Advanced interval based Monte Carlo method for atmospheric dispersion model in risk assessment

2015 ◽  
pp. 2649-2656
Author(s):  
El Safadi ◽  
Olivier Adrot ◽  
Jean-Marie Flaus
Keyword(s):  
Risk Assessment ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Atmospheric Dispersion Model

scholarly journals Simulation code for estimating external gamma-ray doses from a radioactive plume and contaminated ground using a local-scale atmospheric dispersion model

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245932
Author(s):  
Daiki Satoh ◽  
Hiromasa Nakayama ◽  
Takuya Furuta ◽  
Tamotsu Yoshihiro ◽  
Kensaku Sakamoto
Keyword(s):  
Monte Carlo ◽  
Dose Response ◽  
Dose Distribution ◽  
Gamma Ray ◽  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Local Scale ◽  
Response Functions ◽  
Simulation Code ◽  
Atmospheric Dispersion Model

In this study, we developed a simulation code powered by lattice dose-response functions (hereinafter SIBYL), which helps in the quick and accurate estimation of external gamma-ray doses emitted from a radioactive plume and contaminated ground. SIBYL couples with atmospheric dispersion models and calculates gamma-ray dose distributions inside a target area based on a map of activity concentrations using pre-evaluated dose-response functions. Moreover, SIBYL considers radiation shielding due to obstructions such as buildings. To examine the reliability of SIBYL, we investigated five typical cases for steady-state and unsteady-state plume dispersions by coupling the Gaussian plume model and the local-scale high-resolution atmospheric dispersion model using large eddy simulation. The results of this coupled model were compared with those of full Monte Carlo simulations using the particle and heavy-ion transport code system (PHITS). The dose-distribution maps calculated using SIBYL differed by up to 10% from those calculated using PHITS in most target locations. The exceptions were locations far from the radioactive contamination and those behind the intricate structures of building arrays. In addition, SIBYL’s computation time using 96 parallel processing elements was several tens of minutes even for the most computationally expensive tasks of this study. The computation using SIBYL was approximately 100 times faster than the same calculation using PHITS under the same computation conditions. From the results of the case studies, we concluded that SIBYL can estimate a ground-level dose-distribution map within one hour with accuracy that is comparable to that of the full Monte Carlo simulation.

scholarly journals Accidental benzene release risk assessment in an urban area using an atmospheric dispersion model

2016 ◽  
Vol 144 ◽  
pp. 146-159 ◽  
Author(s):  
Son C.H. Truong ◽  
Myong-In Lee ◽  
Ganghan Kim ◽  
Dongmin Kim ◽  
Jong-Hwa Park ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Urban Area ◽  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Atmospheric Dispersion Model

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

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