Development and application of the dynamic system doctor to nuclear reactor probabilistic risk assessments.

Abstract

This LDRD project has produced a tool that makes probabilistic risk assessments (PRAs) of nuclear reactors-analyses which are very resource intensive-more efficient. PRAs of nuclear reactors are being increasingly relied on by the United States Nuclear Regulatory Commission (U.S.N.R.C.) for licensing decisions for current and advanced reactors. Yet, PRAs are produced much as they were 20 years ago. The work here applied a modern systems analysis technique to the accident progression analysis portion of the PRA; the technique was a system-independent multi-task computer driver routine.Initially, the objective of the work was to fuse the accident progression event tree (APET) portion of a PRA to the dynamic system doctor (DSD) created by Ohio State University. Instead, during the initial efforts, it was found that the DSD could be linked directly to a detailed accident progression phenomenological simulation code-the type on which APET construction and analysis relies, albeit indirectly-and thereby directly create and analyze the APET. The expanded DSD computational architecture and infrastructure that was created during this effort is called ADAPT (Analysis of Dynamic Accident Progression Trees). ADAPT is a system software infrastructure that supports execution and analysis of multiple dynamic event-tree simulations on distributed environments. A simulator abstraction layer was developed, and a generic driver was implemented for executing simulators on a distributed environment.As a demonstration of the use of the methodological tool, ADAPT was applied to quantify the likelihood of competing accident progression pathways occurring for a particular accident scenario in a particular reactor type using MELCOR, an integrated severe accident analysis code developed at Sandia. (ADAPT was intentionally created with flexibility, however, and is not limited to interacting with only one code. With minor coding changes to input files, ADAPT can be linked to other such codes.) The results of this demonstration indicate that the approach can significantly reduce the resources required for Level 2 PRAs. From the phenomenological viewpoint, ADAPT can also treat the associated epistemic and aleatory uncertainties.This methodology can also be used for analyses of other complex systems. Any complex system can be analyzed using ADAPT if the workings of that system can be displayed as an event tree, there is a computer code that simulates how those events could progress, and that simulator code has switches to turn on and off system events, phenomena, etc.Using and applying ADAPT to particular problems is not human independent. While the human resources for the creation and analysis of the accident progression are significantly decreased, knowledgeable analysts are still necessary for a given project to apply ADAPT successfully.This research and development effort has met its original goals and then exceeded them.4

Sensitivity Analyses of Steam Generator Tube Thickness on Induced-SGTR in SBO Accident

“…For the case studied, if the uncertainty in the creep rupture parameter is not taken into account, surge line rupture will always precede and preclude rupture of the steam generator tubes. In order to quantify the uncertainty in R, a cumulative distribution function was constructed from experimental data in the form of a lognormal distribution with a mean value of µ = 1 and standard deviation of σ = 0.4 [5,7]. The distribution is given as:…”

The Analysis of Severe Accident Induced Steam Generator Tube Rupture and LERF Risk

“…For the case studied, if the uncertainty in the creep rupture parameter is not taken into account, surge line rupture will always precede and preclude rupture of the steam generator tubes. In order to quantify the uncertainty in R, a cumulative distribution function was constructed from experimental data in the form of a lognormal distribution with a mean value of µ = 1 and standard deviation of σ = 0.4 [7,9]. The distribution is given as…”