Learning Mechanisms for Detecting Abnormal Behaviors in Embedded Systems
Embedded systems are increasingly used in critical infrastructures (e.g., energy production networks) and are therefore prime targets for malicious actors. The use of intrusion detection systems (IDS) that dynamically analyze the system's state is becoming necessary to detect an attack before its impacts become harmful.
The IDS that interest us are based on machine learning anomaly detection methods and allow learning the normal behavior of a system and raising an alert at the slightest deviation. However, the learning of normal behavior by the model is done only once beforehand on a static dataset, even though the embedded systems considered can evolve over time with updates affecting their nominal behavior or the addition of new behaviors deemed legitimate.
The subject of this thesis therefore focuses on studying re-learning mechanisms for anomaly detection models to update the model's knowledge of normal behavior without losing information about its prior knowledge. Other learning paradigms, such as reinforcement learning or federated learning, may also be studied to improve the performance of IDS and enable learning from the behavior of multiple systems.
Electromagnetic Signature Modeling and AI for Radar Object Recognition
This PhD thesis offers a unique opportunity to work at the crossroads of electromagnetics, numerical simulations, and artificial intelligence, contributing to the development of next-generation intelligent sensing and recognition systems. The intern will join the Antenna & Propagation Laboratory at CEA-LETI, Grenoble (France), a world-class research environment equipped with state-of-the-art tools for propagation channel characterization and modelling. A collaboration with the University of Bologna (Italy) is planned during the PhD.
This PhD thesis aims to develop advanced electromagnetic models of near-field radar backscattering, tailored to radar and Joint Communication and Sensing (JCAS) systems operating at mmWave and THz frequencies. The research will focus on the physics-based modeling of the radar signatures of extended objects, accounting for near-field effects, multistatic and multi-antenna configurations, as well as the influence of target materials and orientations. These models will be validated through electromagnetic simulations and dedicated measurement campaigns, and subsequently integrated into scene-level and multipath propagation simulation tools based on ray tracing. The resulting radar signatures will be exploited to train artificial intelligence algorithms for object recognition, material property inference, and radar imaging. In parallel, physics-assisted AI approaches will be investigated to accelerate electromagnetic simulations and reduce their computational complexity. The final objective of the thesis is to integrate radar backscattering-based information into a 3D Semantic Radio SLAM framework, in order to improve localization, mapping, and environmental understanding in complex or partially obstructed scenarios.
We are seeking a student at engineering school or Master’s level (MSc/M2), with a strong background in signal processing, electromagnetics, radar, or telecommunications. An interest in artificial intelligence, physics-based modeling, and numerical simulation is expected. Programming skills in Matlab and/or Python are appreciated, as well as the ability to work at the interface between theoretical models, simulations, and experimental validation. Scientific curiosity, autonomy, and strong motivation for research are essential.The application must include a CV, academic transcripts, and a motivation letter.
Study of Failure Modes and Mechanisms in RF Switches Based on Phase-Change Materials
Switches based on phase change materials (PCM) demonstrate excellent RF performance (FOM <10fs) and can be co-integrated into the BEOL of CMOS processes. However, their reliability is still very little studied today. Failure modes such as heater breakage, segregation, or the appearance of cavities in the material are shown during endurance tests, but the mechanisms of these failures are not discussed. The objective of this thesis will therefore be to study the failure modes and mechanisms for different operating conditions (endurance, hold, power). The analysis will be carried out through electrical and physical characterizations and accelerated aging methods will be implemented.
Code Development and Numerical Simulation of Gas Entrainment in Sodium-Cooled Fast Reactors
In sodium-cooled fast reactors (SFRs), the circulation of liquid sodium is ensured by immersed centrifugal pumps. Under certain conditions, vortices can develop in recirculation zones, promoting the entrainment of inert gas bubbles (typically argon) located above the free surface. If these bubbles are drawn into the primary circuit, they can damage pump components and compromise the safety of the installation. This phenomenon remains difficult to predict, particularly during the design phase, as it depends on numerous physical, geometrical, and numerical parameters.
The objective of this PhD work is to contribute to a better understanding and modeling of gas entrainment in free-surface flows typical of SFRs, through Computational Fluid Dynamics (CFD) simulations using the open-source code TrioCFD, developed by the CEA. This code includes an interface-tracking module (Front Tracking) that is particularly well-suited for simulating two-phase phenomena involving a deformable free interface.
