James B. O'Brien
(Picture N/A)


Emergency Preparedness Specialist, U.S. Nuclear Regulatory Commission
Office of Nuclear Reactor Regulation
MS O-12 H2, U.S. Nuclear Regulatory Commission, Washington, DC 20555
Phone: +1 (301) 415-2919
E-mail: jbo@nrc.gov / obrienj@eng.umd.edu


 

Research Interests

PRA (Probabilistic Risk Assessment)

Expert Systems

System Modeling
 

Educations

PhD Nuclear Engineering from University of Maryland, 1998.
(Title of Dissertation: Methodology for Modeling System Evolution to Support Decisionmaking with an Application in Severe Accident Management)

MS Materials Engineering from Drexel University, 1992.

BS Nuclear Engineering from North Carolina State University, 1982.
 
 
Major Publication

1.  O'Brien, J.  Kim, T., and Reynolds, S.,  "Environmental Standard Review Plan for the review of license renewal applications for Nuclear Power Plants,"  NUREG-1429, U.S. Nuclear Regulatory Commission, 1991.

2.  O'Brien, J.,  "Insights on Emergency Action Levels," Proceedings of the Sixth Topical Meeting on Emergency Preparedness and Response," San Francisco, April 1997, American Nuclear Society.

3.  O'Brien, J.  and Modarres M.,  "Severe Accident Management using a Function Centered Method,"  Proceedings of the Fifth International Workshop on Functional Modeling of Complex Technical Systems, Paris-Troyes, France, July 1997.

 
Hobby

Tennis



  Abstract of Dissertation:

Title: Methodology for Modeling System Evolution to Support Decisionmaking with an Application in Severe Accident Management

A new methodology is developed for modeling a system's evolution to support decisionmaking on alternative actions which affect the system's evolution. The methodology is based upon the goal tree success tree method for hierarchal decomposition of the system's objective. The goal tree success tree structure is used to identify the system's objective and supporting functions and the events and actions which affect realization of these functions.  The events are logically arranged using an event tree format and potential event sequences and end states are identified.  The probability of the occurrence of the events are determined via condition-based logical diagrams (CLDs) and functional logic diagrams (FLDs) which model the propagation of binary logic (in the case of CLDs) and incorporate equations representing the more complex phenomenology (in the case of FLDs) associated with these events. The analytic hierarchy process is then used to evaluate the alternative actions affecting the end states and provide a recommendation on the preferred actions for meeting the system objective. The CLDs and FLDs provide a mechanism for modeling diverse knowledge, i.e., deterministic, probabilistic, logic based, as well as temporal, in a uniform manner.  This methodology is used to develop a model for analyzing severe accident phenomena and alternative actions for mitigating a severe accident at a nuclear power plant.  This severe accident model is then used as the knowledge base for a real-time expert system.  Tests run using this expert system demonstrate its capability to calculate the probability of various accident progression end states and provide recommendations on the priority for implementing severe accident mitigation strategies.  In addition, research was performed to evaluate the use of the FLD concept to model containment failure from direct containment heating as analyzed using the Risk Oriented Accident Analysis Methodology.  A system of hierarchically linked FLDs were developed which illustrate the relative effect of input parameters on intermediate and final level parameters.  This research has illustrated the usefulness of this modeling methodology to integrate diverse knowledge in a manner useful in supporting decisionmaking. 
 


 
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