The Quick Urban and Industrial Complex (QUIC) atmospheric transport and dispersion modelling system, developed by the Los Alamos National Laboratory, is evaluated using measurement data from the Joint Urban 2003 gas-tracer measurements conducted in Oklahoma City, USA. This activity has been coordinated within the Urban Dispersion International Evaluation Exercise (UDINEE) project, led by the European Commission-Joint Research Centre. Four different setups for the QUIC program are evaluated using different types of wind-speed data, such as local onsite measurements and flow fields produced by the Weather Research and Forecasting mesoscale model. The simulation results are evaluated against measured data for instantaneous puff releases from intensive operation period 4 of the Joint Urban 2003 field experiment. The selection of performance measures is based on the assumptions made for the UDINEE project. The differences in the results of simulations for various setups are described.

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<p>There are many ways to quantify initiating event probability and most of them are described in document “Defining initiating events for purposes of probabilistic safety assessment”, developed by the International Atomic Energy Agency . This guide describes seven methods: engineering evaluation or technical study of plant; reference to previous probabilistic safety assessment; EPRI list of initiating events; logical classification; plant energy balance fault tree; analysis of operation experience for actual plant; failure mode and effect analysis. In practice, currently many of PSA specialists use EPRI list of IEs, which has been originally prepared for single hazard and application to multiple hazards is not straightforward. Therefore other approaches are considered. In the paper combined method based on fragility functions and Bayesian network is proposed in order to elaborate for easier and more accurate approximation of the probability of initiating events caused by multiple hazards. In this respect, first of all, events fragility functions for hazards considered or multi-hazard fragility function are needed, which can have various form like , for example, parameterized fragility functions or logit fragility function. The next step is to develop a model the Bayesian network with the implementation of derived fragility functions. This can be performed using widely available computing programs for interactive building Bayesian network models .Depending on the hazards considered, the Bayesian network should be then developed accordingly. Example of such Bayesian network will be given.</p><p>Finally after calculating the probability of initiating events using this combined method, the results can be used in Event Trees and Fault Trees already developed for considered nuclear installation, in order to update the estimations of probabilities. Such an approach has also practical meaning as it will reduce man-month costs in comparison with the approach based on building full PSA models in Bayesian network.</p>

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