Operational performance risk assessment in support of a supervisory control system

A. Guler, M. Muhlheim, S. Cetiner, R. Denning

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A supervisory control system is being developed for multiunit advanced small modular reactors to minimize human interventions during normal and abnormal operations. In the supervisory control system, control action decisions are made based on a probabilistic risk assessment that employs event trees and fault trees. Although traditional probabilistic risk assessment tools are implemented, their scope is extended to normal operations, and the application is reversed to assess the success of non-safety related systems and to enable continued operation of the plant. This extended probabilistic risk assessment approach is called operational performance risk assessment (OPRA). OPRA helps to identify available paths, combine control actions for maintaining plant conditions within operational limits, and to quantify the likelihood of success of these operational trajectories to optimize the selection of alternative actions without activating reactor protection system. In this paper, a case study of OPRA in a supervisory control system is demonstrated for the Advanced Liquid Metal Reactor (ALMR) Power Reactor Inherently Safe Module (PRISM) design, specifically the power conversion system. The scenario investigated involved a condition in which the feedwater control valve that was observed to be drifting to the closed position. Alternative plant configurations that would allow the plant to continue to operate at full or reduced power were identified using OPRA. Dynamic analyses were performed with a thermal-hydraulic model of the ALMR PRISM system using Modelica to evaluate the magnitude of safety margins. Successful recovery paths for the selected scenario were identified and quantified using the supervisory control system.

Original languageEnglish
Title of host publication10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017
PublisherAmerican Nuclear Society
Pages1125-1132
Number of pages8
ISBN (Electronic)9781510851160
StatePublished - 2017
Event10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017 - San Francisco, United States
Duration: Jun 11 2017Jun 15 2017

Publication series

Name10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017
Volume2

Conference

Conference10th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2017
Country/TerritoryUnited States
CitySan Francisco
Period06/11/1706/15/17

Funding

This project was funded by the US Department of Energy's Office of Nuclear Energy under the Instrumentation, Control, and Human-Machine Interface technical area of the Advanced Reactor Technologies program. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

FundersFunder number
US Department of Energy
US Department of Energy's Office of Nuclear Energy
U.S. Department of Energy
Interface
Office of Nuclear Energy

    Keywords

    • Operational performance risk assessment
    • Supervisory control system

    Fingerprint

    Dive into the research topics of 'Operational performance risk assessment in support of a supervisory control system'. Together they form a unique fingerprint.

    Cite this