| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1729191 | Annals of Nuclear Energy | 2011 | 6 Pages |
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., the classical method and Bayesian method. The aim of using these methods is to calculate the operational failure rate (λ) and demand failure probability (p). The results show that the operational failure rate is 1.7E−3 per hour and the demand failure probability is 2.4E−2 demand per day for Daya Bay NPP. By comparing the results obtain from classical and Bayesian methods with EDF (Electric De France) it is concluded that the design and construction of Daya Bay NPP is very different than EDF therefore the reliability parameters used in Daya Bay NPP is based on the classical method.
► Updating the reliability data for the emergency diesel generator of Daya Bay NPP is the main theme of this research. ► From three sources data has been collected (EDF, Bayesian and Classical). ► A computer based program UDEDG (Update Data for Emergency Diesel Generator) has been designed. ► Operational failure rate and demand failure probability have been calculated. ► Comparison of data proves that classical results are suitable for EDG in Daya Bay NPP.
