Applications - Europaiet.jrc.ec.europa.eu/apsa/sites/apsa/files/files/documents/APSA... · applications, such as when PSA is to be used as a day-to-day tool for decision making

Edited by M. Patrik and C. Kirchsteiger

Proceedings of the Kick off meeting

JRC Network

Incorporating Ageing Effects into PSA

Applications

European Commission DG JRC – Institute for Energy

Nuclear Safety Unit Probabilistic Risk & Availability Assessment Sector

October 2004


Institute for Energy

energyrisks.jrc.nl

EUROPEAN COMMISSION DIRECTORATE GENERAL JRC JOINT RESEARCH CENTRE Institute for Energy Nuclear Safety Unit - Probabilistic Risk & Availability Assessment Sector


Proceedings of the Kick off meeting

JRC Network on

Incorporating Ageing Effects into PSA Applications

European Commission DG JRC – Institute for Energy

Nuclear Safety Unit Probabilistic Risk & Availability Assessment Sector

October 2004


TABLE OF CONTENTS EXECUTIVE SUMMARY 1. BACKGROUND

1.1. Introduction 1.2. Background 1.3. APSA Network 1.4. References

2. KICK OFF MEETING SUMMARY AND RECOMMENDATIONS

2.1. General 2.2. Summary of discussions 2.3. Work packages 2.4. Recommendations for future work

APPENDIX I: Workshop Program APPENDIX II: Workshop Presentations APPENDIX III: Questionnaire Responses APPENDIX IV: Workshop Participants

EXECUTIVE SUMMARY The Ageing PSA Network Kick-off meeting was organized by the Institute of Energy (IE) of the European Commission's Joint Research Centre (JRC) on 16 -17 September 2004 at Petten, Netherlands, with the aims to open the JRC Network on “Incorporating Ageing Effects into Probabilistic Safety Assessment”, to start discussion of ageing issues in relation to incorporating ageing effects into PSA tools and to come to some consensus on objectives and work packages of the Network, taking into account expectations of potential participants. At the kick-off meeting 20 participants from Europe and the USA actively attended, see meeting agenda and list of participants in Appendices I and II. A questionnaire focused on partners’ current and past activities and experience in use of PSA applications, ageing studies and incorporating ageing effects into PSA tools, was sent to all potential partners before the meeting. A specific part of the questionnaire was included to identify partners’ expectations from the Network activities and ways of their possible participation. Appendix III contains condensed versions of the responses to the questionnaire from all potential partners, organised according to the four parts of the questionnaire: o General questions related to use of risk informed applications, o Questions related to ageing studies, o Questions related to incorporating ageing effects into PSA tools and o Questions related to preferences and expectations. The presentations and discussions at the meeting confirmed the main conclusion from the previously organized PSAM 7 pre-conference workshop on “Incorporating PSA into Ageing Management”, Budapest, 10-11 June 2004, that incorporating ageing effects into PSA seems to be more and more a hot topic particularly for risk assessment and ageing management of nuclear power plants operating at advanced age /more than 25-30 years/ and for the purpose of plant life extension /2/. However, it also appeared that at present there are several on-going feasibility or full studies in Europe in this area, but not yet a completed APSA leading to applications. Participants have agreed that the Network activity will start with performing a survey and documenting available methods and approaches for incorporating ageing effects into PSA and with discussing the potential use of APSA applications. An important task will also be “Case studies and benchmark exercise”. Preliminary topics for case studies were discussed at the meeting. It appeared that the mentioned survey of available methods and approaches will be helpful to clarify this issue and a final definition of the scope of case studies and benchmark exercises to be performed within the Network can be expected by early 2005. Continuously updated information on the APSA Network is available under: http://www.energyrisks.jrc.nl/APSA

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1. BACKGROUND 1.1. Introduction

The Kick-off meeting was organized on 16-17 September 2004 at Petten, Netherlands, with aim to open JRC Network on “Incorporating Ageing Effects into Probabilistic Safety Assessment (PSA)” and start network activities by discussion of ageing issues in relation to incorporating ageing effects into PSA tools and with discussion of potential use of APSA tools. As an important planned outcome of the meeting was to come to some consensus on objectives and work packages of the Network, taking into account potential partic ipants expectations. The meeting was organized in 4 parts as a round table discussion on the following topics:

• Risk informed applications (Part 1) • Ageing studies performed (Part 2) • Incorporating ageing effects into PSA and use of APSA applications (Part 3)

In the last part of the workshop, a discussion on the Network proposal and its future activities was organized. A round table discussion was performed by participants on the basis of responses to the questionnaire distributed by JRC in August 2004. The questionnaire focused on partners’ current and past activities and experience in the use of PSA applications, ageing studies and incorporating ageing effects into PSA tools. A specific part of the questionnaire identified the partners’ expectations from the Network and proposed ways of possible participation. 1.2 Background Ageing, which could be defined as a general process in which characteristics of components, systems and structures ("equipment") gradually change with time or use, eventually leads to degradation of materials subjected to all service conditions and could cause a reduction in component and systems safety margins below limits provided in plant design or regulatory requirements. It is then possible that degradation not revealed during normal operation and testing could lead to a failure or even multiple common cause failures of redundant components under non-standard operating conditions or accidents. The potential for failures and problems resulting from ageing may even increase in the future as more and more NPPs approach the last period of their nominal design lifetime. In this period plants become more vulnerable to failure and it is important to monitor conditions of equipment so as to initiate repair or replacement before minimum safety margins are compromised. Therefore, equipment ageing has become one of the most important aspects in NPP lifetime management as well as in the safety assessment particularly then in period of end of life operation and life extended operation. Be effective in ageing management means looking at the right spots with the right techniques and one of the most effective tool which could be used for that purpose

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and which complements the deterministic approach and supports the traditional defence in depth philosophy is PSA. PSA is increasingly being used as integral part of the safety related decision - making process. The methodology has matured over the past decade and PSA is nowadays seen as an effective and essential tool to complement the traditionally performed deterministic analysis. The extent to which PSA tools can contribute to risk informed decisions at each particular case within the management process depends on specific characteristics of the PSA model, e.g. its quality, completeness and level of details. Relatively simple PSA models may be adequate for certain limited applications; for more specific applications, such as when PSA is to be used as a day-to-day tool for decision making at site, a detailed and comprehensive model is necessary. Lack of treatment of ageing issues with respect to advanced NPP ageing represents one of the aspects, which could have significant impact on the practical use and credibility of PSA tools and following decision-making. Therefore, incorporation of ageing effects into current PSA models would increase the credibility of PSA studies and applications and also enhance their capability to practically support safety related decision making in sense of treatment ageing effects on risk assessment results especially in case of plant advanced age operation or extended life operation. The current standard PSA tools do not adequately address important ageing issues:

• As a main basic assumption, current PSA methods and resulting PSA studies assume that initiating event frequencies as well as component failure rates are constant in time. It is not so clear for which type of components this assumption might be acceptable under certain conditions and for which it clearly results in under-estimation of risk due to equipment ageing.

• Effects from passive components are essentially limited in current PSA models to the

treatment of pipe breaks and various damage and fragility models used for external events. Most recent work in developing estimates for piping system failure rates is based on service data with piping failures due to various degradation mechanisms. However, the assumption that pipe breaks are dominated by degradation mechanisms is inconsistent with the assumption of constant failure rates. Further, it is evident from recent work that there are uncertainties in the existing models for predicting the degradation rates and failure modes of degradation mechanisms of passive components. This issue is of particular importance for example in RI-ISI applications that attempt to introduce such models in to characterize the failure rates of piping system components.

• Ageing degradation mechanisms of piping may be divided in two groups based on

resulting failure modes: those that may cause rupture and those that may cause cracking. For example radiation embrittlement, thermal ageing of cast stainless steel components and vibratory fatigue of small diameter piping may cause rupture. Low-cycle fatigue, high cycle thermal fatigue and stress corrosion cracking of components may cause cracking. The mechanisms that have potential to cause rupture are likely to have significantly more risk impact and are candidates to be incorporated into more realistic APSA models.

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• Other active or passive components neglected in the basic PSA models as having very

low failure probability, but which could have an increasing contribution due to ageing effects, should also be considered (I&C, cables, structures..).

• Explicit consideration of the risk effects of ageing is an important feature of ageing

risk assessment evaluation. By explicitly considering the risk effects of ageing, ageing contributors can be prioritised according to their risk importance and ageing management activities can thereby be focused on important areas and the ageing management strategies can be made cost effective. Ageing contributors should include both active and passive components, which are susceptible to ageing.

• Explicit consideration of ageing effects allows component failure data to be evaluated

for ageing effects and associated risk implications. Ageing of single components and simultaneous ageing of multiple components exhibited in data can be evaluated for their risk effects.

• Considering that APSA can be a tool for ageing management, and that maintenance

and testing are the ways for ageing management, the risk effects of maintenance and testing should explicitly be considered in APSA.

In summary,

• Effects from equipment ageing would not be completely addressed by models that are based on the current PSA structure and current PSA failure rates.

• It is not clear in which cases the current simplifications are sufficient and in which not (both for active and passive components).

• Active or passive components that the basic PSA model neglect, as having very small failure probabilities and the principal degradation mechanisms, e.g. fatigue, embrittlement and erosion-corrosion, should be also considered in appropriate way.

• The risk effects of simultaneous ageing of multiple components should be evaluated.

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1.3 APSA Network

Within the Institute for Energy (IE) of the Joint Research Centre (JRC) of the European Commission, located at Petten, Netherlands, a Network on “Incorporating Ageing Effects into Probabilistic Safety Assessment (PSA)” is opened within the framework of the JRC FP-6 institutional work program. Main objective of this activity is to develop and operate a Network of interested parties from Europe and beyond on the topic of Incorporating Ageing Effects into PSA (Ageing PSA (APSA)) and use of APSA applications. More detailed technical objectives are: • Evaluation of available methods and approaches on incorporation of ageing

effects into PSA; • Identification of necessary information on ageing issues to be addressed in PSA

tools for specific PSA applications; • Demonstration of the impact of different levels of ageing information included in

a PSA model on the overall PSA results; • Discussion of reliability models and data to be used for modelling of ageing

effects in PSA models; • Demonstration of approaches and models feasibility via case studies; • Identification of further research needs; The working method is a Network of operators, industry, research, academia and consultants with an active interest in the area (physical networking via a series of workshops and virtual networking via the Internet). Network partners are supposed to have their national/own scientific programmes in this area or in related ones. It is expected that the APSA Network will result in a better understanding of important issues in modelling of ageing phenomena in PSA applications, increased knowledge on use of several approaches and methods to include ageing effects into PSA models, new experience based on particular case evaluations and feasibility studies and information on the effort implied by using different methods. Expected outcomes and deliverables of the APSA Network are:

• Survey of available approaches and methods to incorporate ageing effects into PSA;

• Conclusions regarding use and development of potent ial APSA applications • Conclusions and information regarding the relevance of explicitly including

ageing effects in PSA models by means of available experience and case studies;

• Collection of resulting information and continuous updating via a Network driven specific website.

Dissemination of results, experience, meeting discussions and conclusions and available references will be done via a specific APSA Network website.

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Tasks and schedule: • Establishment and operation of Network website www.energyrisks.jrc.nl/APSA

9/2004 – 5/2006 • Documentation of available methods and approaches

10/2004 – 6/2005 • Discussion of potential APSA applications

10/2004 – 6/2005 • Case studies and benchmark exercises

1/2005 – 4/2006 • Evaluation of network

4/2006 – 6/2006 Throughout the project, close cooperation with related activities will be made, whenever appropriate, such as the OECD's OPDE project, the JRC's ENIQ TG-Risk, etc.

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1.4 References /1/ Patrik, M., Kirchsteiger, C., “Incorporating Ageing Effects into Probabilistic

Safety Assessment Applications”, JRC IE Report , EUR 21204 EN, Petten, July 2004

/2/ Hollo, E., Results of Summary Discussions on Incorporating PSA into Ageing

Management, PSAM7-pre conference workshop, June 11, 2004

/3/ IAEA, “Safety Aspects of Nuclear Power Plant Ageing“, IAEA-TECDOC-540, 1990.

/4/ IAEA, “Methodology for the Management of Ageing of Nuclear Power Plant

Components Important to Safety“, Technical Report Series No. 338, 1992. /5/ IAEA, “Applications of Probabilistic Safety Assessment /PSA/ for Nuclear

Power Plants“, IAEA-TECDOC-1200, February 2001. /6/ IAEA, “Implementation and Review of Nuclear Power Plant Ageing

Management Programme“, IAEA Safety Report Series No. 15, 1999. /7/ Fleming, K.N., “Issues and Recommendations for Advancement of PRA

Technology in Risk-Informed Decision Making“, NUREG/CR-6813, April 2003.

/8/ Poloski, J.P., et al., “Rates of initiating Events at U.S. Nuclear Power Plants:

1987-1995“, NUREG/CR-5750, February 1999. /9/ Cojazzi, G., Masini, R., Pulkkinen U., “Nuclear Power Plants Ageing“,

Technical Note No.I.97.199, European Commission, JRC, November 1997. /10/ Sanzo, D., Kvam, P., Apostolakis G., “Survey and Evaluation of Aging Risk

Assessment Methods and Applications”, NUREG/CR-6157, November 1994. /11/ Vesely, W.E., “Approaches for Age-Dependent Probabilistic Safety

Assessment with Emphasis on Prioritization and Sensitivity Studies”, NUREG/CR-5587, August 1992.

/12/ Smith, C.L., Shah, V.N., Kao, T., Apostolakis, G., “Incorporating Aging

Effects into Probabilistic Risk Assessment – A Feasibility Study Utilizing Reliability Physics Models“, NUREG/CR-5632, August 2001.

/13/ Vesely, W.E., “Risk evaluation of Aging Phenomena: the Linear Aging

Reliability model and its Extension”, NUREG/CR-4769, April 1987.

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2. KICK OFF MEETING SUMMARY 2.1 General The Network's Kick-off meeting was organized by JRC's Institute of Energy (JRC-IE), 16-17 September 2004, at Petten, Netherlands, with the aims to open the "Ageing PSA" (APSA) Network, to start discussion on ageing issues in relation to incorporating ageing effects into PSA tools and to come to some consensus on objectives and work packages of the Network, taking into account the expectations of the potential Network participants. The kick-off meeting was attended by 20 participants from Europe and the USA (see agenda in Appendix I and list of participants in Appendix IV). Christian Kirchsteiger, head of the NSU Probabilistic Safety Assessment Sector, opened the Workshop by welcoming the participants and Horst Weißhäupl, head of the JRC-IE Nuclear Safety Unit (NSU), introduced the mission and structure of the Institute and NSU's activities. Milan Patrik defined then the background and objectives of the meeting as well as the main ideas of the APSA Network. The meeting was organized in 4 parts as a round table discussion on the following topics:

• Risk informed applications (Part 1) • Ageing studies performed (Part 2) • Incorporating ageing effects into PSA and use of APSA applications (Part 3)

In the last part of the workshop, a discussion on the Network proposal and its future activities was organized. The following specific papers related to APSA were presented in order to stimulate discussion: Part 2:

o Characterization of time dependent effects due to ageing (T. Aldemir) o Elaboration of experimental data for purposes of component ageing modelling

by means of accelerated life simulation (J. Holy) Part 3:

o Feasibility of Ageing PSA. The key tasks and major difficulties of development (A. Rodionov)

o CEA works about « ageing in PSA » (N. Devictor) o Some consideration regarding PSA and ageing analysis (M. Nitoi)

A round table discussion was performed by all participants on the basis of their responses to the questionnaire distributed by JRC in August 2004 (see Appendix III). This questionnaire focused on partners’ current and past activities and experience in the use of PSA applications, ageing studies and incorporating ageing effects into PSA tools. A specific part of the questionnaire identified the partners’ expectations from

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the Network and proposed ways of possible participation. 21 responses were received by JRC before the meeting. The condensed questionnaire responses from all potential partners are included in Appendix III, organised according to its 4 sections:

o General questions related to use of risk informed applications, o Questions related to ageing studies, o Questions related to incorporating ageing effects into PSA tools, and o Questions related to preferences and expectations.

2.2 Summary of discussions The presentations and discussions at the meeting confirmed the main conclusion from the previously organized PSAM 7 pre-conference workshop on “Incorporating PSA into Ageing Management”, Budapest, 10-11 June 2004, that incorporating ageing effects into PSA seems to be more and more a hot topic particularly for risk assessment and ageing management of nuclear power plants operating at advanced age /more than 25-30 years/ and for the purpose of plant life extension. Further, the discussion showed that it is very important to identify for what specific applications we really need APSA tools, and how detailed such tools should be for an effective use. Also, it became clear that at present there are several feasibility or on-going studies in Europe in the area, but not yet a completed APSA leading to applications. Participants agreed that the APSA Network activity should start by making a survey and a documentation of available methods and approaches for incorporating ageing effects into PSA and with a discussion about the potential use of APSA applications. A part of discussion would be here an identification of component types for which APSA really should be used as a useful support tool in ageing management. There is a strong feeling about focusing mainly on active components. A specific attention should be paid also to both passive and active components with regard to their differences in data availability and possible development. An important task will also be a development and performance of case studies and benchmark exercises. Preliminary topics for case studies were discussed. It appeared that the mentioned survey of available methods and approaches will be helpful to clarify this problem and a final definition of the scope of case studies and benchmark exercise to be performed within the Network can be expected by not later than early 2005. Continuously updated information on the APSA Network will be available under: http://www.energyrisks.jrc.nl/APSA

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2.3 Work packages The last part of the meeting was related to definition of work packages. Proposals for the Network's main tasks and activities were introduced by JRC and discussed, resulting in the following list of initial tasks:

Establishment and operation of Network website The website, which will serve as a platform for dissemination of APSA Network related information, will contain information about the Network's objectives, goals and tasks, information about meetings, discussions and conclusions and will be put into operation by October 2004. The site will also include information about available references and studies related to Network activities and the issue of APSA in general. The website will be regularly updated in relation with APSA Network needs and will be available under www.energyrisks.jrc.nl/APSA.

Documentation of available methods and approaches Participants have agreed that the real Network activity will start with this task and a survey and documentation of available methods and approaches for incorporating ageing effects into PSA will be made here together with a documentation and discussion of relevant approaches and identification of further research needs (both for active and passive components). Further, it would be of interest to prepare a collection of selected methodological problems and add this to the resulting report. The task is scheduled to last from October 2004 to May 2005. JRC will prepare the draft structure of the report (i.e. list of contents) and will contact Network partners to form an editorial team for this task. One of the inputs could be an existing CEA APSA state-of-the-art report, which could probably be made available by mid of November 2004.

Discussion of potential applications Identification of needs and discussion of potential APSA applications for risk assessment and risk management activities is a crucial task. It could help to clarify the real needs for incorporating ageing effects into PSA applications. Discussions at the meeting showed that we probably do not need any APSA application for, say, the first 25 years of plant operation because ageing related degradation of components performance is not supposed to be a serious problem during this period. The period of operation at which APSA tools are becoming more relevant, is during advanced plant life operation and especially for the purpose of extended life operation when it is also essential to ensure that the safety margins are not compromised. How to modify current PSA models in order to use them for specific applications should be clarified and discussed together with the issue of data

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necessary for modelling and quantification. Discussion of limitations, uncertainties and dependencies should be part of this task. Finally, proposals for some first case studies will be prepared here. The task will be performed largely in parallel to the development of the state-of-the-art report. Close contact with experts in plant ageing and life management is recommended here in order to help formulating some policy on how to use APSA applications and for which occasion.

Case studies and benchmark exercises Objective of this task is to demonstrate solving of selected problems of modelling ageing effects into PSA models by using different available methods and approaches in the form of jointly agreed individual feasibility / benchmark / case studies for active and passive components, data evaluation, etc. The following steps are foreseen: • Selection of topics for case studies and benchmark exercises, • Preparation of data, models, incorporation of ageing effects, • Study evaluation. The precise topics of the case studies / benchmark exercises have not yet been formulated, but it is expected that the discussion on the development of the state-of-the-art report will help to determine which exercises would be beneficial for the Network partners. Another source of information will be the set of responses, which are expected to be received by JRC following the distribution of the APSA Network Questionnaire by the OECD/NEA WGRISK secretariat to all its members. JRC will distribute a list of proposals on case studies / benchmark exercises to the Network partners before the end of 2004. The task is scheduled to last from January 2005 to April 2006.

2.4 Recommendations for future work JRC will prepare a paper /early October/ for OECD/NEA WGRISK in order to get additional input. JRC will attend an OECD Workshop on “Wire system ageing assessment” under OECD's Halden project and will discuss there possible links to the APSA Network. The APSA Network activities planned for the near future are:

• To start operation of APSA Network website (October 2004) • To start development of the state-of-the-art report (October 2004-May 2005)

o Preparation of the report structure (by JRC): § CEA report on state-of-the-art (from CEA) § Available reports on comparison of approaches and

methodologies (from all partners) § Comments from the Network Partners (all)

o Development of state-of-the-art report: § Volunteering of partners for editorial team (all?) § Development of individual chapters (editorial team)

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• Definition of topics for benchmark exercises / case studies: § New Questionnaire (November 2004-December 2004) § Discussion on development of state-of-the-art report § Evaluation of responses on questionnaire as received from

OECD WGRISK members (December 2004) • To start discussion on potential APSA applications (October 2004-May 2005)

§ Establishment of working group/questionnaire preparation • Network organisation and scope of activities:

o Introduction of APSA Network at OECD Halden Project on Wire systems ageing and discussion of possible links (October 2004).

APPENDIX I

Workshop Program


Kick-off Meeting

JRC Network on Incorporating Ageing Effects into PSA

Applications (APSA Network)

Agenda

Day 1 Opening 9.00 Coffee Break /10.45-11.15/ Lunch /13.00 –14.00/ Coffee Break /15.30 –16.00/ 9.00 Introduction Welcome to NSU at JRC's Institute for Energy H. Weißhäupl Organisation of Workshop C. Kirchsteiger Introduction of Participants all Introduction of JRC APSA Network M. Patrik Part 1 Risk informed applications

Round table discussion on use of risk informed all (Part 1 of Questionnaire distributed) Part 2 Ageing studies performed

Characterization of time dependent effects due to ageing T. Aldemir Elaboration of experimental data for purposes of J. Holy component ageing modeling by means of accelerated life simulation Individual presentations and round table discussion on ageing studies and analyses (Part 2 of Questionnaire distributed)


Part 3 Incorporating Ageing Effects into PSA and use of APSA Applications

Feasibility of Ageing PSA. The key tasks and major A. Rodionov difficulties of development CEA works about « ageing in PSA » N. Devictor Some consideration regarding PSA and ageing analysis M. Nitoi Individual presentations and round table discussion on incorporating ageing effects into PSA and PSA applications and on use of APSA (Part 3 of Questionnaire distributed)

Day 2 9.00 Part 3 – continuation Coffee Break /10.30-11.00/ Lunch break /12.30-13.30/ Part 4 JRC Network JRC APSA Network Proposal M. Patrik

Network discussions, expectations, task proposals all

Conclusions, Recommendations and Future activities 16.00 End of workshop

APPENDIX II

Workshop Presentations

1

Incorporating Aging Effects into PSA/PRA Feasibility and Benchmark Exercise

Introduction of JRC Network/Project

Probabilistic Risk & Availability Assessment of Energy Systems

Milan PatrikChristian Kirchsteiger

September 16, 2004

Contents

• Introduction

• Background • Plants age, safe operation, ageing management

• Project Stimuli

• Overview of Experience

• Project objectives

• Participants

• Working method, Project benefits

Introduction

• JRC - Department of Probabilistic Risk and Availability Assessment of Energy Systems

• Is opening the Project / Network

on

• Incorporating Ageing Effects into PSA Applications

• Including Feasibility & Benchmark Exercise

Background

• Nuclear Power Plants Age

• Age is going Up

• average age >21 years - Chart

Operational Reactors by Age

0

5

10

15

20

25

30

351 4 7

10 13 16 19 22 25 28 31 34 37 40

Age

Num

ber

of u

nits

IAEA PRIS 2004

Background

• Safe operation

• It is important to assure continuation of plant safe operation

• It is essential to assess the effects of age-related degradationof plant structures, systems and components /SSCs /

• Better understanding of behavior of age-degraded structures and components is clearly needed to ensure that the degradation can be adequately managed for the continued safe operation

Background

• Ageing management

• Ageing must be effectively managed

• since probability of equipment failure resulting form ageing normally increases with time unless countermeasures are taken

• Ageing management becomes more and more important

• Effective Ageing management

• looking in the right spots with the right techniques

Background

• Project/Network stimuli

• Role of PSA in effective Decision Making is evident

• PSA/PRA as a part of effective Ageing management program

• Increasing Specific Applications Needs

• Maintenance and inspection programs priorities, etc.

