Novel architecture and signal processing for mobile optical telecommunications
Free-Space Optical Communications (FSO) rely on transmitting data via light between two distant points, eliminating the need for fibers or cables. This approach is particularly valuable when wired connections are impractical or prohibitively expensive.
However, these links are highly susceptible to atmospheric conditions—fog, rain, dust, and thermal turbulence—which attenuate or distort the light beam, significantly degrading communication quality. Current solutions remain costly and limited, both in terms of optical compensation hardware and signal processing algorithms.
Within this framework, the thesis aims to design high-performance, robust mobile optical links capable of adapting to dynamic and disturbed environments. The study will focus on leveraging Silicon-based Optical Phased Arrays (OPAs)—a technology derived from low-cost LiDAR systems—offering a promising path toward compact, integrated, and cost-effective architectures.
The primary focus of the research will be developing advanced algorithmic approaches for signal processing and compensation. The PhD candidate will be tasked with designing a dedicated simulation environment to evaluate and validate architectural choices and algorithmic strategies before practical experimentation.
The overarching goal is to propose an integrated, flexible, and reliable architecture that ensures uninterrupted optical communication in motion, with potential applications in aerospace, space, and terrestrial domains.
Modeling the impact of defects in Steel–Concrete Structures. Identification of critical defects through metamodeling and optimization algorithms
To meet growing constructability challenges, steel–concrete (SC) structures are emerging as a promising alternative to conventional reinforced concrete structures. These elements are composed of infill concrete, two external steel plates, and steel shear studs that ensure composite action. While such structures present a clear interest due to their overall mechanical behavior, the presence of the steel plates prevents visual inspection of the concrete casting quality. It is therefore essential to characterize the impact of possible defects. This is the context of the proposed PhD research. Building upon recent results obtained in the laboratory, the goal is to develop a numerical framework to account for defects in steel–concrete structures. The thesis will be structured in several stages: validation of a modeling strategy for the mechanical behavior of defect-free SC structures, introduction of defects in the simulations and assessment of the applicability of the numerical approach, development of a metamodel and sensitivity analysis, and identification of critical defect configurations through optimization algorithms. One of the operational objectives of this doctoral work is to provide a tool capable of identifying critical defect configurations (size, position, and number) with respect to a given target quantity of interest (such as loss of strength or reduction in average stiffness). The research will therefore rely on the use and further development of state-of-the-art numerical tools in the fields of finite element modeling, optimization techniques, sensitivity analysis, and metamodeling. The thesis will be carried out within a rich collaborative environment, notably in partnership with EDF.
Artificial Intelligence for the Modeling and Topographic Analysis of Electronic Chips
The inspection of wafer surfaces is critical in microelectronics to detect defects affecting chip quality. Traditional methods, based on physical models, are limited in accuracy and computational efficiency. This thesis proposes using artificial intelligence (AI) to characterize and model wafer topography, leveraging optical interferometry techniques and advanced AI models.
The goal is to develop AI algorithms capable of predicting topographical defects (erosion, dishing) with high precision, using architectures such as convolutional neural networks (CNN), generative models, or hybrid approaches. The work will include optimizing models for fast inference and robust generalization while reducing manufacturing costs.
This project aligns with efforts to improve microfabrication processes, with potential applications in the semiconductor industry. The expected results will contribute to a better understanding of surface defects and the optimization of production processes.
Control & optimization of fuel cell temperature
Proton exchange membrane fuel cells (PEMFC) represent a key technology for the development of clean and sustainable energy systems, particularly for heavy-duty transport applications where their energy density is very attractive. However, in order to represent a viable industrial alternative, a number of obstacles still need to be overcome, including operating costs and, above all, the durability of the systems under real-world conditions. Among the levers for action, optimizing operating conditions is a promising avenue for limiting the degradation phenomena occurring within the cell. The operating temperature is a particularly key parameter because it affects all aspects of the system, from the kinetics of degradation mechanisms to the thermal capacity that the system can dissipate, including the water balance within the fuel cell. Despite the influence of this parameter on durability, it is generally only optimized at the system level to achieve the best performance, the shortest possible response time and to limit the size of the thermal management system.
The aim of this thesis is to work on optimizing the temperature management of a fuel cell within a system, taking into account not only performance but also sustainability criteria. To do this, the impact of operating temperature on degradation mechanisms will be analyzed using various simulation tools already available at LITEN and the teams' fifteen years of experience in studying PEMFC fuel cell degradation. Various thermal architectures will be proposed and evaluated in conjunction with the work on temperature control optimization. The latter will be implemented on a real fuel cell system in order to demonstrate the relevance of the proposed solution using concrete experimental data.
