Advance Liquid Metal Reactor Discrete Dynamic Event Tree/Bayesian Network Analysis and Incident Management Guidelines (Risk Management for Sodium Fast Reactors)

Technical Report · Wed Apr 01 04:00:00 EDT 2015

DOI:https://doi.org/10.2172/1177842· OSTI ID:1177842

Denman, Matthew R. ^[1]; Groth, Katrina M. ^[1]; Cardoni, Jeffrey N. ^[1]; Wheeler, Timothy A. ^[1]

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1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Accident management is an important component to maintaining risk at acceptable levels for all complex systems, such as nuclear power plants. With the introduction of self-correcting, or inherently safe, reactor designs the focus has shifted from management by operators to allowing the system's design to manage the accident. Inherently and passively safe designs are laudable, but nonetheless extreme boundary conditions can interfere with the design attributes which facilitate inherent safety, thus resulting in unanticipated and undesirable end states. This report examines an inherently safe and small sodium fast reactor experiencing a beyond design basis seismic event with the intent of exploring two issues: (1) can human intervention either improve or worsen the potential end states and (2) can a Bayesian Network be constructed to infer the state of the reactor to inform.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE Office of Nuclear Energy (NE), Nuclear Reactor Technologies (NE-7)
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 1177842
• Report Number(s): SAND--2015-2484; 579783
• Country of Publication: United States
• Language: English

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