In this paper, we used a 3-D discrete-element model, Grains3D, which allows the simulation of unsteady granular flows of monodisperse soft spherical particles in a common situation (i.e., down a rectangular channel). A series of numerical dam-break experiments was performed to predict the behavior of granular columns that propagate down a rough horizontal surface from different initial conditions (varying the initial aspect ratio). Numerical results were compared to those obtained experimentally by Lajeunesse et al. (Phys Fluids 17:103302, 2005) from a similar configuration. Runout distance, temporal flow evolution, deposit morphology and internal flow structures of similar laboratory experiments were quantitatively reproduced as well as prediction of empirical and theoretical scaling laws. This paper highlights that such fully 3-D simulations of soft-spheres can remarkably capture dam-break collapses performed in a rectangular channel. Moreover, Grains3D can provide a complete physical description of such complex unsteady systems which will be the topic of future on-going studies.

Bedload sediment transport of two-size coarse spherical particle mixtures in a turbulent supercritical flow was analyzed with image and particle tracking velocimetry algorithms in a two-dimensional flume. The image processing procedure is entirely presented. Experimental results, including the size, the position, the trajectory, the state of movement (rest, rolling, and saltation), and the neighborhood configuration of each bead, were compared with a previous one-size experiment. Analysis of the solid discharge along the vertical displayed only one peak of rolling in the two-size bed, whereas three peaks of rolling appeared in the one-size case due to a larger collective motion. The same contrast is evidenced in spatio-temporal diagrams where the two-size mixtures are characterized by the predominance of saltation and a smaller number of transitions between rest and rolling. The segregation of fine particles in a bed formed by larger particles was analyzed taking into account the neighborhood configurations.

<p lang="en-GB">Large-scale fires such as warehouse fires that have occurred in recent years or dramatic accidents like the Paris Notre-Dame Cathedral fire in 2019 have stressed the need to develop means of assessing the toxicity risks to the population and the environment of smoke plumes. A key challenge is to quickly provide the authorities with information on the areas impacted by the plume and the pollutant concentration levels to which the population is likely to be or to have been exposed. The Laboratoire Central de la Préfecture de Police (LCPP) aims to deploy a number of devices for measuring pollutants and tracers of smoke combustion during a fire. Subsequently, the application of an atmospheric dispersion model within the framework of a data assimilation approach should provide a source characterisation and a finer estimate of the concentration levels at points of interest.</p> <p lang="en-GB">To characterise the source, noticeably the released mass of pollutants and the emission height linked to a plume rise, an inverse problem method has been implemented. It is based on a Bayesian Markov Chain Monte Carlo (MCMC) technique meant to quantify the uncertainties associated with the emission estimation. Since the emission height strongly influences the atmospheric dispersion in the vicinity of the source, two approaches are used to estimate it. The first one consists in finding the emission time rate for each considered height and the second one consists in focussing on a single emission height and its associated emission time rate using a discrete distribution to describe the vertical profile. We use the Lagrangian Parallel Micro Swift Spray (PMSS) model developed by AriaTechnologies fed with meteorological fields provided by Météo-France to represent the atmospheric dispersion of smoke.</p> <p><span lang="en-GB">Our inverse method is applied to a large warehouse fire that occurred in Aubervilliers near Paris in 2021 using real observations. Abnormal concentrations of particulate matter were recorded, with a peak at 160 </span><span lang="el-GR">µ</span><span lang="fr-FR">g</span><span lang="en-GB">.m</span><sup><span lang="en-GB">-3</span></sup><span lang="en-GB">, located in the centre of Paris about 6 km from the source. They were collected by the LCPP and AirParif, the local air quality agency, and are used to retrieve the emission with a quantification of uncertainties and a sensitivity analysis of model error. The resulting emission height of the source, mainly between 200 and 300 m, coincides with the terrain observation for an emission rate of less than 1000 kg/h throughout the duration of the fire. A sensitivity analysis to the initial approximation of the source (the prior) shows its importance. It suggests to improve our method by incorporating the statistical parameters of the observation error into the MCMC method.</span></p>

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