 17, 2008
Main tasks : (Terms of references EUR 22645 EN )
• Task 1. Organization and coordination of network activities
• Task 2. Analysis of main PSA tasks with regards to Ageing PSA (in
progress)
• Task 3. Selection of the SSC to be considered in Ageing PSA (in
progress)
• Task 4. Reliability and data analysis for active components (in
progress)
• Task 5. Reliability and data analysis for active components II.
Common Cause Failures (started)
• Task 6. Reliability and data analysis for passive components (started)
• Task 7. Incorporation of age-depended reliability parameters and data
into PSA model (in progress)
• Task 8. Ageing PSA development and applications (started)
11
EC JRC Network on Aging PSA : goals, tasks,
working approach
12
October 17, 2008
Participants :
• 15 organizations from EC MS, Swiss, RF, Armenia and Korea (network agreement). In
addition, active participation from CNSC/Canada, D.Kelly and C.Atwod/USA
Operating Agent : JRC
Network Coordinator :
A.Rodionov (Task 1)
Steering Committee
Chairmen : M.Patrik
Network Operation :
TG for Task 2
Task leader :
• Working groups
M.Patrik
• Case studies and
(NRI/CZ)
benchmark exercises,
Participants :
• Steering Committee,
- JRC
- INR/RO
• Expert meetings,
- JSI/SI ?
- NRSC/AM
• Workshops
- VEIKI/HU
• Web site : http://safelife.jrc.nl/APSA
TG for Task 3
Task leader :
M.Nitoi (INR/RO)
Participants :
- JRC
- CNE/RO
- VEIKI/HU
- NRI/CZ
- NRSC/AM
- IRSN*
- CNSC*
TG for Task 4
Task leader :
A.Rodionov(JRC)
Participants :
- INPE/RF
- CNE/RO
- LEI/LT
- JSI/SI ?
- IRSN*
- CNSC*
- VEIKI*
TG for Task 7
Task leader :
D.Serbanescu
(JRC)
Participants :
- IRSN
- CNE/RO
- LEI/LT
- JSI/SI
- ENEA/IT
- TUS/BG
October 17, 2008
1. INTRODUCTION :
PSA Application in the Long-Term Operation of NPPs
Rationale of the Ageing PSA Network
2. SELECTION OF SYSTEMS, STRUCTURES AND COMPONENTS SENSITIVE TO AGEING
Proposed Approach
Related Uncertainties and Limitations
3. ACTIVE COMPONENTS RELIABILITY ASSESSMENT
Task Specification: Incorporation of Ageing Effects into the PSA Model
Time-Dependent Reliability Models
Data issues
4. IMPACT OF AGEING EFFECTS ON THE SYSTEM AND PLANT LEVELS
Approach Proposed for Demonstration
System Level Effect
Plant Level Effect
5. CONCLUSIONS
13
SELECTION OF SSCs SENSITIVE TO AGEING
October 17, 2008
14
 Current Ageing Management practice :
• often limited to passive components
• if not based on expert judgments
 Proposed Approach includes three elements :
• prioritize the SSCs which are modeled in PSA using RIF,
• perform trend analysis of available reliability data,
• use qualitative assessment or Ageing Failure Modes and Effect
Analysis (AFMEA) for a limited number of components
All three steps are consecutive and complementary.