Background

• Project/Network stimuli - continuation

• Currently PSA tools do not adequately address ageing effects

• Impact on decision-making conclusions , being done with support of Risk Informed PSA Applications

• Credibility of PSA Tools

• Explicit consideration of ageing issues is important feature of Risk Assessment evaluation

• allows to prioritize the contributors according to their risk importance

• ageing activities can be focused on important issues

Background


• Systematic portion of work should continue

• Ageing cannot be addressed by models that are based solely on the current PSA structure and failure rates

• Systems, structures and components, that the basic PSA model neglect as having very small failure probabilities and the principal degradation mechanisms , e.g. fatigue and erosion-corrosion, shouldalso be considered.

ExpertOpinion

OperatingExperience

List of SelectedSSCs/Mechanisms

Fatigue Embrittlement Corrosion/Erosion

Other AgingMechanisms

Inspection,Test,Maintenance

Probabilityof Failure Modelling Aging Mechanisms

PSA

PlantInformation

Event TreeAnalysis

Fault TreeAnalysis

PSA Results

NUREG 6157

Selection of Aging SSCs/Mechanisms

Background


• OECD NEA/WGRISK Survey in Member Countries

• Levels of Priorities on PSA Topics - Specific Methods Development

• HRA/SPSA

• Fire Risk Analysis / Modelling of Aging Issues / Software Reliability

• Seismic

• Uncertainty Analysis

• Reliability of Passive Systems

• Other External Events

OECD/NEA WGRISK – Country Priorities

MLMMMLMHHHMMMLModelling Ageing

Issues in PSA

B6

United

Kingdom

Switzerland

Spain

Slovenia

Slovakia

Mexico

Korea

Japan

Italy

Hungary

France

Finland

Czech

Republic

Belgium

COUNTRY

TOPIC

Background

• Overview of experience • Incorporating of ageing effects into PSA tools is a quite new application

• Limited experience and a few of practical examples

• Some approaches and models available

• Systematic portion of work has to continue

• => Development of a Project/Network

“Incorporating Ageing Effects into PSA Applications”

Project objectives

• Evaluation of available methods and approaches • to incorporate ageing effects into PSA

• Discussion of potential APSA applications• in sense of necessary information on ageing to be addressed

in PSA tools

• Demonstration of impact on risk assessment results• in sense of different scopes, reliability models and data

to be used for modeling of ageing effects

Project Objectives

• Demonstration of feasibility • approaches and models

• Identification of further research needs

• Evaluation of effort and “effectiveness”• implied by different approaches in incorporating ageing effects into PSA

Working method

• A network of operators, research, industry and consultants

• With an active interest in the area

• Networking via series of workshops and via internet

• E-mail

• APSA website

Topics for Discussions

• Example of Topics to be discussed within the project • Applications of APSA

• Incorporating Ageing Effects into PSA models

• Treatment of passive components /new PSA models inputs/

• Treatment of active components /modification of current reliability models/

• Dominant degradation mechanisms for specific components in NPPs

• Particular models availability and feasibility for APSA applications.

• Inspection, test and maintenance policy for particular ageing mechanisms

• Data availability and scope of data collection, data analysis

• Potential changes to standards, guidance and regulations

Project benefits


• The benefits of such a project would be • a better understanding of important issues related to incorporating

ageing effects into PSA

• increased knowledge on use of several approaches and methods to include ageing effects in PSA models

• some experience based on particular case evaluations

• available information reflected efforts implied by different methods

• others

• Czech Republic /UJV Rez/

• Finland /VTT, TVO/

• France /CEA, EDF, Framatome, IRSN/

• Germany /EON, Vattenfall/

• Hungary /VEIKI/

• Italy /ENEA/

• Lithuania /LEI/

• Japan /JAERI, Maritime Research/

• Korea /KAERI/

• Slovakia /Relko/

• Switzerland /KKG/

• UK /BE, Rolls-Royce Naval Marine/

• USA /Ohio St. University, Los Alamos NL, Sandia NL, Statwood Consulting/

Potential Project Partners

Kick-off meeting

• Incorporating Ageing Effects into PSA Applications

• Introductory discussions concerning

• how ageing is currently addressed in PSA tools and applications

• what approaches are being currently used to incorporate aging into PSA

• what applications are of main interest

• Consensus on objectives, work packages and schedule• expectations

• Let’s start Kick off meeting discussion

Any New Ideas, Commentsand Recommendations

are welcomed

Conclusion

Characterization of Characterization of TimeTime--Dependent Effects Dependent Effects

on Component on Component Unavailability Due to Unavailability Due to

AgingAging

Tunc AldemirTunc Aldemir

The Ohio State UniversityThe Ohio State University

§§ BackgroundBackground

§§ Overview of a general methodology to model timeOverview of a general methodology to model time--dependent effectsdependent effects

§§ Unavailability under periodic surveillance testingUnavailability under periodic surveillance testing

§§ Unavailability under random surveillance testingUnavailability under random surveillance testing

§§ ConclusionConclusion

Presentation organizationPresentation organization

BackgroundBackground§§ TimeTime--dependent unavailability of aging components dependent unavailability of aging components

can exhibit mathematically complex behavior.can exhibit mathematically complex behavior.

§§ The unavailability may be also dependent maintenance The unavailability may be also dependent maintenance historyhistory

§§ First failure distributions may not be continuous First failure distributions may not be continuous functionsfunctions

§§ Renewal theory provides a feasible approach to model Renewal theory provides a feasible approach to model aging effects on component unavailabilityaging effects on component unavailability

A renewal theory approach A renewal theory approach to aging modelingto aging modeling

q(t) : Unavailability at time tq0(t|u,t0): Unavailability at time t, given that last test occurred at time u and last repair occurred at toh(u)du: Probability that the last test was completed within du around time u prior to time tR(t) : Reliability function for the componentw(t) : Failure frequency at time tg(t|t')dt: Probability that the component is restored to “good” state withi n dt around time t with the same

age by time t, given that failure occurred at time t0f(t|t0)dt: Probability that the component fails within dt time t, given that last surveillance testing occurs at

time t0

≥′≤+′

= ∫ ∫ otherwise 0

or )0|()|()'(')|()( 0 0

000

0

ututtfttgtwdtttfdttw

t t

≥′≤

+′−′−

= ∫ ∫∫′

otherwise 1

or )()0,|()|()'(')(),|()()( 0

0 000000

0

0

ututuRutqttgtwdttuRtutqdtuthdutq

u tt

Last testbegins

Component failsComponent restoredto “good” state

Last test ends

tt00 u’u’ uu tt

RenewalRenewaldensitydensity

Unavailability under periodic Unavailability under periodic surveillance testingsurveillance testing

( )

≥≥+∫∫

+

∫∫+−

=−−

=

−−

−−−∑−−

otherwise 1

1 -

-)(1

)(00

0

)(

0

)()(

1

)()(

111

nTt)T(nee

eeTWpp

tq tnT

kTtTkn

tdttdt

n

k

tdttdt

kkk

λλ

λλ

q(t): Unavailability at time t?(t): Failure rate at time tpk: Probability that component is restored to as -good-as-new state following repair at the kth

surveillance testing

∑=

−−

−

−−

∫−

∫+

∫−

∫=

+−−+ n

k

tdttdt

kk

tdttdt

n

TknTknTnnT

eeTWpeepTW

1

)()(

1

)()(

0

)1(

0

)(

0

)1(

00 )()(λλλλ

Unavailability under periodic Unavailability under periodic surveillance testing surveillance testing –– Motor Motor operated valveoperated valve

<−

=

==≤≤−

=

+

+−

−

+

months 12 intervalTest 1

year 5

7/year07008.001

)(1

0

0

1

0

te

tte

tFt

τ

τ

βλ

β

τβ

βτλ

τλ

Unavailability under periodic Unavailability under periodic surveillance testing surveillance testing –– Diesel Diesel generatorgenerator

<−

=

==≤≤−

=

+

+−

−

+


year 1

7/year07008.001

)(1

0

0

1

0

te

tte

tFt

τ

τ

βλ

β

τβ

βτλ

τλ

Unavailability under periodic Unavailability under periodic surveillance testing surveillance testing –– Diesel Diesel generatorgenerator

<−

=

==≤≤−

=

+

+−

−

+


year 1

3/year07008.001

)(1

0

0

1

0

te

tte

tFt

τ

τ

βλ

β

τβ

βτλ

τλ

Unavailability under periodic Unavailability under periodic surveillance testing surveillance testing –– Generic 1Generic 1Test interval 6 months

Test interval 12 months

year 1 3

/year07008.0

1

01

)(

0

1

10

0

==

=

<−

≤≤−

=

+

+−

−

+

τβ

λ

τ

β

τβ

βτλ

τλ

te

tte

tFt



year 1 7

/year07008.0

1

01

)(

0

1

10

0

==

=

<−

≤≤−

=

+

+−

−

+

τβ

λ

τ

β

τβ

βτλ

τλ

te

tte

tFt



year 1 7

/year05256.0

1

01

)(

0

1

10

0

==

=

<−

≤≤−

=

+

+−

−

+

τβ

λ

τ

β

τβ

βτλ

τλ

te

tte

tFt

Unavailability under random Unavailability under random surveillance testingsurveillance testing

g(t0|t’): Probability that component is restored to as -good-as-new state at time t0, given that last repair occurred at time t’

?(t): Failure rate at time t?: Inspection ratep: Probability that component is restored to as -good-as-new state following repair

( )∫

−∫

+

∫−

∫+

−−=

−−−−−−

−

∫∫−− tutttu

tdttdtu

tdttdtut

t

t

eetreedtedup

eptq

00

0

0

0

0

)'(')'('

0

0

)'(')'('

0)(

0

)(

1)1()(

λλλλν

ν

∫ ′=0

000 )|()'(')(

t

ttgtwdttr∫

+∫

−=−−

∫tt

t

tdtt tdt

etetttrdttw 00

)'('

0

)'('

000 )()()()(λλ

λλ

Unavailability under random Unavailability under random surveillance testing surveillance testing -- Solution using Solution using

Laplace Transforms for initially new componentsLaplace Transforms for initially new components

?(t): Failure rate at time t?: Inspection ratep: Probability that component is restored to as -good-as-new state following repair

+−+

−++

−−+−

+−+

−++

+−

=

)(~)1(

)(~

)](~1[)](

~1[

)(~)1()(~

)()1(

)(~

sRs

pssR

sRspssRsp

sRs

pssR

pss

psq

νν

ν

ννν

νν

ν

νν

)](~

1[)](~1)[(

)(~sRsps

sRsssw

−−+−+

=νν

ν)](

~1[

)](~

1[)(~

sRspssRsp

sr−−+

−=

ννν

∫

=−

t

tdt

eLsR 0

)'('

)(~ λ

Unavailability under random Unavailability under random surveillance testing surveillance testing -- A comparison to A comparison to periodic testing for a battery with constant failure rateperiodic testing for a battery with constant failure rate

year/05256.0=λ

1/year periodic inspection

1/year random inspection

t (year)

w(t)

\yea

r

year/05256.0=λ

1/year periodic inspection

1/year random inspection

t (year)

q(t)

\yea

r

Unavailability under random Unavailability under random surveillance testing surveillance testing –– Perfect vs. Perfect vs. imperfect repair for a battery with constant failure rateimperfect repair for a battery with constant failure rate

?: Failure rate ?: Inspection ratep: Probability that component is restored to as -good-as-new state following repair

1/year

year/05256.0

=

=

ν

λ

t (year)

w(t)

\yea

r

p = 0.95

p = 0.99

p = 0.9991/year

year/05256.0

=

=

ν

λ

t (year)

w(t)

\yea

r

p = 0.95

p = 0.99

p = 0.999

Unavailability under random Unavailability under random surveillance testing surveillance testing –– Time Time dependent behavior of repair density for linearly aging dependent behavior of repair density for linearly aging componentscomponents

??:: Inspection rateInspection rate

t/b

r(t/b

)/b?

b?=5

b?=10

b?=12

2

)(

−

= bt

etR

Unavailability under random Unavailability under random surveillance testing surveillance testing –– Asymptotic Asymptotic solutions under perfect repairsolutions under perfect repair

?(t): Failure rate at time t?: Inspection rate

∫

=−

t

tdt

eLsR 0

)'('

)(~ λ

)0(~

1)(

Rw

νν

+=∞

)0(~1)(

Rr

νν

+=∞

)0(~

1)(~

)(R

Rq

ννν

+=∞

Unavailability under random Unavailability under random surveillance testing surveillance testing –– Asymptotic Asymptotic solution for linear aging ratesolution for linear aging rate

22

20

)(

−

−

== btt

eetR ττλ

??00:: prepre--aging failure rateaging failure rate1/1/tt :: aging rateaging rate??:: inspection rateinspection rate

=

22)(

2

2 sberfce

bsR b

sπ

πννb

rw+

=∞=∞2

2)()(

νννπνππν

πν

νπν

ν

)()()(

2)(

21

22

22

1)(

42

2

2

∞=

∞≈

+−

+≈

+

−

=∞

wrbbb

b

berfeb

q

b

0/2 λτ=b

Unavailability under random Unavailability under random surveillance testing surveillance testing –– Asymptotic Asymptotic behavior for a plant components aging linearlybehavior for a plant components aging linearly

Circuit breaker with ? = 1/year

Relay with ? = 1/year

Circuit breaker with ? = 12/year

Relay with ? = 12/year

Unavailability under random Unavailability under random surveillance testing surveillance testing –– Time dependent Time dependent unavailability as a function of Weibull shape factorunavailability as a function of Weibull shape factor

a: shape factorb: scale factor?: inspection frequency

t /b

q(t)

a=2

b?=5 in all cases

a=3

a=4

Unavailability under random Unavailability under random surveillance testing surveillance testing –– Asymptotic Asymptotic solution for general Weibull distributionsolution for general Weibull distribution

a

bt

etR

−

=)( ??:: inspection rateinspection rate

)0('~1)0(~1)()(

RbRrw

νν

νν

+=

+=∞=∞

)0('~

1)('

~

)0(~

1)(

~)(

RbbRb

RR

qν

ννν

νν+

=+

=∞

atetR −=)('

Unavailability under random Unavailability under random surveillance testing surveillance testing –– Asymptotic Asymptotic behavior as a function of Weibull shape factorbehavior as a function of Weibull shape factor

a: shape factor b: scale factor ?: inspection frequency

ConclusionConclusion

§§ Renewal theory seems to be a feasible option to Renewal theory seems to be a feasible option to quantify quantify timetime--dependent effects on component dependent effects on component unavailability due to aging.unavailability due to aging.

§§ Closed form solutions for the asymptotic the failure Closed form solutions for the asymptotic the failure rate and unavailability can be obtained using Laplace rate and unavailability can be obtained using Laplace transforms.transforms.

§§ Obtaining the detailed time behavior may not be a Obtaining the detailed time behavior may not be a trivial numerical task. trivial numerical task.

QUESTIONS…

?

?Thank you !!!

??

?

?

EC workshop on Incorporating Ageing Effects into PSA ApplicationsSeptember 16–17, 2004, Petten, Netherlands

Elaboration of Experimental Data for the Purposes of Component Ageing Modeling by Means of Accelerated

Life Simulation

Jaroslav HolyNuclear Research Institute Rez plc

Reliability and Risk Assessment Department


2 ----------Jaroslav Holy----------Nuclear Research Institute Rez, plcReliability and Risk Assessment Department

The main points of the presentation

qgeneral information about the project

qplanning of simulated accelerated life experiment –issues related to statistical methods

qmethods to be utilized in the analysis of dataprovided with experiment

qsummary of inputs and requirements regarding planof experiments



Basic information about the project (1)

q IRSN/DES/SERS Feasibility Study of an Accelerated Ageing Test Program for Motor-Operated valves

q major part of work performed in Nuclear Research Institute Rezin the Division of Integrity and Technical Engineering(technical coordination of the project – Andrey Rodionov from IRSN side, Jan Fridrich from NRI side)

q the theoretical issues regarding application of mathematical-statistical methods and the general points connected with PSA matter were solved in NRI Division of Nuclear Safety(Department of Risk and Reliability Analysis)



Basic information about the project (2)

q support of PSA level 1 for French 900 MWe nuclear power plants

q reflection of increasing importance of aging issues in French NPPs operation

qmotor operated valves of emergency core cooling systems selected as appropriate subject of ageing related analysis

q experiment-based accelerated ageing simulation decided being the preferred method of analysis



Basic information about the project - the main objectives

q to evaluate feasibility of accelerated ageing tests (fidelity point of view), including simulation of simultaneous effects of a number of ageing mechanisms

q to justify, propose and plan the way, the tests shoud be performed

q to propose statistical support for planning and preparation of the tests and provide methodological tools for analysis of datacollected during the accelerated tests

q to specify the requirements for the statistical test plan with description the number of test samples, the way of dealing with failed sample and criteria for ending the test



Information about the analysis in the Feasibility Study report

qsummary information including the main conclusion in Section 11 - Statistical Aspects of the Test Program

qdetails about the analysis in Appendix 7 - Statistical Support of valves Accelerated Life experiment -Methods, Comments, Proposals



Two main goals of the work related to theoretical statistical issues

qto solve statistical matters connected with planningand preparation of the experiment

qto suggest methodological tools for analysis of datacollected during the experiment



Basic points of test planning strategy addressing statistical data elaboration issues

qthe experimental data obtained must be suitable for statistical data analysis…

qthus the assumptions of selected mathematical methods have to be fulfilled…

qthe most basic assumptions are related to the size ofstatistical data sample…



Basic points of test planning strategy addressing statistical data elaboration issues (2)

q the more statistical data we have, the more statistical methods we can applied and the better and more credible results of application we can obtain

q on the other hand, the more statistical data we decide to have, the more expensive the experiment is going to be

q the main goal of the statistical support of the experiment was to solve optimisation task - scope of the experiment versus price of the experiment



Preliminary conclusions made on the base of other experiment characteristics

qbasic subject of statistical analysis - time of failureof valve (within accelerated life)

qthese failure times form basic statistical sample for detailed elaboration

qtheoretical data analysis will be focussed on fatal failures only (relation to PSA)



Basic preliminary conclusions made on the base of other experiment characteristics (2)q on the base of preliminary evaluation of statistical methods

taken into consideration for analysis - 10 elements of statistical sample were defined as minimum for standard applicationof methods

q with less than 10 elements, most of standard methods may notbe used directly and some specific approaches have to be considered

q 60 years of operation planned being simulated for every valve

q for this time period, preliminarily expected starting failure rates and "average" ageing potential, a good chance of reachingrequired 10 failures having 10 valves at disposal was indicated



Test and data elaboration strategy for sufficient size of data sample

qjust 10 or more data points (valves failures during accelerated life)

qall basic methods of life data treatment and estimation of Weibull distribution parameters are applicable

qgood chance that the results will be credible and the ageing model derived will be flexible enough



Data elaboration strategy for moderately less than sufficient data size (5-9 data points obtained)

q the basic methods of life data sample elaboration do not work and some special, higher uncertainty methods have to be used

q prolongation of the experiment represents reasonable possibility, 20 more years was estimated being suitable extension

q the point of the extension is that the data from very late simulated period of valves life may bring important and realistic corrections of parameters obtained for earlier valves life

q specific graphic method at disposal suitable for this size of sample



Data elaboration strategy for highly insufficient data size (3-5 data points obtained)

q there is no good direct alternative of analysis

q even the prolongation of the experiment may not yield sufficient number of additional failures

q if the failure times are concentrated into the last period of valve lives (20 years), a significant aging tendency is indicated and the prolongation can be still helpful…

q otherwise the special methods for close to zero size of data sample have to be applied



Test and data elaboration strategy for zero or close to zero size of data sample

q3-5 data points (failure times) scattered over all the period of valve life or less than 3 data points

qclassic methods must not be used, highly biased or completely wrong results would have been produced with high probability

qthe class of so-called WeiBayes methods is strongly recommended



Basic points of methodology proposed for evaluation of experiment results

q in classic PSA (without ageing modeling), constant failure rate is expected (exponential distribution of times between failures)

q some other distribution has to be used, when ageing is taken into consideration

q two parameters Weibull distribution was selected as a proper modeling tool

q three parameters Weibull distribution and lognormaldistribution are the alternatives



Methods for estimation of Weibulldistribution parameters

qgraphical method using Weibull paper

qregression method

qmaximum likelihood method



Comments to the graphical method of Weibulldistribution parameters estimation

qsimple, but still effective

qcan be used for limited data size

qcan be applied without commercial software

qcan be used in a simple manner even for estimation of parameters of three-parameters Weibull distribution



Comments to the regression method of Weibull distribution parameters estimation

q linear regression can be used for two-parameters Weibull, no commercial software necessary

q non-linear regression has to be used for three-parametersWeibull, commercial software necessary

q two variants of regression possible - regression "on x axis" and regression „on y axis"

q to some difference from other applications of regression method, the results of using these variants are fairly different

q for component ageing data, regression "on y axis" should be preferred



Comments to the maximum likelihood method of Weibull distribution parameters estimation

qmost efficient and precise method of estimation

qa broad set of advantages provided that the input data sample is more than sufficient

qquality of results is very sensitive to the quality and scope of input data set

qthe method should not be used (even for approximate calculations) when the data sample is small



Specific features and needs of censored dataq the best case of data sample - complete data sample

q in practice - right censored data (by time) since the subjects of the experiment are very reliable

q the typical aproach is to transfer the censored data sample to pseudocomplete data sample and to apply estimation method to the transferred data sample

q this approach is well possible to be used as long as the original data sample is not ultra-censored with very small real data points

q an example of ultra-censored data sample are data taken from several years of plant operation

q in case of the experiment planned, ultra-censored data are not expected being the product



Summary of requirements regarding statistical data analysis (1)

qRecommended number of subjects of the tests (valves): 10

qRequired quantitative outputs from the tests: failure time points (related to the beginning of valve life)

qTime units for direct specification of failure time points during the experiment: opening-closing cycles, hours

qTime units used in data analysis: hours




qClass of failures considered (relevant failures): fatal failures of valve function only

qDominant failure mode belonging to the considered class: fail to open

qOther important failure modes analyzed: 1)fail to close 2)internal leakage (if critical) 3)external leakage (if critical)




q Probability distribution used for modeling of aging influence: two-parameter Weibull, three parameter Weibull

q Preferred method of estimation of Weibull distribution parameters: regression method

q Other methods of estimation of Weibull parameters: MLEmethod, graphical method

qMethod of estimation of Weibull parameters in case of lack of data: WeiBayes




q Other Weibull distribution characteristics estimated: mean, median, 5+95% percentile, failure rate, characteristic life, variance

q Experimental data fit with theoretical distribution analysis: YES

q Data fit parameters: correlation coefficient, CCC coefficient

qWeibull distribution tests against other distributions (lognormal): NO




qUncertainty analysis: YES

qUncertainty parameters: variance, standard deviation, confidence boundaries

qLevel of confidence: 90%




q Expected type of data: right censored, with significant impact of censoring

q Type of censoring: by time

q Repair of failed specimen: possible, addressed in consequent data analysis

q Length of valve life simulation proposed: 60 years of calendar time

q Prolongation of simulation, if necessary: possible, 20additional years




qGeneric data as additional information source: yes, if necessary

qSources of generic data: operational experience from French PWRs, Weibull data generic databases




qWay of analysis: manual or by means of commercial software

qManual analysis proposed for: transfer of right censored data to pseudocomplete data, graphical estimation of Weibull distribution parameters, regression method for construction of two parameters Weibull distribution, evaluation of correlation coefficient

q Commercial software using proposed for: regression method for construction of three-parameters Weibull distribution, MLE method for construction of Weibull distribution, interval estimates, confidence boundaries, testing of hypothesis regarding several different sub-populations of data etc.