Atomic scale modeling of radiation induced segregation in Zr(Nb) alloys
Nuclear fuel cladding made of zirconium alloys constitute the first safety barrier in pressurized water reactors. The microstructure of these alloys not only controls mechanical properties, but also phenomenon such as corrosion or growth under irradiation. Enabling a more flexible use of nuclear energy in the mix while maintaining the structural integrity of fuel cladding under both operating and accidental conditions, we must understand the detailed mechanisms of microstructure evolution under irradiation. Numerous studies point toward the center part played by Nb in such microstructural evolution. For instance, diffusion flux coupling between solutes (Nb) and point defect created by irradiation gives rise to local Nb segregation, as well as precipitates which are not seen in non-irradiated samples. Atomic scale modeling brings in information that complements that obtained from experimental observations, allowing to confirm or disprove the evolution scenarios found in the literature. The aim of this Ph.D. work is to use the tools which have been developed to study irradiation effects in ferritic steels, and apply them to Zr alloys, with a focus on radiation induced segregation. Electronic structure calculations in the density functional theory approximation will be used to study the interactions between niobium atoms and point defects. From this data, we are able to compute transport coefficients, from which we can discuss quantitatively solute/point defect flux coupling and radiation induced segregation effects.
Experimental study of Nanometric-Scale Microstructural and Microchemical Evolution in Zirconium Alloys under Irradiation
Zirconium-based alloys are used as fuel cladding material for pressurized water reactors due to their low thermal neutron absorption cross-section, good mechanical strength, and excellent corrosion resistance. However, despite decades of research, the mechanisms governing the evolution of their microstructure and microchemistry under irradiation are still not fully understood. These phenomena strongly influence the in-reactor performance and lifetime of the materials
Neutron irradiation generates displacement cascades in crystalline material, producing large numbers of point defects (vacancies and interstitials) that can cluster and drive atomic redistribution. The high concentration of point defects promotes radiation-induced segregation and precipitation of alloying elements. In Zr1%Nb alloys, irradiation leads to the unexpected formation of high density Nb-rich nanoprecipitates. This phenomenon has significant implications on the macroscopic properties of the material, notably its post-irradiation creep and corrosion behavior in reactors.
This PhD project aims to elucidate the mechanisms responsible for the precipitation of Nb-rich nanoprecipitates under irradiation. A Zr1%Nb alloy will be irradiated with ions at various doses and temperatures, followed by advanced nanoscale characterization using transmission electron microscopy (TEM) and atom probe tomography (APT). These complementary techniques will provide detailed information on the spatial distribution of alloying elements and the nature of point defect clusters at the atomic scale. Based on these results, a comprehensive mechanism for irradiation-induced precipitation will be proposed, and its implications for the macroscopic properties and in-reactor performance of zirconium alloys will be assessed. By improving the fundamental understanding of irradiation-induced microstructural evolution, this research aims to contribute to the development of more radiation-resistant zirconium alloys for nuclear applications.
Experimental study and numerical simulation of deformation mechanisms and mechanical behavior of zirconium alloys after irradiation
The cladding of nuclear fuel rods used in Pressurized Water Reactor, made of zirconium alloys, is the first barrier for the confinement of radioactive nuclei. In-reactor, the cladding is subjected to radiation damage resulting in a change of its mechanical properties. After in-reactor use, the fuel rods are transported and stored. During these various steps, the radiation damage is partially annealed, leading to another evolution of the material properties. All these evolutions are still not well understood.
The objective of this PhD work is to better understand the deformation mechanisms and the mechanical behavior of zirconium alloys after irradiation, and after a partial annealing of the radiation damage. This will help to better predict the behavior of the cladding tube after use and thus guaranty the confinement of radioactive nuclei.