Selection process
Component modeled
in PSA
Risk Importance
Reliability data
Reliability data
Reliability data
Trend analysis
Select
Rank 3
No
Trend analysis
AFMEA
Select
Rank 5
Select
Rank 6
No
No
AFMEA
Select
Rank 2
AFMEA
Select
Rank 4
Select
Rank 7
No
Trend analysis
Select
Rank 1
AFMEA
No
No
SELECTION OF SSCs SENSITIVE TO AGEING
16
October 17, 2008
Decision matrix for selection of SSCs susceptible for ageing
Risk Importance
Trend in failure
rate
AFMEA
conclusion
1
High
Identified
-
2
High
-
Sensitive
3
High
Absent
Sensitive
4
Low
Identified
-
5
Low
-
Sensitive
6
-
Identified
-
7
-
-
Sensitive
Rank
SELECTION OF SSCs SENSITIVE TO AGEING
October 17, 2008
Related Uncertainties and Limitations
Prioritization by risk importance limitations:
• (+) permits significantly reduce the list of SSCs,
• (-) it deals only with SSCs modeled in PSA,
• (-) importance of particular SSCs could be changed with time due to the ageing,
Trend analysis
• (+) direct indication of ageing,
• (+) provide the basis for modelling,
• (-) lack of data,
Qualitative assessment
• (+) could cover SSCs initially neglected in PSA and those for which there is not
enough failure data for trend analysis,
• (-) very time-consuming and resource-intensive,
• (-) qualitative results
17
October 17, 2008
1. INTRODUCTION :
PSA Application in the Long-Term Operation of NPPs
Rationale of the Ageing PSA Network
2. SELECTION OF SYSTEMS, STRUCTURES AND COMPONENTS SENSITIVE TO AGEING
Proposed Approach
Related Uncertainties and Limitations
3. ACTIVE COMPONENTS RELIABILITY ASSESSMENT
Task Specification: Incorporation of Ageing Effects into the PSA Model
Time-Dependent Reliability Models
Data issues
4. IMPACT OF AGEING EFFECTS ON THE SYSTEM AND PLANT LEVELS
Approach Proposed for Demonstration
System Level Effect
Plant Level Effect
5. CONCLUSIONS
18
ACTIVE COMPONENTS RELIABILITY ASSESSMENT
19
October 17, 2008
Integration of SSC ageing model to PSA
• time-dependent reliability parameters
• PSA model
• CDF at different age-points
l(t)
lav,
i
(10, 20, 30 and 40 years of operation)
[ti, ti+1]
Time-dependent reliability model :
• collect and process reliability data,
• fit one of the parametrical models and calculate the model parameters,
• if necessary, improve the results by Bayesian approach and generic data,
• evaluate the unavailability factors for given age values, taking into account
model parameters, periodic tests and maintenance data
t
Time-Dependent Reliability Models
20
October 17, 2008
Choose the model
–
–
–
–
Constant failure intensity (rate) :  q ;t = const
Linear :  q ;t   q1  q 2t
Log-linear or exponential : ln  q ;t   q1  q2t
Power-low (Weibull) :  q ;t   q1tq
2
q2 > 0 means a positive trend in time
The procedure for choosing the model and parameters includes the following
steps:
–
–
–
–
verification of model validity,
parameter estimation,
characterization of uncertainties of estimated parameters and the whole model,
assessment of possible extrapolation and uncertainties of extrapolation
Time-Dependent Reliability Models
October 17, 2008
The following issues require
specific attention when
analyzing and interpreting the
results:
– relative increase in failure
intensity (rate) in time with
regard to constant failure rate,
– impact of burn-in failures,
– uncertainties of extrapolation
21
Time-Dependent Reliability Models
22
October 17, 2008
Component
group
Best
fitted
model
Parameters
:
q
=c
q=c q=c q=c
q
p-value
0.005
#32.2
const
0.005
1
1
1
0.005
1.11
1.56
1.91
0.067
0.58
1.75
5.26
0.075
0.26
1.56
9.45
0.0011
0.72
0.46
0.35
0.00064
0.74
1.66
3.74
0.54
0.0018
#32.2 /early
failures
Weibull
0.49
excluded
0.65
log-
0.013
linear
#39.1
0.11
0.07
Log-
#39.1/early
0.0032
linear
failures
0.18
excluded
0.14
#48.3
Weibull
0.0035
-0.65
0.54
#48.3/early
Log-
failures
liner
excluded
0.00021
0.081
0.997
Data issues
October 17, 2008
Possible sources of data :
• reliability data for NPPs (generic and/or specific),
• reliability data for similar components from other industries,
• accelerated ageing reliability tests
Reliability data from fossil plants 20-40 years old (NERC and VGB data)
Main conclusions
In general (good news), with age plants “learn” : availability and performance increase
or maintained constant with the age of the plant
Particular cases of ageing :
• increasing failure rates are identified for several types of components as pumps,
funs, valves, switchers, boilers, heaters, etc. ( ageing parameters for linear aging
model are comparable with TRIGALEX data );
• “minimal repair” maintenance strategy could lead to increase in failure rate;
• even with decreasing or constant failure frequency, reliability of component could
degrade with age because of increasing of repair frequency and its duration
23
Activities and results : Reliability and data analysis
for active components (Task 4)
October 17, 2008
24
Data issues
25
October 17, 2008
Reliability data for NPPs:
(questionnaire on data availability and
accessibility - conclusions EUR23084EN)
PSA reliability data
- well structured and of high quality,
- easily accessible (DB or electronic
docs),
- not sufficient for ageing
assessments
l=const => n + St)
Additional data has to be extracted
and processed from raw data
PSA Reliability DB
IE frequencies
Raw data
sources
Component
parameters
reliability
Operating (defect)
and maintenance
logs
Processed component
failure,
performance
and maintenance data
Abnormal
Operational Events
(LER)
Reporting
System
Processed
Operational
data
Operating
maintenance
procedures
Generic
data
(Reliability parameters
and IE frequencies)
Other reliability DBs (vendor DB,
NDE of piping systems DB, I&C
elements DB, etc.)