Transparent n°1

Incorporating Aging Effects into Probabilistic Safety Assessment Applications.

EC JRC workshop 16-17 September 2004.

Feasibility of Aging PSA.

Presented by A. Rodionov – Institut de Radioprotection et de SûretéNucléaire (IRSN), France.

Transparent n°2

Contexte

q Goals and advantages of APSAØ Risks related to the aging impact to safety

Ø Main differences with the standard PSA 1

Ø Possible applications of APSA

q Main tasksØ Definition of AM and elaboration of reliability models

Ø Incorporation of reliability models into PSA

Ø Impact to safety

q Feasibility

q Conclusions

Transparent n°3

Risks related to the aging impact to the safety

Aging impact to safety

Operational and environmental stressors and

loads

DesignQualificationSurveillanceMaintenance

SSC reliability/availability

Safety of NPP

SSC degradation due to the

aging

RISK BARRIERE TARGET

Transparent n°4


PSA issues

q Possible impact on the IEs definitions and frequencies

ü frequent events (as a transients) – operational experience and prediction of f = f(t)

ü IE for which f calculated as reliability model

ü rare events – physical reliability models (?)

ü aging multiple failures (intersystems) initiators

q Possible impact on the system performance

ü success criteria and functional limits

üCCF of redundant elements

üCCF due to the same AM of several systems

üModification of list of dominant contributors in the CDF and system unavailability

Transparent n°5


PSA issues

q Possible impact on the component reliability

ü domination of aging failures in failure rate (neglected failure mechanisms, lifetime parameter)

ü increasing of unreliability - monotone / discrete / monotone after wearout beginning

ü age as a time in operation/standby, number of demands, number/amplitude of stressors

ü renewal effects of PT and PM

Main question :

Does the reliability of SSC significantly decrease with time ?

How to measure this evolution?

What is an aging impact on the global safety of NPP?

Transparent n°6

Goals and advantages of APSA

qMain differences with the standard PSA 1

- λ = f (t, PT and PM) for active component failure rates / initiating events frequencies / passive components ;

- impacts of periodical tests and maintenance to the unavailability of SSC are explicitly modelled ;

- CDF = f (t, PT and PM).

Transparent n°7

Possible applications of APSA

q Tool to evaluate the risks related to the aging effects (contributors to and distribution of) ;

q Expertise of effectiveness of surveillance programme (periodicaltests, in-service inspections, RCM) ;

q Expertise of utility life extension programme

examples of actual difficulties :

ü residual lifetime estimation (design/ operational experience/ prediction),

ü qualification (simulation of aging mechanisms/ representativity for period of extension),

ü effectiveness of preventive maintenance and inspections (volume and periodicity).

Transparent n°8

Major difficulties

q Level of analysis

Ø from <component – FM – unavailability>

to <component – sub-component – AM – FM – surveillance – unavailability>

q Availability of reliability models

Ø simple enough to calculate unavailability (age, renewal, nature of failure)

Ø not too much parameters to estimate

q Initial data and parameters estimation

Ø Possible data sources

ü Op.exp. (observation period, censoring, nature of failure, stres sors)

ü Reliability tests (simulating approach, synergism, sample size)

ü R&D in property of materials (amount of data, correlation with op.exp.)

Ø Parameters calculation (algorithms, representativeness)

q Incorporation of aging effects into PSA model

Ø Level of details, synchronization of unavailability calculations

Transparent n°9

Main tasks

1. Definition of AM and elaboration of reliability models for IEsfrequencies, components reliability and CCF.

ü Identification of AM, theirs importance and corresponding failure modes (Aging FMEA).

ü Analysis of existing data sources (operating experience, laboratory reliability tests, physical models) and choice of reliability model.

ü Data collection (failure/demands/loads data, PT/PM data, performing of reliability tests) and parameters estimation.

Transparent n°10

Main tasks

2. Incorporation of reliability models into PSA.

Possible modifications on the level of

ü Active components – additional gates and BE in the FT,

ü Passive components - additional gates and BE, changing of FT structure,

ü IE – changing of parameter or additional gates and BE in the FT,

ü CCF effects - changing of parameter or additional gates and BE, changing of FT structure.

3. Impact to safety.

ü CDF as a function of time.

ü SSC contribution and importance.

ü CDF distribution.

Transparent n°11

Feasibility

In the frame of feasibility study one sensitivity PSA calculation was done to illustrate possible impact to CDF from aging and surveillance programme of active components.

Then four tasks were proposed to evaluate the feasibility of APSA in the frame of the pilot project :

Ø Task 1. Performing an Aging FMEA for several types of active components (valves).

Ø Task 2. Development of the statistical algorithms for reliability parameters estimation in case of operational data.

Ø Task 3. Preparation of accelerated aging reliability tests for selected types of components (MOV).

Ø Task 4. Elaboration of physical reliability models for passive components (pipes).

First three tasks were performed in 2002-2004.

Transparent n°12

Feasibility / Results of sensitivity study

LOCA, active components, failure on demand, French and US operational experience data, PT and PM

CDF as a function of age of the unit

2,88E-06

7,12E-05

5,08E-05

0,00E+00

1,00E-05

2,00E-05

3,00E-05

4,00E-05

5,00E-05

6,00E-05

7,00E-05

8,00E-05

ref 32 ans 40 ans

Transparent n°13


Pompes : MP 16 ans

Vannes : MP 10 AR

32 ans 40 ans

indisponibilité

Transparent n°14


Contribution to the CDF by sub-families

(PB – SLOCA, BI – MLOCA, GB – LLOCA, BV – PRZ Steam LOCA)

Modèle de référence

GB3%

BI15%

PB81%

BV1%

32 ans

GB26%

BI65%

PB9%

BV0%

40 ans

GB23%

PB15%

BV0%

BI62%

Transparent n°15

Feasibility / Pilot project results/Task 1

q Aging FMEA for several types of active components (valves).

Main steps :

1. Regroupment and selection of components

2. Identification of AMs for each selected component

3. Identification of corresponded FM and their criticity

4. Definition of AM importance

5. Analysis of periodical tests and preventive maintenance actions effect

6. Conclusions / input data for reliability model (AM/FM, PT/PM periodicity, type of renewal)

Transparent n°16

Feasibility / Pilot project results / Task 2

q Statistical algorithms for reliability parameters estimation in case of operational data

Problem specification :

Data sources - op. exp. failure data ;

- op.exp. loads and stressors data ;

- op.exp. maintenance renewal data.

Incompleteness - highly censored data.

Availability of algorithms for parameters estimation using specific and generic data, as well, as expert judgments ?

Transparent n°17


++++− λ, ω, NShock risk competive

+-++− β, η, η0 , T0

Risk competive Weibull

+--+− β, ηSimple Weibull

+-++− λ0, a, T0Risk competive linear

+--+− λ0, aSimple lineair

Renewal maintenan

ce data

Data about cumulated number of

stress

Nature of failure

Failure data

(criticity, age)

ParametersReliability Model

Transparent n°18


Following algorithms for Weibull and Shock models were developed and tested :

- maximum likelihood (ML) ;

- stochastic expectation maximization (SEM) ;

- Bayesian restoration maximization (BRM).

Tests were done using simulated and real data.

Transparent n°19


Choice of calculation algorithm depends from the size of statistical sample (n) and censoring rate (m/n)

Sample size, n

Censoring rate, m/n

6 < n < 20 20 < n< 40 40 < n < 100

n > 100

Complete sample :m = n

ML ML ML ML

m/n > 0.75 SEM, BRM ML, SEM ML ML

0.5 < m/n < 0.75 SEM, BRM SEM, BRM ML, SEM ML

m/n < 0.5 SEM, BRM SEM, BRM SEM, BRM

ML, SEM

Transparent n°20


q Preparation of accelerated aging reliability test program for selected types of components (MOV).

The aim of reliability laboratory test is to determine the reliability parameters as a function of simulated “time into operation” (age)

Ø Type of component : VELAN motor operated gate valve.

Ø Operating conditions : standby, high pressure, normal temperature, boron water.

Ø Accidental conditions : have to be simulated on the end of the test series.

Ø Average number of mechanical cycles : 30-40 per year.

Ø AM to be simulated : wear, fatigue, corrosion and thermal aging.

Ø Sample size : 10 units.

Ø Equivalent period of operation : 40 and 60 years.

Ø Test termination criteria : time/failure terminated.

Transparent n°21


q The test strategy is based on the following issues :ü identification of significant AM

ü selection and justification of available simulation approaches when it is technically feasible

ü definition of test conditions to simulate of each significant AM

q The test strategy consists of :ü definition of a test cycle , as a sequence of typical operating, environmental

and maintenance conditions (actions and loads) to be periodically repeated during the test

ü test performance as a repetition of the test cycles till the component relevant failure occurs or till the end of component lifetime simulation

ü estimation of equivalent time to failure from laboratory failure time

ü statistical evaluation of failure data from all test samples to obtain the required reliability distribution parameters

Transparent n°22


q Test program difficulties

üsimulation of aging mechanisms and results interpretation

ü test planning and organization (estimation of “simulated time”, synergism of AMs, etc.)

üavailability and modification of test facilities

üoptimization of test duration (1-1,5 year)

ü results interpretation

ücost (1,5 –1,9 M€)

Transparent n°23

Feasibility / conclusions

q Aging PSA required more sophisticated and detailed analysis of relation component/ AM/ FM probability

q As reliability models have more parameters, as more initial dataneeded to calculate them

q Representativness of operating experience data for long terms extrapolation is a big question

q Complement sources of data could be reliability tests and physical reliability models

Transparent n°24

Project proposals

q IRSN interests to learn :

- How data are they collected ? Which are the important data ?

- - What are the main problems of methodology ( for example how to treat the possible dependencies) ?

- Are there already some results and applications ?

q IRSN propose following tasks to add

1/ Reliability data elaboration. Data nomenclature and data sources, choice of mathematical model. Parameters estimation.

2/ Reliability tests for one type of component.

3/ Physical models for different aging mechanisms. Possibility to incorporate in PSA model.

4/ Aging FMEA approach development or analysis for one type of component.

1

CEA works about « ageing in PSA »

Nicolas Devictor

CEANuclear Energy Division

Reactor Studies DepartmentInnovative System Studies Service

[email protected]

2004CEA/Cadarache – Reactor operation and reliability laboratory

PSA activitiesPast activities

• Level 1 PSA - Framework of the cooperation CEA- Electricité de France– Development and validation of methods to rewrite models from Lesseps under Risk

Spectrum.– Extension of Boolean methods with applications to specific or long time sequences.– Suitability of Level 1 PSA for application on passive structures (applications to ISI, “OMF-

Structures” and optimisation of margins…)., for the different programs in a lifetime project.– Impact of different uncertainties in Level 1 PSA in decision-making processes.

• Level 2 PSA – Contract from IRSN– Probabilistic methods to manage uncertainties.

On-going projects• PSA for NRNF like research reactor, nuclear waste facility, fuel cycle facility …• Are PSA good risk comparison tools for different nuclear facilities ? → comparison of PSA and QRA• How can we use PSA to help designers in case of future or advanced reactor (risk-informed) ?• Model developments

– Level 1 PSA in a design phase for a research reactor– Level 1 PSA in a early design phase for GFR (Gas Fast cooled Reactor, Gen IV)

Other tasks, that could be useful in some PSA applications• Reliability Method for Passive Systems (RMPS – European contract, 2001-2004)

– Development of a methodology to assess the thermal-hydraulic passive system reliability;– Introduction of passive system unreliability in the accident sequence analysis.

• Development of human factor models that are suitable for CEA fac ilities


« Ageing » activities

• Mainly funded by « R&D for nuclear industry » Program Division– Co-operation with partners (EDF, Framatome-ANP, IRSN…)

• Main components– Reactor vessel – Containment

• Contents of the works– Change in material properties (concrete, steel…)– Metal damage indicator based upon radiation dose– Deterministic models (best-estimated, understanding of phenomenon)

+ probabilistic approach


Possible interest for the « ageing in PSA » project• No specific work on the subject at present time.• About “ageing in PSA”

– Interest for the subject is linked to our activities in support to our partners on lifetime extension program

• NPP : reactor vessel (metal damage indicator based upon radiation dose, PTS…), containment (concrete)… - support to our partners.

– A collaboration with JAERI is beginning (ageing of different components, and mainly reactor vessel, possible extension to PSA).

– Exploratory study – what is the impact for designer ?

• About « ageing »– Exchange of information between experts– Set up of general methodologies (cost sharing, if possible consensus)

• About « methodology »– Exchange of information between experts– Set up of general methodologies (cost sharing, if possible consensus)

At the present time, no decision has been taken about our participation to the network.


CEA-EDF joint work• Included in a more big EDF program• Duration: 2001-2002• Objectives of the joint work

– Studies of the consequences of the introduction of ageing in PSA.– Studies the use of PSA in the optimisation of the NPP lifetime.

• Bibliographical study on the 2 subjects

• Meaning of the word “ageing”– Evolution of physical properties or characteristics with the tim e– Changes in law, rules,…– Obsolescence...

• Relevance of the subject – One of the criteria for the NPP lifetime extension is the safety

level.– PSA is one of the useful tools for the safety demonstration.


NPP lifetime managementNPP lifetime management or PLIM (nuclear Power plant LIfe Management) =

taking into account several points of view like ageing, economical and regulatory aspects :

– Optimisation of the exploitation, maintenance, lifetime of SSC (System, Structure and Components ) : ageing of SCC depends on their age, their working operation and maintenance program.

– A sufficient level of safety and availability.• Required safety level could change with the time – new rule, new

knowledge…– Competitiveness of the plant should be interesting with regard to other energy

plant.• Co-ordination of different programs

– preventive maintenance program,– inspection, surveillance, testing, …– data collection,– component qualification,– programs about critical components (containment, vessel, heat exchanger…).

→Need the systematic identification of critical SSC→Figure from AIEA Safety Report Serie n° 15, 1999 (see Figure 1, JRC paper)


Use of Level 1 PSA in lifetime program• To take precautions for the use of PSA results

– Dependence of the scope of the PSAfor examples: problem for the reactor vessel and the containment

– Interest for a component that has a strong functional influence about the core damage.

• Passive component or system ⇒ more or less modelled in Level 1 PSA– A lot of passive components (pipes, reinforcement, safety system, etc.)– Slower degradation kinetic– The size of operating feedback database is often very small.– A lot of uncertainties in data and degradation models– If maintenance is possible, high cost.

⇒ Adequacy of PSA model must be checked for each studiedpassive system.• Figure 2 of JRC paper from MIT report describe the potential place of PSA in a lifetime program (4 steps).• Possible use of Level 1 PSA in the framework of ’Risk informed decision making’’ :

– Risk Centred Maintenance / RI In Service Testing /RI In Service Inspection.– An important task : to be able to detect a drift in the reliability data ⇒ link with

RCM, RI- IST and RI-ISI• Question : R&D tasks seems needed to clarify the best use of PSA in the ageing management.


Ageing and PSA – 1st approach

Simulation method

« Age dependantPSA »

(Vesely)

Modèle EPS Niveau 1

Extraction des informations :

Description des événements de base, Probabilités de défaillances, Durée de mission, Intervalle de tests, … .

Données issues de l’exploitation :

Taux de défaillance, Taux de vieillissement, Intervalle de tests, Plannification de remise en état, Plannification des inspections, ….

Calcul de fiabilité en fonction du

temps

Probabilité de défaillance pour chaque défaillance prise

en compte dans l’EPS

Nouvel ensemble

d’événements de base

Réévaluation du Modèle EPS

Niveau 1 pour chaque année de

vie restante

Résultats de l’EPS

de niveau 1 pour chaque

année de vie restante

Coupes minimales

Analyse

Résultats finaux

Points clés

Etudes de sensibilité

Programme « durée de vie »

et Programme de maintenance

Modifications de certains paramètres

Analyse de sensibilité

« usual » PSA

Ageing PSA

Component failure rate

Constant

Change in the failure rate could be included in the PSA model.

Surveillance and testing Influence of testing is only on the status « functioning / non functioning » or the component (« up or down »)

Effects of tests on failure ratevalues are modelled.

Maintenance Only unavailability period are taken into account.

Effects of maintenance on failure rate values are modelled

Repair, replacement Not taking into account Effects on f ailure rate values are modelled.

Risk assessment A constant safety level is computed. A risk level depending of the plant age is computed.

Maintenance efficiency Contribution to the risk level of the unavailability period is assessed.

The maintenance influence for the ageing management is too assessed.


Ageing and PSA – 2nd approachStatistical approach (Vesely, NPAR program )

• Data from PSA : equation of core damage frequency C as a function of input data qi (component unavailability, failure probability of structures, occurrence frequency of initiating events)• Ageing implies an increase ∆qi ⇒ ∆C• Taylor development applied to ∆C as a function of ∆qi

• Sensitivity coefficients S ij =j° derivation of C divide by j. • They can be computed from reference model of the Level 1 PSA indepently of ageing effect (possible with CAFTA, not with RSW).• Assumptions made by Vesely :

– Linear evolution of the failure rate,– Taylor development: order 2– Validity of these assumptions ?

qqqqSqqqSqqSqSC ninkji kjiijk

ji jiiji ii ∆∆∆∆++∆∆∆+∆∆+∆=∆ ∑∑∑

>>>........... 21...123


Ageing and PSA : comparaison by Westinghouse• Statistical approach

– Easy and fast to implement.– It allows to apprehend the effects of ageing on the core damage

frequency.– Main results:

• with regard to the passive equipment, of which the probability of failure except effects due to ageing is generally rather weak, even if their failure probability increases significantly, their contribution remains nevertheless generally weaker than those of the active components.

• Simulation method– More complex to implement.– It makes possible to obtain results for each year of life of the plant and

especially to apprehend the impact not only of maintenance and test programs, but also their planning in time for each equipment.

– Main results:• importance of planning in the time of the actions of maintenance

and tests. The method of simulation indeed highlighted a "cyclic" evolution and a big amplitude of results variation whose origin came from planning in time from the tests and maintenance,


Other possible R&D tasks

• Consistency between PSA input data and structural reliability results

– Level 1 PSA → data are linked to a functional failure mode– Structural reliability → data are linked to a mechanical degradation

or a physical phenomenon. And we have assumptions about the environment.

– Different scale → size effect ?– Which method for the aggregation ?

{Component ; mechanical degradation } → {Component ; Failure mode } → Functional Equipment

• Ageing– Coupling of different ageing phenomena– Taking into account effect of inspection and testing process.


CEA organisation

R&D for NUCLEA

R ENERGY

DEFENSE

R&Tfor

INDUSTRY

Fundamental Research STAFF

R&T for INDUSTRY

15%

R&D for NUCLEAR ENERGY

35%

Fundamental Research

17%DEFENSE

33%


NUCLEAR ENERGY DIVISION

NUCLEAR DEVELOPMENT & INNOVATIONP. Bernard

R&D FOR NUCLEAR INDUSTRYJ-C. Bouchter

SIMULATION & EXPERIMENTAL TOOLS

P. Ledermann

CLEAN-UPE. Pochon

CROSS PROJET UNITF. Pupat

VALRHOCenter

L. Martin-Deider

DSP

DPI

DRSN

DMN

DM2S

DPC D2S

DDCO

DRCP

DIEC

DCP

DTE

CADARACHECenter

P. Amenc-Antoni

SACLAYCenter

J-P. Pervès

Finance Div.M. Bedoucha

Nuclear Safety & Quality Div.

J-P. Langlois

Pro

gra

m M

anag

emen

t D

ivis

ions

DTAP

DGI

DEC

DER

DTN

Nuclear Energy Division Dep. Dir : R. LUCATJ. Bouchard Sc. Dir : Y. Vandenboomgaerde

Com. Dir : F. Bazile

SOME CONSIDERATIONS REGARDING PSA AND

AGEING ANALYSIS

Mirela Nitoi, Ilie TurcuInstitute for Nuclear Research Pitesti,

Romania

16-17 September 2004, Petten

Ageing - the continuous time-dependent degradation of materials due to normal service conditions, which include normal operation and transient conditions (IAEA 1990).


Ageing Management

• Design• Environment• Operation• Maintenance• Risk• Monitoring


The ageing management should have to be developed for all types of components, as:

-active components (pumps, valves, motors, circuit breakers)-passive elements (structures, piping, electrical cable)-large infrastructure systems (buildings and facility-support systems)


The ageing aspects are very important for:

•the components from the coolant agent•the components which are necessary to shut-down the reactor and to maintain it in a safe state•the components which are necessary to minimize the exposure in case of an accident


PSA application in ageing study

• The assessment of impact of components and structures ageing to plant safety level

• The prioritization based on risk of ageing management activities


Ageing Analyses Phases

• Identification of critical components• Identification and evaluation of ageing

effects• Development of mitigation methods


The significance of ageing

• Component level • System level• Core-melt frequency level• Accident consequences level


Mitigation methods

• Safety significance of component• Its expected ageing degradation• Operating and maintenance procedures• Economical aspects


The sensitivity analysis performed tried to assess the changes in system unavailability due to assumed increase in failure probability because of components ageing.

The study focuses on the evaluation of ageing impact on system safety level rather than making an initial assessment or analysis of aging, including the identification of aging causes, mechanism, and effects.


Study Problems

• lack of specific data - in the process of components failure rates allocation the generic data were used – the Cernavoda data collection system started few years ago, and the collected data are not very numerous

• the amount of failure rate due to ageing available and the information on the degree of component degradation (usually obtained by surveillance and condition monitoring) is very limited


Assumptions

• it was assumed the same ageing rate for all the components (even there is a short term and a long term ageing)

• the failure rates of components follows the traditional bath-tub curve

• to quantify the effects of age-related degradation, we use the linear aging model for all the components


The safety importance was studied at system level with a qualitative and quantitative fault tree analysis. Minimal cut-sets identified shows which parts of the system are most important for the system unavailability. The system unavailability is evaluated with and without taking into account the possible ageing effects of components.

The analysis provides information on the importance of increasing in failure rates (increase due to ageing) to the system safety.


Class IV is an a.c. power supply system which provides electrical power to the process, control, instrumentation and lighting loads through the plant. The system supplies the equipment which can tolerate long interruption in feeding, without affecting the personnel or the plant safety.

The system is supplied either the unit or the service transformers from the external grid and the 24kV generator system.


The electrical system was chosen for the study because there are a lot of cables and for these types of equipment there is no planned preventive or corrective maintenance, and they are originally designed to reach the end of plant life with an adequate safety margin.

We try to see the effects of the ageing, in order to see at what level of the failure rates increase, the effects of ageing will be significant to system availability.


