Impact of equipment reliability on safety classification of research reactors

Abstract

The article presents the analysis of the unique operational data on equipment failures in the MARIA research reactor spanning from 2000 to 2023. This was compared with the updated statistics of the IAEA and the U.S. NRC concerning equipment reliability of research and commercial reactors, respectively. The analysis is the follow-up to the MARIA safety classification process. The problem of the input data selection and the impact of the equipment reliability data on the classification results was considered. The analysis revealed that the MARIA equipment exceeds the reliability standards for research reactors, although it is below the average for commercial power plants. The equipment reliability estimates were then improved by applying the Crow-AMSAA models to the MARIA failure rates and updating the generic databases with operational experience using the Bayesian approach . However, no evidence was found to promote using one data source over another in the safety classification of research reactors. Instead, the Integrated Reliability Data Aggregation (IRDA) approach was proposed, where multiple data sources are combined by the Monte Carlo-based algorithm complemented by the Value Tree Analysis (VTA) methods for weighting the inputs.

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