Event
and
Design,
commissioning
and manufacturing
information
Data issues
26
October 17, 2008
Nomenclature of PSA Component Reliability Data
Processed data (2b)
Reliability parameters (2a)
1. Component group
2. Failure modes
3. Parameters :
•Failure rate,
•Failure prob. per demand,
•Mean time to repair,
•Unavailability due to
the maintenance.
4. Uncertainty
Data for parameters estimation
1. Component group
2. Component description / limits
3. Operating mode
4. Component function
5. Failure modes
6. Failure criteria
7. Sample (# and list of components)
8. Observation period
9. Stressors (av. # of hrs or d per year)
10. Cumulated stressors
11. # of failures per failure mode
12. Estimation method / assumptions
Data for cumulated operation
time
13. Component ID (sub-group)
14. # of compon. in sub-group
15. # of hrs or demands / year
16. Observation period
17. Total cumulated stressors
Failure data
18. Unit / component ID
19. Failure date
20. Reactor state
21. Failure mode
22. Criticality factor
23. Repair time
24. Failure cause / description
Data issues
27
October 17, 2008
Age-dependent reliability models :
1) simple models or trend assessment;
2) models which include test and maintenance evaluations;
3) comprehensive models
Categories of additional data needed:
Availability and accessibility of data for different
types of reliability models
Type 1 models
100%
90%
• component commissioning date,
80%
• failure/censoring times,
70%
60%
• component replacement date.
50%
Type 2 models - data listed for Type 1, plus:
40%
30%
• tests and maintenance strategy
20%
– type and periodicity,
10%
• degree of component renewal (CM and PM)
0%
In fact these data needed for T1 models
to make the assumptions about renewal process
Type 3 - data listed for Type 1 and Type 2, plus:
• component lifetime,
• cumulative number of hours in operation, number of demands,
• average and extreme levels of operating
and environmental stressors
Type 1
Type 2
K1 - availability
K2 - accessibility
Type 3
Data issues
October 17, 2008
Main conclusions :
• Processed data about failures and component performance could be certainly used
for age-dependent reliability analysis, but is not enough for this purpose
• PSA reliability data collection process does not include any requirement to perform
a statistical validation of assumptions about constant failure rate or trend analysis
• Improving reliability data collection could greatly help with PSA and age-dependent
reliability analysis applications in risk-informed decision making process
28
Needs for Advances Time-Dependent Reliability Analysis
October 17, 2008
29
 Practical implications :
• reliability analysis of ageing trend has to be a part of the process.
 Experience of application
• analysis of ageing trends (large populations) :
 (?) data collection covers only risk important components => no data available
for all components potentially susceptible to ageing; also for many components
statistical data are not enough,
 Typical results of analysis :
• ~ 30% of analysis cases : not enough failure statistic (with sufficient
demands/operating times) = very reliable, no ageing
• ~ 20-25% of analysis cases : constant failure rate = no ageing,
• ~ 5-15% of analysis cases : decreasing failure rate – after burn-in period and after
modifications
– What have to be considered as parameters?