BUS SHORTCIRCUIT28%

BUS DE-ENERGIZED17%

MAIN TRANSFORMER TR02 FAILURE & NO

TRANSFER ACHIEVED26%

MAIN TRANSFORMER TR01 FAILURE AND

SISTEM TRANSFORMER TR05 FAILURE

1%

SISTEM UNIT TRANSFORMER TR03

FAILURE & NO TRANSFER ACHIEVED

1%

MAIN TRANSFORMER TR01 FAILURE & NO

TRANSFER ACHIEVED26%

MAIN TRANSFORMER TR02 FAILURE AND

SISTEM TRANSFORMER TR05 FAILURE

1%

WITHOUT THE EFFECT OF COMPONENT AGEING INCORPORATED IN THE MODEL

Top Value: 7.03986781476137E-05

BUS SHORTCIRCUIT

18%

BUS DE-ENERGIZED

18%

MAIN TRANSFORMER TR02 FAILURE & NO TRANSFER

ACHIEVED20%

UNISOLATED SHORT CIRCUIT

FROM LOADS13%

SISTEM UNIT TRANSFORMER TR03 FAILURE & NO TRANSFER

ACHIEVED10%

MAIN TRANSFORMER TR01 FAILURE & NO TRANSFER

ACHIEVED19%

FAILURE OF BOTH SUPPLY

CIRCUIT BREAKERS

2%

WITH THE EFFECT OF COMPONENT AGEING INCORPORATED IN THE MODEL

Top Value: 2.53708640641628E-03

The study should be further refined, as the aging factor should be different for the active and passive components (the different ageing rates of components influence the failure rates and the importance of components).


Conclusions

• some components have shown a definite change in their characteristics due to ageing - there are components which have a small contribution in a basis PSA analysis and can become major components in an ageing analysis

• the fault trees must be developed to a resolution level which permits the ageing effects modelling

• there should be developed systematic procedures for the incorporation of ageing effects in PSA


Conclusions (cont.)

• there should be made sensitivity analysis which can prioritize the major contributors on ageing risk

• the mean frequency of core damage should be assessed at every 5 years, using models and parameters which include ageing effects

• before the truncation of the cut-sets, it should be made an evaluation to establish if the sets with ageing effects has the potential to became dominant contributor


Conclusions (cont.)

• ageing of components and structures causes the failure rate to increase with time

• component and structure can be prioritized with regard to where aging control is important

• aging monitoring programs can be instituted to monitor the most risk-important aging contributors


References• Kaisa Simola - Reliability methods in nuclear power plant ageing

management, Helsinki, May 1999• * * * - Evidence of Aging Effects on Certain Safety-Related

Components, NEA/CSNI, September 1995• IAEA- TECDOC-547, The Use of Probabilistic Safety

Assessment in the Relicesing of Nuclear Power Plants for Extended Lifetimes, Vienna, 1990

• IAEA- TECDOC-540, Safety aspects of nuclear power plant ageing, Vienna, 1990

• * * * - Aged material collection, Workshop, Belgium, June 1995


Incorporating Aging Effects into PSA/PRA Feasibility and Benchmark Exercise

Project Proposal

Milan PatrikChristian Kirchsteiger

Kick-off meetingSeptember 17, 2004

Contents

• Project objectives

• Main Tasks

• Deliverables

• Discussion

Project objectives

• Evaluation of available methods and approaches • Survey and evaluation, state of the art, methodology problems

• Discussion of potential APSA applications• Evaluation of impact of components ageing on safety level

• End of life operation, life extension / Ageing management, RI ISI, maintenance support, etc./

• Demonstration of impact on risk assessment results• Data preparation /selected type/

• Models for selected active and passive components

• Risk evaluation

Project Objectives

• Demonstration of feasibility• selected approaches for modeling of active/passive components failures

• Identification of further research needs

• Evaluation • effort and “effectiveness” implied by different approaches

in incorporating ageing effects into PSA tools

Project Main Tasks - Proposal

• Task 1

• WEB site operation• Under development

• Project description /objectives, tasks,etc./

• News, meetings, publications, results

• references, links, etc.

• www.energyrisks.jrc.nl


• Task 2

• Available Methods and Approaches• survey, evaluation and documentation, state of the art /?

• Physical models for different ageing mechanisms

• methodology problems /?

• dependencies

• data collection and elaboration issues

• /what data, how to collect, how to analyze, data sources/

• discussion of further research needs


• Task 3

• Ageing PSA Applications• Identification of potential applications

• End of life operation, life extension

• Ageing management, identification of weak points, etc.

• Risk assessment, importance evaluation, maintenance, RI ISI, etc.

• Way of incorporating ageing effects into PSA models for particular applications

• Reliability models, data, PSA model modifications

• Data collection issues

• Identification of data needed and elaboration for particular application

• Discussion of limitation and uncertainties


• Case Study - Task 4• Selection of topics for case studies

• Data collection and analysis /selected type of component/

• Use of ageing models models for active components

• Selected types

• Use of ageing models for passive components

• Selected pipes

• etc.

• Preparation of data, models, incorporating of ageing effects • PSA models are supposed to be used for some case study applications


• Case Study - Task 4• Evaluation

• feasibility and effectiveness for particular approaches

• also a discussion on changes to standards, guidance and regulations


• Deliverables• State of the art report /appendix on selected methodological problems/

• Recommendations how to incorporate ageing effects into PSA Applications

• Simplifications

• Steps for particular applications, data and models to be used

• ? Procedure / guidelines for incorporating ageing effects ?

• Data collection and analysis report• Guidelines / ?Procedure? how to provide failure rates for APSA

• Case studies evaluation report /appendix for each case study/

• Web site on ageing PSA - APSA Network

Schedule


09/2004 - 04/2005Ageing PSA /APSA/ Applications

Task 3

09/2004 - 04/2005Available Methods and Approaches, Methodological Problems, etc.

Task 2

09/2004 - 05/2006Establishment and Operating of APSA Website

Task 1

Schedule

Incorporating Aging Effects into PSA Applications

04/2006 - 06/2006Evaluation of the project, proposals for next activities

Task 5

12/2004 - 04/2006Selected APSA Applications –Case studies, Evaluation

Task 4

Kick-off meeting

• Incorporating Aging Effects into PSA Applications

• Topics for discussion • Which tasks do you support ?

• What scope of particular tasks is interesting for you ?

• What is your view of case studies ?

• What deliverables are useful?

• Comments to proposed schedule…

Kick-off discussion

• Incorporating Aging Effects into PSA Applications

• Discussion follow up• Draft of work program will be sent to all potential participants

• comments

• decision on participation in specific working groups

• idea about scope of participation

• Working groups

• Definition of detail work plan

RELKO Ltd. Engineering and Consulting ServicesRELKO Ltd. Engineering and Consulting Services

1/9

Workshop on Incorporating Ageing Effects into PSA Applications, JRC, Petten, September, 16-17, 2004

PSA and PSA Applications in Slovak Republic

Zoltán KovácsRELKO Ltd, Engineering and Consulting Services

Bratislava, Slovak Republic


2/9


Contents

u General PSA informationu Ageing studies u Incorporating ageing effects into PSAu Project preferences and conclusions


3/9


General PSA information

- Each Slovak NPP has prepared level 1 and 2 PSA study for full power operation and low power and shutdown operatingmodes.- Based on the PSA models the riskmonitor (EOOS) was developed and implemented for V1 and V2 NPP at J. Bohunice.- The Safety Monitor for the Mochovce NPP is under development.


4/9



- Riskmonitor is used in the control room by operators, by safety department and the maintenance department of the plant.

- Riskmonitor is applied for identification of high risk configurations, for calculation of AOTs and for calculation of risk profile for planned maintenance activities during refuelling outage


5/9



- Guidelines of IAEA and NUREGs are used in development of PSA applications. - ASME RA-S-2002 is also applied at the present time. This standard is a technically adequate document in this area.- The PSA studies and PSA applications are periodically updated after plant modifications. Quantitative safety goals are defined for safety systems, CDF and LERF.- Ageing effect is not implemented in the PSA. There is no such requirement from the regulatory authority.


6/9


Ageing studies

- No ageing studies are performed to support PSA activities.

- Analyzing data for trends and ageing is being performed at the present time.

- The data are analysed to assess the presence of time trends in failure rates and probabilities

- Modeling a trend normally involves detailed mathematics


7/9


Incorporating ageing effects into PSA

- Ageing is not addressed in the PSA- This task is planned for the future- The existing data collection project will support this activity


8/9


Project preferences and conclusions

- The main objective: to clarify and work out the methodology for APSA in this project.

- RELKO proposal of case studies:

1) Data analyses to asses the presence of time trends in failure rates and probabilities, comparison of various approaches and to show how to interpret the output and translate it into the quantities needed for PSA.

2) Implementation of ageing into the PSA models for the selected passive and active components and systems.


9/9


Project preferences and conclusions

- Advanced techniques are needed that address modeling of time trends(ageing). Examples must be worked out and provided within the project to guide the analysts.

- Ordinarily, the analyses involve complex mathematical techniques. There are various approaches, some of them implemented into computer software. The project should focus on the interpretation of outputs for application in PSA.

L. Burgazzi FIS-NUC 1

RISK INFORMED APPLICATIONS

• 1.1 In Italy there are not NPPS in operation (after the Chernobyl accident the Government took the decision to shutdown the existing NPPS and to stop the construction of new ones). As a consequence the activity and the research related to PSA aspects underwent a significant reduction: PSA studies have mostly been focused on non reactor nuclear facilities and particularly have concerned the application of the probabilistic approach with regard to the safety assessment of international fusion projects, as e.g. fusion reactor ITER (International Thermonuclear Experimental Reactor) and experimental facility IFMIF (International Fusion Materials Irradiation Facility).

• 1.2 In general the safety assessment studies are being performed bas ing on the methodology of a traditional nuclear Probabilistic Safety Assessment that can be traditionally split into three more phases: the hazard analysis, the reliability analysis and the consequence assessment. So far the current commonly adopted PSA standards are followed (NUREG, e.g. NUREG CR-2300 PRA Procedure Guide, IAEA), accounting for the specificities of the facility.


RISK INFORMED APPLICATIONS cont’d

• 1.3 Within these projects normally the risk studies are being performed in the light of the updated design of the facility, without keeping them as a “living” entity. Specific safety criteria should have to comply with the licensing requirements of the hosting country. For majority of cases they are not site specific studies.

• 1.4 Ageing effects have not been considered in these studies.


AGEING STUDIES PERFORMED

• 2.1 No studies about ageing effects on PSA have been conducted, only a survey on the ageing mechanisms involving structures and components. Degradation of the function/performance of components in time (e.g. pumps, compressors, valves) and thus decrease of the reliability function is envisaged, in terms of reliability models.

• 2.2 Ageing mechanisms of materials of relevant NPP components (reactor pressure vessel, containment, piping, steam generator, valve and pump body for instance).

• 2.3 Irradiation embrittlement, fatigue, erosion, corrosion, stress corrosion cracking, thermal ageing, creep. No estimations of failure probability of components under estimation were made.

• 2.4 No studies about active components were performed, only the partconcerning the materials (e.g. valve body).


INCORPORATING AGEING EFFECTS INTO PSA AND USE OF APSA APPLICATIONS

• 3.1 Actually PSA ageing is not considered in the previous studies.

• 3.2 At present it is envisaged to incorporate passive components into the PSA studies to address the ageing effects, with reference for example to material embrittlement mechanisms of radiation exposed components (like vessel, targets). Selection of the components should be made on the basis of experience and engineering judgement.

• 3.3 Degradation mechanisms leading to component failure have been incorporated implicitly directly in the failure model, through the exponential reliability function. For the assessment of components and system failure probabilities fault tree technique has been adopted and RISK SPECTRUM code has been utilised.

• 3.4 Up to now ageing effects have not been addressed for active components.


INCORPORATING AGEING EFFECTS INTO PSA AND USE OF APSA APPLICATIONS cont’d

• 3.5 Current models are not suitable to address the ageing effects. The adoption of the Weibull distribution (for describing the wear out part of the bathtub curve) instead of the commonly adopted exponential distribution to model the failure is envisaged.

• 3.6 Focal points should be: ageing mechanisms and appropriate modelling of failure rate vs time, analysis of CCF among components environmentally caused, structural reliability assessment of structures and components, study of system/component performance function vs time, residual life assessment.

• 3.7 Data collection is not focused on ageing issues.

• 3.8, 3.9 At present adoption of APSA for maintenance and inspection optimisation purposes are not planned, even though this is one of the most relevant applications.


PROJECT PREFERENCES AND EXPECTATIONS

• 4.1 The main expectance is the construction of a consistent reliabil ity model for incorporating the ageing effects into the reliability studies in order to get a more realistic picture of the behaviour of the components during time and to achieve useful information for maintenance optimisation.

• 4.2 Passive and active components should be studied in the present project: while passive components can be treated by means of the structural reliability, active components, for which not so many studies have been performed, deserve more attention. The tasks should include:- ageing degradation mechanisms analysis- data collection or data inference process- ageing degradation mechanisms probabilistic model (focus of the activity)- simulation on a system (active one)

• 4.3 In principle there are not preclusions to the participation in almost all the tasks with the exception of the aspects pertaining to the structural reliability, pointing rather to the performance degradation evaluation of components during time.Reliability assessment of passive systems, currently underway, is linked to this research activity.

British Energy 1. General Questions

• BE Operate 7 AGRs (twin unit NPPs) and 1 PWR• Main use of PSA

– Support to the safety case

– Support for ALARP arguments

• For 2 AGR NPPs, PSA supports a Risk Monitor. • For PWR, Risk Informed In service Inspection and

Risk-Informed testing


• PSAs run on Risk Spectrum software• All plant faults, internal and external hazards

modelled• The models are fully maintained and have a

complete set of documentation• Living PSA

– Formal update every 3 years – Major plant / safety case changes as they arise


• Advancements in PSA methodologies and applications are reviewed

• Advancements adopted where there is safety benefit

• PSA Assessed against IAEA and ASME standards / guidelines

• Broad consistency demonstrated with these


• PSA is assessed against British Energy Nuclear Safety Principles

• Risk criteria in the form of a dose-frequency staircase

• Consistent with NII Safety Assessment Principles• No requirement to address ageing effects in PSA

British Energy 2. Ageing Studies Performed

Passive Components• Fuel

– All safety cases assume End-of-Life properties– Deterministic success criteria


Passive Components• Graphite core

– Graphite Core Safety Cases presented for each station– All degradation mechanisms addressed including:

• Changes in material properties• Cracking of bricks

– Deterministic success criteria


Passive Components• Pressure vessel penetrations, in-vessel structures

– Component Lifetime Assessments performed– All degradation mechanisms reviewed (Creep-Fatigue

limiting for AGRs)– Review of degradation to present and forward

prediction to End-of-Life– Adequate integrity at End-of-Life or tolerable

consequences of failure demonstrated– Deterministic success criteria


Passive Components• Pipework (Steam and Feed and Cooling Water

Systems)– Maintained in line with the requirements of the relevant

codes (e.g. ASME)– Integrity criteria dependent on consequences of failure– Deterministic success criteria


Passive Structures• Boiler (steam generator) tubes

– Component failure probability derived and included in PSA

– Statistical treatment of experimental data – Probability of water-side and gas-side wall thinning

combining to result in tube failure following pressure transients


Active components • Safety System Reviews

– For all significant safety systems– Carried out every three years– Plant performance reviewed against required safety

duty– plant reliability over review period compared with

reliability data in the PSA (for the most significant plant items)


Active Components• SSRs (continued)

– Where plant is degraded, a programme of repair and replacement is established

– if appropriate, maintenance and testing intervals are amended.

– If repair/replacement not appropriate, the reduced reliability is incorporated in the PSA and the impact on risk is reviewed

British Energy 3. Incorporating Ageing Effects in PSA

• Active Components – Ageing is primarily addressed by trending of active

component reliabilities – Data taken from System Safety Reviews

• Passive Components– Ageing of boiler tubes explicitly modelled for a number

of AGRs– For other passive components, BE has yet to decide

whether to incorporate ageing effects into PSA models


• In general, degradation mechanisms addressed deterministically.

• Boiler tube failure mechanisms are addressed probabilistically. – Conditional probabilities of failure are determined by

statistical treatment of failure mechanisms.


• Ageing effects for active components in PSA

– System Safety Reviews (SSRs) performed for safety significant systems

– Carried out every three years – PSA plant reliability data amended to reflect ageing /

degradation affects


• Would you agree to the opinion that ageing cannot be addressed by models based on current PSA structure?

• BE has incorporated ageing into its PSAs for some components (boiler tubes).

• Since component failure resulted in a significant change in fault progression, this was not trivial

• Widespread modelling of ageing mechanisms using this approach would add significant complexity and may not be feasible


• What further actions and developments, based on your experience and needs, are necessary to be performed to properly address ageing in PSA studies and applications?

• We do not have any views on this.


• How is your data collection system focused on ageing issues?

• Data from SSRs used for trending– to identify degradation in plant performance

– to identify the need for repair / replacement.


• Have you used or do you plan to use PSA for ageing management and maintenance and inspection activities?

• We do not currently use PSA for these activities


• In which applications and activities do you see a potential for use of APSA and what applications are of your main interest?

• We are still seeking to learn the benefits we can obtain from the use of APSA.

British Energy 4. Project Preferences and Expectations

• What is your expectation from this project/network and what kind of information would you like to receive from it?

• We are looking at this project to see what benefits there may be for continued operation to End-of-Life and for lifetime extension.


• Which case studies should be performed within the network, how should be corresponding tasks of work defined and organized?

• We have not yet formed an opinion.


• In which individual tasks or case studies would you like to participate, what are your requirements for these tasks and how would your participation link to your own current research programs?

• We need to understand more about the project before we determine the extent of our participation.

1 of 16

JRC Network on Incorporating Ageing Effects into PSA Applications

Contribution to Project Kick-off Meeting

Attila BareithVEIKI Institute for Electric Power Research

16-17 Sept. 2004, JRC Petten

2 of 16APSA/KICK-OFF

Section 1 - Risk Informed Applications4 Major PSA applications for the Paks NPP

– Risk based prioritisation and evaluation of safety enhancement measures

– Risk monitoring– PSA based event analysis of operational events– Development of a risk prediction system to be used during

emergencies

4 Trial applications– Review of specific Tech. Specs. requirements

– Development of risk based safety indicators– Evaluation of operator training programme on simulator


Section 1 - Risk Informed Applications, cont’d4 Ongoing or planned activities

– Risk based ranking of plant components and systems– PSA based safety assessment for power uprate– Monitoring maintenance effectiveness– Risk informed evaluation of lifetime extension

4 PSA quality– Internationally accepted guidelines followed (IAEA Safety Series,

NRC Procedure Guides)

– PSA standards were not applied/available– Guidelines or standards do not guarantee quality– Internal and external reviews used extensively


Section 1 - Risk Informed Applications, cont’d4 Living PSA programme for Paks NPP

– Annual PSA update• Models• Results• Documentation

– Data updated less frequently– Ageing effects not considered yet

4 No explicit probabilistic safety criteria– General safety goal: CDF < 10-4 and LERF < 10-5

– Some application specific safety criteria (e.g. CCDP < 10-6)


Section 2 - Ageing Studies Performed4 Comprehensive ageing management studies in the past 6

years for equipment of high safety significance– Ageing management programme (AMP) based on IAEA

methodology– AMP covers operation and design– Typical contents of an AMP review report (operation)

• Description of AMP process• Operation• Maintenance• Periodic tests and inspection• Analysis and evaluation


Section 2 - Ageing Studies Performed, cont’d

4 Reactor pressure vessel4 Reactor vessel internals4 Reactor vessel supports4 CRDM-s4 Reactor cooling system4 Piping connected to RCS4 Steam generators4 Main circulating pumps4 Pressurizer4 Main gate valves4 Hydro accumulators4 Selected pumps, valves and connecting

piping

4 Emergency diesel generators4 Containment structure4 Containment penetrations (mechanical

and electrical)4 Containment isolation valves4 Containment liners4 Feed water piping, pumps, valves4 Safety related heat exchangers4 Piping supports4 Spent fuel pools4 Containment ventilation system

Example of components included in AMP


Section 2 - Ageing Studies Performed, cont’d4 Major potential degradation mechanisms identified

– Low cycle fatigue– Irradiation embrittlement– Stress corrosion cracking– Erosion-corrosion– Boric acid corrosion

– Thermal ageing– Erosion– Microbiologically induced corrosion– Other local forms of corrosion (pit, crevice,..)


Section 2 - Ageing Studies Performed, cont’d4 Typical results of AMP includes identification of relevant

degradation mechanisms and the associated consequences4 No risk based prioritisation of degradation mechanisms yet4 No attempt made so far to describe the effect of

degradation mechanisms on equipment failure rate by probabilistic models


Section 2 - Ageing Studies Performed, cont’d4 Examples of measurements and experiments performed in

the framework of AMP– Radiation embrittlement– Stress corrosion cracking of stainless steel components– Corrosion of high strength steels– Thermal ageing

– Fatigue– Environmental qualification of cables

4 The above measurements and experiments had no PSA related objectives


Section 3 - Incorporating Ageing into PSA4 Ageing effects not considered in Paks PSA4 Trial applications to evaluate ageing effects on test interval4 No decision yet on component types to be addressed in

ageing PSA– Focus on active components first– Passive components not excluded either

4 Degradation mechanisms not addressed in Paks PSA4 Simple reliability model to describe test related wear-out

of active components (pumps and valves):

+⋅λ=λ

10010

pi


Section 3 - Incorporating Ageing into PSA, cont’d4 Need for significant advancement in the PSA modelling of

ageing – Theoretical foundations– Hypothesis checking based on available data

4 Recommendations on PSA applications can follow after advancement in modelling and data support


Section 3 - Incorporating Ageing into PSA, cont’d4 Proposed ingredients of an ageing PSA developmental process

– Selection of component/equipment types– Identification/selection of degradation mechanisms – Development of reliability models (hypotheses) for a probabilistic

description of ageing– Definition of data requirements for reliability models– Review of available data from experience– Verification of reliability models and selection of appropriate models if

allowed by available data– Conduct of experiments to support model verification– Collection of data in the long run– Development of tools for full scope PSA modelling of ageing– Restructuring and quantification of PSA with ageing incorporated.


Section 3 - Incorporating Ageing into PSA, cont’d4 Data

– Data collection at Paks not focused yet on explicitly revealing ageing effects

– Raw data can be helpful - effort intensive– AMP is expected to yield insights– Chances are to make improvements in data collection and evaluation

(integrated into AMP)

4 Use of PSA for ageing management, maintenance and inspection– Use of risk information (including PSA) for evaluating maintenance

effectiveness at Paks - ongoing– Use of PSA for ageing management - currently under consideration


Section 3 - Incorporating Ageing into PSA, cont’d4 Potential applications of ageing PSA

– Use of PSA information to rank components for ageing management

– Prediction of safety level (CDF, LERF) with ageing PSA models– Early warning of potential deteriorating performance– Development of recommendations for remedial actions in

• Ageing management programme• Maintenance or inspection activities

– Risk follow-up


Section 4 - Project Preferences

4 Expectations– Comprehensive review of state-of-the art– Description of available and evolving methods for probabilistic

ageing modelling– Recommendations for most promising methods– Recommendations for ageing PSA applications– Access to field experience on raw and processed data

– Definition of further actions needed to make advancement

4 Case study– To be discussed


Section 4 - Project Preferences, cont’d4 Interests

– Each project task in principle

4 Task 1– No ageing reliability models developed by VEIKI– Focus: review of internationally accessible methods

4 Task 2– Active participation of each partner is seen necessary

4 Task 3– Uncertainties

• Maturity of available methods• Data accessibility

4 Task 4– To be focused on most promising PSA applications

ROBERTAS ALZBUTAS

1

LEI interests and proposals in ageing research area

Vaidas MATUZASLithuanian Energy Institute/Ignalina NPPLaboratory of Nuclear Installation Safety

Breslaujos 3, LT-3035 Kaunas, Lithuania

Phone: (+370 7) 40 19 73Fax: (+370 7) 35 12 71

E-mail: [email protected]

2

PSRA Group at LEI

•Level 1 and Level 2 Probabilistic Safety Assessment of Ignalina NPP;

•Probabilistic analysis of external events;

•Uncertainty and sensitivity analysis;

•Reliability parameters estimation and software development;

•Single failure analysis for complex technical systems;

•Risk minimization and reliability control methods development and application;

ROBERTAS ALZBUTAS

3

PSA Status at Ignalina NPP

•PSA Level 1 study started in 1991

•PSA Level 2 study started in 1999

•Living PSA & maintained

•Ageing effects are not directly assessed

•Some indirect assessment of ageing effects (LPSA, data updating process using Bayes procedures)

4

LEI interests

•Information exchange

•Development and testing of software

•Research in aging statistical estimation area

•Development of ageing study case, based on selected INPP systems e.g. Emergency power supply system

ROBERTAS ALZBUTAS

5

Expectations from the project

•Methodological description of the APSA approach

•Identification of the most important PSA software improvements needed to address ageing effects

•Identification of FT/ET modifications needed

•Extension of current PSA software (e.g. Risk-Spectrum)

6

LEI proposals/contribution to APSA network

•Aging case study on specific INPP system•Development of aging statistical analysis procedures/methods•Testing of developed methods on case studies•Implementation of developed methods into existing IgnalinaNPP PSA model•Providing Ignalina NPP statistical data for the project purposes•INPP PSA model is available for the APSA network

APPENDIX III

Questionnaire Responses

EUROPEAN COMMISSION DIRECTORATE GENERAL JRC JOINT RESEARCH CENTRE Institute for Energy

Nuclear Safety Unit - Probabilistic Risk & Availability Assessment Sector

Incorporating

Ageing Effects into PSA Applications APSA Network

Questionnaire Responses

September 2004

1. GENERAL QUESTIONS RELATED TO USE OF RISK INFORMED APPLICATIONS

1.1 Please, briefly present the status of the use of probabilistic risk assessment in your

country/company/institution for risk informed applications. What applications are being used or are under consideration?

