As part of the sustainable use of nuclear energy within a carbon-free energy mix in combination with renewable energies, fourth-generation fast neutron reactors are crucial for closing the fuel cycle and controlling uranium resources. Ensuring the safety of such a sodium-cooled reactor relies for a significant part on the early detection of gas voids in their circuits. In these opaque and metallic environments, optical imaging methods are ineffective, making it necessary to develop innovative techniques.
This PhD project is part of the development of Electrical Impedance Tomography (EIT) applied to liquid metals, a non-intrusive approach enabling the imaging of local conductivity distributions within a flow.
The work will focus on the study of electromagnetic phenomena in two-phase metal/gas systems, in particular the skin effect and eddy currents generated by oscillating fields.
Artificial-intelligence approaches, such as Physics-Informed Neural Networks (PINNs), will be explored to combine numerical learning with physical constraints and will be compared with purely numerical simulations.
The objective is to establish refined physical models adapted to metallic environments and to design inversion methods robust against measurement noise.
Experiments on Galinstan will be conducted to validate the models and demonstrate the feasibility of detecting gas inclusions in a liquid metal.
This research, carried out at IRESNE Institute of CEA Cadarache, will open new perspectives in electromagnetic imaging for opaque, highly conductive media.
Dispersion engineering (DE) refers to the control of how electromagnetic waves propagate in a structure by shaping the relationship between frequency and phase velocity. Using artificially engineered materials and surfaces, this relationship can be tailored to achieve non-conventional propagation behaviors, enabling precise control of dispersive effects in the system. In antenna design, dispersion engineering can enhance several key aspects of radiation performance, including gain bandwidth, beam-scanning accuracy, and in general the reduction of distortions that arise when the operating frequency changes. It can also enable additional functionalities, such as multiband operation or multifocal behavior in lens- and reflector-based antennas.
This thesis aims to investigate the underlying physics governing the control of phase and group velocities in two-dimensional artificial surfaces with frequency-dependent effective impedance properties. A particular emphasis will be placed on spatially fed architectures, such as transmitarrays and reflectarrays, where dispersion plays a crucial role. The objective is to derive analytical formulations within simultaneously control of both group and phase delay, develop general models, and assess the fundamental limitations of such systems in radiation performance. This work is especially relevant for high-gain antenna architectures, where the state of the art remains limited. Current dispersion-engineered designs are mostly narrowband, and no compact high-gain solution (> 35 dBi) has yet overcome dispersion-induced degradations, which lead to gain drop and beam squint.
The student will develop theoretical and numerical tools, investigate new concepts of periodic unit cells for the impedance surfaces, and design advanced antenna architectures exploiting principles such as true-time delay, shared-aperture multiband operation, or near-field focsuing with minimized chromatic aberrations. The project will also explore alternative fabrication technologies to surpass the constraints of standard PCB processes and unlock new dispersion capabilities.