DISPLAY-2: a two-dimensional shallow layer model for dense gas dispersion including complex features

A review of numerical models to predict the atmospheric dispersion of radionuclides

The field of atmospheric dispersion modeling has evolved together with nuclear risk assessment and emergency response systems. Atmospheric concentration and deposition of radionuclides originating from an unintended release provide the basis of dose estimations and countermeasure strategies. To predict the atmospheric dispersion and deposition of radionuclides several numerical models are available coupled with numerical weather prediction (NWP) systems. This work provides a review of the main concepts and different approaches of atmospheric dispersion modeling. Key processes of the atmospheric transport of radionuclides are emission, advection, turbulent diffusion, dry and wet deposition, radioactive decay and other physical and chemical transformations. A wide range of modeling software are available to simulate these processes with different physical assumptions, numerical approaches and implementation. The most appropriate modeling tool for a specific purpose can be selected based on the spatial scale, the complexity of meteorology, land surface and physical and chemical transformations, also considering the available data and computational resource. For most regulatory and operational applications, offline coupled NWP-dispersion systems are used, either with a local scale Gaussian, or a regional to global scale Eulerian or Lagrangian approach. The dispersion model results show large sensitivity on the accuracy of the coupled NWP model, especially through the description of planetary boundary layer turbulence, deep convection and wet deposition. Improvement of dispersion predictions can be achieved by online coupling of mesoscale meteorology and atmospheric transport models. The 2011 Fukushima event was the first large-scale nuclear accident where real-time prognostic dispersion modeling provided decision support. Dozens of dispersion models with different approaches were used for prognostic and retrospective simulations of the Fukushima release. An unknown release rate proved to be the largest factor of uncertainty, underlining the importance of inverse modeling and data assimilation in future developments.

An approach for estimating toxic releases of H2S-containing natural gas

China is well known being rich in sulfurous natural gas with huge deposits widely distributed all over the country. Due to the toxic nature, the release of hydrogen sulfide-containing natural gas from the pipelines intends to impose serious threats to the human, society and environment around the release sources. CFD algorithm is adopted to simulate the dispersion process of gas, and the results prove that Gaussian plume model is suitable for determining the affected region of the well blowout of sulfide hydrogen-containing natural gas. In accordance with the analysis of release scenarios, the present study proposes a new approach for estimating the risk of hydrogen sulfide poisoning hazards, as caused by sulfide-hydrogen-containing natural gas releases. Historical accident-statistical data from the EGIG (European Gas Pipeline Incident Data Group) and the Britain Gas Transco are integrated into the approach. Also, the dose-load effect is introduced to exploit the hazards' effects by two essential parameters - toxic concentration and exposure time. The approach was applied to three release scenarios occurring on the East-Sichuan Gas Transportation Project, and the individual risk and societal risk are classified and discussed. Results show that societal risk varies significantly with different factors, including population density, distance from pipeline, operating conditions and so on. Concerning the dispersion process of hazardous gas, available safe egress time was studied from the perspective of individual fatality risks. The present approach can provide reliable support for the safety management and maintenance of natural gas pipelines as well as evacuations that may occur after release incidents.

The Viareggio LPG railway accident: event reconstruction and modeling

This manuscript describes in detail the LPG accident occurred in Viareggio on June 2009 and its modeling. The accident investigation highlighted the uncertainty and complexity of assessing and modeling what happened in the congested environment close to the Viareggio railway station. Nonetheless, the analysis allowed comprehending the sequence of events, the way they influenced each other, and the different possible paths/evolutions. The paper describes suitable models for the quantitative assessment of the consequences of the most probable accidental dynamics and its outcomes. The main finding is that after about 80 s from the beginning of the release the dense-gas cloud reached the surrounding houses that were destroyed successively by internal explosions. This fact has two main implications. First, it shows that the adopted modeling framework can give a correct picture of what happened in Viareggio. Second, it confirms the need to develop effective mitigation measures because, in case of this kind of accidents, there is no time to apply any protective emergency plans/actions.