Automatic plume episode identification and cloud shine reconstruction method for ambient gamma dose rates during nuclear accidents

Zhang, Xiaole; Raskob, W.; Landman, Claudia; Trybushnyi, D.; Haller, Christoph; Yuan, Hongyong

doi:10.1016/j.jenvrad.2017.07.014

Cited by 8 publications

(6 citation statements)

References 31 publications

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“…Reprinted with permission from ref. [ 228 ]. Copyright (2017) Elsevier B.V. Noble gasses, for example, 133 Xe, are first released into the ambient environment if the reactors are damaged.…”

Section: Source Term and Particle Size Distributionmentioning

confidence: 99%

“…Adding to the myriad challenges are the large uncertainties of meteorological fields, which cause cumulative errors in the model results. Environmental observations are also important for evaluating risk and supporting emergency responses [ 228 ]. Unlike these models, environmental observations are considered to be more reliable, but the spatial distributions of observation networks are usually sparse.…”

Section: Combination Of Models and Observationsmentioning

confidence: 99%

See 1 more Smart Citation

Atmospheric dispersion of chemical, biological, and radiological hazardous pollutants: Informing risk assessment for public safety

Zhang

Wang

2022

Journal of Safety Science and Resilience

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“…Reprinted with permission from ref. [ 228 ]. Copyright (2017) Elsevier B.V. Noble gasses, for example, 133 Xe, are first released into the ambient environment if the reactors are damaged.…”

Section: Source Term and Particle Size Distributionmentioning

confidence: 99%

Section: Combination Of Models and Observationsmentioning

confidence: 99%

Atmospheric dispersion of chemical, biological, and radiological hazardous pollutants: Informing risk assessment for public safety

Zhang

Wang

2022

Journal of Safety Science and Resilience

Self Cite

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“…Atmospheric dispersion model of radioactive materials into the environment plays important roles in supporting the decision makers of nuclear emergency responses [5][6][7][8][9]. There are a number of commonly used software for radioactive dispersion modeling.…”

Section: G a Siwabessy Multipurpose Reactor (Rsg-gas) Is A Researchmentioning

confidence: 99%

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

Yuniarto

Hikmat

2019

Tri Dasa Mega

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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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“…Therefore, source term inversions have received extensive attention. Because the gamma dose rate in air can be measured rapidly and in real-time, there have been many research methods to estimate source terms based on gamma dose rate monitoring data, including optimal interpolation [5], data assimilation [6][7][8], Kalman filtering [9][10], Bayesian methods [11,12], and least squares [13][14][15][16][17][18]. Since the Fukushima accident, more attentions have been paid to source term inversion and more methods have been used to perform the study [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Inversion Method for Multiple Nuclide Source Terms in Nuclear Accidents Based on Deep Learning Fusion Model

et al. 2023

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During severe nuclear accidents, radioactive materials are expected to be released into the atmosphere. Estimating the source term plays a significant role in assessing the consequences of an accident to assist in actioning a proper emergency response. However, it is difficult to obtain information on the source term directly through the instruments in the reactor because of the unpredictable conditions induced by the accident. In this study, a deep learning-based method to estimate the source term with field environmental monitoring data, which utilizes the bagging method to fuse models based on the temporal convolutional network (TCN) and two-dimensional convolutional neural network (2D-CNN), was developed. To reduce the complexity of the model, the particle swarm optimization algorithm was used to optimize the parameters in the fusion model. Seven typical radionuclides (Kr-88, I-131, Te-132, Xe-133, Cs-137, Ba-140, and Ce-144) were set as mixed source terms, and the International Radiological Assessment System was used to generate model training data. The results indicated that the average prediction error of the fusion model for the seven nuclides in the test set was less than 10%, which significantly improved the estimation accuracy compared with the results obtained by TCN or 2D-CNN. Noise analysis revealed the fusion model to be robust, having potential applicability toward more complex nuclear accident scenarios.

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Automatic plume episode identification and cloud shine reconstruction method for ambient gamma dose rates during nuclear accidents

Cited by 8 publications

References 31 publications

Atmospheric dispersion of chemical, biological, and radiological hazardous pollutants: Informing risk assessment for public safety

Atmospheric dispersion of chemical, biological, and radiological hazardous pollutants: Informing risk assessment for public safety

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

Inversion Method for Multiple Nuclide Source Terms in Nuclear Accidents Based on Deep Learning Fusion Model

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