Annonces

We are pleased to announce our two-week fall school "Bridges over turbulent matters: Navigating across observations, concepts and models", to be held in Cargèse (Corse, France) from October 21 to 31, 2025.To apply, please visit the school website: https://turbazur.github.io/cargese2025/

Going back to Kolmogorov, there has been the paradigm in the more fundamental turbulence community of one universal state of homogeneous isotropic turbulence. In the last 15 years or so it has become more and more clear that this is not the case and that there can be several different states of turbulence, with transitions between these states. The transitions between the different states normally are of subcritical nature, just as the transition from laminar pipe or channel flow to turbulent pipe of channel flow. There, the origin of the subcritical nature is the nonnormality of the operator, combined with the nonlinearity of the Navier-Stokes equation. The nonnormality is intimately related to the local shear of the flow. All this also holds for turbulent flow, where one locally also has strong shear.

Multiphase flows are common in nature and engineering. Atmospheric flows often involve the dispersion of droplets or solid particulate matter (dust, sand, ice crystals in clouds); marine systems are populated by plankton, sediments or microplastics. Industrial applications of disperse flows include particle separators,filtration systems, atomisers and combustion devices, spray dryers, bubble columns; interfacial and free-surface flows are widespread in chemical and process industry.

Création de la Division Physique Non Linéaire (DPNL) de la Société Française de Physique (SFP)

Cet ouvrage présente les bases de la turbulence aux chercheurs en écologie marine, et les couplages de l’écologie marine avec la turbulence, aux chercheurs en turbulence provenant d’autres disciplines. Il s’adresse aux doctorants, jeunes chercheurs et chercheurs confirmés intéressés par ces deux sujets et leurs interactions.

The Leeds Institute for Fluid Dynamics is delighted to partner with the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge, the UK Fluids Network, and the Journal of Fluid Mechanics to deliver a regular webinar series on fluids-related topics.

L’objectif de ce post-doctorat est de caractériser expérimentalement les bosses de bruit d’ingestion de turbulence en soufflerie et en canal hydraulique dans des configurations maritimes simplifiées (sous-marin ou bateau de surface), afin de déterminer les paramètres qui influent sur l’apparition des bosses et leur caractéristique.

Bubble columns are common in processes, i.e. biomethanation, hydrogen production, CO₂ sequestration... but their flow dynamics is not well understood. Indeed, in air–water bubble columns in the heterogeneous regime, collective dynamics plays a significant role [Mezui et al., JFM, 2022, 2023]. Meso-scale structures appear that induce buoyancy driven turbulent convection. Several questions remain: what controls these meso-scale structures? does an asymptotic heterogeneous state at exist high gas flow rates? what is the axial development of the flow?... When surfactants are added, a foam layer formq at the top of the column. A characterization of the bubble size inside the layer are necessary for understanding the dynamics, and for developing efficient separation processes. These flows will be investigated using Doppler optical probes [Lefebvre et al., CES, 2022]. Experiments and measuring technique are available. The post-doc will contribute to the collaboration with Shizuoka University.

The work consists of performing direct numerical simulations (DNS) in a highly stratified turbulence regime in order to study the interactions between large structures, gravity waves, and eddies. The objective is to extract and analyze these components and their interactions using methods developed by the research group. The results will help the theoretical team in Rouen to develop analytical equations describing different moments of order, covering energy, cascade directions, and extreme fluctuations.

Institut Pprime, through its Aerodynamics, Acoustics & Turbulence research group, seeks a highly motivated Research Engineer to join an applied research project in partnership with CNRS-Innovation and Airbus.

This project is a postdoctoral proposal in the stochastic physics of turbulence aiming to analyze stylized models of multifractal transport and to assess their relevance for turbulent transport.

Dans le cadre du projet « MAchine LEArning for Fluid system efficiency » (MALEAF), soutenu par l’Agence Nationale de la Recherche, l’Ecole Navale recrute un chercheur post-doctorant en mécanique des fluides expérimentale, analyse et assimilation de données d’écoulement pour 2 ans.Mots clés : PIV, POD, assimilation de données, modèle d’ordre réduit, hydrofoils

Fluid-structure interactions (FSI) in a nuclear reactor core involve thermalhydraulics mechanisms at different scales. FSI simulations at the local (CFD) scale are feasible only for reduced domains. Such domains must however be representative of the actual core conditions. A multi-scale approach is therefore required to understand how to consistently simulate the core thermalhydraulics and the related FSI phenomena.

Caractérisation multi-échelle de processus non-linéaires à partir des données : Application à la turbulence hydrodynamique et à l’acoustique sous-marine.Mots clés : Décompositions pilotées par les données, POD, machine Learning, écoulementLe sujet de cette thèse porte sur les méthodes de décomposition pilotées par les données pour l’analyse de processus physiques multi-échelles et non-stationnaires, issus de systèmes non-linéaires. Cette large classe de signaux regroupe, par exemple, les écoulements transitionnels ou turbulents, les écoulements océaniques, les signaux MAD ou les signaux issus de systèmes DAS1 ou réseaux d’OBS1. Ce besoin d’outils d’analyse de données physiques s’inscrit dans les axes «Analyse et modélisation de la donnée maritime» et «Acquisition de la donnée et compréhensions des phénomènes physique». On vise à classifier et caractériser, voire améliorer, différentes méthodes de décomposition pilotées par les données (e.g. POD2, BOD2, SPOD2, DMD2, ainsi que EMD , EEMD2, MEMD2, et les d

En tentant de tirer profit du coût mesuré des approches RANS et des qualités prédictives des approches LES, les approches hybrides RANS/LES présentent un intérêt fort pour de nombreuses applications mais continuent à se heurter au problème de la gestion des zones de transition. En l’absence d’instabilité hydrodynamique naturellement présente dans le domaine de calcul ou lorsque celle-ci n’est pas suffisamment résolue, la qualité des prévisions LES dépend ainsi en grande partie des fluctuations prescrites dans la zone de transition. L’objectif du post-doctorat proposé en collaboration avec le CEMEF est de développer une méthode d’apprentissage automatique de génération de fluctuations pour les zones de recouvrement RANS/LES. Deux axes ont été identifiés visant à réduire l’étendue des zones grises ; le premier concerne spécifiquement la qualité du signal synthétique généré alors que le deuxième axe s’attache aux paramètres de contrôle d’une méthode de forçage.

The wind turbine production in a floating wind farm depends essentially on its position, the wind and the state of the sea. The influence of the state of the sea, in particular, is poorly known, because it has not been an influential factor in the development of installed wind farms. First of all, the influence of the movement of the platform directly affects the production capacity of the wind turbine. But beyond that, it induces significant modifications to the wake, and in the context of commercial farms, where the turbines are not widely spaced, leads to interactions between turbines which are still unknown. As Numerical simulations are very expensive, from numerical simulation and historical data, the environmental conditions can be modeled by stochastic models which are faster to simulate. hus, by combining these stochastic models with the physical model, it is possible to evaluate the uncertainty relating to the key parameters (extractable energy, wake topology).

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