ENACT - Optimizing MRI for Energy Systems: Integrating Artificial Intelligence into Imaging Methods and Data Processing

école doctorale

équipe

Axe Transverse IRM

contexte

The “MRI for Engineering” team at LEMTA is developing research into mass transfer and fluid flows in the fields of energy and energy processes. The methods used are based on nuclear magnetic resonance (NMR), in the time domain (TD-NMR) and imaging (MRI). The subjects studied are highly interdisciplinary, often involving several laboratories and industrial players, with applications such as nuclear safety, membrane processes, mixing phenomena, water transfer in fuel cells, heat storage, etc... Although efforts to develop robust and reliable methods in healthcare have been intense and fruitful, their optimization for energy and process applications still requires further development: in such systems the samples are of variable size and composition, which makes the NMR signal weak and the images noisy. Furthermore, the fluids flow in complex geometries, often at high velocity. The proposed thesis topic is part of a new initiative to implement artificial intelligence (AI) tools at various stages of the experimental workflow, for more efficient data and image processing, and to improve acquisition methods, particularly in magnetic resonance velocimetry (MRV). The thesis will be carried out between the LEMTA laboratory and the startup APREX , which develops AI tools based on adapted algorithms and software suites with the aim of contributing to the digital transition of industry. The new tools and methods will be implemented on the software used to control the new MRI platform at LEMTA.

spécialité

Énergie et Mécanique

laboratoire

LEMTA – Laboratoire Energies & Mécanique Théorique et Appliquée