• ~ 20-30% of analysis cases : increasing failure rates – detailed engineering
investigation is required before conclusion about ageing
– ??? issues
October 17, 2008
1. INTRODUCTION :
PSA Application in the Long-Term Operation of NPPs
Rationale of the Ageing PSA Network
2. SELECTION OF SYSTEMS, STRUCTURES AND COMPONENTS SENSITIVE TO AGEING
Proposed Approach
Related Uncertainties and Limitations
3. ACTIVE COMPONENTS RELIABILITY ASSESSMENT
Task Specification: Incorporation of Ageing Effects into the PSA Model
Time-Dependent Reliability Models
Data issues
4. IMPACT OF AGEING EFFECTS ON THE SYSTEM AND PLANT LEVELS
Approach Proposed for Demonstration
System Level Effect
Plant Level Effect
5. CONCLUSIONS
30
IMPACT ON THE SYSTEM AND PLANT LEVELS
October 17, 2008
• To calculate the impact of ageing on the risk profile as a function of unit age, it was
proposed to use CDF as the average value at one-year intervals calculated for
different age points, for example for 10, 20, 30 and 40 years in operation
• A three-loop PWR PSA model for a Large LOCA initiating event was considered for
this purpose. The model consists of 4 Event Trees developed for full power operation
and hot shutdown reactor states
• The set of “virtual” reliability data was prepared on the basis of the results of case
studies, available generic data sources and expert opinions. The data includes timedependent reliability models for certain mechanical, electrical and I&C components of
Low Pressure Safety Injection (LPSI) and Containment Spray (CSS) Systems
• “As bad as old” preventive maintenance was considered in all cases
• Quantification has been calculated for a reference value (no ageing effects
considered) and age points of 10, 20, 30 and 40 years
31
32
October 17, 2008
Examples of component reliability data
Relative increasing of failure probability
Relative increasing in failure rate
10000.00
6.00
5.00
1000.00
4.00
RWST level sensors
3.00
CSS pump's motors
(log linear)
100.00
CSS pumps
2.00
pump's motors
(Weibull)
10.00
1.00
1.00
0.00
10
10
20
30
Age
40
20
30
0.10
Age
40
System Level Effect
33
October 17, 2008
Results of calculations for CSS:
• Unavailability increases with time by > than
one order of magnitude with regard to the
reference value (see Fig. 3)
• Up to 30, the main contributor to
unavailability is the failure of level sensors
in the RWST
But at the age of 40 the dominant impact
on system unavailability is failure of the
CSS pump motors
CSS unavailability
9.00E-03
8.00E-03
7.00E-03
6.00E-03
5.00E-03
4.00E-03
3.00E-03
2.00E-03
1.00E-03
0.00E+00
Ref. value
Q(t)
10
20
30
40
Age
Fractional contribution to CSS unavailability
%
60
HF
50
MOVs on
sump line
LS
40
• “No ageing” contributors : HF - human error
(20% fractional contribution to the
reference value) and CSS pumps fail to
start (2% contribution to the reference
value)
30
Pump FS
20
Pump FR
10
Pump Motor
0
10
20
30
Age
40
Plant Level Effect
34
October 17, 2008
Impact of SSC ageing on CDF
LLOCA CDF
7.E-07
6.19E-07
6.E-07
5.E-07
CDF
• CDF increases from 6.58E-8 at 10 years to
6.19E-7 at 40 years. In comparison with
the reference value the increase is by a
factor of 8.6 by the end of the designed
lifetime
4.E-07
CDF in time
3.E-07
2.E-07
1.E-07
CDF ref.
