Improving our understanding of the fine-scale atmospheric processes (natural with clouds, or induced by anthropogenic activities with pollutant dispersion or wildland fires) requires developing and validating numerical models, which is closely linked to the acquisition of in situ data.
This PhD project aims at designing a data assimilation approach that integrates data from UAVs (Unmanned Aerial Vehicles) in order to improve plume dynamics numerical models and to answer air quality scientific issues. It is at the interface between the field of atmospheric sciences and the field of autonomous unmanned aerial systems. The key idea of this project is to obtain more accurate numerical simulations of a pollutant plume dynamics, in order to explore and better understand the interactions between the surface and the atmosphere in situations that are critical for air quality (industrial accidents, wildfires).
The main objective of the PhD project is to define processes allowing a fleet of UAVs to acquire data that are optimal for plume modeling. The MUST case will be used as a test case study to verify and validate the approach. We expect to provide a proof of concept of using UAVs to better model micro-scale atmospheric processes.
This PhD thesis is at the interface between computational fluid dynamics, data assimilation and robostics. The keywords are the following ones: atmospheric dispersion, data assimilation, computational fluid dynamics, UAVs, metamodels, uncertainties. The PhD thesis will be carried out through a collaboration between CECI (CNRS-Cerfacs) and LAAS (CNRS-Université fédérale de Toulouse), two research laboratories located in Toulouse, France.
Here are the main skills requires by this PhD project:
– Skills in computational fluid dynamics and/or applied mathematics (ex: treatment of uncertainties, Bayesian inference)
– Fluency in English (written, oral)
– Skills in programming (ex: Python)
– Quality: autonomy, rigor, dynamism, team-spirit
If you are interested by this PhD topic and you wish to know more, please contact Mélanie Rochoux (CECI) and Simon Lacroix (LAAS) and provide a detailed CV, a cover letter and a few referees of past projects/internships.
Mélanie Rochoux, email@example.com, 05 61 19 30 72
Simon Lacroix, firstname.lastname@example.org, 05 61 33 62 66