Study of the behaviour of mixed oxide fuels with degrade isotopy at the beginning of life.
France has decided to adopt a 'closed' nuclear fuel cycle. This involves processing spent fuel to recover valuable materials such as uranium and plutonium, while other compounds such as fission products and minor actinides constitute final waste. UO2 fuel irradiated in pressurised water reactors (PWRs) is currently reprocessed to produce plutonium (PuO2), which is then reused in the form of mixed oxide (MOX) fuel. This fuel is then irradiated in PWRs, a process known as plutonium monorecycling. The CEA is currently studying the multi-recycling of materials using fuels containing Pu from the processing of spent MOX assemblies. However, this multi-recycled plutonium contains a higher proportion of highly alpha-active isotopes (Pu238, Pu240 and Pu241/Am241), resulting in more severe alpha self-irradiation than current MOX fuels experience [1]. This exacerbates certain physical phenomena [2-5], such as fuel swelling due to helium precipitation and the creation of crystal defects and decreased thermal conductivity [6-8], which can alter its behaviour in the reactor.
The proposed thesis will study the impact of these phenomena on the behaviour of MOX fuels at the beginning of the irradiation, using a combination of experimentation and modelling. Heat treatments will be employed to analyse the mechanisms of crystal defect healing and helium behaviour. Various experimental techniques will be employed to characterise the structure and microstructure (X-ray diffraction, scanning electron microscopy (SEM), Raman spectroscopy and microprobe analysis), defect densities (transmission electron microscopy (TEM)), helium release (KEMS), thermal gradient reproduction (CLASH laser) and thermal conductivity (LAF laser). The results will inform simulations modelling the microstructure and thermal properties.
This cross-disciplinary study will improve our understanding of the phenomena involved in the initial power-up of fuels damaged by alpha self-irradiation, particularly the impact of helium produced by decay.
You will be based at the Multi-Fuel Design and Irradiation Laboratory (LECIM) within the Research Institute for Nuclear Systems for Low-Carbon Energy Production at CEA/Cadarache. For the experimental part of the project, you will collaborate with the Chemical Analysis and Materials Characterisation Laboratory (LMAT) at CEA/Marcoule and the European Research Centre (JRC) in Karlsruhe. You will have the opportunity to publish your results through scientific publications and conference presentations. This role offers the chance to develop your expertise in a variety of techniques that can be applied across multiple fields of materials science and engineering.
[1]O. Kahraman, thésis, 2023.[2]M. Kato et al., J Nucl Mater, 393 (2009) 134–140.[3]L. Cognini et al., Nuclear Engineering and Design 340 (2018) 240–244.[4] T. Wiss et al., Journal of Materials Research 30 (2015) 1544–1554.[5]D. Staicu et al., J Nucl Mater 397 (2010) 8–18.[6] T. Wiss et al.,Front. Nucl. Eng. 4 (2025) 1495360.[7]E.P. Wigner, J. Appl. Phys. 17 (1946) 857–863.[8]D. Staicu et al., Nuclear Materials and Energy 3–4 (2015) 6–11.
Parallel simulation and adaptive mesh refinement for 3D solids mechanics problems
The challenge of this PhD thesis is to implement adaptive mesh refinement methods for non-linear 3D solids mechanics adapted to parallel computers.
This research topic is proposed as part of the NumPEx (Digital for Exascale) Priority Research Programs and Equipment (PEPR). It is part of the Exa-MA (Methods and Algorithms for Exascale) Targeted Project. The PhD will take place at CEA Cadarache, within the Institute for Research on Nuclear Energy Systems for Low-Carbon Energy Production (IRESNE), as part of the PLEIADES software platform development team, which specializes in fuel behavior simulation and multi-scale numerical methods.
In finite element simulation, adaptive mesh refinement (AMR) has become an essential tool for performing accurate calculations with a controlled number of unknowns. The phenomena to be taken into account, particularly in solids mechanics, are often complex and non-linear: contact between deformable solids, viscoplastic behaviour, cracking, etc. Furthermore, these phenomena require intrinsically 3D modelling. Thus, the number of unknowns to be taken into account requires the use of parallel solvers. One of the current computational challenges is therefore to combine adaptive mesh refinement methods and nonlinear solid mechanics for deployment on parallel computers.
The first research topic of this PhD thesis concerns the development of a local mesh refinement method (of block-structured type) for non-linear mechanics, with dynamic mesh adaptation. We will therefore focus on projection operators to obtain an accurate dynamic AMR solution during the evolution of refined areas.
