Prediction of elastic wave dispersion effects using a semi-analytical model under high-frequency approximation
Ultrasonic testing (UT) methods are a fundamental component of non-destructive testing (NDT). They are widely used to inspect mechanical components such as welds (in nuclear and petrochemical industries) and composite material structures (in aeronautics). To understand the physical phenomena involved in a given configuration, simulation is a valuable tool and sometimes an essential step in implementing the inspection process.
Modeling approaches fall into two main categories: purely numerical models based on finite elements (FE) and semi-analytical methods derived from high-frequency (HF) approximations, such as paraxial rays. While the latter are often favored for their computational efficiency, they introduce simplifications that can compromise the quantitative accuracy of results, particularly for phenomena like dispersion (variation in wave speed with frequency), which are common in certain industrial contexts.
This thesis project aims to enhance the paraxial ray approach by integrating models of dispersive interfaces (composite interplies, coupling layers), dispersive viscoelastic media, and a modal guided wave model. The goal is to develop a simulation tool capable of faithfully reproducing realistic inspection configurations, thereby improving the representativeness of the results.
Gyrokinetic modelling of the nonlinear interaction between energetic particle-driven instabilities and microturbulence in tokamak plasmas
Tokamak plasmas are strongly nonlinear systems far from thermodynamic equilibrium, in which instabilities of very different spatial scales coexist, ranging from large-scale macroscopic oscillations to microturbulence. The presence of energetic ions produced by fusion reactions or by auxiliary heating further enhances these instabilities through wave–particle resonances. Microturbulence is responsible for heat and particle transport in the thermal plasma, while instabilities driven by energetic particles can induce their radial transport and, consequently, their losses. Both phenomena degrade the performance of present tokamak plasmas, and possibly also those of burning plasmas such as ITER.
Recent results, however, show that these instabilities, which have long been studied separately, can interact nonlinearly, and that this interaction may lead to an unexpected improvement of plasma confinement.
The objective of this project is to investigate these multiscale interactions using the gyrokinetic code GTC, which is able to simultaneously simulate turbulence and energetic-particle-driven instabilities. This work aims to improve the understanding of the nonlinear mechanisms governing plasma confinement and to identify optimal regimes for future fusion plasmas.
Impact of magnetohydrodynamic on access and dynamics of X-point radiator regimes (XPR)
ITER and future fusion powerplants will need to operate without degrading too much the plasma facing components (PFC) in the divertor, the peripheral element with is dedicated to heat and particle exhaust in tokamaks. In this context, two key factors must be considered: heat fluxes must stay below engineering limits both in stationary conditions and during violent transient events. An operational regime recently developed can satisfy those two constraints: the X-point Radiator (XPR). Experiments on many tokamaks, in particular WEST which has the record plasma duration in this regime (> 40 seconds), have shown that it allowed to drastically reduce heat fluxes on PFCs by converting most of the plasma energy into photons and neutral particles, and that it also was able to mitigate – or even suppress – deleterious magnetohydrodynamic (MHD) edge instabilities known as ELMs (edge localised modes). The mechanisms governing these mitigation and suppression are still poorly understood. Additionally, the XPR itself can become unstable and trigger a disruption, i.e., a sudden loss of plasma confinement cause by global MHD instabilities.
The objectives of this PhD are: (i) understand the physics at play during the interaction XPR-ELMs, and (ii) optimise the access and stability of the XPR regime. To do so, the student will use the 3D non linear MHD code JOREK, the European reference code in the field. The goal is to define the operational limits of a stable XPR with small or no ELMs, and identify the main actuators (quantity and species of injected impurities, plasma geometry).
A participation to experimental campaigns of the WEST tokamak (operated by IRFM at CEA Cadarache) – and of the MAST-U tokamak operated by UKAEA – is also envisaged to confront numerical results and predictions to experimental measurements.
Robust multi-material topological optimization under manufacturability constraints applied to the design of superconducting magnets for high-field MRI
MRI scanners are invaluable tools for medicine and research, whose operation is based on exploiting the properties of atomic nuclei immersed in a very intense static magnetic field. In almost all MRI scanners, this field is generated by a superconducting electromagnet.
The design of electromagnets for MRI must meet very demanding requirements in terms of the homogeneity of the field produced. In addition, as the magnetic field becomes more intense, the forces exerted on the electromagnet increase, raising the issue of the mechanical strength of the windings. Finally, the “manufacturability” of the electromagnet imposes constraints on the shapes of acceptable solutions. The design of superconducting electromagnets for MRI therefore requires a meticulous effort to optimize the design, subject to constraints based on magneto-mechanical multiphysics modeling.
A new innovative multiphysics topological optimization methodology has been developed, based on a density method (SIMP) and a finite element code. This has made it possible to produce magnet designs that meet the constraints on the homogeneity of the magnetic field produced and on the mechanical strength of the windings. However, the solutions obtained are not feasible in practice, both in terms of the manufacturability of the coils (cable windings) and their integration with a supporting structure (coils held in place by a steel structure).
