VMS- and OES-based hybrid simulations of bluff body flows

International audienceFlows past bluff bodies show turbulent near wall behavior in various conditions. For example, for a high Reynolds incident flow, the boundary layer at front side of a circular cylinder may show a transition to a turbulent boundary layer. After separation, the back of the cylinder is in contact with the turbulent wake. Analogously, the turbulent wake of a first obstacle can hit the front of a second one

The dynamics of finite size neutrally-buoyant particles in an isotropic turbulence

Un dispositif expérimental a été construit dans le but d'étudier la dynamique de particules de taille finie en suspension dans un écoulement turbulent isotrope à vitesse moyenne faible. Les caractéristiques de la turbulence ont été mesurée, et les échelles pertinentes de temps et d'espace ont été mesurées. Des particules de tailles millimétriques ont ensuite été ajoutées avec une technique de suivi. Les statistiques de vitesses des deux phases ont été calculées et comparées

Spatial prediction of groundwater potentiality in large semi‐arid and karstic mountainous region using machine learning models

The drinking and irrigation water scarcity is a major global issue, particularly in arid and semi‐arid zones. In rural areas, groundwater could be used as an alternative and additional water supply source in order to reduce human suffering in terms of water scarcity. In this context, the purpose of the present study is to facilitate groundwater potentiality mapping via spatial‐modelling techniques, individual and ensemble machine‐learning models. Random forest (RF), logistic regression (LR), decision tree (DT) and artificial neural networks (ANNs) are the main algorithms used in this study. The preparation of groundwater potentiality maps was assembled into 11 ensembles of models. Overall, about 374 groundwater springs was identified and inventoried in the mountain area. The spring inventory data was randomly divided into training (75%) and testing (25%) datasets. Twenty‐four groundwater influencing factors (GIFs) were selected based on a multicollinearity test and the information gain calculation. The results of the groundwater potentiality mapping were validated using statistical measures and the receiver operating characteristic curve (ROC) method. Finally, a ranking of the 15 models was achieved with the prioritization rank method using the compound factor (CF) method. The ensembles of models are the most stable and suitable for groundwater potentiality mapping in mountainous aquifers compared to individual models based on success and prediction rate. The most efficient model using the area under the curve validation method is the RF‐LR‐DT‐ANN ensemble of models. Moreover, the results of the prioritization rank indicate that the best models are the RF‐DT and RF‐LR‐DT ensembles of models