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The calculation of the consequences associated with a pool fire consists in a stepwise procedure where a number of parameters must be characterized, which depend on the geometrical size and shape of the flame. A number of calculation models exists in the literature, characterized by different levels of accuracy and complexity. In the present work we will focus on the characterization of the geometrical configuration of the flame generated from a pool fire: some of the most commonly adopted models will be shortly recalled, and compared against experimental data taken from the literature. It is expected that this would provide useful information about the range of applicability and the level of accuracy of these models. Also, it will help improve the quality of the results, and reduce the time required for carrying out important applications such as consequence assessment and risk analysis, where a large number of calculations must be run.

In France, one home fire occurs every 2 minutes and these accidents account for 10,000 victims each year. Majority of home fires can spread very quickly because of polymer materials, increasingly used in dwelling houses. Currently, modeling fire development to aid the scale-up from bench to full scale is a big challenge. Studies combining experiments and modeling at increasing scale have already been performed. In this work, radiant panel with heat flux concentrator has been developed and used to study the combustion of household materials. The area of radiative source is equal to 2 m². Ignitability, mass loss and smoke composition (CO, CO2 and O2) data have been recorded to evaluate heat release rate. The results have been compared with those from cone calorimeter on small samples (100 cm²) at 50 kW/m² in order to study the scale effect of the testing device.

A possible event during a domino effect escalation is the projection and impact of a fragment on a storage. The fragment can be a consequence of a previous industrial accident, or may originate from a terrorist action. If this previous event (triggering event) is an explosion, the fragment impact can be combined with others effects such as blast or fireball. Many papers can be found about the impact of a fragment, a blast or heat fluxes on a tank during a domino effect. But very few work focused on a combination fragment + blast + fire ball. An experimental work was performed in order to study that topic. Fragments were launched against tanks containing LPG. A pyrotechnic setup was used to generate a blast effect and a fire ball. The influence of three effects (fragment, blast, heat) on the tank is be presented and discussed in order to better understand the domino effect occurrence in chemical plants.

Assessment of likely consequences of a potential accident is a major concern for loss prevention and safety promotion in process industry. Loss of confinement on a storage tank, vessel or piping on industrial sites could imply atmospheric dispersion of toxic or flammable gases. Gas dispersion forecasting is a difficult task since turbulence modeling at large scale involves expensive calculations. Therefore simpler models are used but remain inaccurate especially when turbulence is heterogeneous. The present work aims to study if Artificial Neural Networks coupled with Cellular Automata could be relevant to overcome these gaps. Two methods are reviewed and compared. An example database was designed from RANS k- e CFD model. Both methods were then applied. Their efficiencies are compared and discussed in terms of quality, real-time applicability and real-life plausibility.

This paper is a contribution to the characterisation of chemicals solubilization in seawater due to marine accident. Experimental tests were performed at large laboratory scale in a large seawater column (CEC) to investigate the mass transfer process for n-butanol release. This column is fitted with glass windows in order to visualize the chemical behaviour in the water column. Experiments were performed with n-butanol at low mass flow rate to perform a droplet flow and to evaluate the solubilization processes at the droplet scale. The mass transfer occurs in the boundary layer which develops on the droplet surface. This solubilization layer detaches from the droplet and generates a persistent cloud of solubilization in the droplet wake. The results on the variation of droplet diameter along the CEC show a decrease of a factor 1.64 which corresponds to a volume loss close to 80 %. Physics of the two phase flow is presented and highlights the solubilization processes in the wake of the droplets with trailing edges vortices. The comparison of measurements with Clift’s correlation (Clift, 2005) for droplet rising velocity shows a good agreement for data obtained at the top of CEC but large discrepancies occur at the bottom. This difference can be attributed to the droplet flow regime which corresponds to a non-stationary regime with droplets rising to the terminal velocity.

Industrial activities are increasingly dependent on each other. Several recent events (e.g. Tsunami and earthquake in Japan in 2011) illustrate the consequences (e.g. humans, economic…) of interactions between industrial infrastructures. The state-of-the-art review focused mainly on the risk assessment and interdependencies between critical infrastructures. The aim of this paper is to present an approach able to determine an infrastructure vulnerability level and risk scenarios development based on Seveso regulations and critical infrastructures. The vulnerability infrastructure level is assessed with a multi-criteria analysis. The goal is to identify several criteria according to physic, functional, economic, social and environment context of the infrastructure in the territory. The risk scenarios are developed in order to estimate the consequences in a territory of a threat on one or several infrastructures.

Assessment of likely consequences of a potential accident is a major concern of loss prevention and safety promotion in process industry. Loss of confinement on a storage tank, vessel or piping on industrial sites may imply atmospheric dispersion of toxic or flammable gases. Gas dispersion forecasting is a difficult task since turbulence modeling at large scale involves expensive calculations. Therefore simpler models are used but remain inaccurate especially in near field of the gas source. The present work aims to study if Neural Networks and Cellular Automata could be relevant to overcome these gaps. These tools were investigated on steady state and dynamic state. A database was designed from RANS k-E CFD and Gaussian plume models. Both methods were then applied. Their efficiencies are compared and discussed in terms of quality, real-time applicability and real-life plausibility.

During wildland fires, wildland-urban interfaces may cause significant problems for emergency managers throughout the world. Several works focused on safety zones aiming to prevent houses to burn, but no work focused on the LPG tanks which can be located in the surroundings of houses. A finite elements modelling was developed to calculate safety distance preventing from BLEVE. The safety distances required by law in several countries (50 m; 30 m; 25 m) are checked. It appears that the required safety distances are correct to prevent the tank from BLEVE.

The events in March of 2011 in Japan have provided us with an example of what can happen when large LPG spheres are exposed to severe fire engulfment. This paper presents an approximate failure analysis of a sphere exposed to a severe fire engulfment scenario. It estimates the expected failure time of the sphere based on predicted wall temperatures and internal pressure buildup. The prediction of the pressurization rate is based on a two-zone, thermally stratified liquid model. It shows that the pressurization rate depends strongly on the initial fill level. At high fill levels, the sphere can pressurize much faster then would be expected if the liquid were well mixed and isothermal. This rapid pressurization can lead to early failure. The analysis considered two fire heat flux conditions and shows how prediction of failure time can be affected by high temperature stress rupture. The analysis also considers various initial fill conditions to predict BLEVE hazards at failure. The results are in reasonable agreement with limited observations and data from the March 2011 incident in Japan.