Reliability Data Update Method (RDUM) based on living PSA for emergency diesel generator of Daya Bay nuclear power plant

In the field of Living Probabilistic Safety Assessment (LPSA) the reliability data updating is an important factor. In risk analysis equipment failure data is needed to estimate the frequencies of events contributing to risk posed by a facility. Five years data of Emergency Diesel Generator (EDG) of Daya Bay Nuclear Power Plant (NPP) has been studied in this paper. The data updating process has been done by using two methods (i.e.) classical method and Bayesian method. The aim of using these methods is to calculate operational failure rate (λ) and demand failure probability (p). The results show that operational failure rate is 1.7E−3 per hour and demand failure probability is 2.4E−2 per day of Daya Bay NPP. By comparing the results obtain from classical and Bayesian method with EDF (Electric De France) it is concluded that the design and construction of Daya Bay NPP is very different with EDF so reliability parameters used in Daya Bay NPP is based on classical method.