The objective of this thesis is to enhance the topological optimization method by formalizing and implementing manufacturing constraints related to the winding method, residual stresses resulting from pre-tensioning the cables during winding, and the presence of a structural material capable of absorbing the forces transmitted by the coils.
Designing a hybrid CPU-GPU estimator for neutron transport: Advancing eco-efficient Monte Carlo simulations
Digital twins incorporating Monte Carlo simulation models are currently being developed for the design, operation, and decommissioning of nuclear facilities. These twins are capable of predicting physical quantities such as particle fluxes, gamma/neutron heating, and dose equivalent rates. However, the Monte Carlo method presents a major drawback: high computational time to achieve acceptable variance levels.
To enhance simulation efficiency, the eTLE estimator has been developed and integrated into the TRIPOLI-4® Monte Carlo code. Compared to the conventional TLE (Track Length Estimator), eTLE offers lower theoretical variance, particularly in highly absorbing media, by contributing to the detector response even when particles do not physically reach it. Nevertheless, its computational cost remains significant, especially when evaluating multiple detectors.
Two recent PhD works have proposed variants to overcome this limitation. The Forced Detection eTLE- (Guadagni, EPJ Plus 2021) employs preferential sampling that directs pseudo-particles toward the detector at each collision. It is particularly effective for small detectors and configurations with moderate shielding, especially for fast neutrons. The Split Exponential TLE (Hutinet & Antonsanti, EPJ Web 2024) is based on an asynchronous GPU approach, offloading straight-line particle transport to the graphics processor. Through multiple sampling, it maximizes GPU utilization and enables more efficient exploration of phase space.
The proposed thesis aims to combine these two approaches into a hybrid estimator named seTLE-DF. This new estimator could be used either directly or to generate importance maps without relying on auxiliary deterministic calculations. Its implementation will require dedicated GPU developments, particularly to optimize the geometry library and memory management in complex geometries.
This research topic aligns with green computing objectives, aiming to reduce the carbon footprint of high-performance computing. It relies on a hybrid CPU-GPU strategy, avoiding full porting of the Monte Carlo code to GPU. Solutions such as half-precision formats will be considered, and an energy impact assessment will be conducted before and after implementation. The future PhD student will be welcomed with the IRESNE Institute (CEA Cadarache)and will acquire strong expertise in neutron transport simulation, facilitating integration into major research institutions or companies within the nuclear sector.
Microemulsion model: Towards the prediction of liquid-liquid extraction processes
This multi-scale modeling PhD project aims to develop innovative theoretical approaches and numerical tools to predict the extraction processes of strategic metals, which are essential for the energy transition. Among the existing methods, liquid-liquid extraction is a key process, but its underlying mechanisms remain poorly understood. To address these challenges, the solvent phases will be represented as microemulsions through a synergy of mesoscopic and molecular modeling approaches.
The mesoscopic approach will involve the development of a code based on microemulsion theory using a random wavelet basis. This code will enable the characterization of the structural and thermodynamic properties of the solutions. The molecular approach will rely on classical molecular dynamics simulations to evaluate the curvature properties of the extractants, which are essential for bridging the two scales.
The new high-performance computational code may integrate artificial intelligence techniques to accelerate the minimization of the system’s free energy while accounting for all chemical species present with a minimal number of parameters. This will pave the way for new research directions, such as predicting speciation and calculating thermodynamic instabilities in ternary phase diagrams, thereby identifying unexplored experimental conditions.
This PhD thesis, conducted at the Mesoscopic Modeling and Theoretical Chemistry Laboratory at the Marcoule Institute for Separation Chemistry, will have applications in the recycling domain and extend to the broader field of nanoscience, thereby expanding the impact of this work.
The PhD candidate, with a background in physical chemistry, theoretical chemistry, or physics and a strong interest in programming, will be encouraged to disseminate their scientific results through publications and presentations at national and international conferences. By the end of the thesis, the candidate will have acquired a broad range of skills in theoretical chemistry, modeling, numerical computation, and physical chemistry, providing numerous career opportunities in both academic research and industrial R&D.
Axion searches in the SuperDAWA experiment with superconducting magnets and microwave radiometry
Axions are hypothetical particles that could both explain a fundamental problem in strong interactions (the conservation of CP symmetry in QCD) and account for a significant fraction of dark matter. Their direct detection is therefore a key challenge in both particle physics and cosmology.
The SuperDAWA experiment, currently under construction at CEA Saclay, uses superconducting magnets and a microwave radiometer placed inside a cryogenic cryostat. This setup aims to convert potential axions into measurable radio waves, with frequencies directly linked to the axion mass.
The proposed PhD will combine numerical modeling with hands-on experimental work. The student will develop a detailed model of the experiment, including magnetic fields, radio signal propagation, and detector electronics, validated step by step with real measurements. Once the experiment is running, the PhD candidate will participate in data-taking campaigns and their analysis.
This project provides a unique opportunity to contribute to a state-of-the-art experiment in experimental physics, with direct implications for the global search for dark matter.
