A low-Mach volume-of-fluid model for the evaporation of suspended droplets in buoyancy-driven flows

This study introduces a comprehensive numerical model capable of simulating the evaporation of suspended droplets under different gravity conditions. Unlike previous studies, this work provides a detailed description of the multicomponent evaporation process by integrating: (i) interface-resolved evaporation; (ii) suspension by the action of the surface tension force, and (iii) variable physical properties. The model effectively captures complex phenomena such as thermal expansion, natural convective fluxes, and liquid internal recirculation, which cannot be directly resolved using more widespread spherically-symmetric models. Validation against experimental data confirms the model's accuracy in predicting the droplet evaporation dynamics, and its utility in resolving discrepancies between prior numerical simulations results and experimental data. The model was implemented in the Basilisk framework; both the code and the simulations setups are freely available on the Basilisk sandbox

Gis-analysis to assess landslide susceptibility in a fluvial basin of NW Sicily (Italy).

Landslide hazard assessment, effected by means of geostatistical methods, is based on the analysis of the relationships between landslides and the spatial distributions of some instability factors. Frequently such analyses are based on landslide inventories in which each record represents the entire unstable area and is managed as a single instability landform. In this research, landslide susceptibility is evaluated through the study of a variety of instability landforms: landslides, scarps and areas uphill from crown. The instability factors selected were: bedrock lithology, steepness, topographic wetness index and stream power index. The instability landform densities computed for all the factors, which were arranged in Unique Condition Unit, allowed us to derive a total of three prediction images for each landslide typology. The role of the instability factors and the effects generated by the use of different landforms were analyzed by means of: a) bivariate analysis of the relationships between factors and landslide density; b) predictive power validations of the prediction images, based on a random partition strategy. The test area was the Iato River Basin (North-Western Sicily), whose slopes are moderately involved in flow and rotational slide landslides (219 and 28, respectively). The area is mainly made up of the following complexes: Numidian Flysch clays (19%, 1%), Terravecchia sandy clays (5%, 1%), Terravecchia clayey sands (3%, 0.3%) and San Cipirello marly clays (9%, 0%). The steepness parameter shows the highest landslide density in the [11â 19°] class for both the typologies (8%, 1%), even if the density distributions for rotational slides are right-asymmetric and right-shifted. We obtained significant differences in shape when we used different instability landforms. Unlike scarps and areas uphill from crowns, landslide areas produce left-asymmetric and left-shifted density distributions for both the typologies. As far as the topographic wetness index is concerned, much more pronounced differences were detected among the instability landforms of rotational slides. In contrast, the flow landslides produce normal-like density distributions. The latter and the rotational slide landslide areas produce the highest density values in the class [5.5â 6.7], despite an abrupt decreasing trend starting from the first class [3.2â 4.4], which is generated by the density values of the rotational slide scarps and areas uphill from crowns. The stream power index at the foot of the slopes, which was automatically derived using a GIS-procedure, shows a positive correlation with the landslide densities marked by the maximum classes: [4.8â 6.0] for flows, and [6.0â 7.2] for rotational slides. The validation procedure results confirmed that the choice of instability landform influences the results of the susceptibility analysis. Furthermore, the validation procedure indicates that: a) the predictive models are generally satisfactory; b) scarps and zones uphill from crown areas are the most diagnostically unstable landforms, for flow and rotational slide landslides respectively