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Limitations of traditional tools for beyond design basis external hazard PRA

Journal Article · · Nuclear Engineering and Design
 [1];  [2];  [2]
  1. North Carolina State Univ., Raleigh, NC (United States); North Carolina State Univ., Raleigh, NC (United States)
  2. North Carolina State Univ., Raleigh, NC (United States). Center for Nuclear Energy Facilities and Structures
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Probabilistic risk assessment (PRA) is being used increasingly by the nuclear industry for safety during normal operations as well as for the protection against external hazards. Computation of total risk in an external hazard PRA is dependent on hazard assessment, fragility assessment, and systems analysis. A systems analysis for propagation of component fragilities is conducted using event and fault trees. The event and fault trees for an actual power plant can be fairly large in size, which imposes computational challenges. Hence, certain assumptions are employed for computational efficiency. These assumptions typically represent the conditions imposed during the design basis (DB) scenario. The traditional PRA tools based on these assumptions are also widely applied to perform risk assessment in the context of beyond design basis (BDB) scenarios. However, some of these assumptions may not be valid for certain BDB scenarios. In addition, the probability of dependent failures also increases in BDB scenarios due to common cause failures (CCF) which usually results from design modifications, human errors, etc. In this manuscript, a simple and a relatively more complex illustrative examples are used to show the limitation of these assumptions in the numerical quantification of risk for the case of BDB conditions. Case studies with CCF events across multiple fault trees are also presented to illustrate the effect of these assumptions when traditional approach is used in BDB risk assessment. It is shown that the assumptions are valid for the case of DB conditions but may lead to excessively conservative risk estimates in the case of BDB conditions. Finally, a Bayesian network based top-down algorithm is proposed as an alternative tool for accurate numerical quantification of total risk in systems analysis.
Research Organization:
North Carolina State Univ., Raleigh, NC (United States)
Sponsoring Organization:
USDOE Advanced Research Projects Agency - Energy (ARPA-E)
Grant/Contract Number:
AR0000976
OSTI ID:
1848325
Alternate ID(s):
OSTI ID: 1776154
Journal Information:
Nuclear Engineering and Design, Journal Name: Nuclear Engineering and Design Journal Issue: C Vol. 370; ISSN 0029-5493
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

73 NUCLEAR PHYSICS AND RADIATION PHYSICS
Bayesian network
Beyond design basis accidents
Common cause failure
Event tree
Fault tree
Logic tree
Nuclear Science & Technology
PRA
Probabilistic risk assessment