ABSTRACT

The accident in Fukushima Dai-ichi nuclear power plants reconfirms the necessity of the safety assessment considering multiple nuclear reactor units. However, consideration of the interdependency among safety systems or events in multiple units as well as the time dependency of accident progressions is difficult in the conventional event tree method, which is widely used in probabilistic risk assessments. Recently, the continuous Markov-chain Monte-Carlo (CMMC) method coupled with a plant safety analysis or a severe accident analysis code has been paid attention to address these issues. In the present study, the CMMC coupling method is applied to the risk assessment of multiple units to clarify the benefits and issues to be resolved of this method. Since the CMMC coupling method requires many executions of an accident analysis code, a meta-model that simplifies systems and physical phenomena in accidents is used in this study to reduce computational cost. Furthermore, the inverse transform sampling method is newly adapted. Numerical analyses of BWR accident under station blackout with loss of cooling capability are carried out considering the correlation among the availabilities of mitigation systems. The results suggested that the CMMC coupling method can quantitatively treat the interdependency and time dependency among events in multiple units.

摘要

福岛第一核电站事故再次证实了考虑多核反应堆机组进行安全评估的必要性。然而，在广泛用于概率风险评估的常规事件树方法中，考虑多个单元中安全系统或事件之间的相互依赖性以及事故进程的时间依赖性是困难的。最近，连续马尔可夫链蒙特卡罗 (CMMC) 方法与工厂安全分析或严重事故分析代码相结合，已受到关注以解决这些问题。在本研究中，CMMC 耦合方法被应用于多个单元的风险评估，以阐明该方法的好处和需要解决的问题。由于 CMMC 耦合方法需要多次执行事故分析代码，本研究使用了一种简化系统和事故物理现象的元模型，以降低计算成本。此外，新适应了逆变换采样方法。考虑到缓解系统可用性之间的相关性，对停电并失去冷却能力的BWR事故进行了数值分析。结果表明，CMMC耦合方法可以定量处理多单元事件之间的相互依赖性和时间依赖性。考虑到缓解系统可用性之间的相关性，对停电并失去冷却能力的BWR事故进行了数值分析。结果表明，CMMC耦合方法可以定量处理多单元事件之间的相互依赖性和时间依赖性。考虑到缓解系统可用性之间的相关性，对停电并失去冷却能力的BWR事故进行了数值分析。结果表明，CMMC耦合方法可以定量处理多单元事件之间的相互依赖性和时间依赖性。