Solutions rapides pour la prévision des risques de pollution atmosphérique

International audienceEn cas de rejet accidentel de radionucléides dans l'atmosphère, l'utilisation d'émulateurs permet d'obtenir rapidement des résultats utiles à la prise de décision. Cependant, ces prédictions sont complexes et l'utilisation de méthodes mathématiques avancées est nécessaire

EMULATORS FOR THE RAPID PREDICTION OF CONSEQUENCES IN CASE OF NUCLEAR HAZARDS

International audienceIn the event of an accidental release of radionuclides into the atmosphere, the use of emulators (also known as surrogate models) makes it possible to quickly obtain useful results to help decision-making. However, the predictions of high dimension data is complex and the protective actions must be parametrized by a limited number of variable to be predicted by emulators

Uncertainty study on atmospheric dispersion simulations using meteorological ensembles with a Monte Carlo approach, applied to the Fukushima nuclear accident

International audienceIn emergency cases, when nuclear accidental releases take place, numerical models, developed by IRSN (French Institute of Radiation Protection and Nuclear Safety), are used to forecast the atmospheric dispersion of radionuclides. These models compute the quantity of radionuclides in the atmosphere, their deposited amount on the ground, and the subsequent gamma dose rate. Their results are used to make recommendations to protect the population in case of nuclear accident. However, the simulations are subject to considerable uncertainties. These uncertainties originate from different sources: input variables (weather forecasting, source term), physical parameters used in the models (turbulent diffusion, scavenging coefficient, deposition velocity, etc.) and model approximations (representativeness and numerical errors). This paper presents the propagation of input uncertainties through an Eulerian radionuclide transport model, ldX, applied to the Fukushima nuclear disaster. This uncertainty propagation involves perturbing the input variables and making numerous calls to the model. The perturbations should be broad enough to cover the possible range of variation of uncertain variables. Weather forecast ensembles are used to take into account meteorological uncertainties, and several source terms from the literature are included. The following step is to evaluate the spread of the outputs in order to draw insights about the subsequent uncertainties. In order to assess the quality of the ensemble of simulations, comparisons with radiological observations were carried out, using statistical indicators, both deterministic such as RMSE (Root Mean Square Error) or FMS (Figure of Merit in Space), and probabilistic indicators such as rank histograms, Brier score and DRPS

Using meteorological ensembles for atmospheric dispersion modelling of the Fukushima nuclear accident

In: Proceedings of the 17th international conference on harmonisation within atmospheric dispersion modelling for regulatory purposes