Industrial fire simulation and uncertainty associated with the Emission Dispersion Model
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Date
2014-10-01
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Journal Clean Technologies and Environmental Policy
Abstract
The use of numerical modeling in the field of industrial fire accidentology has become common nowadays and this tendency is expected to increase with the development of performance simulation tools. Despite the constant development of fire modeling tools, the current state of the art is not yet able to accurately predict fire phenomena. This gap between the reality and simulations is probably due to the presence of some level of uncertainty, which may occur from the meteorological inputs, diffusion assumptions, plume dynamics, or emission production. To cope with the presence of uncertainties in the input data, we propose an uncertainty analysis enabling to avoid as much as possible bad decisions that may have a large impact in domains such as safety. In this study, we are interested in the uncertainty propagation related to NO2 atmospheric dispersion resulting from a crude oil tank fire. Uncertainties were defined a priori for each of the following input parameters: wind speed, NO2 emission rate, and viscosity and diffusivity coefficients. For that purpose, a Monte Carlo approach has been used. In order to evaluate the importance of the considered parameters on the NO2 dispersion, new sensitivity indicator has been developed. The obtained results showed that the viscosity coefficient and the wind speed are the most significant input parameters with respect to NO2 concentration near to the source of fire, while the wind speed and the initial concentration are the important parameters for distant areas.