1.53E-07
6.58E-08
9.48E-08
7.18E-08
0.E+00
10
• Once the most sensitive components (LPSI
and CSS pump motors and level sensors)
are in the MCSs of dominant sequences,
the relative contribution of the sequences
to the total risk of Large LOCA remains
approximately the same with age
• The same picture can be seen for
contributions to the risk associated with the
different reactor states and location of the
pipe break
20
30
40
Age
Fussel-Vesely Impotance
1.80E-01
1.60E-01
1.40E-01
1.20E-01
1.00E-01
8.00E-02
6.00E-02
4.00E-02
2.00E-02
0.00E+00
LPSI pump Fail to
Run
LPSI valves Fail to
Open
HE on RWST
sensors
CSS pump Fail to
Run
RWST level sensors
10
20
30
Age
40
CSS pump's motor
Fail to Start
Plant Level Effect
35
October 17, 2008
• Sensitivity analysis of the reliability model chosen for the pump motors
• As a base case, the log-linear model was considered. The Weibull
model was applied as alternative for sensitivity analysis
• The generic conclusion from this analysis is the need to examine the
accuracy of several model alternatives before applying one to PSA
Relative increasing of failure probability
LLOCA CDF
10000.00
7.E-07
6.19E-07
6.E-07
1000.00
100.00
pump's motors
(Weibull)
10.00
CDF
5.E-07
CSS pump's motors
(log linear)
4.E-07
3.E-07
1.92E-07
2.E-07
1.E-07
1.00
10
20
30
40
7.18E-08
0.E+00
10
0.10
Age
20
30
Age
40
CDF in time (sensitivity)
CDF ref.
CDF in time (base case)
October 17, 2008
1. INTRODUCTION :
PSA Application in the Long-Term Operation of NPPs
Rationale of the Ageing PSA Network
2. SELECTION OF SYSTEMS, STRUCTURES AND COMPONENTS SENSITIVE TO AGEING
Proposed Approach
Related Uncertainties and Limitations
3. ACTIVE COMPONENTS RELIABILITY ASSESSMENT
Task Specification: Incorporation of Ageing Effects into the PSA Model
Time-Dependent Reliability Models
Data issues
4. IMPACT OF AGEING EFFECTS ON THE SYSTEM AND PLANT LEVELS
Approach Proposed for Demonstration
System Level Effect
Plant Level Effect
5. CONCLUSIONS
36
Conclusions
October 17, 2008
37
 Ageing effects can alter the conclusions of reference PSA studies. In particular, they
can impact on:
• system unavailability and CDF,
• dominant accident sequences and contributors to CDF,
• component risk importance measures.
 Considering ageing effects in PSA and reliability analysis could help in the selection
and prioritization of SSCs for ageing management and maintenance optimization as
part of a risk-informed decision-making process
 The main problems relate to the methodology, data and resource availability
 The purpose of the EC-JRC Ageing PSA Network’s activities is to provide PSA
engineers with practical approaches, methods and advice on how evaluate the
importance of ageing issues by means of PSA modeling.
The results presented demonstrate methods and approaches proposed for the
selection of SSCs susceptible to ageing, the development of time-dependent
reliability models and the evaluation of ageing effects on overall plant safety
Summary of 2008 activities
October 17, 2008
• Scientific publications :
• 1 published + 2 submitted (Task 4)
• Case Studies : 2 completed
• Task 3 EUR report is ready for registration
• Task 4 EUR 23079 EN is published
• End users support :
• Guideline for Analysis of Data Related to Aging of NPP Components and Systems –
final version is ready for the review (JRC reference report, Task 4)
• Collaboration in ISTC project on APSA for Armenian NPP
• Policy Support :
• E&I Training on Advanced Time-Dependent Reliability Data Analysis, 6-9 October
2008
• Contribution as Invited expert to IAEA workshop on VVER PSA
• Results dissemination :
• PSA’2008 Int. Conference – 6 papers presented by Network participants
• interview for EUROSAFE Tribune
• Update of APSA Web-site
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Conclusions
October 17, 2008
The following topics are planned for further development :
 areas of possible PSA application in ageing management via riskinformed approaches (Task 8),
 reliability data collection and parameter estimation : CCF (Task 5),
 passive component age-dependent reliability models (Task 6),
 the incorporation of ageing effects into the PSA model (Task 7).
Network Meeting December 4-5, 2008, Prague, Czech Republic.
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October 17, 2008
Thank you very much for your attention!
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