Decision Analytic Framework for a Decision Support System for Nuclear Emergency Management

2016 ◽  
pp. 163-169 ◽  
Author(s):  
Simon French ◽  
Jim Smith
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Emergency Management ◽  
Support System ◽  
Analytic Framework ◽  
Nuclear Emergency

scholarly journals THE STUDY OF ATMOSPHERIC DISPERSION MODEL ON ACCIDENT SCENARIO OF RESEARCH REACTOR G. A. SIWABESSY USING HOTSPOT CODES AS A NUCLEAR EMERGENCY DECISION SUPPORT SYSTEM

2019 ◽  
Vol 21 (1) ◽  
pp. 1
Author(s):  
Arif Yuniarto ◽  
Moh. Cecep Cepi Hikmat
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Research Reactor ◽  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Google Earth ◽  
Radioactive Materials ◽  
Atmospheric Dispersion Model ◽  
Nuclear Emergency

G.A. Siwabessy Multipurpose Reactor (RSG-GAS) is a research reactor with thermal power of 30 MW located in the Serpong Nuclear Area (KNS), South Tangerang, Banten, Indonesia. Nuclear emergency preparedness of RSG-GAS needs to be improved by developing a decision support system for emergency response. This system covers three important aspects: accident source terms estimation, radioactive materials dispersion model into the atmosphere and radiological impact visualization. In this paper, radioactive materials dispersion during design basis accident (DBA) is modeled using HotSpot, by utilizing site-specific meteorological data. Based on the modelling, maximum effective dose and thyroid equivalent dose of 1.030 mSv and 26 mSv for the first 7 days of exposure are reached at distance of 1 km from the release point. These values are below IAEA generic criteria related to risk reduction of stochastic effects. The results of radioactive dispersion modeling and radiation dose calculations are integrated with Google Earth Pro to visualize radiological impact caused by a nuclear accident. Digital maps of demographic and land use data are overlayed on Google Earth Pro for more accurate impact estimation to take optimal emergency responses.Keywords: G.A. Siwabessy research reactor, Nuclear emergency, Atmospheric dispersion model, Decision support system, HotSpot codes

A Distributed Scenario-Based Decision Support System for Robust Decision-Making in Complex Situations

2013 ◽  
pp. 213-231
Author(s):  
Tina Comes ◽  
Niek Wijngaards ◽  
Michael Hiete ◽  
Claudine Conrado ◽  
Frank Schultmann
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Emergency Management ◽  
Distributed System ◽  
Support System ◽  
Irrelevant Information ◽  
Informed Decision Making ◽  
Processing Information ◽  
Flexible Adaptation

Decision-making in emergency management is a challenging task as the consequences of decisions are considerable, the threatened systems are complex and information is often uncertain. This paper presents a distributed system facilitating better-informed decision-making in strategic emergency management. The construction of scenarios provides a rationale for collecting, organising, and processing information. The set of scenarios captures the uncertainty of the situation and its developments. The relevance of scenarios is ensured by gearing the scenario construction to assessing alternatives, thus avoiding time-consuming processing of irrelevant information. The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (principles and processes) to both the problem at hand and the information available. This approach ensures that each decision can be founded on a coherent set of scenarios. The theoretical framework is demonstrated in a distributed decision support system by orchestrating experts into workflows tailored to each specific decision.

A Distributed Scenario-Based Decision Support System for Robust Decision-Making in Complex Situations

2011 ◽  
Vol 3 (4) ◽  
pp. 17-35 ◽  
Author(s):  
Tina Comes ◽  
Niek Wijngaards ◽  
Michael Hiete ◽  
Claudine Conrado ◽  
Frank Schultmann
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Emergency Management ◽  
Support System ◽  
Irrelevant Information ◽  
Informed Decision Making ◽  
Processing Information ◽  
Flexible Adaptation ◽  
Distributed Decision

Decision-making in emergency management is a challenging task as the consequences of decisions are considerable, the threatened systems are complex and information is often uncertain. This paper presents a distributed system facilitating better-informed decision-making in strategic emergency management. The construction of scenarios provides a rationale for collecting, organising, and processing information. The set of scenarios captures the uncertainty of the situation and its developments. The relevance of scenarios is ensured by gearing the scenario construction to assessing alternatives, thus avoiding time-consuming processing of irrelevant information. The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (principles and processes) to both the problem at hand and the information available. This approach ensures that each decision can be founded on a coherent set of scenarios. The theoretical framework is demonstrated in a distributed decision support system by orchestrating experts into workflows tailored to each specific decision.

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