scholarly journals Source Reconstruction of Atmospheric Releases by Bayesian Inference and the Backward Atmospheric Dispersion Model: An Application to ETEX-I Data

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yungang Zhao ◽  
Yuanyuan Liu ◽  
Li Wang ◽  
Jianping Cheng ◽  
Shilian Wang ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Standard Deviation ◽  
Release Rate ◽  
Source Term ◽  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Source Location ◽  
Concentration Data ◽  
Posterior Probability Distribution ◽  
Atmospheric Dispersion Model

Source term reconstruction methods attempt to calculate the most likely source parameters of an atmospheric release given measurements, including both location and release amount. However, source term reconstruction is vulnerable to uncertainties. In this paper, a method combining Bayesian inference with the backward atmospheric dispersion model is developed for robust source term reconstruction. The backward model is used to quantify the relationship between the source and measurements and to reduce the search range of the Bayesian inference. A Markov chain Monte Carlo method is used to sample from the multidimensional parameter space of the source term. The source location and release rate are estimated simultaneously, and the posterior probability distribution is produced by applying Bayes’ theorem. The proposed method is applied to a set of real concentration data from the ETEX-I experiment. The results demonstrate that the source location is estimated to be −2.86° ± 1.01°E, 48.25° ± 0.33°N, and the release rate is estimated to be 20.16 ± 3.56 kg/h. The true source location is correctly estimated to be within a one standard deviation interval, and the release rate is correctly determined to be within a three standard deviation interval.

scholarly journals Method of Source Identification following an Accidental Release at an Unknown Location Using a Lagrangian Atmospheric Dispersion Model

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1305
Author(s):  
Spyros Andronopoulos ◽  
Ivan V. Kovalets
Keyword(s):  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Source Location ◽  
Location Estimation ◽  
Source Inversion ◽  
Inversion Algorithm ◽  
Start Time ◽  
Time Duration ◽  
True Value ◽  
Atmospheric Dispersion Model

A computationally efficient source inversion algorithm was developed and applied with the Lagrangian atmospheric dispersion model DIPCOT. In the process of source location estimation by minimizing a correlation-based cost function, the algorithm uses only the values of the time-integrated concentrations at the monitoring stations instead of all of the individual measurements in the full concentration-time series, resulting in a significant reduction in the number of integrations of the backward transport equations. Following the source location estimation the release start time, duration and emission rate are assessed. The developed algorithm was verified for the conditions of the ETEX-I (European Tracer Experiment—1st release). Using time-integrated measurements from all available stations, the distance between the estimated and true source location was 108 km. The estimated start time of the release was only about 1 h different from the true value, within the possible accuracy of estimate of this parameter. The estimated release duration was 21 h (the true value was 12 h). The estimated release rate was 4.28 g/s (the true value was 7.95 g/s). The estimated released mass almost perfectly fitted the true released mass (323.6 vs. 343.4 kg). It thus could be concluded that the developed algorithm is suitable for further integration in real-time decision support systems.

A Research Reactor Source Term and Dose Results in the Event of a LOCA

2014 ◽  
Author(s):  
Charalampos Pappas ◽  
Andreas Ikonomopoulos ◽  
Athanasios Sfetsos ◽  
Spyros Andronopoulos ◽  
Melpomeni Varvayanni ◽  
...  
Keyword(s):  
Research Reactor ◽  
Source Term ◽  
Dispersion Model ◽  
Ventilation System ◽  
Atmospheric Dispersion ◽  
Reactor Core ◽  
Forecast Model ◽  
Scale Model ◽  
Continuous Reactor ◽  
Reactor Building

The present study discusses the source term derivation and dose result calculation for a hypothetical accident sequence in the Greek Research Reactor – 1 (GRR-1). A loss-of-coolant accident (LOCA) has been selected as a credible accident sequence. The source term derivation has been based on the GRR-1 confinement performance where the inventory has been computed assuming continuous reactor operation. A core damage fraction of 30% has been considered for the calculations while conservative core release fractions have been employed. The radionuclides released from the reactor core to the confinement atmosphere have been subjected to natural decay, deposition on and resuspension from various internal surfaces before being led to the release pathway. It has been assumed that an emergency shutdown is initiated immediately after the beginning of the accident sequence and the emergency ventilation system is also activated. Subsequently, the source term has been derived comprising of noble gases, iodine and aerosol. The JRODOS computational software for off-site nuclear emergency management has been utilized to estimate the dose results from the LOCA-initiated source term that is released in its entirety from the reactor stack at ambient temperature. The Local Scale Model Chain in conjunction with the DIPCOT atmospheric dispersion model that is embedded in JRODOS have been used with proper parameterization of the calculation settings. Five weather scenarios have been selected as representative of typical meteorological conditions at the reactor site. The scenarios have been assessed with the use of the Weather Research and Forecast model. Total effective, skin, thyroid, lung and inhalation doses downwind of the reactor building and up to a distance of 10 km have been calculated for each weather scenario and are presented. The total effective gamma dose rate at a fixed distance from the reactor building has been assessed. The radiological consequences of the dose results are discussed.

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

Parallelisation of the Lagrangian atmospheric dispersion model NAME

2013 ◽  
Vol 184 (12) ◽  
pp. 2734-2745 ◽  
Author(s):  
Eike H. Müller ◽  
Rupert Ford ◽  
Matthew C. Hort ◽  
Lois Huggett ◽  
Graham Riley ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Atmospheric Dispersion Model
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