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Radiation source rate estimation through data assimilation of gamma dose rate measurements for operational nuclear emergency response systems

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This paper presents an evaluation of an innovative data assimilation method that has been recently developed in NCSR Demokritos for estimating an unknown emission rate of radionuclides in the atmosphere, with real–scale experimental data. The efficient algorithm is based on the assimilation of gamma dose rate measured data in the Lagrangian atmospheric dispersion model DIPCOT and uses variational principles. The DIPCOT model is used in the framework of the nuclear emergency response system (ERS) RODOS. The evaluation is performed by computational simulations of dispersion of Ar–41 that was emitted routinely by the Australian Nuclear Science and Technology Organisation's (ANSTO) previous research reactor, HIFAR, located in Sydney, Australia. In this paper the algorithm is evaluated against a more complicated case than the others used in previous studies: there was only one monitoring station available each day and the site topography is characterised as moderately complex. Overall the estimated release rate approaches the real one to a very satisfactory degree as revealed by the statistical indicators of errors.

Keywords: radiation source rate estimation, data assimilation, variational method, Lagrangian models, nuclear emergency response, air quality, air pollution, atmospheric dispersion modelling, radionuclides, radionuclide emissions, gamma dose rate, gamma radiation, DIPCOT model, simulation, nuclear safety, nuclear emissions, nuclear energy, nuclear power

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