Quantifying the impact of risk mitigation measures using SPAR-H and RCM Approaches: Case study based on VVER-1000 systems

Abstract

Probabilistic Safety Assessment (PSA) provides a systematic and quantitative approach to assess the risk associated with different components and systems within a nuclear power plant. By quantifying the impact of risk mitigation measures, decision-makers can prioritize and implement solutions that have the most significant impact on reducing risk. Fault Tree Analysis (FTA) is employed as a systematic method within PSA, encompassing all modes of failure across equipment and associated support systems, including unavailability due to maintenance (UDM), human errors (HEs), and common cause failures (CCFs). In the present research, the Extra Borating System (EBS) and the Chilled Water Operating Circuit System (CWOCS) of essential loads are modeled in the SAPHIRE code using VVER-1000 design data. Through importance analysis employing the Fussell-Vesley criterion, the most significant basic events for these two systems are identified. Subsequently, the outcomes of the importance analysis are examined using diversity, SPAR-H, and Reliability Centered Maintenance (RCM) techniques. Recommendations such as the enhancement of diversity, increasing staff training, promoting Human Machine Interface (HMI), reduction of maintenance time, and improvement of power supply reliability are proposed for the most crucial basic events. The ensuing impact of these measures on the reliability of the EBS and CWOCS is subsequently assessed. Through a comparison between the new failure probability and the previous, it is determined that improvements in CCFs contribute a 30% effect; HEs have a 14% effect and UDMs have a 5% effect, with a cumulative impact of 35% on the failure probability of the EBS system. Similarly, for the CWOCS system, enhancements in CCFs contribute 20%, UDMs 17%, and improved power supply reliability 19%, with a cumulative impact of 29%.