BibTeX

@inproceedings{GrothESREL2015,
title = {Proof-of-concept accident diagnostic support for sodium fast reactors},
author = {K M Groth and M R Denman and T Jones and M Darling and G Luger},
year = {2015},
date = {2015-09-01},
booktitle = {Proceedings of the European Society for Reliability Annual Meeting (ESREL 2015)},
address = {Zurich, Switzerland},
abstract = {Severe accidents pose unique challenges for nuclear power plant operating crews, including limitations in plant status information and lack of detailed diagnosis and response planning support. Simulation-based PRA provides an opportunity to garner detailed insight into severe accidents; this insight has implications for both HRA and accident management. In this work, we present a framework leveraging simulation-based PRA methods to provide real-time diagnostic support for nuclear power plant operators during severe accidents. This paper presents a prototype model for diagnosing reactor system states associated with loss of flow and transient overpower accidents after an earthquake in a generic Sodium Fast Reactor. We discuss a vision for using this framework to enhance human performance and modeling},
keywords = {Artificial intelligence, Bayesian Networks, Decision support systems, Dynamic PRA, nuclear power, Probabilistic risk assessment (PRA), risk-informed procedures},
pubstate = {published},
tppubtype = {inproceedings}
}

Abstract

Severe accidents pose unique challenges for nuclear power plant operating crews, including limitations in plant status information and lack of detailed diagnosis and response planning support. Simulation-based PRA provides an opportunity to garner detailed insight into severe accidents; this insight has implications for both HRA and accident management. In this work, we present a framework leveraging simulation-based PRA methods to provide real-time diagnostic support for nuclear power plant operators during severe accidents. This paper presents a prototype model for diagnosing reactor system states associated with loss of flow and transient overpower accidents after an earthquake in a generic Sodium Fast Reactor. We discuss a vision for using this framework to enhance human performance and modeling.