The National Atmospheric Release Advisory Center modelling and decision-support system for radiological and nuclear emergency preparedness and response

2007 ◽  
Vol 4 (3) ◽  
pp. 524 ◽  
Author(s):  
John S. Nasstrom ◽  
Gayle Sugiyama ◽  
Ronald L. Baskett ◽  
Shawn C. Larsen ◽  
Michael M. Bradley
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Emergency Preparedness ◽  
Emergency Preparedness And Response ◽  
Atmospheric Release ◽  
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

scholarly journals A GIS Based University’s Campus Evacuation Plan in Case of Emergencies

2020 ◽  
Vol 5 (1) ◽  
pp. 71-82
Author(s):  
Olayinka Waziri Otun ◽  
Shedrack Ighodalo Arekhandia
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Emergency Preparedness ◽  
Emergency Evacuation ◽  
Host Community ◽  
University Campus ◽  
Binary Logistic Regression Model ◽  
Location Allocation ◽  
Evacuation Plan

Abstract Emergencies are bound to happen anywhere at any time and as such pre-planning is necessary.  This study outlined a procedure by which students on a university campus can be evacuated safely, while optimising use of available resources. Applications of optimisation techniques in campus emergency planning studies are not common, especially in developing countries. Collaboration of students is essential for a successful campus emergency evacuation, as such this study examined factors that will predict students’ behaviour in an emergency. The study adopted a location-allocation (L-A) model based decision support system (DSS) to implement the campus evacuation plan.  The DSS was implemented within a geographic information system (GIS) environment.   A total of 150 students were selected randomly across six faculties at Olabisi Onabanjo University, Nigeria for the study. In the event of an emergency it is proposed that all the students will move to designated assembly areas.  The output from the emergency decision support system will be used to direct students from the assembly areas to appropriate evacuation points. The DSS was specifically applied in this study to find the locations of five evacuation points that will minimise travel distances of all students from thirteen assembly areas. The results from the DSS showed the average travel distance is 328.43 metres.  This study used the binary logistic regression model to predict factors that will influence students to assist in an emergency. The result of the analysis showed that their level of consciousness of emergencies is the only factor that will significantly influence them to assist in an emergency. The findings from this study showed that for a disaster resilient university it must develop an all-hazards comprehensive plan, conduct regular emergency training and exercises, and develop a partnership with the host community for joint use of emergency resources.  Keywords: Decision Support System ; Emergency Preparedness; Evacuation Plan; Location-Allocation Models; University Campus.

scholarly journals Decision Support System Este for Nuclear and Radiological Emergencies: Atmospheric Dispersion Models

2020 ◽  
Author(s):  
Ludovít Lipták ◽  
Eva Fojcíková ◽  
Monika Krpelanová ◽  
Viera Fabová ◽  
Peter Čarný
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Emergency Preparedness ◽  
Large Scale ◽  
Atmospheric Dispersion ◽  
Nuclear Accident ◽  
Particle Model ◽  
Dispersion Models ◽  
Energy Agency

The systems ESTE are running in nuclear crisis centers at various levels of emergency preparedness and response in Slovakia, the Czech Republic, Austria, Bulgaria, and Iran (at NPP monitored by International Atomic Energy Agency, IAEA). ESTE is a decision support system, running 24/7, and serves the crisis staff to propose actions to protect inhabitants against radiation in case of a nuclear accident. ESTE is also applicable as decision support system in case of a malicious act with radioactive dispersal device in an urban or industrial environment. Dispersion models implemented in ESTE are Lagrangean particle model (LPM) and Puff trajectory model (PTM). Described are models approaches as implemented in ESTE. PTM is applied in ESTE for the dispersion calculation near the point of release, up to 100 km from the point of nuclear accident. LPM for general atmospheric transport is applied for short-range, meso-scale and large-scale dispersion, up to dispersion on the global scale. Additionally, a specific micro-scale implementation of LPM is applied for urban scale dispersion modelling too. Dispersion models of ESTE are joined with radiological consequences models to calculate a complete spectrum of radiological parameters - effective doses, committed doses and dose rates by various irradiation pathways and by various radionuclides. Finally, radiation protective measures, like sheltering, iodine prophylaxis, or evacuation, evaluated on the base of predicted radiological impacts are proposed. Dispersion and radiological models of the state-of-the-art ESTE systems are described. Results of specific analyses, like number of particles applied, initial spatial distribution of the source, height of the bottom reference layer, are presented and discussed.

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