UJV (CZ) For a long time, our company has been completely responsible for development

and application of NPP Dukovany PSA model (4x440 VVER-213 reactor). We have been also partially responsible for PSA effort regarding other Czech and Slovak plants (Temelín, Bohunice, Mochovce). The spectrum of applications it a very typical one and it includes most of the most typical applications (risk monitor, evaluation of plant modifications, risk and reliability based maintenance, evaluation of plant Tech-Spec. etc.).

VTT (FIN) In Finland PSAs exist for all operating NPPs and also for the new one that is under construction. VTT is presently reviewing as a consult some topics such as Human Reliability and System Analysis of the PSA for the new unit Olkiluoto 3. In general the PSA related research at VTT includes methodology and quality development as well as reviewing of PSAs. The related risk informed applications that are developed or researched at VTT include: PSA for shutdown, risk informed methodologies for PSA, RI-ISI pilot studies, human reliability analysis, software reliability analysis, preparation of a PSA quality template and data base development.

IRSN (FR) In France PSA is not a regulatory requirement, but PSAs have been performed on a voluntary basis by IRSN (technical support of the Safety Authority) and by EDF (utility), respectively for the 900MWe and for the 1300MWe standardized series of PWRs. The PSA results have been used for significant safety improvements of the existing plants. Some important applications for IRSN and EDF are: the reduction of risk during shutdown situations, the periodic safety reassessment of the plants the probabilistic analysis of events the improvement of technical specifications and of operating procedures Moreover EDF is also using PSA for optimization of plant operation (maintenance). Besides, PSA is introduced since the beginning of the design of the new plants (EPR project) as a complement of deterministic analysis.

CEA (FR) No risk-informed applications in CEA. CEA skills on PSA has been developed from works jointly with Electricité de France, and for their needs. A design Level 1 PSA is under development by CEA teams for GFR (under the GenIV framework). Some requirements on the use of PSA for helping the assessment of the expected lifetime prediction could be added⇒ interest for the subject. Design level 1 PSA are too under development for some research reactors. CEA’s interest for the subject is linked to our activities in support to EDF, Framatome, IRSN… A collaboration with JAERI is beginning this year.

EDF (FR) There is a great variety of PSA applications at EDF, in terms of both their purposes and their development maturity. They can be classified in three categories:

- Applications for the operating plant fleet, to assess the safety level (periodic safety review – plant vulnerabilities identification).

- Applications for assisting and substantiating the design of future plants

(system definition). - Applications for optimizing operating practice (probabilistic analysis of

plants events, maintenance optimization, OTS reassessment). In addition to these generic applications for all the country’s plants as a whole, EDF is currently developing the use of PSA for helping day-to-day unit operation. Periodic testing optimization and safety classification based on PSA results are applications currently developed in the USA plants and which are part of our technical survey.

VEIKI (HU) The main areas of PSA applications for the Paks NPP in Hungary have so far been the following:

- Risk based prioritisation and evaluation of safety enhancement measures - Risk monitoring - PSA based event analysis of operational events - Development of a risk prediction system to be used during emergencies

Additiona lly, trial applications of PSA models and approaches have been made to:

- Review specific Tech. Specs. requirements - Develop risk based safety indicators - Evaluate adequacy of operator training at the plant’s full scope simulator

Ongoing or planned activities cover: - Risk based ranking of plant components and systems - PSA based safety assessment for power uprate - Monitoring maintenance effectiveness - Risk informed evaluation of lifetime extension

ENEA (I) In Italy there are not NPPS in operation (after the Chernobyl accident the Government took the decision to shutdown the existing NPPS and to stop the construction of new ones). As a consequence the activity and the research related to PSA aspects underwent a significant reduction: PSA studies have mostly been focused on non reactor nuclear facilities and particularly have concerned the application of the probabilistic approach with regard to the safety assessment of international fusion projects, as e.g. fusion reactor ITER (International Thermonuclear Experimental Reactor) and experimental facility IFMIF (International Fusion Materials Irradiation Facility).

LEI (LT) Ignalina NPP have been developing Level 1 PSA model since 1991. This model is used for assessment of various modifications before implementation. Now implementation of diverse shutdown system into INPP unit 2 started and incorporation of this system into PSA model is under consideration. PSA model was used for 300 mm piping RI-ISI study, optimization of diesel generators testing intervals and other applications.

INR (RO) The Cernavoda plant probabilistic model for risk assessment has been developed in several stages during the last fifteen years. At present, the Level 1, full scope model is updated to the operating plant configuration and is used for risk informed evaluations during plant operation. The PSA study was used mainly:

- as a source of risk knowledge (for each topic, the risk contributors were clearly described)

- in assessment of plant design (the design contributors were prioritized, as the design deficiency)

The main tool developed for performing PSA applications in Cernavoda NPP is the risk monitor, which will be used to evaluate the effects of changes in system configuration, component status due to maintenance or component failure and

changes in the environment external to the plant, which may cause an initiating event. Some other applications are under consideration:

- for accident management (the development of accident procedures) - for risk-based operation applications (risk prioritization of components,

technical specifications evaluation, risk-focused data collection, precursor evaluation, risk-based maintenance and testing optimizations, risk-based aging evaluations)

The PSA study can be used also as a risk training tool (the training presentation packages are organized as educational courses). PSA can be used connected with Reliability centered maintenance (RCM) –for developing and optimizing a maintenance program. PSA is used to support NPP periodic safety review – the identification of real cost-effective improvements to safety. Examples of CPSE 95 (Cernavoda Probabilistic Safety Evaluation study, 1995, before the start of plant operation) results:

- 40 design changes implemented during commissioning: RSW, RCW, Chilled Water system, Instrument Air, ECCS, Feedwater and condensate system, moderator and end shield cooling system

- additional inspection tests for moderator, end shield cooling, liquid zone control, fire water system, PHTS overpressure protection

- actions included in APOP/ OM - additional commissioning tests (test of batteries to assure that are able to

provide supply to moderator pony motor for more than 40 minutes, test to assure that main feedwater pump can run with Steam generator at atmospheric pressure for at least 10 minutes)

- requirement for specific deterministic analysis (Calandria behavior after loss of end shield cooling inventory, PHT behavior after one pressurize relief valve spurious opened)

Examples of Cernavoda NPP design changes taking into account PSA results: - Back-up cooling system, in case of loss of Service Water, to class III DG

and chilled water system; - Local air tank to moderator and SDCS HX control valves for loss of IAS

followed by loss of class III; - Automatic closure (total or partial) of moderator and SDCS HX control

valves for dual computer failure followed by loss of class III (on DG’s sequencer first step).

- ECC improvements like: - dousing tank level triplicated measurements; - closure of MV71, 72, 79, 80 on low level water tank; - check valve tests.

A PSA study for the testing/research reactor TRIGA at INR Pitesti is under development. The study is considering the current usual PSA applications.

RELKO (SK) Each Slovak NPP has prepared level 1 and 2 PSA study level 1 (and level 2) for full power operation and low power and shutdown states. Based on the PSA models the riskmonitor (EOOS) was developed and implemented for V1 and V2 NPP at J. Bohunice. The safety monitor for the Mochovce NPP is under development. Riskmonitor is used in the control room by operators, by safety department and the maintenance department of the plant. Riskmonitor is applied for identification of high risk configurations, for calculation of AOTs and for calculation of risk profile for planned maintenance activities during refuelling outage.

Forsmark NPS (SWE)

Outputs from PSA are used to find weaknesses in the plant design. PRA are used to evaluate the daily safety status of the plant to develop a safety index. PRA has been used to develop some criterias for allowable outage time and for acceptance of maintenance during operation. PRA are performed but not fully accepted in the following areas:

- prioritation of modifications- the safety value are calculated - RI-ISI

Test optimisation. British Energy (UK) British Energy operates 7 Advanced Gas Cooled Reactors and 1 Pressurised

Water Reactor. For these NPP, the PSA is primarily used as support to the safety case and to support the presentation of ALARP arguments. In addition, for 2 AGR NPPs, the PSA supports the use of a Risk Monitor. For Sizewell B (PWR), there is some use of Risk Informed In service Inspection and Risk-Informed testing.

Rolls Royce (UK) Rolls-Royce has applied PSA/PRA since the late 1970s as a complement to the Design Justification (DJ). Applications of PSA have included:

- Providing an assessment of the level of safety of the plant for comparison with explicit standards, i.e. safety criteria such as those published by the Nuclear Installations Inspectorate (NII).

- Identifying the most effective areas for improvement of the plant, e.g. in support of the justification that risks have been reduced to a level that is As Low As Reasonably Practicable (ALARP).

- Supporting the design process, e.g. by assessing design and operations changes or by setting targets.

- Supporting the operation of the plant, e.g. by assessing tests/trials, or by supporting maintenance including Risk Based In-Service Inspection (RBISI). Work is underway to implement a Risk Monitor to make such support more efficient.

LANL (USA) Our use of probabilistic risk assessment generally is used as a qualitative tool from a modified process method described in AIChE, Guidelines for Hazard Evaluation Procedures (Reference 1) for our Process Hazard Analysis documents. This method is consistent with DOE Standard-3009-94 (Reference 2) and DOE-HDBK-3010-94 (Reference 3), which are guidance documents used to meet regulation requirements. The method allows for consideration of potential effects upon workers, the public, and the environment (receptors), which is necessary to provide details for SAR accident analysis, screening and updating. Emphasis of this method is on consequence rather than frequency and both are binned.

LNPP (RUS) - Formally PSA in Russia is one of legal study challenged by regulatory body to be presented in the frame of NPP in-depth safety assessment for licensing proposes;

- Year to date the Leningrad NPP owns two PSA level 1 Models (Unit 1 and Unit 2);

- LNPP PSA applications are mainly safety upgrade measures development and safety benefit justification

- Any PSA applications (Living PSA use) are under consideration (in the frame of Sweden-Finland-LNPP joint-cooperation programme (LISA-C), started in 2003)

NMRI (JAP) In our institute, we originally used PSA for the safety evaluation of Marine Reactor Systems, Marine reactor of Nuclear ship Mutsu, and Advanced reactor systems MRX, DRX which are in design stage. Recently, we have been applying

the PSA method to Ordinary ships. In that analysis, we evaluate the occurrence frequencies of various marine accidents, and evaluate the Cost-effectiveness of new safety systems for the prevention of marine accidents.

Vattenfall (GER) - In Germany Risk informed applications are not officially accepted - On lower level risk informed applications are conducted for

- TechSpec modifications, - to determine the importance of events, - to determine the influence of plant modifications on safety

Statwood Consulting (USA)

I can only tell about two related projects that I am currently associated with, the NRC Industry Trends Program and the Mitigating System Performance Index. [See Eide and Zeek, 2004, PSAM 7 Proceedings, pp. 1158-1162.] We use a linear approximation of the full PRA model to give a quick approximation of the plant-specific PRA with updated parameters. We use the most recent 3 years of plant-specific data (for mitigating systems) or the most recent one year of industry data (for initiating events), and a constrained noninformative prior, to obtain Bayesian estimates of the current parameters and to monitor the current state of the plant or industry. We have considered other priors, especially mixture priors, but have chosen not to try to persuade others to use these less familiar priors. [See Atwood & Youngblood, 2004, PSAM 7 Proceedings, pp. 444-449.] We anticipate seeing up-and-down bounces more than long-term adverse trends, but either could be detected.

1.2 What is the nature and quality of risk assessment models and documentation? Do you follow any particular established standards/guidelines? If yes, what is the origin of this standard, and what are your views on its adequacy and applicability in your specific applications?

UJV (CZ) During the long term NPP Dukovany Living PSA project (since 1996, approximately), the quality, credibility and potential for applications of NPP Dukovany PSA has been gradually increased up to the level, which is considered being adequate for many applications and risk informed decisions with independent specialists as well as plant staff. Within this process, we have been continually following IAEA standards (defined in Safety Series, TECDOCs etc.). Recently, the ASME-2 standard has appeared being interesting alternative and extension to IAEA approach and we have been trying to follow it too.

VTT (FIN) In Finland the authority concerning nuclear power plants, Radiation and Nuclear Safety Authority of Finland (STUK), has published several regulatory guides on nuclear and radiation safety. These guides do not provide provide the actual risk assessment models, so they must be taken from elsewhere. I am not aware of what are the specific risk assessment models that are applied in Finnish PSAs. The regulatory guides present the requirements for the documentation. Two most relevant Finnish regulatory guides that involve risk assessment issues are YVL 2.8 “Probabilistic safety analysis in safety management of nuclear power plants” (28.5.2003) and YVL 3.8 “Nuclear power plant pressure equipment. In-service inspection with non-destructive testing methods” (22.9.2003). YVL 2.8 states that the licensee or applicant for an operating licence has to submit level 1 and 2 PSAs to the STUK. YVL 3.8 states that in the drawing up of inspection programmes for Safety Class 1, 2, 3 and 4 piping and Class EYT (non-nuclear) piping as well as in the development of inspection programmes for operating plants, risk-informed methods shall be utilised to ascertain the inclusion in the inspection scope of those components posing the highest risk. Furthermore YVL 3.8 states that the in-service inspection basic requirements shall be according to ASME Boiler and Pressure Vessel Code, Section XI, Rules for In-service Inspection of Nuclear Power Plant Components, Division 1, (ASME Code, Section XI), and deviations from the Code shall be justified and it shall be demonstrated that a corresponding level of safety and reliability can be achieved. The regulatory guides specify in wich areas PSA based methods shall be applied. The guides do not provide detailed guidelines on the utilization of PSA.

IRSN (FR) The original French studies are very detailed and did not follow a specified standard. Since two PSA teams are working in parallel (IRSN and EDF), it makes it possible to have a very complete mutual external review. This detailed external review, including independent assessments, is carried out for each important application. More recently the safety authority required to formalize the development and use of PSA, and a Basic safety Rule (RFS 2002-1) has been written.

EDF (FR) We have developed an internal standard for PSA development (level 1 internal events at power and shutdown) which follows the requirements of a Basic Safety Rule (non prescriptive) issued in 2002 jointly by EDF and the Safety Authorities (good practices – acceptable methods). We intend to develop a specific standard for PSA applications.

VEIKI (HU) Both the level 1 and level 2 PSAs for NPP Paks have been performed in accordance with internationally accepted guidelines, especially that of the IAEA (Safety Series) and NRC (Procedure Guides). Standards were not yet available at the time of performing these studies. PSA quality is affected by many factors, e.g. adequacy of methods, data and tools; level of expertise in PSA; plant knowledge; QA procedures; peer reviews, etc. Thus guidelines or standards in themselves do

not determine PSA adequacy/quality. ENEA (I) In general the safety assessment studies are being performed basing on the

methodology of a traditional nuclear Probabilistic Safety Assessment that can be traditionally split into three more phases: the hazard analysis, the reliability analysis and the consequence assessment. So far the current commonly adopted PSA standards are followed (NUREG, e.g. NUREG CR-2300 PRA Procedure Guide, IAEA), accounting for the specificities of the facility.

LEI (LT) PSA model was developed according to IAEA standards/guidelines. Quality of models and documentation is acceptable for various applications. Level 1 Ignalina NPP model and documentation was reviewed by IAEA IPSART review missions twice in 1999 and 2001.

INR (RO) The Probabilistic Safety Evaluation Study for Cernavoda plant (CPSE) started in 1988, under IAEA support, and each phase of the PSA study was reviewed by an IPERS mission. The Romanian PSA study follows IAEA guidelines. The recommendations and the guidance provided by previous IAEA expert missions and reviews were carefully implemented. The PSA study is developed under a Quality Assurance Program. The CPSE Quality Assurance Program is consistent with the principles and requirements of the IAEA and with the recommendations for safety of nuclear installations. Objective of CPSE study “as-build”:

- to provide a safety design verification of the Cernavoda NPP Unit 1 using probabilistic methods and to identify the most effective areas of improvement

- to identify those initiating events and accident sequences that dominate the total core melt frequency and have the main contribution to the different plant damage states considered

RELKO (SK) Guidelines of IAEA and NUREGs are used in this area. Standard for PRA for NPP applications, ASME RA-S-2002 is also applied in the present time. This standard is a technically adequate document in this area.

Forsmark NPS (SWE)

To perform PRA our PSA-model is used. As PSA-models are updated by a 3- year project, we have to decide for each application which models are being used. Our PSA are not based on any specific standard. It is based on the experts experiences and some national general positions on content and detail ness. On a high level the PSA follows a PSA-handbook developed by the inspectorate. We have had some hope that the review from the inspectorate should bring some standardization in to the process. But as the inspectorate hires different consultants to review the studies they have not been standardized so far. Performing PRA-work has not so far developed specific demands into the PSAs.

British Energy (UK) All of our PSAs run on Risk Spectrum software. The PSAs model all plant faults, internal and external hazards. The models are fully maintained and have a complete set of documentation. Our PSAs are assessed against IAEA and ASME standards / guidelines. Broad consistency has been demonstrated with the standards / guidelines for the applications to which the PSAs have been put.

Rolls Royce (UK) When adopting the use of PSA, various US standards were used to inform our approach, e.g. NUREG/CR-2300. This has been updated by review of specific standards on particular methods and by consideration of the needs of regulators. Other PSAs, e.g. that for Sizewell B, also influence the requirements.

LANL (USA) See above. It is a very effective tool for our applications, which predominately deals with processes in a research and development environment rather than a standard operating environment that is more routine and more solid reliability

data exists. LNPP (RUS) - Safety series No.50-P-4 (7, 10, etc) by IAEA; Russian standards and

guidelines by Gosatomnadzor; PSA guidelines by SKI (Sweden) and STUK (Finland), etc.

- Adequacy and applicability are quite acceptable (during model development phase); still known living PSA procedures and applications (e.g. based on IAEA-TECDOC-1200) are good for initial mind (personal opinion).

Vattenfall (GER) - There exists a Standard on how to perform a PSA BfS-KT-16/97 Methods for PSA BFS-KT-18/97 Data for envent and fault trees

- The Standard is the result of BfS Working Group on PSA for Kernkraftwerke

- Standard gives only methods on how to perform PSA - No guidance and criteria for risk informed applications


In the programs mentioned above, we use SPAR models, NRC standardized models, which give results similar to the plants’ own PRA models, but which are more consistent to each other. They are continually being improved to make them more closely match the plants’ individual systems and procedures.

1.3 How do you ensure consistency with state-of-the art? Is the risk assessment maintained as a “living” entity? If so, how often is it updated? Are there any risk goals/ risk criteria that are used for specific applications? If so, are they qualitative or quantitative and are there any compliance requirements?

UJV (CZ) The PSA study for NPP Dukovany is really maintained as a “living entity”. There are two basic directions of PSA model development followed in NPP Dukovany Living PSA – 1)addressing of changes in plant design and operation 2)addressing of new methodological developments, new results of thermohydraulic analysis, new sources of data etc. There are some criteria being used for specific applications /TechSpecs evaluations, RI ISI, etc./

VTT (FIN) The consistency with state-of-the art is ensured by closely following and, when necessary, applying new relevant method development to PSA. The regulatory guide YVL 2.8 states the follow ing: The licensee has to regularly update the PSA to correspond to the operating experience. In addition the PSA model shall be updated always when a substantial change is made in the plant design or in the procedures or when a new substantial risk factor is found. The licensee shall maintain a database of the reliability of safety related components, initiating events and human errors. STUK reviews the updates of PSA and evaluates their acceptability. The regulatory guide YVL 2.8 demands in case of an accident the fulfillment of the following numerical design objectives to cover the whole nuclear power plant during design and construction:

- The mean value of the probability of core damage is less than 1E–5/a. - The mean value of the probability of a release exceeding the target value

defined in section 12 of the Government Resolution (395/1991) must be smaller than 5E–7/a.

I do not know of other risk goals/ risk criteria that are applied in Finland in PSA. Also the risks assessed for piping systems in RI-ISI are those of core damage.

IRSN (FR) As explained above, the mutual reviews ensure the quality of the studies. EDF (FR) Our PSA models (one per series) are updated every 10 years according to the

Periodic Safety Reviews of our plants. We take account of operating experience, design and operation evolution. We have no regulatory probabilistic goals or criteria. We use “reference values” which are considered as acceptable by both EDF and Safety Authorities in the applications. For example : the acceptable integrated risk increase in case of safety function unavailability is 1E-07 (the CDF is about 1E-05/plant.year) ; this value may be used for example to define AOT in OTS PSA application. The evaluation of such a risk increase due to the unavailability of a system must be done taking into account the “limits” of PSA models and the uncertainties related to (often need sensitivity analysis and deterministic complementary considerations – asked by Basic Safety Rule).

VEIKI (HU) There is a living PSA programme in place. It includes an annual update of PSA models, results and documentation. The great number of plant modifications (safety improvement measures) made this frequent update necessary. Although safety criteria are not yet in use in Hungary for PSA, the PSA applications listed under question 1.1. have had some specific, application dependent safety goals. For example, prioritisation and evaluation of safety enhancement measures were performed to evaluate whether core damage frequency could be lowered below the internationally accepted value of 10-4 per year for NPPs of the same vintage as the Paks plant. During PSA based event analysis each event that has a conditional core damage probability larger than 10-6 per year is consider as a precursor to core damage. Also, a core damage index

(CDI) is calculated each year and compared with the nominal value of the base PSA. Risk based evaluation of surveillance test intervals within review of Tech. Specs. requirements aimed at the lowest average core damage frequency that could be possible achieved.

ENEA (I) Within these projects normally the risk studies are being performed in the light of the updated design of the facility, without keeping them as a “living” entity. Specific safety criteria should have to comply with the licensing requirements of the hosting country. For majority of cases they are not site specific studies.

LEI (LT) Updating of PSA model once a year is defined in procedures. Up to now 5 phases of Level 1 PSA model are completed and continious model development is on-going. This is also linked to new deterministic plant response studies available.