In order to achieve this goal, original experimental methods and advanced numerical simulations will be used. Ion irradiations will be conducted in order to reproduce the radiation damage. Heat treatments will then be done on the specimens after irradiation. Small tensile samples will be strained in situ, after annealing, inside a transmission electron microscope, at room temperature or at high temperature. Deformation mechanisms observed at nanometer scale and in real time will be simulated using dislocation dynamics, at the same time and space scales. Large scale dislocation dynamics simulations will then be conducted in order to deduce the single-crystal behavior of the material. In parallel with this study at the nanometric scale, a study will also be conducted at the micrometric scale. Nanoindentation and micropillar compression tests will be performed to assess the mechanical behavior after irradiation and annealing. The results of mechanical tests will be compared with large-scale dislocation dynamics numerical simulations.
This study will allow a better understanding of the special behavior of zirconium alloys after irradiation and annealing and then help to develop physically based predictive models. In a future prospect, this work will contribute to improve the safety during transport and storage of spent nuclear fuel.
Effect of gravity on agitation within a turbulent bubbly flow in a channel
Understanding two-phase flows and the boiling phenomenon is a major challenge for the CEA, for both the design and safety of nuclear power plants. In a Pressurized Water Reactor (PWR), the heat generated by the nuclear fuel is transferred to the water in the primary circuit. Under accident conditions, the water in the primary circuit can enter a nucleate boiling regime, or even evolve to a boiling crisis. While the phenomenon of boiling is the subject of numerous studies, the dynamics of the generated bubbles also receive special attention at the CEA. This thesis will focus on the coupling between the turbulence generated by a shear flow and the agitation induced by the bubbles. Its originality lies in the study of the effect of gravity, achieved by tilting the channel, a parameter that can generate complex flow regimes.
This experimental work will be based on the new CARIBE facility at CEA Saclay. The PhD student's mission will be to characterize the different flow regimes and then to conduct a detailed study of the flow by implementing specific metrology (including Particle Image Velocimetry (PIV), hot-film anemometry, and optical probes). Conducted within the LE2H laboratory, the project will benefit from a close collaboration with the LDEL (CEA Saclay) and the IMFT (Toulouse). The PhD student will work in a dynamic environment with other PhD students and will present their work at national and international conferences.
We are looking for a candidate with a background in fluid mechanics and a strong interest in experimental work (a Master's thesis internship is possible). This PhD offers the opportunity to develop expertise in instrumentation, data analysis, and turbulent two-phase flows—skills that are highly valued in the energy, industrial, and academic research sectors.
Localised solidifications in Molten Salt Reactors
In a Molten Salt Reactor (MSR), the nuclear fuel is a liquid, high-temperature salt which acts as its own coolant. Some accidental transients (over-cooling of the fuel, leak) may cause localised solidifications of the fuel salt in the core. These solidifications will have in turn an impact on the salt flow in the core, as well as its neutronic behavior, and could lead to a localised over-heating of the core vessel. Such transients are not well studied, although they have a major impact on the safety and design of an MSR.
The objective of the PhD is to study different accidental transients that would lead to localised solidifications, and to study their impact on the neutronics and thermal-hydraulics of the core. These analyses will require the use of multiphysics, MSR-adapted numerical tools, such as the CFD code TrioCFD and its extensions TRUST-NK (neutronics) and Scorpio (reactive transport), as well as the deterministic neutronic code APOLLO3. In order to balance precision and computation time, different models will be tested, depending on the transient studied: 1D/ turbulent 3D (RANS, LES) models for thermal-hydraulics ; diffusion / SPn transport / Sn transport for neutronics.
Numerical modelling of large ductile crack progagation and assessment of margins comparing to engineering approach
Predicting failure modes in metal structures is an essential step in analyzing the performance of industrial components where mechanical elements are subjected to significant stress (e.g., nuclear power plant components, pipelines, aircraft structural elements, etc.). To perform such analyses, it is essential to correctly simulate the behavior of a defect in ductile conditions, i.e., in the presence of significant plastic deformation before and during propagation.
Predictive numerical simulation of ductile tearing remains an open scientific and technical issue despite significant progress made in recent years. The so-called local approach to fracture, notably the Gurson model (and its modified version GTN), is widely used to model ductile tearing. However, its use has limitations: significant computation time, simulation stoppage due to the presence of completely damaged elements in the model, and non-convergence of the result when the mesh size is reduced.
The aim of this thesis is to develop the ductile tear simulation model used at LISN so that it can be applied to large crack propagation on complex structures. It also aims to compare the results obtained with engineering methods that are simpler to implement.