Reliability Data Analysis

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Cody Long
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1 IAEA Training Course on Safety Assessment of NPPs to Assist Decision Making Reliability Data Analysis Lecturer Lesson Lesson IV IV 3_5 3_5 Workshop Information IAEA Workshop City, XX XX - City -XX, Country Month, Year Year

Lecturer Lesson Lesson IV IV 3_5 3_5 Workshop

2 Objective and Need of Reliability Data Analysis The reliability data in a PSA is needed to quantify the PSA and obtain risk estimates. Otherwise only qualitative information, such as minimal cut sets or single failures, can be obtained. Reliability data is needed for: Initiating event frequencies Component failure probabilities Component outage probabilities Common cause failures (not addressed here) Human error probabilities (not addressed here) Probability of special basic events (case specific) PSA results depend exclusively on the model logic and data. Therefore, an adequate acquisition of reliability data is essential since data will strongly influence the PSA results. IAEA Training Course on Safety Assessment 2

Reliability data is needed for: Initiating event frequencies Component failure probabilities Component outage probabilities Common cause failures (not addressed here) Human error

3 Type of Reliability Data Sources Expert judgement Generic data sources: National data banks International experience of NPPs of same or different types Wide industry experience Generic data based on expert judgement Plant specific experience IAEA Training Course on Safety Assessment 3

different types Wide industry experience Generic data based on expert

4 Initiating Event Data For frequent initiating events : Data can be mainly based on plant specific data. Data can be collected from the incident reporting system. If not enough specific data is available, use generic data. Analyse generic data to account for applicability of generic experience. Use Bayesian analysis if necessary to combine generic experience with plan specific analysis. Always check applicability and quality of generic data sources. For infrequent initiating events: Perform system analysis to derive system failure frequency, e.g. failure of support systems Perform structural integrity analysis for structural failure rates Otherwise use the generic plant experience that best fits to your needs, or use engineering judgement IAEA Training Course on Safety Assessment 4

Use Bayesian analysis if necessary to combine generic experience with plan specific analysis. Always check applicability and quality of generic data sources.

5 Component Failure Probabilities Reliability Models Used for Components in a PSA 1 Components failing to run or fulfilling its function during a given mission time, e.g 24 hours. An exponential distribution of life time is assumed. Failure rates (λ) are to be obtained. Failure probabilities are calculated as: U(t) = 1 - exp (- λ t), t = mission time. 2 Standby components failing to fulfil its mission when they are required. An exponential distribution of life time is assumed. Failure rates (λ) are to be obtained. Mean unavailability between consecutive tests is calculated as: U(τ) ~ 1/2 λ τ, τ : test interval 3 Components with a constant failure probability per demand. This probability needs to be estimated. IAEA Training Course on Safety Assessment 5

2 Standby components failing to fulfil its mission when they are required. An exponential distribution of life time is assumed. Failure rates (λ) are to be obtained.

6 Use of Component Reliability Models For components running under normal conditions and during the accident, the failure to run model (1) is used For standby components, the standby model (2) is used. If the component needs to work during the accident, the failure to run (1) has to be modelled in addition. Example: A valve of a safety system needs to open (standby model). A pump of the same system needs to start (standby model) and to run during a certain time (failure to run model) For components which failure probability is mostly challenged by the number of demands, rather than the idle time, a failure on demand is used. Example: A turbopump demanded to restart after a shutdown, following a previous successful first start. 1. U(t) = 1 - exp (- λ t), t = mission time. 2. U(τ) ~ 1/2 λ τ, τ : test interval 3. U = p, constant probability IAEA Training Course on Safety Assessment 6

A pump of the same system needs to start (standby model) and to run during a certain time (failure to run model) For components which failure probability is mostly challenged by the number of

7 Selection of Component Reliability Data To the extent possible use plant specific experience, taking into account the resources available. Plant data is the most appropriate, but often not available in a usable form. If plant experience is small to allow direct estimates, with adequate level of confidence, a Bayesian update of generic data is recommended When necessary, generic data should be carefully selected, taking into account: plant characteristics and similarity of equipment component boundaries, level of detail and failure definitions used in the PSA. They should match with the definitions of the generic sources. generic data sources based on operational experience preferably to those based on expert judgements use relatively new data sources professionally developed, and independently reviewed IAEA Training Course on Safety Assessment 7

If plant experience is small to allow direct estimates, with adequate level of confidence, a Bayesian update of generic data is recommended When necessary, generic data should be carefully selected,

8 Gather Plant Information to Obtain Specific Reliability Data A typical maximum likelihood estimate for a failure rate (λ) is: λ = (No. of failures +0.5) / (No. of items x Reference time) Therefore, 3 elements of information are needed: An adequate inventory of components. A large amount of components provides a more confident estimate. However, grouping together components that exhibit significant design or operational differences can increase estimate uncertainty. Reference time, e.g. calendar time or running time, should be adequately selected and estimated. The later can be estimated, when results valid, based on plant computer, counters, etc. For failures on demand, the number of valid demands is to be estimated. Number of failures: From maintenance records, other plant information More statistical evidence exists for running components than for standby components. Component boundaries in the model need to be taken into account Plant records should be complete, retrievable, well documented. Plant Management support is essential A PSA specialist should do the analysis. Craftsmen do the maintenance and testing, but they may not be the most trained to decide whether a repair can be considered a failure for PSA purposes or not. IAEA Training Course on Safety Assessment 8

However, grouping together components that exhibit significant design or operational differences can increase estimate uncertainty. Reference time, e.g. calendar time or running time, should be adequately selected and estimated.

9 Component Outage Probabilities Component and system outages due to maintenance or testing are analysed and grouped in a number of basic events based on the similar impact on the system functionality due to the realignments required A Estimates are necessary of the frequency and duration of such outages, for each mode of operation considered. These estimates can be derived from system outage logs, maintenance records, periodic test procedures or other plant documentation, or from engineering judgement. The average outage time probability is the ratio of the sum of outage times to the total time at each mode of operation considered. U = tout / t total IAEA Training Course on Safety Assessment 9

These estimates can be derived from system outage logs, maintenance records, periodic test procedures or other plant documentation, or from engineering judgement.

10 Conclusions Use plant specific data whenever possible Don t waste resources for collecting plant specific data when these data will have low impact on the results and good estimates can be obtained easier Use Bayesian analysis if plant experience is not enough. Check validity of generic sources. Sometimes they are old, based on non valid generic sources or on expert judgement. If possible use generic data from similar components/plants. Use engineering judgement if generic data is not available or cannot be trusted. IAEA Training Course on Safety Assessment 10

Check validity of generic sources. Sometimes they are old, based on non valid generic sources or on expert judgement.

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