INR (RO) The PSA study was updated after each IPERS mission, in order to include the recommendation of the reviewers. CPSE Phase A:

- a limited scope Level 1 PSA 1988-1992 - event trees (9 initiating events) - fault trees (17 systems) - Per Review by IAEA IPERS Mission, October 1990 (preliminary)

CPSE Phase B: - “as designed”: 1993-1995 - event trees (34 initiating events) - fault trees (33 systems) - Peer - Reviews by IAEA IPERS Mission, July 1995 (unit 1 commissioning)

CPSE Phase B: - “as built”: 1995-1997 (unit 1 commercial operation) - event trees (40 initiating events groups) - fault trees (36 systems)

Cernavoda Unit 1 PSA – “as operated”: 2000-2003 The Cernavoda data collection system starts few years ago, and when we have plant specific data, the reliability component data base will be reviewed and the study will be updated. The PSA study is intended to became a living PSA in the future. The damage core frequency (below 1.E-06 CANDU, 1.E-05 PWR) is the typical criterion for PSA level 1 study. Risk significance criteria: when the failure rates are varied then the risk change methods needs to be assessed as to whether it is significant or not. The risk change will be judged as insignificant if it is within the statistical uncertainties associated with the risk result. If the statistical uncertainties are not calculated then the factor 1/x ¼ will be used which is characteristic of PSA uncertainties. For the optimization of the component testing it was considered that any component with a Fussel-Vesely importance greater than 0.005 is regarded as potentially risk-significant. A component which has a Risk Achievement Worth of 2 or more is regarded as potentially risk-significant.

RELKO (SK) The PSA studies and PSA applications are periodically updated after plant modifications. Quantitative safety goals are defined for safety systems, CDF and LERF.

Forsmark NPS (SWE)

The consistency is received by using consultants that has broad experiences. It is also received by some national working groups that develop common positions on some issues. We are just now in a face with large update of our studies so we do not have specific work focusing on” living status”. When the up-gradings are

ready we shall up-date the PSAs to be refelt the actual status of the plant. We have common goals for for CDF and on Risk for radioactive releases from each plant -- 10-5 and 10-7. Concerning criteria’s for different applications we have no specific criteria’s. We develop different relative criteria’s for the different application cases.

British Energy (UK) We constantly review advancements in PSA methodologies and applications. Where we perceive there to be sufficient safety benefit from such developments, we adopt such advancements. Is the risk assessment maintained as a “living” entity? Yes The PSAs are updated every 3 years. Yes, we use the British Energy Nuclear Safety Principles. These specify risk goals / criteria in the form of a dose-frequency staircase and are consistent with the NII Safety Assessment Principles.

Rolls Royce (UK) PSAs are reviewed an updated periodically. In addition, a database of changes, including methods, is maintained including estimates of the effects (positive or negative) on risk. For significant changes in design or operation, a specific PSA is produced. Regulation is by both principles and by safety criteria. For the work undertaken by Rolls-Royce both the civil regulator (UK Health and Safety Executive (HSE) Nuclear Installations Inspectorate (NII)) and the Ministry of Defence (MoD) Naval Nuclear Regulatory Panel (NNRP) are applicable. Both define similar requirements. The NII Safety Assessment Principles (SAPs) present the civil expectations. Key princip les are: there is a tolerability limit on exposure to radiation during normal operation; there is a tolerability limit on accident risks; and, exposure and risks should be reduced to a level that is As Low As Reasonably Practicable (ALARP).

LANL (USA) Updates are done annually in a summary manner. Daily changes are reviewed through the Unreviewed Safety Question Process (Reference 4). Process Hazard Analyses are updated as necessary. Risk is evaluated in all these documents and any perceived increase in risk must obtain NNSA/DOE approval.

LNPP (RUS) - Annual update of PSA report (as fore configuration permanent changes the model is updated before (during safety measures verification stage); in the beginning of the year the PSA model data are updated on the base of previous year data analysis).

- Risk goal is 1E-05 1/a (risk criteria is 1E-04 1/a) - Compliance requirements are qualitative (see above).

* Actually, living PSA is not always keeping in mind mentioned criteria. We use risk increase factor (RIF) or risk decrease factor (RDF) (as well as others) to assess importance for safety.

NMRI (JAP) There are some quantitative criteria in maritime field. We referenced these criteria.


The above programs are only trying to detect risk-significant degradations, not to build a full CDF meter. When the program is implemented, we will update the plant-specific results quarterly and the industry results at least annually. The criterion for the plant-specific mitigating systems is to compare ∆ CDF (=current - baseline) with 1E- 6/yr or 1E-5/yr or 1E- 4/yr. The criterion for the industry - wide trends in initiating events has not yet been established.

1.4. Is there any recommendation/requirement in the guidelines you have used to address ageing effects in your PSA models and applications? In the overall PSA guidelines (IAEA), addressing of aging effects is generally recommended, however, a more detailed guidance is not given?

UJV (CZ) There is not any recommendation. VTT (FIN) Besides updating the PSA when necessary, there are to my knowledge no other

recommendations/ requirements in the related Finnish guidelines to address the effects of ageing.

IRSN (FR) The PSAs are “living”, updated at least for each periodic safety review of each plant series (10 years). There are no general quantitative Safety objectives. However for specific applications some indicative objectives can be used. These particular objectives are generally given in terms of relative or qualitative results. There is no requirement for addressing ageing effects.

CEA (FR) Not at the present. NB: a bibliographical study on the use of ageing model in PSA has been done by CEA.

EDF (FR) The standard and the Basic Safety Rule does not address the incorporation of ageing into PSA.

VEIKI (HU) No.

ENEA (I) Ageing effects have not been considered in these studies. LEI (LT) Ageing effects were not modeled directly in PSA. INR (RO) In the IAEA guidelines there is no specific and detailed recommendation for the

addressing ageing effects in PSA. Due to : - the lack of specific data (we use generic data in the study – the

Cernavoda collection system started few years ago, and the collected data are not very numerous)

- the amount of failure rate available and the information on the degree of component degradation (usually obtained by surveillance and condition monitoring), is very limited the ageing effects were not considered in the component reliability data.

RELKO (SK) Ageing effect is not implemented in the PSA. There is no such requirement from the regulatory authority.

Forsmark NPS (SWE)

No.

British Energy (UK) No. Rolls Royce (UK) There are requirements to address all stages in a plant lifecycle but no specific

requirements to incorporate ageing effects into a PSA. Specific applications, such as a design modification or change in planned lifetime, would require a review and update to ensure that the risk estimates were still applicable.

LANL (USA) Not to my knowledge. LNPP (RUS) So far we didn’t use any factors addressing of ageing effects. We use so-called

error factors for reliability parameters (estimated statistically mainly). Trend analysis guideline and its applicability for prognosis aims are under development (by the way LISA-C scope).

Statwood (USA) No.

2. QUESTIONS RELATED TO AGEING STUDIES PERFORMED

2.1 Please, briefly present what studies related to assessment of ageing effects have you performed or do you plan to perform?

UJV (CZ) Under the auspice of IRSN/DES/SERC, feasibility study of an accelerated ageing test program for motor operated valves was performed by NRI Rez Division of Integrity and Technical Engineering. The decision about continuation of the project is about to be made. 2)The new project covering all aspects of long term nuclear power plant operation with special consideration of NPP Dukovany specific features is under preparation. In this project, ageing phenomenon is going to play a very significant role.

VTT (FIN) Most of my research work at VTT are related to the structural integrity of power plant components. In several projects I have studied the ageing of power plant components due to different degradation mechanisms by applying structural mechanics, fracture mechanics and probabilistic methods. These projects have included numerous defect growth simulations, both deterministic and probabilistic, and literature surveys. The analysis tools I have used include FEM code ABAQUS, probabilistic fracture mechanics based codes PIFRAP and ProSINTAP, as well as some deterministic fracture mechanics based in-house analysis codes. Through some projects for private Finnish energy utilities I am also familiar with the application of the ASME code. In some research projects and in a pilot study I have gained experience of RI-ISI, PSA I know only through literature surveys. I plan to continue research work in these fields by widening my knowledge of and gaining experience on modelling the ageing degradation of power plant components, probabilistic analysis methods, RI-ISI and possibly PSA.

IRSN (FR) In the frame of feasibility study one sensitivity PSA calculation was done to illustrate possible impact to CDF from aging and surveillance programme of active components. Then four tasks were proposed to evaluate the feasibility of APSA in the frame of the pilot project :

- performing the Aging FMEA for several types of active components (valves),

- development of the statistical algorithms for reliability parameters estimation in case of operational data,

- preparation of accelerated aging reliability tests for selected types of components (MOV),

- elaboration of physical reliability models for passive components (pipes).

First three tasks were performed in 2002-2004. CEA (FR) Studies for the lifetime extension of the Phenix Nuclear Power Plant

- Support to EDF and Framatome for the lifetime extension (reactor vessel, containment,...)

EDF (FR) The main applications up to now are related to maintenance optimization: - RCM applied to pipes (PSA model was only used to assess pipe

importance to safety - RAW evaluation – ageing was not incorporated in PSA. Ageing effect was assessed with degradation mechanisms simplified models (kinetics)

- SG surveillance and maintenance optimization (probabilistic approach but no links with PSA model)

VEIKI (HU) In the past 6 years comprehensive ageing management studies have been performed for high safety related equipment. The component specific ageing

management programme (AMP) review was based mainly on the IAEA methodology according to TR: 338. Appendix 1 shows examples for the contents of the AMP review programme

ENEA (I) No studies about ageing effects on PSA have been conducted, only a survey on the ageing mechanisms involving structures and components. Degradation of the function/performance of components in time (e.g. pumps, compressors, valves) and thus decrease of the reliability function is envisaged, in terms of reliability models.

LEI (LT) Statistical aging analysis of Ignalina NPP electrical components, 1998. Diesel generators aging analysis, 2002.

INR (RO) Several years ago we performed a study, based on a literature survey, dealing with the impact of component ageing on probabilistic modelling and we tried to identify the solutions to take into account the ageing effects into PSA analyses. We perform a sensitivity study regarding the effects of ageing on system safety level. We try to evaluate the safety importance of assumed increases in the components failure probabilities. We consider that if a raise of a certain component failure rate doesn’t have a major effect, the ageing analysis for that component is expected to have a small importance. The sensitivity analysis focuses on the evaluation of ageing impact on system safety level rather than making an initial assessment or analysis of aging, including the identification of aging causes, mechanism, and effects. The study is intended to be further refined, as the aging factor should be different for the active and passive components (the different ageing rates of components influence the failure rates and the importance of components).

RELKO (SK) No such analyses are performed to support PSA activities. Analyzing data for trends and ageing is being performed at the present time.

Forsmark NPS (SWE)

We don’t have such plans.

British Energy (UK) Our safety cases all assume End-of-Life properties for fuel and graphite core, based on a consideration of ageing / degradation effects. For significant passive components / structures (e,g, pressure vessel penetrations and all in-vessel structures), Component Lifetime Assessments (CLA) are carried out. These demonstrate adequate integrity at End-of-Life or demonstrate tolerable consequences of failure. With respect to ageing / degradation, pipework (Steam and Feed and Cooling Water Systems) is maintained in line with the requirements of the relevant codes (e.g. ASME), taking into account the consequences of failure. For boiler tubes (boilers are the equivalent of steam generators), ageing studies are carried out to determine the probability of failures at End-of-Life. Ageing of active components is reviewed by System Safety Reviews

Ohio St. Univ. (USA) - Time dependent effects under periodic maintenance - Use of periodic surveillance of active components to mitigate the aging

effects of passive components LANL (USA) Ageing studies have been and are being performed on various specific

components. Aging effects on glovebox gloves have been performed. Storage of radioactive waste over time has been simulated in aging studies and I am sure that there are more that I do not know about. These are conducted as R & D efforts.

LNPP (RUS) Plan is to perform regress analysis based on current statistic for component group selected on the base of PSA model importance analysis results. Phases of work are 1) Importance analysis 2) Data selection 3) Statistical regress analysis for reliability parameters

4) Model quantification for each future time cut-set using prognosis (trend) data 5) Comparison analysis (with safety criteria) and so on. Study is based on idea that annual change of component failure rate means trend of ageing (“no ageing physical mechanism” study approach).

Vattenfall (GER) - No PSA Ageing study has been performed - An extensive monitoring of components concerning ageing is performed,

e.g. - I/C-systems, determine the trend of failure rate - electrical equipment, determine the trend of failures,

once Weibull distribution has been used to decide if Ageing is the reason

- determine fatigue of mechanical components Statwood Consulting (USA)

Around 1990, we did a study with detailed maintenance records from one site. One of the most useful data sets was for 12 motor-operated valves over 10 years, with over 40 failures. This allowed aging to be seen clearly. [Atwood, 1992, Rel. Eng. & System Safety, vol. 37, pp. 181-194.]. Around 1993, we used a probabilistic structural mechanics code to simulate many possibilities for an initial crack in a weld, and concluded that the weld was more likely to leak than rupture, and that any ruptures are more likely early in life rather than late in life. The effect on the PRA was then investigated. [Phillips et al., 1994, J. Pressure Vessel Technol., vol. 116, pp. 295-301]. In 1995, I took part in a review of aging studies from 6 countries, which tentatively concluded that active components generally do not present an aging problem at well-maintained plants. [Magleby et al, 1996, NUREG/CR-6442, INEL-95/0654, NEA/CSNI/R(95) 9.].

2.2 What components and mechanisms were of your main interest? UJV (CZ) The feasibility study was focused on a very specific class of components of

French NPPS – motor operated valves located on discharge lines of primary circuit emergency cooling systems.

VTT (FIN) The components I have mainly studied are NPP RPVs, safe-ends and piping, and the degradation mechanisms the effect of which I have mainly analysed are intergranular stress corrosion cracking (IGSCC), fatigue induced cracking (mechanical, thermal and environment affected) and material fatigue (low-cycle).

IRSN (FR) Active components which have an important contribution to the global risk. All aging mechanisms possible to appear and to develop during the operation were considered in the Aging FMEA.

CEA (FR) - Reactor vessel : metal damage indicator based upon radiation dose, PTS - Containment: ageing of the concrete

EDF (FR) See a table presenting the main components and degradation mechanisms: Component (Passive)

Degradation (ageing) Mechanism

Failure mechanism

SRA ? Other ageing studies

RPV (Reactor Pressure Vessel)

Irradiation embrittlement Thermal ageing

Brittle fracture Yes Yes (unirr. Parts)

Steam Generator (tube bundle, support plates)

stress corrosion IGA wastage fretting wear

Tube leak or break

yes

Cast elbows Thermal ageing (austeno-ferritic steel)

Fast fracture: Tearing initiation / unstable propagation

Partial (material stat. properties)

Piping (Main Coolant System)

Fast fracture: Tearing initiation / unstable propagation

Yes (safety coefficients)

Yes(RCM)

Piping (secondary system)

Flow accelerated corrosion (carbon steel) Other types of corrosion

Fast fracture: Tearing initiation / unstable propagation Thickness loss

yes Yes(RCM)

Pressurizer no Yes Some ageing phenomena: Irradiation embrittlement, thermal ageing, creep, fatigue, corrosion, wear, loss of prestressing, environment effects, concrete degradations, differential settlements…

VEIKI (HU) The following is a list of systems, structures and components (SSCs) included in the full scope aging management studies prepared between 1995-2001 for the Hungarian NPP AMP:

- Reactor pressure vessel - Reactor vessel internals - Reactor vessel supports - CRDM-s - Reactor cooling system - Piping connected to RCS

- Steam generator - Main circulating pump - Pressurizer - Main gate valve - Hydro accumulator - High safety significance pumps, valves and connecting piping - Emergency diesel generator - Containment structure - Containment penetrations (mechanical and electrical) - Containment isolation valves - Containment liners - Feed water piping, pumps, valves - Safety related heat exchangers - Piping supports - Spent fuel pools - Containment ventilation system

A limited scope AMP review have been performed for some non safety related component as well, like turbine condensers, high pressure feed water pre-heaters, turbines. The list of the most important potential degradation mechanisms is as follows:

- low cycle fatigue - Irradiation embrittlement - Stress corrosion cracking - Erosion-corrosion - Boric acid corrosion - Thermal ageing - Erosion - Microbiologically induced corrosion - Other local forms of corrosion (pit, crevice,..)

ENEA (I) Ageing mechanisms of materials of relevant NPP components (reactor pressure vessel, containment, piping, steam generator, for instance).

LEI (LT) Electrical components, diesel generators. INR (RO) The study focuses on the behavior of cables and circuit breakers and their failure

mode (their contributions to the achievement of top event increases with the incorporation of ageing effects).

RELKO (SK) not applicable. Forsmark NPS (SWE)

So far none.

British Energy (UK) See above. Rolls Royce (UK) All primary pipework and vessels have been subject to ageing studies. These

studies have focused on the structural integrity of the components and primarily considered fatigue as a failure mechanism arising from the temperature, pressure and system initiation transients that have occurred in the past and may occur in the future. Additional investigations have looked at potential for corrosion of particular components under specific conditions. This has been done to identify for example:

- Timescales to particular events such as loss of sufficient material to constitute a risk of a leak.

- Range of sizes of leaks and their relative probability. - Changes needed to reduce the potential for corrosion.

Some of these investigations have also been incorporated into specific risk models.

Ohio St Univ. (USA) None specific. LANL (USA) The above. LNPP (RUS) Components are determined based on importance analysis (simply using “Risk

Spectrum” for instance). Ageing mechanisms (if do you mean process) study will be important if there is lack of statistics. For example, pressurized pipes/vessels break (leak) and other passive component failures related to initiating event causes.

NMRI (JAP) Pump, Heat exchanger, Air operated valve, Motor operated valve, relief valve, Tank Erosion, corrosion, Wear out, degradation of a function.

Vattenfall (GER) - An extensive monitoring of components concerning ageing is performed, e.g.

- I/C-systems, determine the trend of failure rate - electrical equipment, determine the trend of failures,



1990 study: Components that gave the most failures events (i.e. the most data). For most component types we had trouble seeing aging with the data we had not enough components or long enough age span. We did not identify mechanisms. 1993 study: Crack growth in a piping weld. 1995 study: Whatever the existing studies considered, a great variety of active components.

2.3 Have you identified which mechanisms are the most serious in terms of critical impact on the function of specific NPP components or their parts?

UJV (CZ) An approximate rough prioritisation of ageing mechanisms was done in the feasibility study based on previous experience. Have you made any estimation of components failure probability in relation with specific mechanisms or their combinations? No detailed estimation has been made. Such estimation was defined as one of the main goals of the study, the feasib ility was evaluated for. What data and models have you used then? It has been is supposed that Weibull distribution may be an appropriate tool for explicit description of ageing potential. However, the task of transfer of simulation observations data into the values of distribution parameters was evaluated being rather difficult.

VTT (FIN) I have identified the criticality of the degradation mechanisms for the surveyed components by using available failure data literature, on the other hand in projects for private Finnish energy utilities the customers have provided this information. I have made probabilistic time dependent crack growth simulations for IGSCC and fatigue (mechanical and thermal) induced cracking, the results of which have been component failure probabilities due to respective degradation mechanisms. I have not performed component failure probability analyses for joint action of several degradation mechanisms, altough through literature I am familiar with several of such models. The models I have used have mainly been based on probabilistic fracture mechanics, e.g. a randomised version of the Paris-Erdogan equation for fatigue induced cracking. I have also performed a few statistical estimations based on operating experience data. I presented a selection of the analysis codes I have used in the NPP component analyses in my answer to question 2.1. Besides open literature, the data I have used has come from laboratory research performed in the related projects at VTT and in projects for private Finnish energy utilities from the customers.

IRSN (FR) 1) In the frame of Aging FMEA the importance of each aging mechanism and probability of its occurrence were analyzed by expert judgments, as well as effectiveness of periodical tests and preventive maintenance programs. 2) Not yet. 3) We would like to use tree types of data: operating experience of French PWR, periodical tests and preventive maintenance data and results of laboratory reliability tests.

CEA (FR) Have you made any estimation of components failure probability in relation with specific mechanisms or their combinations? What data and models have you used then?

EDF (FR) Have you made any estimation of components failure probability in relation with specific mechanisms or their combinations? What data and models have you used then?

VEIKI (HU) Have you identified which mechanisms are the most serious in terms of critical impact on the function of specific NPP components or their parts? Yes, see answer to question 2.2 above. Have you made any estimation of components failure probability in relation with specific mechanisms or their combinations? No. What data and models have you used then? N/A.

ENEA (I) Irradiation embrittlement, fatigue, erosion, corrosion, stress corrosion cracking, thermal ageing, creep. No estimations of failure probability of components under estimation were made.

LEI (LT) Failure causes were not explicitly analysed.

Plant specific failure data were used and known statistical models were applied, including trend analysis.

INR (RO) There are ageing specific failure modes for components as corrosion, mechanical fatigue, thermal fatigue, thinning, faulty insulation, natural deterioration, drift. For the breakers dirty contacts and oxidation of contacts are considered age related failures. Corrosion leads to loss of protective coatings. Natural deterioration leads to failure of fuses, resistor, switches, coils. Thinning is caused by erosion-corrosion. There is a possibility that the degradation of the isolation cable to lead to open circuit or short circuit failure mode for the cable. We did not performed systematic studies to address the impact of ageing mechanisms and their modelling aspects in PSA specific for Cernavoda plant. The plant is in operation from 1996 and a component ageing management program is established recently.

RELKO (SK) Not applicable. Forsmark NPS (SWE)

No.

British Energy (UK) Have you identified which mechanisms are the most serious in terms of critical impact on the function of specific NPP components or their parts? Yes. Have you made any estimation of component failure probability in relation with specific mechanisms or their combinations? In general, no. A conservative deterministic approach is usually adopted which assumes component failure if identified criteria are not satisfied. However, for boiler tubes, explicit failure probabilities have been derived from a consideration of specific failure mechanisms. What data and models have you used then? A statistical treatment was adopted based on experimental data to determine the extent of boiler tube wall thinning. This determined the probability of water-side and gas-side wall thinning combining to result in tube failure in the event of boiler pressure transients.

Rolls Royce (UK) FMECA type studies have addressed impact of particular failure modes and ageing mechanisms on component function by expert elicitation however analytical models have not been developed to enable a quantitative assessment to be performed.

Ohio St Univ. (USA) No. LANL (USA) Have you made any estimation of components failure probability in relation with

specific mechanisms or their combinations? What data and models have you used then? The studies conducted have been of an R & D nature and experimental rather than data analysis.

LNPP (RUS) See above. NMRI (JAP) TIRGALEX Vattenfall (GER) - An extensive monitoring of components concerning ageing is performed,

e.g. - determine fatigue of mechanical components


No.

2.4 What kind of ageing studies/analyses have you performed for active components? UJV (CZ) The feasibility study mentioned above is oriented particularly to the class of

active components. VTT (FIN) None. IRSN (FR) See answer for 2.1. EDF (FR) None. VEIKI (HU) No other ageing studies/analyses have been performed than those evaluations included in

the AMP. Appendix 2 shows an example of the results from the AMP studies. ENEA (I) No studies about active components were performed, only the part concerning the

materials (e.g. valve body). LEI (LT) See 2.1. INR (RO) To quantify the effects of age-related degradation on active components, the

linear aging model (ref. NUREG/ CR-6415) can be used. In this model, the failure rate of a component λ (t) is expressed as a sum of two independent failure rates, one associated with random failure, λ 0, and the other associated with failures due to aging α , so λ (t) = λ 0 + α t The assumption used by the linear aging model are:

- the component failure rate is proportional to the amount of deterioration - both the occurrence time and the severity of deterioration are considered

to be random - the occurrence of deterioration is described by a stationary Poisson

process RELKO (SK) Not applicable. Forsmark NPS (SWE)

We have done very little, almost nothing.

British Energy (UK) For all significant safety systems, System Safety Reviews are carried out every three years. These review plant performance against the required safety duty, including a comparison of plant reliability for the most significant plant items against the reliability data in the PSA. Where these reviews identify that plant is degraded, a programme of repair and replacement is established and, if appropr iate, maintenance and testing intervals are amended. Where repair/replacement is not appropriate, the reduced reliability is reflected back into the PSA where the impact on risk is reviewed.

