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Proceedings of the Eighth International Conference on Probabilistic Safety Assessment & Management (PSAM)

Editor
Michael G. Stamatelatos
Michael G. Stamatelatos
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Harold S. Blackman
Harold S. Blackman
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ISBN-10:
0791802442
No. of Pages:
2576
Publisher:
ASME Press
Publication date:
2006

The Swedish nuclear power utility Oskarshamn Power Group (OKG), is investigating how the use of a risk monitor can facilitate and improve risk-informed decision-making at their nuclear power plants. A pilot project was initiated and carried out in 2004. The project included investigating if a risk monitor can be used for optimizing surveillance test intervals (STI) for diesel- and gas turbine generators with regard to risk level.

STIs can be analyzed probabilistically with the use of a risk monitor. The risk monitor in this case uses a PSA model in which time dependent reliability models are included. The risk monitor must meet the following requirements:

• Possibility to vary test intervals in the time dependent reliability models.

• Ability to perform time dependent analyses (i.e. analyses at actual time points)

• Possibility to consider the specific test time points of different equipment

The Oskarhamn 2 (O2), PSA Level 1 model was converted into a risk monitor using RiskSpectrum RiskWatcher (RSRW) software. The converted PSA model included the complete PSA model for the power operation mode. RSRW makes a complete requantification for every analysis based on the whole model without truncation. Time dependent reliability data are taken into account, i.e. a shorter test interval will increase the components availability (possibility to e.g. start on demand).

The converted O2 model was used to investigate whether it would be possible to balance longer test intervals for diesel generators, gas turbine generators and high pressure injection system with shorter test intervals for the low pressure injection system, while maintaining a low risk level at the plant.

The results show that a new mixture of test intervals can be implemented with small changes in the risk as calculated with the risk monitor model. The results indicate that the total number of test activities for the systems included in the pilot study could be reduced by 20% with maintained level of risk.

A risk monitor accounting for test interval variation in availability calculations for components is well suited for evaluation of test interval strategies. It also enables the analyst to evaluate the risk level over a period of time including the impact the actual plant status may have on the risk level.

In this paper, the following limitations have been discussed;

• Can reliability models and reliability data used for modeling of component failures in the PSA model, be used also when STIs are changed?

• How is CCF treated when changing STIs?

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