The other area of research will focus on the effective treatment of contact between deformable solids in a parallel environment. This will involve extending previous work, which was limited to matching contact meshes, to the case of arbitrary contact geometries (node-to-surface algorithm).
The preferred development environment will be the MFEM tool. Finite element management and dynamic re-evaluation of adaptive meshes require assessing (and probably improving) the efficiency of the data structures involved. Large 3D calculations will be performed on national supercomputers using thousands of computing cores.
his will ensure that the solutions implemented can be scaled up to tens of thousands of cores.
Modeling of a non-equilibrium dispersed phase and its fragmentation
In the context of the sustainable use of nuclear energy to produce carbon-free electricity, fourth-generation reactors, also known as "fast neutron" reactors, are necessary to close the fuel cycle.
This thesis falls within the framework of safety studies associated with such sodium-cooled reactors, and more particularly the hypothetical situation of a molten core relocating by gravity towards the core catcher at the bottom of the reactor vessel. A jet of corium (mixture of molten fuel and structural elements of the core) then interacts violently with the coolant, inducing, among other things, the fragmentation of the corium jet into droplets coupled with film boiling of the coolant. Characteristics of the resulting dispersed phase of corium and its fragmentation are crucial for studying the risk of runaway and steam explosion.
The aim of this thesis is to model a dispersed phase and its fragmentation in a surrounding fluid, using an approach that is both efficient and able to account to the scale variations and thermal imbalances between the droplets and the carrier phase. The method considered to meet these objectives is the method of moments, which derives from a kinetic model. It requires adequate closure and numerical schemes that satisfy non-standard constraints, while offering, in return, a crucial cost/accuracy compromise in the context studied. The advancements will be a priori implemented in the CFD software SCONE, built on the CEA's open-source TRUST platform.
The main work location will be based at the LMAG (Laboratory of Severe Accidents Modeling) at the IRESNE Institute of CEA Cadarache. Part of the work will also be carried out at the EM2C Laboratory (Molecular and Macroscopic Energetics, Combustion) – CNRS/CentraleSupélec in Paris.
The future PhD will work in a scientific dynamic environment and will acquire skills enabling to aspire to academic and industrial R&D positions.
Keywords : Dispersed Phase, Fragmentation, Kinetic, Method of Moments, Multiphase, Numerical methods, Severe Accidents.
UO2 Powders: Morphological Characterization of Aggregates and Study of Their Interactions Using a Combined Experimental and numerical Approach
This PhD thesis is part of the optimization of nuclear fuel fabrication processes, which rely on the powder metallurgy of uranium dioxide (UO2) and plutonium dioxide (PuO2). These powders exhibit a hierarchical microstructure composed of crystallites forming rigid aggregates, themselves agglomerated into larger structures. The morphology and interactions between aggregates play a key role in the macroscopic behavior of the powders—particularly their flowability, compressibility, and agglomeration capacity—and directly influence the quality of the fuel pellets obtained after pressing and sintering. However, the experimental characterization of these aggregates remains complex and does not yet allow for the establishment of a predictive link between synthesis processes and morphological properties.
The objective of this thesis is to combine experimental and numerical approaches to achieve a detailed characterization of the aggregates in a reference powder. Experimentally, techniques such as Scanning Electron Microscopy (SEM), specific surface area measurement (BET), and laser granulometry will be used to determine particle size, roughness, and size distribution. In parallel, numerical simulations based on the Discrete Element Method (DEM) will be employed to construct a granular digital twin consistent with the experimentally measured properties. This digital twin will allow the reconstruction of the internal structure of the aggregates, the evaluation of interparticle adhesion forces, and the analysis of agglomeration and densification phenomena under controlled conditions.
The PhD will take place at CEA Cadarache within the Institute for Research on Nuclear Systems for Low-Carbon Energy Production (IRESNE). The student will be assigned to the PLEIADES Fuel Development Laboratory (LDOP), which specializes in simulating nuclear fuel behavior (from fabrication to in-reactor performance) and in multi-scale numerical methods. The work will be carried out in collaboration with the CNRS/LMGC in Montpellier, internationally recognized for its research on granular materials, and with the Uranium Fuel Laboratory (LCU – CEA Cadarache), which has extensive experience in the experimental characterization of uranium powders.
The PhD candidate is expected to demonstrate strong skills in numerical simulation and in the physical analysis of results. He will share its results through publications and conference presentations and will have the opportunity to learn or further develop various experimental and numerical techniques that can be applied in other contexts.In particular, the issues related to the physics of granular media — which constitute the core of this PhD — are of significant industrial relevance and are common to many other sectors handling powders, such as pharmaceuticals, agri-food, and powder metallurgy.