Rolls Royce (UK) Quantitative ageing studies for active components have considered fatigue and fracture mechanisms. However qualitative assessments of corrosion and EAC mechanisms have also been carried out for active components as appropriate.

Ohio St Univ. (USA) See 2.1 above. LANL (USA) None. LNPP (RUS) See above (everything is intention). Vattenfall (GER) - An extensive monitoring of components concerning ageing is performed,

e.g. - I/C-systems, determine the trend of failure rate - electrical equipment, determine the trend of failures,



The 1990 and 1995 tasks mentioned above were almost exclusively with active components.

2.5 Have you performed any experiments or models verification? UJV (CZ) No, this was feasibility study with the goal to assess methodology and potential

for performing realistic simulation of components life. VTT (FIN) I have compared the results obtained with several analysis codes for the same

case against each other. I have not performed laboratory research. IRSN (FR) A laboratory reliability test program is developed for motor operated gate valves

of HPSIS, but not implemented due to the budget reduction. VEIKI (HU) There have been several measurements and experiments performed in direct

support of AMP for Paks. A listing of these efforts is given in Appendix 3. However, it is noted that these experiments had no PSA related objectives.

ENEA (I) These kind of activities were not performed. LEI (LT) No. INR (RO) No. RELKO (SK) Not applicable. Forsmark NPS (SWE)

No.

British Energy (UK) No. Rolls Royce (UK) Experimental testing has been, and is being, carried out to investigate EAC and

corrosion mechanisms, which will provide data to support analytical models being developed. A detailed qualitative assessment has been made of the failure mechanisms affecting each component in the plant. Estimates have been made of failure probabilities based on operating history, results of tests, trials and experiments if available, theoretical calculations (for example using Structural Reliability Risk Assessment (SRRA)), and expert judgement by a panel of experts.

Ohio St Univ. (USA) No. LANL (USA) See 2.1 above. There has been experimental and model verific ation on several

types of analysis-most to my knowledge in the area of waste. One of LANLs main missions is expanding knowledge in the arena of aging weapons. These, however, are not traditional industrial type studies.

LNPP (RUS) Experiments (with NPP equipment) are impossible. Component ageing process models itself are not PSA scope (except analysis for safety level trend).


No. The 1990 study mentioned above compared statistical models, i.e. different assumed forms of the trend in the failure rate.

3. QUESTIONS RELATED TO INCORPORATING AGEING EFFECTS INTO PROBABILISTIC SAFETY ASSESSMENT

(PSA/PRA) AND PSA APPLICATIONS AND USING OF APSA

3.1 How is ageing currently addressed in your PSA models? What components were/are under your consideration to address ageing effects?

UJV (CZ) Ageing is not addressed directly (the way, it is recommended in NUREG/CR-5587, for example). Constant failure rate from point of view of aging potential is assumed for plant components. However, a periodical up-date of PSA input parameters based on plant specific data is performed once per five years. This way, the effects of aging, which are reflected in higher frequency of component failures as well as in appearance of some specific new phenomena, may be partially addressed (the last input parameters up-date is just about being finished). All risk important components have been included in plant specific data collection project.

VTT (FIN) The VTT does not own the surveyed PSA models, as they are the property of the Finnish energy utilities. As I mentioned above, this far I know PSA only through literature. To my knowledge, ageing is not currently directly addressed in the PSA models used in Finland, although this subject is under research and serious consideration. I am not aware of what components the researchers involved with PSA are considering to address ageing effects.

IRSN (FR) Presently in IRSN there is no real project in progress for incorporating ageing in PSA. We have only carried out some feasibility studies. So for most of the questions we have not yet precise answer.

EDF (FR) Ageing is not explicitly addressed in our PSA model. VEIKI (HU) Ageing effects are not addressed yet in the PSA models for the Paks NPP. Some

trial applications looked at ageing effects in relation to testing. Adverse effects of testing was taken into account and some simple reliability models were applied to investigate how risk level was affected by these effects. What components were/are under your consideration to address ageing effects? There is no consolidated decision in this aspect yet. Active components will likely be in the focus of attention in the first place. Passive components may also be looked at but there is a need for even more theoretical advancement than in the case of active components.

ENEA (I) Actually PSA ageing is not considered in the previous studies. LEI (LT) Currently ageing is not directly addressed in PSA models, but only by failure

parameters updating. INR (RO) Until now, ageing was not considered in the PSA calculations, but the safety

importance of assumed increases in the components failure probabilities was evaluated. A risk model such as PSA can be used to identify what failure rates are risk sensitive and cause significant variations in the risk if they vary. These risk-sensitive failure rates need to be estimated as accurately as possible. With regard to plant applications, these risk-sensitive failure rates need to have strict quality control and qualification. Failure rates which are identified as not risk-sensitive do not need to be accurately estimated. With regard to plant applications, these risk-insensitive failure rates do not need to have as strict a quality control or qualification process. As a consequence, if a raise of a certain component failure rate doesn’t have a major effect, the ageing analysis for that component is expected to have a small importance, so the ageing analysis should be performed mainly for risk-sensitive components.

It should be mentioned that in any plant exist a special group of components, which are necessary to have a complete integrity both in normal and abnormal operating conditions. This group of components consist of:

- the components from the coolant systems - the components which are necessary to stop the reactor and to maintain it

in a safe state - the components which are necessary to minimize the exposure in case of

an accident For this group of components the ageing aspects are very important.

RELKO (SK) Ageing is not addressed in the PSA.

Forsmark NPS (SWE)

We have no ageing addressed in our models.

British Energy (UK) Ageing is primarily addressed by trending active component reliabilities as identified via SSRs. However, the ageing of boiler tubes is explicitly modelled for a number of AGRs, in the form of conditional probability of boiler tube failure following reactor trip. The most safety significant active components are addressed via the SSRs.

Rolls Royce (UK) For a safety justification, the ageing of components is bounded by performing a risk evaluation using failure rates for structural components applicable to the end of plant life. Other components are treated as though they have a constant failure rate. All components that are considered to be safety significant are considered. Infant mortality (or burn in) effects are counteracted by for example commissioning tests before plant operation.

LANL (USA) Only recently have aging issues been addressed in our PSA models for storage so we have very little data. Gloves are assumed to fail and are addressed that way in our models. Generally our PSA models look at operating experience, operating experience at other facilities and if applicable industrial experience.

LNPP (RUS) See above. As for equipment importance list (I think) it is too early to present it here right now.

Vattenfall (GER) No ageing has been explicitely incorporated. Statwood Consulting (USA)

I have not worked with aging as an explicit part of any PSA model.

3.2 Have you incorporated or do you plan to incorporate passive components into your PSA models to address their ageing effects? How were/will these components be selected?

UJV (CZ) In our PSA models, passive components have been treated only regarding potential for initiating event occurrence. Up to now, there has been no intention to reflect aging effects in IE frequencies explicitly. However, some concrete indications of aging effects importance from point of view of IE occurrence potential have been met in NPP Dukovany operational history.

VTT (FIN) As I mentioned above, this far I know PSA only through literature. However, I would suggest to include the ageing of piping components to PSA, as their failure probabilities can be estimated quite accurately with quite reasonable computational effort. I would select only those components that present a risk that exceeds some suitably defined level.


CEA (FR) According of expected applications (but in a future): - RCM for passive components→ we must integrate some passive

component, and then modelize the ageing (piping, reinforcement) - In case of GenIV concepts with some thermal-hydraulic passive systems, it

could be necessary to incorporate passive components into our PSA models.

EDF (FR) We plan to explicitly make a link between PSA and SRA in order to - Reassess failure frequencies of events (initiators) - Reassess low failure rate components (no feedback) - Allow to contribute to the definition of reliability objectives for structures

according to their importance to safety VEIKI (HU) See answer to question 3.1 above. ENEA (I) At present it is planned to incorporate passive components into the PSA studies to

address the ageing effects, with reference for example to material embrittlement mechanisms of radiation exposed components (like vessel, targets). Selection of the components should be made on the basis of experience and engineering judgement.

LEI (LT) Passive components are modeled as well as active, but aging is not treated directly, see 3.1.

INR (RO) Passive components are of ageing concern because their deterioration may not be recognized until a failure occurs, and they not provide an adequate number of failures to be analyzed statistically. Passive components are often very expensive and difficult to replace. Some passive components (cables, pipes, tank) are incorporated in our PSA model, but their ageing effects are not yet taken into account.

RELKO (SK) No such activities are planned at the present time. Forsmark NPS (SWE)

We do not have such plans today. With work connected with RI-ISI I suppose and hope that we will be able to take such a step. It could also be useful in planning maintenance, risk estimations for the future life of the plant and for optimization of test frequencies to compliment predictive maintenance tools.

British Energy (UK)

This has not yet been decided.

Rolls Royce (UK) Passive components have been assessed by several methods, which have included review of world data, structural reliability models and use of expert judgement. Passive components are selected on the basis of their safety significance and risk of failure to the plant.

LANL (USA) Not at this time. LNPP (RUS) No pipelines (failure) are in the model. Some leaks are related with active

equipment failures (on the data analysis level). Also see above about importance analysis and plans.

Vattenfall (GER) Passive component are partly included, but are not addressed to Ageing.

3.3 Which degradation mechanisms have been addressed in your PSA studies and why? Could you specify how these mechanisms have been modeled? How were the failure probabilities estimated? What models/codes and data have you used?

UJV (CZ) No concrete effort of this kind has been part of our PSA activities up to now. VTT (FIN) As I mentioned above, I have not applied PSA. The Finnish PSAs do not include

models for specific degradation models. However, the Finnish energy utilities have separate models that are applied together with the PSAs with which to analyse and detect possible ageing trends. I do not know the characteristics of these separate models.


EDF (FR) In the RCM approach we have used for pipes we have evaluated the potential for a degradation mechanism on a structural element by using generic degradation models:

- EDF Simplified calculation tools - International operating experience databases - Experimental measurements (EDF, international lab.) - Expert judgments

For the following degradation mechanisms :: - Corrosion-erosion (BRT-CICERO*) - Cavitation-erosion (MDCAVER V2.0**) - Thermal fatigue (MDFath*) - Vibrational fatigue

(* EDF tools) VEIKI (HU) No degradation mechanisms have been incorporated into the Paks PSA yet. ENEA (I) Degradation mechanisms leading to component failure have been incorporated

implicitly directly in the failure model, through the exponential reliability function. For the assessment of components and system failure probabilities fault tree technique has been adopted and RISK SPECTRUM code has been utilised.

LEI (LT) See 3.1. INR (RO) The failure mechanisms included in PSA study were those that induce failure

modes that lead to the achievement of top event considered for the analysis (no explicit degradation mechanism considered). Passive components:

- pipe: external leakage, rupture, plugging, wall thinning - cable: open circuit, short circuit - tank: rupture, external leak

We use generic data for the analysis. RELKO (SK) Not applicable. Forsmark NPS (SWE)

We do not have such models.

British Energy (UK) Degradation mechanisms are currently addressed deterministically. However, boiler tube failure mechanisms are addressed probabilistically. Conditional probabilities of failure are determined by statistical treatment of failure mechanisms.

LANL (USA) Radiolysis, thermal effects, chemical corrosion, material stresses and strains are some of the issues addressed. These calculations are often performed outside our group and we do not routinely run codes ourselves.

LNPP (RUS) See above.

Vattenfall (GER) No time dependent degradatin effects are addressed. Statwood Consulting (USA)

To estimate failure probabilities, I have used standard Bayesian updates of various diffuse priors, and also loglinear modeling (i.e. exponential trend) with Poisson counts. In the 1990 study I also looked at other trend models - Weibull and linear. The problem has not been statistical models. The problem has been lack of data. In the 1993 study we used PRAISE to simulate crack growth, but I did not personally run that code.

3.4 Have you addressed ageing effects for active components? What reliability models and data have you used then? UJV (CZ) No explicit aging related reliability models have been used up to now. The only

way, aging effects have been addressed, is periodic up-date of component failure rates, initiating event frequencies, unavailabilities due to maintenance and residual common cause failures parameters (yes, even for latter two categories, we expect non-negligible effect of aging).

VTT (FIN) This far I have not addressed ageing effects for active components. IRSN (FR) Presently in IRSN there is no real project in progress for incorporating ageing in

PSA. We have only carried out some feasibility studies. So for most of the questions we have not yet precise answer.

EDF (FR) No. VEIKI (HU) In general, ageing has not been addressed in the Paks PSA as given in the answer

above. Ageing related to testing of active standby components has been looked at in a trial application. This included an assumption that the failure rate of active components might increase due to test related wear-out. The following reliability model was used to address increase in failure rates:

+⋅λ=λ

10010

pi

where λ 0 is the initial failure rate λ i is the component failure rate after test i p is a measure for the adverse effect of testing in percentage.

ENEA (I) Up to now ageing effects have not been addressed for active components. LEI (LT) See 3.1. INR (RO) No. The linear model can be used. RELKO (SK) Not applicable. Forsmark NPS (SWE)

We have not done this.

British Energy (UK) System Safety Reviews (SSRs) are performed every three years for safety significant systems. Where these identify the need to amend plant reliability data to reflect ageing / degradation affects within the PSA, this is carried out.

Rolls Royce (UK) Stress (fatigue) mechanisms are modelled in the PSA. SRRA is used to estimate failure rates for pipework. Other mechanisms, such as corrosion and wear, are controlled, as far as possible, and are not modelled explicitly. As there is data collection and operational feedback into the PSA as well as use of data from other sources, some of the data used implicitly includes other failure mechanisms. Active components are modelled as having a constant failure rate.

Ohio St Univ. (USA) Weibull, normal, TIRGALEX data. LANL (USA) See 3.1. LNPP (RUS) Intended study will cover all equipment (of basic events importance list).

There are active components mostly. An answer on last question is obvious (taking into account mentioned above approach). Statistical data (failure rate, time based on operation regime) - see 5 options in Risk Spectrum.

Vattenfall (GER) See 3.1. Statwood Consulting (USA)

The 1990 study assumed that the failures followed a non-homogeneous Poisson process, and estimated the time-dependent failure rate. The 1995 study used whatever models were in the existing studies performed for the various countries.

3.5 Would you agree to the opinion that ageing cannot be addressed by models based on current PSA structure? Are there any simplifications you could recommend to use while modelling ageing effects in PSA for specific applications?

UJV (CZ) We understand incorporation of aging phenomenon into PSA as further possible way of refining it. Although it is probably not possible to address all aspects of aging fully or to a major extent in current PSAs, the attempt to do it partially is still seen as being valuable.

VTT (FIN) As I have not applied PSA, I am not able to answer the first part of this question properly. However, it seems that it could be possible, at least in principle, to modify the PSA so that the failure probabilities would be time dependent. As for the second part of this question, if plant data base has developed to such scope that it includes all relevant geometry, material, load, stress and environmental condition data, it is possible to perform probabilistic ageing degradation analyses for many components with certain analysis codes that are relatively simple, easy to use and computationally economical. So, to my opinion it is in many cases not necessary to use computationally heavy codes, e.g. FEM and CFD based codes, to analyse the ageing degradation of components. This is especially so if the plant data base contains the component stress distributions for the relevant static and transient load cases, as the calculation of those can require a lot of work. The problem with the above mentioned computationally economical probabilistic analysis codes is their availability, as to my knowledge most of them are proprietary.

IRSN (FR) I do not really agree on the fact that PSA structure is not appropriate. I think that it is not a problem of structure but a problem of completeness. The structure of the PSA is useable, but could have to be completed by some components, failure modes or CCFs, which could be important for ageing problems and were not introduced in the PSA. Ageing treatment is mainly a problem of data, and models able to treat data evolution can be used outside of the PSA model, and introduced for sensitivity studies.

In addition

1) Of course we can use the existing structure as a basis for modifications depending of final goals of the study. Possible modifications on the level of Active components – additional gates and BE in the FT, Passive components - additional gates and BE, changing of FT structure, Initiating events – changing of parameter or additional gates and BE in the FT, CCF effects - changing of parameter or additional gates and BE, changing of FT structure. 2) For the purpose of expertise of preventive maintenance program some "adjustment and synchronisation" of time point for the calculation is needed. See example in the presentation.

CEA (FR) With the current structure, big assumptions are done (for example linear behaviour…). The use of more dynamic model could be necessary, then is the current PSA structure suitable?

EDF (FR) Our current PSA model cannot be used directly for Structures analysis because they are not explicitly taken into account. For example, in OMF Structures project we had to use surrogate components to assess the severity of pipes breaks. Moreover in our current model failure rate and initiating event frequencies are assumed to be constant in time.

VEIKI (HU) We believe that there is a need for significant advancement in the PSA modelling of ageing (both theoretical foundations and hypothesis checking based on available data) to be able to properly answer this question. We are not yet prepared to recommend any simplifications or specific methodologies. We need to work more in the general area of ageing modelling and its relation to PSA applications before we can arrive at an answer.

ENEA (I) I agree that ageing can not be addressed by current models. In fact the adoption of the Weibull distribution instead of the commonly adopted exponential distribution to model the failure is envisaged.

LEI (LT) PSA structure is OK for aging incorporation, but computer codes are developed not enough for ageing analysis.

INR (RO) PSA study can be used as a basis for further development of ageing studies. It seems that if in the PSA are modeled all the interest components, the ageing effects can be integrated after (by adding of new components and/or by the modification of failure rates for the components which are already modeled). The ageing effects could be modeled only for the components which are sensitive to the failure rate modifications (so, it’s better to perform initially a sensitivity analysis, in order to see what components are risk sensitive and cause significant variations in the risk if they vary).

RELKO (SK) Not applicable. Forsmark NPS (SWE)

Methods and models as well as data have to be developed to be able to address ageing and the effects of ageing. There exist similarities in how data are treated for test optimization. Based on such experiences methods can be developed.

British Energy (UK) We have incorporated ageing into our PSAs for some components (boiler tubes). However, this was not trivial as failure of the component resulted in a significant change in fault progression. Consequently, a separate PSA model was developed which included a node questioning whether boiler tube failure occurred within the fault progression for every initiating event in the PSA. Widespread modelling of ageing mechanisms using the method we adopted would not be feasible. Are there any simplifications you could recommend to use while modelling ageing effects in PSA for specific applications? No.

Rolls Royce (UK) Existing PSAs do not include explicit consideration of every component and every failure mode of every component. A mixture of judgements and data are used for elimination. For an assessment to take ageing into account explicitly will potentially lead to large variations in risk estimates from current values. This may invalidate some or all of the arguments used to eliminate some components or failure modes from assessment. For a particular application of a PSA, the importance of this effect would need to be judged on a case-by-case basis.

Ohio St Univ. (USA) History and most time-dependent effects cannot be properly handled by PSA codes such as SAPHIRE. However, it may be possible to modify such codes without too much effort to handle time-dependent effects. Modelling history dependent effects needs further studies.

LANL (USA) Failure rate binning rather than trying to obtain a specific number helps simplify the process and is what we use.

LNPP (RUS) Our approach was described above. PSA model could present different results (using different parameters/data). You should have just several generic data base – current data, data in 1 year, data in 2, 3 etc years (everything should be estimated based on trend analysis).

NMRI (JAP) Agree. We now set the project to develop aging-PSA framework.

Vattenfall (GER) Yes, but by using plant specific data could be in a discontinuous way. Comment: If you update the plant specific reliability data every time you quantify your PSA. The result should show up the influence of aging, which should be included in the reliability data. But in this case, you should have a fixed maybe simplified PSA, to exclude model variation.


Simplification: If a failure rate or probability changes in an approximately linear way, the PSA model would only need to store the initial value and the derivative (plus perhaps another parameter to account for changing uncertainty). Then the failure rate or probability could be calculated at any age, at the cost of only modest additional storage requirements in the PSA model.

3.6 What further actions and developments, based on your experience and needs, are necessary to be performed to properly address ageing in PSA studies and applications?

UJV (CZ) In general, the models of individual components, which have been found subjects of significant aging effects, have to be completely changed and generalized. This will need quite new methodological approaches to be followed. In addition, the analysis of operational experience and the way, generic data are elaborated and treated, will need to be changed.

VTT (FIN) Based on what I have read about PSA and on my experience in the field of structural analysis I have the opinion that to properly address ageing in PSA requires the availability of both extensive and high quality data bases. These data bases are needed in the probabilistic component ageing analyses. The analyses can be performed with structural reliability models or with statistical models. I would prefer the former model type, as it contains the modelling of the physical phenomenon or phenomena in question, in addition to which it is difficult or impossible to obtain reliable results with statistical models for passive components due to scarcity of their failure data.

IRSN (FR) No response. CEA (FR) R&D to develop a PSA structure in which static model and dynamic model could

be merged. EDF (FR) We think it would be interesting to answer the following question:

How to model properly and not too conservatively the global effect on the pipe reliability (the pipe is seen as a functional part of the system in the PSA) of several degradation mechanisms likely to affect several components of the pipe (for example welds, elbows, etc.) : link between functional failure mode and failure criterion in codes ? link between pipe reliability and components reliability?

VEIKI (HU) There seems to be a need for a systematic developmental process for adequately addressing ageing in PSA. The following is an arbitrary and preliminary list of tasks that should, in our opinion, be performed within this developmental process.

- identification of component/equipment types that need to be looked at in a PSA with ageing models

- identification/selection of degradation mechanisms that is within the scope of PSA modelling for major classes of components

- development of reliability models (hypotheses) for a probabilistic description of ageing to cover the identified component types and degradation mechanisms

- define data requirements for the reliability models - review of available data from experience (including ageing management

programmes) to evaluate their applicability to verifying reliability models/hypotheses

- verification of reliability models and selection of appropriate models if allowed by available data

- conduct of experiments to support model verification and hypothesis checking

- collection of data in the longer run in accordance with the requirements of the PSA with ageing reliability models

- development of PSA tools (computer programmes) for full scope modelling of ageing in PSA

- restructuring and quantification of PSA with ageing incorporated ENEA (I) Focal points should be: ageing mechanisms and appropriate modelling of failure

rate vs time, CCF among components environmentally caused, structural reliability assessment of structures and components, study of system/component

performance function vs time, residual life assessment LEI (LT) Further PSA computer code developments and data collection in appropriate

format and development statistical data treatment guidelines. INR (RO) - Prioritization of the components

- Before the trunchiation of the cut-sets, it should be made an evaluation to establish if the sets with ageing effects has the potential to became a dominant contributor

- There must be developed systematic procedures for the incorporation of ageing effects in PSA

- A data base which include the material description, the mechanic properties, the ageing history, the degradation mechanism is necessary to be developed

- The components testing and maintenance models must include the equipment replacements and the improvements

- A special attention must be focused on ageing assessment for safety systems or for special operating conditions (as for example, in the event of external events occurrences)

RELKO (SK) Information collection is needed in this area. Forsmark NPS (SWE)

I think that it is important that there exists qualified data concerning the change of failure probabilities based on ageing/time in different environments to be able to get support for developing models and methods for using PSA in ageing evaluations.

British Energy (UK) We do not have any views on this. Ohio St Univ. (USA) For time-dependent effects, incorporation of component models that can represent

periodic surveillance into the PSA codes. LNPP (RUS) Proper data collection and analysis. Failure root cause analysis. One standard

overall database development. Vattenfall (GER) Data collection is most important, Information must be included whether the

component is as good as new or not after maintenance, PSA models must include Weibul distributions. Also development of theoretical models how e.g. passive components are influenced by ageing. Comment: In the moment we collect in the German data collection project ZEDB only failures, determine the failure mode and the time of observation of the component. To determine the time behaviour of the failure rate we need also the date of the failure. Furthermore in the PSA model we assume that after repair the component is as good as new. To include aging we may have to assume that the component is not as good as new after repair but has still a latent failure inside which comes up later. In complex components it may be also difficult to determine whether the fault was due to ageing or due to overload or what ever. I think it is very difficult to distinguish between all this. But we should have a simple working model.


