PSA Applications of the CODAP Event Database Sample Clauses

PSA Applications of the CODAP Event Database. The CODAP event database has been extensively applied by Member Organizations in support of PSA. One line of PSA R&D has focused on development of "hybrid piping reliability models" that incorporate probabilistic fracture mechanics results and insights, service experience considerations and expert judgment. The piping systems of commercial nuclear power plants are subjected to stringent design, manufacturing, fabrication and installation requirements, as well as mandatory and owner-defined in-service inspection (ISI) program requirements that account for past and current service experience. Also important to piping reliability are the aging management programs that have been implemented throughout the nuclear industry to mitigate or eliminate certain types of pipe degradation susceptibilities. Regardless of a chosen approach to piping reliability analysis, independent peer review processes invariably raise questions about the achieved level of realism and statistical uncertainty of quantitative results. How well do the results compare with the applicable service experience data? A particularly challenging peer review question is the one posed when no relevant service experience data is available. How should an analysis best be performed in view of zero major structural failures? Is there a preferred way to condition an assessment by what is known about certain combinations of degradation mechanism, operating environment and loading conditions? The likelihood of a pipe flaw propagating to a significant structural failure (SF) is expressed by the conditional failure probability pSF|DC where “DC” represents degraded condition. With no service data available to support a direct statistical estimation of the conditional probability the assessment can be based on probabilistic fracture mechanics (PFM), expert judgment, or a combination of service data insights, expert judgment and PFM. Different PFM algorithms have been developed, but with a focus on fatigue growth and stress corrosion cracking. There remain issues of dispute with respect to reconciliation of results obtained through statistical estimation versus the physical models of PFM, however. Results from studies to benchmark PFM calculations against field experience have shown PFM computer codes to over-predict pipe failure rates by more than an order magnitude relative to statistical estimates of field experience data [6]. In general, the results obtained with PFM computer codes are quite sensitive to a...
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