Abstract
It has to be ensured that the risk is on an acceptable level at all times during the operation of a nuclear power plant, including different plant operation states. Probabilistic risk assessment (PRA) is mainly used to evaluate the average risk reflecting average plant conditions, but it can also be used estimate how the risk behaves as a function of time based on the expected plant conditions at different time points. Time-dependent PRA can be used to analyse maintenance and test plans, to perform risk follow-up based on past events, to monitor the current risk or to analyse seasonal variations in risk.
This report presents a new time-dependent PRA feature in FinPSA software. The user can specify events, such as maintenance activities or tests, parameter changes and configuration changes to a time line in a task file, and FinPSA automatically calculates and draws the time-dependent risk curve based on that information, existing minimal cut sets and data. More detailed analyses, e.g. computation of importance measures, can also be performed for selected time points. The time-dependent analysis is demonstrated with three simplified analysis cases.
This report presents a new time-dependent PRA feature in FinPSA software. The user can specify events, such as maintenance activities or tests, parameter changes and configuration changes to a time line in a task file, and FinPSA automatically calculates and draws the time-dependent risk curve based on that information, existing minimal cut sets and data. More detailed analyses, e.g. computation of importance measures, can also be performed for selected time points. The time-dependent analysis is demonstrated with three simplified analysis cases.
Original language | English |
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Publisher | VTT Technical Research Centre of Finland |
Number of pages | 26 |
Publication status | Published - 18 Sept 2018 |
MoE publication type | Not Eligible |
Publication series
Series | VTT Research Report |
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Number | VTT-R-04119-18 |
Keywords
- probabilistic risk assessment
- time-dependent
- Maintenance planning