For active components, we need failure data including the age of the hardware that failed, as a minimum. For passive components, more and better data on precursors, such as cracks or other degradations, would be extremely useful. The precursors could be related to failures by some physical or empirical modeling, or could be of interest in their own right.

3.7 How is your data collection system focused on ageing issues? UJV (CZ) Since ageing potential has not been explicitly addressed in our PSAs, the data

collection system has not needed to be adjusted to cover ageing aspects. This is one of our big goals for future.

VTT (FIN) As I do not work in a energy industry utility, I do not have a direct access to a component monitoring data collection system. However, we work in close co-operation with Finnish energy utilities and e.g. develop RI-ISI methodologies for them. The utilities are quite open and willing to share their knowledge in the mutual research projects.

IRSN (FR) Data collection is managed by EDF. Due to the existence of standardized plants, data are collected at a national level, grouped for all the plants independently of their age. A data collection treating ageing problems needs some modifications in the data collection process. Data evolutions have to take into account effect of ageing, effects of testing and of maintenance, and also dependencies between these different effects. The utility data accessible in IRSN are not sufficient for aging analysis.

CEA (FR) R&D to collect and develop model of the evolution of reliability data. EDF (FR) Our data collection system is not really focused on ageing issue. From our

experience, it is very difficult and time consuming to collect all the necessary data for structural reliability assessment.

VEIKI (HU) The data collection systems operated at Paks are not focused on explicitly revealing ageing related effects with respect to component failures and degradation. However, some information can be obtained for this purpose from the available data records. One should turn to the raw data collection sheets to get such information. A significant advancement is the recently introduced ageing management programme (AMP) at Paks that is focused on monitoring safety performance and the underlying degradation mechanisms for key safety related SSCs – see answer to questions 2.2. and 2.3. This programme can yield insights useful for PSA purposes as well.

ENEA (I) Data collection is not focused on ageing issues. LEI (LT) INPP have separate department for various data collection. Every year data about

equipment failure frequencies are collected. These data are compared to earlier collected data and change of failure frequencies because of equipment ageing is assessed. Also statistical data report is issued every year. Aging analysis could be performed based on the data available.

INR (RO) Our data collection system is focused now to obtain plant specific reliability data, not ageing data. In the future we intend to extend the scope of data collection system, in order to collect ageing data for TRIGA reactor.

RELKO (SK) RELKO is responsible for the Slovak data collection project to support PSA and RCM. In this project modeling of trends and ageing is involved.

Forsmark NPS (SWE)

So far we do not have focused the data collection to position ageing effects.

British Energy (UK)

We use our SSRs for trending of plant data to identify degradation in plant performance, to identify the need for repair / replacement.

Rolls Royce (UK) Data collection has been and continues to be a significant activity. For specific ageing-related issues further data collection would be undertaken. This would add to the validation of theoretical models and prompt further model development. Operating history data that is collected is analysed to spot trends or patterns in failures. As many of the events modelled in a PSA are rare, and many are expected never to

occur, improved approaches to making judgements on ageing issues to fill in where there is no data would be beneficial. Existing codes for risk assessment are not, generally, able to address varying failure rates. This leads to a requirement for multiple evaluations for discrete periods of operational life. Modifications to codes used for PSA to facilitate incorporating ageing failure rates directly would be beneficial. This could be through a risk monitor if this was used for living PSA. Further development of models of the effect of maintenance and surveillance activities on failure rates and their likelihood of success would provide an improved quantification of the impact of maintenance for risk-informed PSA applications.

LANL (USA) It isn’t currently. LNPP (RUS) Failure events have categories: degradation, catastrophic, etc (note under

recording). Vattenfall (GER) No specific information is included.

3.8 Have you used or do you plan to use PSA for ageing management and maintenance and inspection activities? UJV (CZ) Yes, new large project for NPP Dukovany oriented to specific features of plant

operation in late period of planned life and in life extension period has been prepared and is in the phase of competition for resources. Incorporation of ageing aspects in the PSA model and all possible consequent applications belong to the most significant points of this project.

VTT (FIN) This far I have not applied PSA, it is possible that I will apply it in the future. IRSN (FR) Ageing management, which is a very important problem, is treated by a mainly

deterministic approach. PSA was used, in addition to other considerations, to identify the SSCs which need a particular attention for ageing management of the plants. Possible applications of APSA:

- Tool to evaluate the risks related to the aging effects (contributors to and distribution of)

- Expertise of effectiveness of surveillance programme (periodical tests, in-service inspections, RCM)

- Expertise of utility life extension programme Examples of actual difficulties:

- Residual lifetime estimation (design/ operational experience/prediction), - Qualification (simulation of aging mechanisms/representativity for period

of extension), - Effectiveness of preventive maintenance and inspections (volume and

periodicity).

CEA (FR) Without object for CEA at the present time. But interest for the maintenance and inspection service for passive components.

EDF (FR) See 2.1 above. VEIKI (HU) There is an ongoing activity on the use of risk information (including PSA) for

evaluating maintenance effectiveness at Paks. A work-plan is expected to be developed for this purpose by the end of 2004. The actual work that will start afterwards is dependent on plant management decision. Use of PSA for ageing management is currently under consideration as a longer term task.

ENEA (I) At present these kinds of activity are not planned, although this could be the most relevant application of the APSA.

LEI (LT) Yes, INPP plan to use PSA for ageing management and maintenance and inspection activities in the near future. Some actions are currently on-going (development of procedures etc.).

INR (RO) We intend to use PSA for the assessment of impact of components ageing to plant safety level (the assessment of core damage frequency according to plant ageing) and also for the improvement of maintenance practices and for optimization of in-service inspection intervals.

RELkO (SK) PSA for ageing can be used in the future. Forsmark NPS (SWE)

There long term ideas in this direction but no plans.

British Energy (UK)

We do not currently use PSA for these activities.

Rolls Royce (UK) Yes, for risk informed ISI applications. Ohio St Univ. (USA)

Only as research activity.

LANL (USA) Currently we do not, it would be nice to move in that direction.

LNPP (RUS) We shall plan and it is main objective of future study. NMRI (JAP) Yes, we have a plan. Vattenfall (GER) No.

3.9 In which applications and activities do you see a potential for use of APSA and what applications are of your main interest? UJV (CZ) In general, addressing of objective existence of aging phenomenon in PSA model

has got a very positive impact on credibility of results of all PSA applications, because the model itself is more realistic. However, some specific areas may be particularly influenced – in-service inspection planning, risk and reliability centered maintenance etc. It should be also pointed out that even human reliability may be significantly influenced with the specific features of plant ageing (increased component failure rates, loss of motivation, loss of experienced experts etc.).

VTT (FIN) In my opinion APSA could at least be useful when preparing a RI-ISI. If time dependencies of failure probabilities were included in a PSA, from which they could be taken to RI-ISI, it would allow one to make predictions of the changing of risk levels in the future. The reliability and accuracy of these predictions would depend on the reliability and accuracy of the time dependent failure probabilities. As I do not have working experience with PSA I am not capable to comment on other potential applications for APSA.

IRSN (FR) Ageing management, which is a very important problem, is treated by a mainly deterministic approach. PSA was used, in addition to other considerations, to identify the SSCs which need a particular attention for ageing management of the plants. Possible applications of APSA:

- Tool to evaluate the risks related to the aging effects (contributors to and distribution of)

- Expertise of effectiveness of surveillance programme (periodical tests, in-service inspections, RCM)

- Expertise of utility life extension programme Examples of actual difficulties:

- Residual lifetime estimation (design/ operational experience/prediction), - Qualification (simulation of aging mechanisms/representativity for period

of extension) - Effectiveness of preventive maintenance and inspections (volume and

periodicity) CEA (FR) Identification of important SSC (according to lifetime management).

Risk Informed In Service Testing. Risk Centered Maintenance for passive component.

EDF (FR) See 2.1 above. VEIKI (HU) - Use of PSA information to rank components for ageing management

- Prediction of safety level (CDF, LERF) with ageing PSA models - Early warning of potential deteriorating performance - Eevelopment of recommendations for remedial actions in the ageing

management programme, maintenance, or inspection activities - Risk follow-up

ENEA (I) APSA could be relevant especially for inspection and maintenance purposes. LEI (LT) Mainly optimization of Inspection and preventive maintenance activities, lifetime

estimation. INR (RO) Ageing PSA can be used for risk-based operation applications, in order to prevent

and mitigate the ageing effects. The analysis is intended to be used for the optimization of maintenance, testing and inspection activities, to support replacement strategy, or for the recommendations of changing of environmental conditions. It can be the bases for deciding whether to prolong or shorten maintenance and test intervals, or whether to introduce new condition monitoring methods.

RELKO (SK) In the future ageing should be involved in the PSA models and PSA applications. Forsmark NPS (SWE)

Look at question 3.2.

British Energy (UK)

We are still seeking to learn the benefits we can obtain from the use of APSA.

Rolls Royce (UK) PSA is used as an input to the specification of maintenance activities, e.g. in setting test and inspection intervals. Key applications of APSA as I see it are:

- Looking at lifetime extension. - Defining maintenance needs. - Improving the realism of the risk models for operational support.

Ohio St Univ. (USA)

Ageing management though surveillance testing.

LNPP (RUS) 1) Management of maintenance and inspection activities (during operation). 2) NPP life extension process.

NMRI (JAP) Nuclear power plants, and after that, ship and other engineering structure. Vattenfall (GER) We see potential for optimization purposes of maintenance or replacement of the

equipment, this is also our main interest.

4. PROJECT PREFERENCES AND EXPECTATIONS

4.1 What is your expectation from this project/network and what kind of information would you like to receive from it? UJV (CZ) Information about approaches used by the participants all over to address ageing

phenomenon (theoretical methodological aspects, concrete applications of methodology for specific types of components, selection of components proved being important from ageing point of view, incorporation of operational experience into quantification etc.).

VTT (FIN) I expect to learn about the European state of the art as well as of the future development directions of the component ageing modelling methods and data bases. I would also like to actively participate in the research to be done in the workshop. As I do not have working experience with PSA I would like to learn about that subject as well. And last, but not least, I am interested in getting acquainted with European experts of component ageing modelling methods and PSA.

IRSN (FR) We are interested by learning about the experience of other organisations with the problems relating to APSA:

- How data are they collected? Which are the important data? - What are the main problems of methodology (for example how to treat

the possible dependencies?) - Are there already some results and applications?

CEA (FR) Exchange of information between experts, set up of general methodologies. EDF (FR) We did not make our decision about EDF participation in the project. VEIKI (HU) Our major expectations are as follows:

- A comprehensive review of the state-of-the art in the subject matter - Description of available and evolving methods for probabilistic ageing

modelling with recommendations for most promising methods - Recommendations for ageing PSA applications - Access to field experience on roe and processed data - Definition of further actions needed to make advancement so that PSA

modelling of ageing can be put into practice for the purpose of PSA applications.

We do not expect much from a case study at this stage because we are uncertain about the maturity of available methods and about the accessibility to data needed for a case study.

ENEA (I) The main expectance is the construction of a consistent reliability model for incorporating the ageing effects into the reliability studies in order to get a more realistic picture of the behaviour of the components during time and to achieve useful information for maintenance optimisation.

LEI (LT) Information exchange, development and testing of software, research in statistical estimation area, development of aging study case.

INR (RO) - State of the art information - Advances in ageing effects modelling for risk estimations - Systematic procedures for the incorporation of ageing effects in PSA - Predictive models to assess reliability for components throughout their

life time - Component ageing data base – information on the variation in time of

material properties under exposure to environment and ageing factors – degradation mechanism

- Optimization of maintenance/surveillance programs - Identification of further research

RELKO (SK) We would like to clarify and work out the methodology for APSA in this project.

Forsmark NPS (SWE)

We want to develop a platform from which it would be possible to start to put demands on data collection and also to start testing of performing APSA- evaluations.

British Energy (UK) We are looking at this project to see what benefits there may be for continued operation to End-of-Life and for lifetime extension.

Rolls Royce (UK) I would like to see this project discussing and defining the best ways to: - Model ageing effects in a PSA. - Collect and analyse the data needed to provide failure rates for

components for an APSA. - Model the failure mechanisms using reliability physics models. - Represent the effect, and effectiveness, of maintenance and surveillance

activities. In addition, I would hope that potential changes to standards, guidance and regulations would be discussed. Perhaps the network could act as a key influence on any such changes.

Ohio St Univ. (USA) A procedure to include dynamic effects of aging in PSA/PRA. LNPP (RUS) Guidelines, data, technology/ideas transfer. NMRI (JAP) Reliability Models for aging, Aging data. Vattenfall (GER) I expect to get a broader view of how ageing models can be used for, what kind of

models are available and how we have data to collect for the purpose. Statwood Consulting (USA)

I do not know enough about the project to have expectations. My dream or hope is to be intimately involved in a study of extensive aging data, where there are complications or challenges in drawing statistical conclusions.

4.2 Which case studies should be performed within the network, how should be corresponding tasks of work defined and organized?

UJV (CZ) The specific topics to be studies could be, for example: 1)selection of the most important components requiring specific ageing quantitative models 2)development of ageing quantitative reliability models, searching for the best fit with operational reality 3)estimation of ageing-related distribution parameters on the base of plant specific experience 4)general problems of skip from “static” PSA model to the dynamic model addressing various aspects of ageing and many others.

VTT (FR) I am interested in case studies concerning the probabilistic ageing modelling of passive components, and mainly of piping systems and the RPV. These case studies should cover all relevant relevant ageing degradation mechanisms, including their possible joint action, damaging the components in question. Collection and evaluation of available probabilistic component ageing modelling methods, as well as discussion of further research and development needs should also be included in the case studies. The evaluation of the analysis methods necessitates the targets of case studies be such that the analysis results of as many modelling tools as possible can be compared against each other. This is also an important aspect from the viewpoint of the verification of the modelling tools. As probabilistic analyses require considerably more input data than determinnistic analyses, the case studies should also include a survey of the availability of data bases, and possibly of the quality of the data they contain. Naturally applications of incorporating the ageing of components to PSA should be included in the case studies. I realise that I have suggested quite many subjects to be included in the case studies, however I consider all of them to be very important. The contents and organisation of the case studies depend naturally of the available financial resources and of the number and experience of the participants. One way to divide the work would be that each case study would consider the modelling of only one degradation mechanism, or joint action of certain degradation mechanisms. Another approach to organise the work would according to component type, so that each case study would consentrate on one certain component type. The survey of the data bases could be one separate case study. If workshop includes laboratory research, that could also form one separate case study. In my opinion the case studies should also include the survey of deterministic physical models of degradation mechanisms, since structural reliability models are based on them.

IRSN (FR) 1) Reliability data elaboration. Data nomenclature and data sources, choice of mathematical model. Parameters estimation. 2) Reliability tests. 3) Physical models for different aging mechanisms. Possibility to incorporate in PSA model. 4) Aging FMEA approach development or analysis for one type of component.

VEIKI (HU) We would rather leave this subject open for discussion during the kick-of meeting, because at this stage we are uncertainty about the feasibility of a useful case study as discussed under question 4.1. above.

ENEA (I) Passive and active components should be studied in the present project: while passive components can be treated by means of the structural reliability, active components, for which not many studies have been performed, deserve more attention. The tasks should include:

- Ageing degradation mechanisms analysis - Data collection or data inference process - Ageing degradation mechanisms probabilistic model (this should be in my

opinion the focus of the activity)

- Simulation on a system (active one) LEI (LT) The network could perform aging study case on specific systems, e.g. emergency

power supply system. Another case study could be performed for research in statistical estimation area: development of aging statistical analysis procedures/methods and testing on case studies. Other case studies could be done on deterministic aging analysis: important aging mechanisms and deterministic lifetime evaluation.

INR (RO) - The ageing of active components, impact on PSA modelling and results - The ageing of passive components and applications - Incorporating specific ageing degradation mechanism into PSA models for

selected type of components RELKO (SK) We propose to have two case studies: 1) Data analyses to asses the presence of time

trends in failure rates and probabilities, comparison of various approaches that have been implemented in the computer software. 2) Implementation of ageing into the PSA models for the selected passive and active systems.

Forsmark NPS (SWE)

So far no ideas.

British Energy (UK)

We have not yet formed an opinion.

Rolls Royce (UK) I suggest that the following case studies be undertaken: - Benchmarking the effects of ageing of different classes of components on

PSA. - Determining physical models for predicting the effects on component

reliability of different ageing mechanisms. This should cover passive and active components and components that are not normally modelled in current PSAs.

- Identifying the sensitivity of the PSA to different ageing mechanisms and the consideration of different components.

- Characterisation of the form of the time-dependent failure rate equation for different component types and generic environments.

- Data collection and analysis pilot study. One or more generic/common PSAs could be used for these studies.

Ohio St Univ. (USA)

Selected event-trees from sample NPPs to be determined.

LNPP (RUS) I would propose idea to issue annual (hand-)book/journal based on different experiences and studies. Different persons who have interest can publish their own articles, overview, reports, etc. Some committee would be responsible for the book/journal edition (one per year).

NMRI (JAP) Demonstration of evaluation of aging effects. Compare different methods.

Vattenfall (GER) The study should concentrate on components, which show real ageing like cables or pipes. Organisation should depend on task and expertise of the participating members as well their resources.

4.3 In which individual tasks or case studies would you like to participate, what are your requirements for these tasks and how would your participation link to your own current research programs?

UJV (CZ) We would like to participate actively, for example, in the development of means for quantitative modeling of ageing potential. Concretely, in selection of the most suitable probability distributions, in finding the methods for estimation of distribution parameters on the base of operational experience and generic data etc.

VTT (FIN) I would like to participate in the tasks that involve the modelling of degradation mechanisms concerning passive components. In order to learn about PSA I would also like to participate in a task that involves the incorporation of the ageing to PSA. To keep the amount of work reasonable, I do not want to participate in very many tasks. I would also like to take part in the defining of the contents and scope the tasks which I will participate. As most or all tasks will be linked to each other through their contents, the exchange of information between tasks should as open and easy as possible. Currently I am working in research projects that involve both deterministic and probabilistic modelling of degradation mechanisms damaging components of both conventional and nuclear power plants. I am also working in a research project which considers the application of RI-ISI. Generally, our participation necessitates support from Finnish energy utilities. Their prerequisite is that the tasks form a meaningful entity with our national projects and that the utilities gain from the work in form of information from other countries.

IRSN (FR) Interested to participate in the development of tasks 1, 2, 4 of 4.2. CEA (FR) Set up of methodology. VEIKI (HU) In principle, we are interested in each project task.

So far we have not yet developed reliability models for ageing. Thus, our contribution to Task 1 could focus on reviewing internationally accessible methods. Though, our longer-term research objectives cover model development. We believe that the success of Task 2 is dependent on the participation of as mane project partners as possible to be comprehensive. This would include out participation too. We see some uncertainties with respect to Task 3 as given above. Task 4 could focus on a limited number of potential applications to enable an in-depth and useful evaluation. A project is under discussion with Paks NPP on the “use of PSA for ageing management”. The simultaneous preparation of the two projects is seen advantageous from the point of view of information exchange and consistency.

ENEA (I) In principle there are not preclusions to the participation in almost all the tasks: only the aspects pertaining to the structural reliability should be excluded, pointing rather to the performance degradation evaluation of components during time. Reliability assessment of passive systems, currently underway, is linked to this research activity.

LEI (LT) LEI interest is to develop case studies on statistical aging analysis and implementation in Risk-Spectrum (mainly first two in 4.2). PSA model (non-aging, based on Risk-Spectrum software) is ready and statistical data could be obtained for the project purposes.

INR (RO) We are interested to participate in the evaluation of the available methods and approaches of ageing effects incorporation into PSA, identify specifications for different PSA applications and perform case studies. We can participate by involving the previous probabilistic models for Cernavoda NPP (95, 97), the present Cernavoda unit 1 models (based on an agreement with Cernavoda organization) and/or models of TRIGA reactor (testing, research reactor, 14 MWth).

During this period our research program is mainly focused on TRIGA reactor PSA models and data.

RELKO (SK) We would like to participate in both case studies. The first case study is linked with our data collection project for the purpose of PSA and RCM.

Forsmark NPS (SWE) We are interested to participate but so far we have no preferences.

British Energy (UK) We need to understand more about the project before we determine the extent of our participation.

Rolls Royce (UK) To be answered after the workshop. Ohio St Univ. (USA) Control system modeling. Ongoing projects include development of a procedure

for updating existing PRAs to incorporate digital control system reliability. LNPP (RUS) Ageing as CCF factor. Review of reports and data. NMRI (JAP) We would like to participate case study by our method.

We are now admitted a new project supported by special fund of “Nuclear technology”, Ministry of Education, Culture, Sports, Science and Technology, Japanese Government. In that project, we will develop a reliability analysis methodology that can handle aging effects on components with any kind of aging model. The methodology will be developed based on the GO-FLOW. And then, develop an Aging –PSA analysis system, which is based on the event tree – GO-FLOW combination with a reliability model for aging. We would like to compare our result of the case study with other participant’s results.

Vattenfall (GER) As an employee of an utility I can contribute information on practical issues like data collection, maintenance, event description etc.


I could contribute the most by developing and applying probabilistic/statistical models and/or methods of data analysis, using real data or simulations. This would be in collaboration with people in the project who know the engineering and physics of the problem, and who have or could get some example data. My work would need to be funded by the project, because I have no funds to support this effort.

APPENDIX IV

Workshop Participants

LIST OF PARTICIPANTS

Aldemir T. The Ohio State University Tel: +1 614 2924627 e-mail: [email protected] USA

Kovacs Z. RELKO Ltd Tel: +421 2 44460138 e-mail: [email protected] SLOVAK REPUBLIC

Bareith A. VEIKI Institute for Electric Power Research Tel: +36 1 4578250 e-mail: [email protected] HUNGARY

Kubanyi J. European Commission Tel: +31 224 565376 e-mail: [email protected] THE NETHERLANDS

Burgazzi L. ENEA Tel: +39 051 6098556 e-mail: [email protected] ITALY

Lanore J.M. IRSN Tel: +33 1 58357648 e-mail: [email protected] FRANCE

Cronvall O. Technical Research Centre of Finland (VTT) Tel: +358 9 4566857 e-mail: [email protected] FINLAND

Matuzas V. Lithuanian Energy Institute Tel: +370 37 401945 e-mail: [email protected] LITHUANIA

Devictor N. CEA Tel: +33 4 42253005 e-mail: [email protected] FRANCE

Moor S. Rolls-Royce Tel: +44 1332 632190 e-mail: [email protected] UNITED KINGDOM

Ellia-Hervy A. Areva Framatome ANP Tel: +33 1 47961743 e-mail: [email protected] FRANCE

Nitoi M. Institute for Nuclear Research Tel: +40 248 213400 ext 151 e-mail: [email protected] ROMANIA

Grime J. British Energy Generation Ltd Tel: +44 1452 652159 e-mail: [email protected] UNITED KINGDOM

Patrik M. European Commission Tel: +31 224 565386 e-mail: [email protected] THE NETHERLANDS

Holy J. Nuclear Research Institute REZ Tel: +420 2 66172167 e-mail: [email protected] CZECH REPUBLIC

Rodionov A. IRSN Tel: + 33 1 58357884 e-mail: [email protected] FRANCE

Hultqvist G. Forsmark Nuclear Power Station Tel: +46 173 81504 e-mail: [email protected] SWEDEN

Vasseur D. Electricite de France R&D Division Tel: +33 1 47654191 e-mail: [email protected] FRANCE

Kirchsteiger C. European Commission Tel: +31 224 565118 e-mail: [email protected] THE NETHERLANDS

Simola K. European Commission Tel: +31 224 565233 e-mail: [email protected] THE NETHERLANDS

Documents

Applications - Europaiet.jrc.ec.europa.eu/apsa/sites/apsa/files/files/documents/APSA... · applications, such as when PSA is to be used as a day-to-day tool for decision making