[Hebrard2004] S.Hebrard, Etude des mécanismes d’évolution morphologique de la structure des poudres d’UO2 en voie sèche, thèse de doctorat, CEA-LSG2M-COGEMA), 2004.
[Pizette2010] P. Pizette, C.L. Martin a, G. Delette, P. Sornay, F. Sans, Compaction of aggregated ceramic powders: From contact laws to fracture and yield surfaces, Powder Technology, 198, 240-250, 2010.
[Tran2025] T.-D. Tran , S. Nezamabadi , J.-P. Bayle, L. Amarsid, F. Radjai , Effect of interlocking on the compressive strength of agglomerates composed of cohesive nonconvex particles, Advanced Powder Technology 36, 2025.
Micromechanical Modeling of the Behavior of Polycristals with Imperfect Interfaces: Application to Irradiated UO2 Fuel
This thesis aims to analyze the thermomechanical properties of UO2 fuel used in pressurized water reactors (PWRs), accounting for the effects of microscopic defects. It focuses particularly on intergranular decohesion phenomena observed at various stages of fuel evolution, notably prior to crack initiation and propagation. The objective of this thesis is to clarify the impact of decohesion on both the local and effective properties of UO2 during irradiation. To this end, intergranular decohesion is modeled at the local scale by means of imperfect interface models, which ensure traction continuity while allowing for a displacement jump at grain boundaries. This modeling approach enables the development of homogenization models incorporating innovative theoretical and numerical advances, capable of capturing the behavior of the fuel at very high temperatures, under off-normal and accidental conditions. This work will be conducted at CEA Cadarache,in the Institute for Research on Nuclear Systems for Low-Carbon Energy Production (IRESNE), in close collaboration with national and international research teams. The tools developed will contribute to improving our understanding of the fuel's properties and to enhancing the accuracy and reliability of existing models, particularly those implemented in the PLEIADES simulation platform developed by the CEA in collaboration with French nuclear industry partners.
Nuclear fuel fragmentation under thermal gradient of fuel during laser heating: correlation, numerical simulation and and adaptation of the experimental setup.
The aim of this thesis is to simulate the cracking of nuclear fuel, which consists of a brittle ceramic material, uranium dioxide, during laser heating experiments. The objective is to compare the numerical results with experimental data through image correlation. This comparison will make it possible to optimize the experimental setup, improve the quality of the experimental results, and move toward a quantitative validation of the gradient damage models used in the simulations.
The starting point of this work is a campaign of uranium dioxide pellet fragmentation by laser heating, carried out as part of the PhD of Hugo Fuentes [1] in one of the experimental laboratories of the Institute for Research on Nuclear Energy Systems for Low-Carbon Energy Production (IRESNE) at CEA Cadarache (DEC/SA3E/LAMIR). This heating technique reproduces temperature gradients representative of reactor conditions. For each test, films showing the evolution of cracks and surface temperature changes in the pellet are available.
These films will be analyzed by digital image correlation (DIC) [3] using an in-house software tool to determine optimal boundary conditions for the numerical simulations and extract relevant data for model validation. The experiments will then be modeled using gradient damage models developed in the PhD theses of David Siedel and Pedro Nava Soto [2]. Based on the results obtained, the PhD candidate will be able to optimize and/or adapt the setup to study other operating conditions and conduct a new experimental campaign.
The PhD student will work in close collaboration between a simulation laboratory and an experimental laboratory within the IRESNE Institute at CEA Cadarache. The proposed work is open-ended and may be promoted through participation in national or international conferences and the publication of scientific articles in high-impact journals.
References
[1] Fuentes, Hugo, Doualle, Thomas, Colin, Christian, Socié, Adrien, Helfer, Thomas, Gallais, Laurent, and Lebon, Frédéric. Numerical and experimental simulation of nuclear fuel fragmentation via laser heating of ceramics. In: Proceedings of Top Fuel 2024, Grenoble, 29 September 2024.
[2] Nava Soto, Pedro, Fandeur, Olivier, Siedel, David, Helfer, Thomas, and Besson, Jacques. Description of thermal shocks using micromorphic damage gradient models. European Solid Mechanics Conference, Lyon, 2025.
[3] Castelier Etienne, Rohmer E., Martin E., Humez B. Utilisation de la dimension temporelle pour ameliorer la
correlation d'images. 20 eme Congres Francais de Mecanique, 2011.