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PhD on Stochastic models for natural dispersion of aerosols, particles and pollutants in turbulent conditions, Institut Camille Jordan & Physics. Lab, Lyon (France)

Du 1 janvier 2023 au 31 décembre 2023

Flexible starting date 
This PhD is part of a joint porject between :
- Institut Camille Jordan (Mathematics), CNRS / Univ. Lyon 1
- Physics Laboratory,  CNRS / ENS de Lyon

Contact : 
- Mickaël Bourgoin (mickael.bourgoin@ens-lyon.fr)
- Charles Edouard Bréhier (charles-edouard.brehier@univ-pau.fr)
- Laurent Chevillard (laurent.chevillard@ens-lyon.fr)
- Romain Volk (romain.volk@ens-lyon.fr)

The present project is at the interface between Maths and Physics and aims at providing accurate, efficient and predictive modeling tools for the transport of particles and pollutants in turbulent conditions as encountered in natural atmospheric and oceanic conditions.

PhD offer

 

Stochastic models for natural dispersion of aerosols, particles and pollutants in turbulent conditions.


The present project is at the interface between Maths and Physics and aims at providing accurate, efficient and predictive modeling tools for the transport of particles and pollutants in turbulent conditions as encountered in natural atmospheric and oceanic conditions. In spite of its ubiquity and major impact, the turbulent dispersion of particles in atmospheric and oceanic flows remains largely misunderstood (regarding the physical mechanisms at play) and unpredictable (regarding the analytical and numerical models used to describe it). This is to be related to the complexity of the turbulent processes involved (non-linear, non-local and multi-scale, eventually non-homogeneous and/or non-stationary in real conditions) and to the additional coupling between the particles and the fluid (in particular due to particles inertia, leading to subtle temporal and spatial filtering of their dynamics).

Within this perspective, stochastic Lagrangian models offer a particularly appealing and versatile framework. While stochastic models are a common framework to describe single particle dispersion processes for inertia-less particles in turbulence (following seminal work by Taylor), their extension to the case of inertial particles is still at its infancy, in particular when it comes to account for non-ergodic effects (preferential sampling) and settling. Besides, the stochastic modeling of pair dispersion, accounting for the multi-scale correlations of turbulence along the energy cascade, largely remains to be explored. The ambition and novelty of this project are to build a complete arsenal of stochastic models able to account simultaneously for several phenomena: (i) particles inertia, (ii) preferential sampling, (iii) gravitational settling, (iv) pair correlation effects, with the versatility to also include (v) turbulence finite Reynolds number effects and intermittency and (vi) large scale background inhomogeneities (accounting for stratification, recirculations, etc.). While some of these points have already been addressed separately by the community in the past, recent progresses (in particular regarding the stochastic modeling of turbulence, of particles inertia, preferential sampling and pair dispersion) by the partners of this project let envision for the first time major progresses for the developments of such complete stochastic modeling in realistic conditions.

The selected PhD student will join a multi-disciplinary team combining strong mathematical and physical expertises, with physicists, experts on the couplings between particles and turbulence (Romain Volk and Mickaël Bourgoin from Laboratoire de Physique (ENS de Lyon / CNRS)), and physicists and mathematicians experts in stochastic modeling (Laurent Chevillard from Laboratoire de Physique (ENS de Lyon / CNRS) and Charles-Edouard Bréhier from Laboratoire de Mathématiques et de leurs Applications (LMAP, Université de Pau et des Pays de l'Adour)

During the PhD, the student is expected to develop mathematical models using stochastic processes, to implement and test them with numerical experiments and to compare the results with real data.

The candidate may have master degree from mathematics or physics, and shall have skills on stochastic processes and scientific computing and appetite for multi-disciplinary research. Knowledge on fluid dynamics, turbulence, transport phenomena for instance may be useful but can be acquired during the PhD.

The funding of the PhD is granted and supported by IMPT (Institut des Mathématiques pour la Planète Terre). 

Starting date :           as soon as possible

Duration :                   3 years

 

Contacts :                

Candidates shall send their application (including a motivation letter and a CV) to

-   Mickaël Bourgoin (mickael.bourgoin@ens-lyon.fr)

-   Charles Edouard Bréhier (charles-edouard.brehier@univ-pau.fr)

-   Laurent Chevillard (laurent.chevillard@ens-lyon.fr)

-   Romain Volk (romain.volk@ens-lyon.fr)