Multi-Probe Cosmological Mega-Analysis of the DESI Survey: Standard and Field-Level Bayesian Inference
The large-scale structure (LSS) of the Universe is probed through multiple observables: the distribution of galaxies, weak lensing of galaxies, and the cosmic microwave background (CMB). Each probe tests gravity on large scales and the effects of dark energy, but their joint analysis provides the best control over nuisance parameters and yields the most precise cosmological constraints.
The DESI spectroscopic survey maps the 3D distribution of galaxies. By the end of its 5-year nominal survey this year, it will have observed 40 million galaxies and quasars — ten times more than previous surveys — over one third of the sky, up to a redshift of z = 4.2. Combining DESI data with CMB and supernova measurements, the collaboration has revealed a potential deviation of dark energy from a cosmological constant.
To fully exploit these data, DESI has launched a “mega-analysis” combining galaxies, weak lensing of galaxies (Euclid, UNIONS, DES, HSC, KIDS) and the CMB (Planck, ACT, SPT), aiming to deliver the most precise constraints ever obtained on dark energy and gravity. The student will play a key role in developing and implementing this multi-probe analysis pipeline.
The standard analysis compresses observations into a power spectrum for cosmological inference, but this approach remains suboptimal. The student will develop an alternative, called field-level analysis, which directly fits the observed density and lensing field, simulated from the initial conditions of the Universe. This constitutes a very high-dimensional Bayesian inference problem, which will be tackled using recent gradient-based samplers and GPU libraries with automatic differentiation. This state-of-the-art method will be validated alongside the standard approach, paving the way for a maximal exploitation of DESI data.
Multiphysic modeling of sintering of nuclear fuel pellet: effect of atmosphere on shrinkage kinetics
Uranium dioxide (UO2) fuels used in nuclear power plants are ceramics, for which solid-phase sintering is a key manufacturing step. The sintering stage involves heat treatment under controlled partial O2 pressure that induces coarsening of UO2 grain and then consolidation and densification of the material. Grain growth induce material densification and macroscopic shrinkage of the pellet. If the green pellet (powder obtained by pressing, manufacturing step before sintering) admit a highly heterogeneous density, this gradient leading to differential shrinkage and the appearance of defects. Furthermore, the sintering atmosphere, i.e., the gas composition in the furnace, impacts grain growth kinetics and thus the shrinkage of the pellet. Advanced simulation is the key to improving understanding of the mechanisms observed as well as optimizing manufacturing cycles.
The PhD thesis aims at developing a Thermo-chemo-mechanical modeling of sintering to simulate the impact of the gas composition and properties on the pellet densification. This scale will enable us to take into account not only the density gradients resulting from pressing, but also the oxygen diffusion kinetics that have a local impact on the densification rate, which in turn impacts the transport process. Therefore, a multiphysics coupling phenomenon has to be modelled and simulated.
This thesis will be conducted within the MISTRAL joint laboratory (Aix-Marseille Université/CNRS/Centrale Marseille CEA-Cadarache IRESNE institute). The PhD student will leverage his results through publications and participation in conferences and will have gained strong skills and expertise in a wide range of academic and industrial sectors.
Numerical simulation of turbulence models on distorted meshes
Turbulence plays an important role in many industrial applications (flow, heat transfer, chemical reactions). Since Direct Simulation (DNS) is often an excessive cost in computing time, Reynolds Models (RANS) are then used in CFD (computational fluid dynamics) codes. The best known, which was published in the 70s, is the k - epsilon model.
It results in two additional non-linear equations coupled to the Navier-Stokes equations, describing the transport, for one, of turbulent kinetic energy (k) and, for the other, of its dissipation rate (epsilon). ). A very important property to check is the positivity of the parameters k and epsilon which is necessary for the system of equations modeling the turbulence to remain stable. It is therefore crucial that the discretization of these models preserves the monotony. The equations being of convection-diffusion type, it is well known that with classical linear schemes (finite elements, finite volumes, etc ...), the numerical solutions are likely to oscillate on distorted meshes. The negative values of the parameters k and epsilon are then at the origin of the stop of the simulation.
We are interested in nonlinear methods allowing to obtain compact stencils. For diffusion operators, they rely on nonlinear combinations of fluxes on either side of each edge. These approaches have proved their efficiency, especially for the suppression of oscillations on very distorted meshes. We can also take the ideas proposed in the literature where it is for example described nonlinear corrections applying on classical linear schemes. The idea would be to apply this type of method on the diffusive operators appearing in the k-epsilon models. In this context it will also be interesting to transform classical schemes of literature approaching gradients into nonlinear two-point fluxes. Fundamental questions need to be considered in the case of general meshes about the consistency and coercivity of the schemes studied.
During this thesis, we will take the time to solve the basic problems of these methods (first and second year), both on the theoretical aspects and on the computer implementation. This can be done in Castem, TrioCFD or Trust development environments. We will then focus on regular analytical solutions and application cases representative of the community.