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Title: Cognitive decision errors and organization vulnerabilities in nuclear power plant safety management: Modeling using the TOGA meta-theory framework

Abstract

In the field of nuclear power plant (NPP) safety modeling, the perception of the role of socio-cognitive engineering (SCE) is continuously increasing. Today, the focus is especially on the identification of human and organization decisional errors caused by operators and managers under high-risk conditions, as evident by analyzing reports on nuclear incidents occurred in the past. At present, the engineering and social safety requirements need to enlarge their domain of interest in such a way to include all possible losses generating events that could be the consequences of an abnormal state of a NPP. Socio-cognitive modeling of Integrated Nuclear Safety Management (INSM) using the TOGA meta-theory has been discussed during the ICCAP 2011 Conference. In this paper, more detailed aspects of the cognitive decision-making and its possible human errors and organizational vulnerability are presented. The formal TOGA-based network model for cognitive decision-making enables to indicate and analyze nodes and arcs in which plant operators and managers errors may appear. The TOGA's multi-level IPK (Information, Preferences, Knowledge) model of abstract intelligent agents (AIAs) is applied. In the NPP context, super-safety approach is also discussed, by taking under consideration unexpected events and managing them from a systemic perspective. As the nature ofmore » human errors depends on the specific properties of the decision-maker and the decisional context of operation, a classification of decision-making using IPK is suggested. Several types of initial situations of decision-making useful for the diagnosis of NPP operators and managers errors are considered. The developed models can be used as a basis for applications to NPP educational or engineering simulators to be used for training the NPP executive staff. (authors)« less

Authors:
 [1];  [2];  [1];  [1]
  1. UTFISST, ENEA Casaccia, via Anguillarese 301, Rome (Italy)
  2. ECONA, Centro Interuniversitario Elaborazione Cognitiva Sistemi Naturali e Artificiali, via dei Marsi 47, Rome (Italy)
Publication Date:
Research Org.:
American Nuclear Society, 555 North Kensington Avenue, La Grange Park, IL 60526 (United States)
OSTI Identifier:
22106054
Resource Type:
Conference
Resource Relation:
Conference: ICAPP '12: 2012 International Congress on Advances in Nuclear Power Plants, Chicago, IL (United States), 24-28 Jun 2012; Other Information: Country of input: France; 26 refs.; Related Information: In: Proceedings of the 2012 International Congress on Advances in Nuclear Power Plants - ICAPP '12| 2799 p.
Country of Publication:
United States
Language:
English
Subject:
22 GENERAL STUDIES OF NUCLEAR REACTORS; 96 KNOWLEDGE MANAGEMENT AND PRESERVATION; COMPUTERIZED SIMULATION; DECISION MAKING; ERRORS; HUMAN FACTORS; HUMAN FACTORS ENGINEERING; INFORMATION; KNOWLEDGE MANAGEMENT; NUCLEAR POWER PLANTS; REACTOR ACCIDENTS; REACTOR SAFETY; REACTOR SIMULATORS; SAFETY ENGINEERING; TRAINING; VULNERABILITY

Citation Formats

Cappelli, M., Gadomski, A. M., Sepiellis, M., Wronikowska, M. W., and Poznan School of Social Sciences. Cognitive decision errors and organization vulnerabilities in nuclear power plant safety management: Modeling using the TOGA meta-theory framework. United States: N. p., 2012. Web.
Cappelli, M., Gadomski, A. M., Sepiellis, M., Wronikowska, M. W., & Poznan School of Social Sciences. Cognitive decision errors and organization vulnerabilities in nuclear power plant safety management: Modeling using the TOGA meta-theory framework. United States.
Cappelli, M., Gadomski, A. M., Sepiellis, M., Wronikowska, M. W., and Poznan School of Social Sciences. 2012. "Cognitive decision errors and organization vulnerabilities in nuclear power plant safety management: Modeling using the TOGA meta-theory framework". United States.
@article{osti_22106054,
title = {Cognitive decision errors and organization vulnerabilities in nuclear power plant safety management: Modeling using the TOGA meta-theory framework},
author = {Cappelli, M. and Gadomski, A. M. and Sepiellis, M. and Wronikowska, M. W. and Poznan School of Social Sciences},
abstractNote = {In the field of nuclear power plant (NPP) safety modeling, the perception of the role of socio-cognitive engineering (SCE) is continuously increasing. Today, the focus is especially on the identification of human and organization decisional errors caused by operators and managers under high-risk conditions, as evident by analyzing reports on nuclear incidents occurred in the past. At present, the engineering and social safety requirements need to enlarge their domain of interest in such a way to include all possible losses generating events that could be the consequences of an abnormal state of a NPP. Socio-cognitive modeling of Integrated Nuclear Safety Management (INSM) using the TOGA meta-theory has been discussed during the ICCAP 2011 Conference. In this paper, more detailed aspects of the cognitive decision-making and its possible human errors and organizational vulnerability are presented. The formal TOGA-based network model for cognitive decision-making enables to indicate and analyze nodes and arcs in which plant operators and managers errors may appear. The TOGA's multi-level IPK (Information, Preferences, Knowledge) model of abstract intelligent agents (AIAs) is applied. In the NPP context, super-safety approach is also discussed, by taking under consideration unexpected events and managing them from a systemic perspective. As the nature of human errors depends on the specific properties of the decision-maker and the decisional context of operation, a classification of decision-making using IPK is suggested. Several types of initial situations of decision-making useful for the diagnosis of NPP operators and managers errors are considered. The developed models can be used as a basis for applications to NPP educational or engineering simulators to be used for training the NPP executive staff. (authors)},
doi = {},
url = {https://www.osti.gov/biblio/22106054}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2012},
month = {7}
}

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