Doctorante / Doctorant H/F

BRIEF

The efficiency of passive techniques for flow control is of main importance for several fields interested in optimizing the performance and efficiency of fluid and/or thermal components of many engineering systems (i.e automotive).  Nowadays, in the framework of fluid mechanics, experimental measurements and advanced numerical methods are capable not only of an accurate general description of flow characteristics, but can also guarantee high spatiotemporal resolutions analysis of complex physical phenomena. While real-world case studies demonstrate the tangible benefits of these achievements, they unfortunately involve high costs due to heavy data processing, which is time-consuming and resource-intensive. Particularly when dealing with complex three-dimensional flows and designs, this often leads to too costly and non-affordable optimization approaches. In the global worldwide framework of the inevitable double carbon constraint (energy-climate), the main objective of this PhD project is to develop a low-cost methodology for developing and analyzing passive flow control techniques based on cutting-edge coupling of experimental and CFD (Computational Fluid Dynamics) via Frugal Artificial Intelligence tools. This innovative method will be applied to devices such vortex generators, which produce longitudinal vortical flow structures and are extensively employed in various passive configurations. This low-tech intensification technique can be seen as a paramount for multiple applications in fluid mechanics, aerodynamics, heat and/or mass transfers. Developing such an efficient approach implies an in-depth examination of the physics of the flow phenomena involving vorticity generation, and a robust and low-cost optimization procedure to achieve optimal performance and efficiency.