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Risk assessment for the optimization of the grid of a telemetric network monitoring system.

Authors :
Salpadimos, N.
Karfopoulos, K.
Seimenis, I.
Potiriadis, C.
Carinou, E.
Housiadas, C.
Source :
Journal of Environmental Radioactivity. Nov2023, Vol. 268, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

The goal of this work was to develop a methodology for risk assessment in case of an accident originating from a nuclear power plant, and consequently, to improve the relevant radiation monitoring network. In specific, the study involved risk estimation in Greece from a transboundary nuclear power plant accident. The tool employed was JRODOS (Java-based Real-time Decision Support), which is a system for off-site emergency management of radioactive material in the environment. This tool, widely used to generate and study scenarios for nuclear accidents worldwide, provides valuable insight to facilitate emergency preparedness and response. The probability of the plume arriving at numerous regions within the country was calculated, along with the maximum dose rates in case of transport. A risk assessment was performed, and geographical regions were prioritized in terms of risk-based environmental radioactivity burden. A total of 29 administrative districts were identified as low to medium-risk regions. Acquired results were used to determine the optimal spatial distribution of detectors for upgrading the existing monitoring network of environmental radioactivity. • Using JRodos to study daily release scenarios for a whole year, from an NPP near Greece. • Calculation of plume transport probabilities and maximum dose rates for different administrative districts. • Development of a methodology for risk assessment. • Categorization of the country's administrative districts according to risk. • Determination of spatial distribution of radiation monitoring stations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0265931X
Volume :
268
Database :
Academic Search Index
Journal :
Journal of Environmental Radioactivity
Publication Type :
Academic Journal
Accession number :
169949443
Full Text :
https://doi.org/10.1016/j.jenvrad.2023.107249