This thesis focuses on the development of advanced numerical methods to simulate fluid-particle interactions in complex environments. These methods, initially used in industrial applications such as combustion and multiphase flows, will be enhanced for integration into simulation codes for exascale supercomputers and adapted to meet the needs of astrophysics. The objective is to enable the study of astrophysical phenomena such as the dynamics of dust in protoplanetary disks and the structuring of dust in protostars and the interstellar medium. The expected outcomes include a better understanding of planetary formation mechanisms and disk structuring, as well as advancements in numerical methods that will benefit both industrial and astrophysical sciences.
The performance of micro-LEDs (µLEDs) is crucial for micro-displays, a field of expertise at the LITE laboratory within CEA-LETI. However, simulating these components is complex and computationally expensive due to the incoherent nature of light sources and the involved geometries. This limits the ability to effectively explore multi-parameter design spaces.
This thesis proposes to develop an innovative finite element method to accelerate simulations and enable the use of topological optimization. The goal is to produce non-intuitive designs that maximize performance while respecting industrial constraints.
The work is divided into two phases:
Develop a fast and reliable simulation method by incorporating appropriate physical approximations for incoherent sources and significantly reducing computation times.
Design a robust topological optimization framework that includes fabrication constraints to generate immediately realizable designs.
The expected results include optimized designs for micro-displays with enhanced performance and a methodology that can be applied to other photonic devices.
The performance of a tokamak plasma largely depends on to the level of turbulent transport. Trapped electron modes are one of the main instabilities responsible for turbulence in tokamaks. On the other hand, electron cyclotron resonance heating is a generic heating system for tokamaks. Both physical processes rely on resonant interactions with electrons. Non-linear interaction between the resonant processes is theoretically possible. This thesis aims to evaluate the possibility of exploiting this non-linear interaction to stabilize the trapped electron modes instability within tokamak plasmas, using a heating source present on many tokamaks, including ITER. This control technique could improve the performance of certain tokamaks without any extra cost.
The thesis will be based on a theoretical understanding of the two processes studied, will require the use of the gyrokinetic code GYSELA to model the non-linear interactions between resonant processes, and will include an experimental aspect to validate the identified turbulence control mechanism.
This PhD will take place at the CEA–LETI, a major European actor in the semiconductor industry, and more precisely, at the Nanocharacterization platform of the CEA–LETI witch offer world-class analytical techniques and state-of-the-art instruments. Our team aims to accompany the industry in the development of new characterization tools and so to meet the metrological needs of future technological nodes. Over the past few years, pioneer developments on a new metrology technique based on hard x-ray scattering called CD-SAXS were done at the PFNC. This technique is used to reconstruct the in-plane and out-of-plane structure of nanostructured thin-films with a sub-nm resolution. In this project, we are looking to extend the CD-SAXS approach leveraging the recent breakthrough in the development of low-energy x-ray sources (A. Lhuillier et al. 1988, Nobel prize 2023) called High Harmonics Generation (HHG) sources. Therefore, you will participate in the development of a new and promising characterization methods called Low-energy critical dimension small angle x-ray scattering. The very first proof of concept of this new measurement was conducted in November 2023.
Mission:
In order to include in the data reduction the measurement specificities of this new approach (multi-wavelength, low energy, …) your mission will focus on several aspects to explore in parallel:
- Develop new modeling tools to analyze the data:
o Finite element simulations with Maxwell solver
o Analytical Fourier Transform (similar to standard CD-SAXS) vs dynamical theory
o Comparison between the two approaches
- Build new models dedicated to lithography problematic (CD, overlay, roughness)
- Define the limitations of the technique through the simulation (in term of resolution (nm), uncertainty)
This work will support the development of CD-SAXS measurements with a laboratory HHG (High Harmonic Generation) source lead by a Postdoctoral fellow.
In multiple industries, such as metal forming and additive manufacturing, the discrepancy between the desired shape and the shape really obtained is significant, which hinders the development of these manufacturing techniques. This is largely due to the complexity of the thermal and mechanical processes involved, resulting in a high computational simulation time.
The aim of this PhD is to significantly reduce this gap by accelerating thermo-mechanical finite element simulations, particularly through the design of a tailored neural network architecture, leveraging theoretical physical knowledge.
To achieve this, the thesis will benefit from a favorable ecosystem at both the LMS of École Polytechnique and CEA List: internally developed PlastiNN architecture (patent pending), existing mechanical databases, FactoryIA supercomputer, DGX systems, and 3D printing machines. The first step will be to extent the databases already generated from finite element simulations to the thermo-mechanical framework, then adapt the internally developed PlastiNN architecture to these simulations, and finally implement them.
The ultimate goal of the PhD is to demonstrate the acceleration of finite element simulations on real cases: firstly, through the implementation of feedback during metal printing via temperature field measurement to reduce the gap between the desired and manufactured geometry, and secondly, through the development of a forging control tool that achieves the desired geometry from an initial geometry. Both applications will rely on an optimization procedure made feasible by the acceleration of thermo-mechanical simulations.
As part of the development of new liquid-liquid extraction separation processes, experimental tests are implemented to demonstrate the recovery of valuable elements sufficiently decontaminated from impurities. These tests are commonly carried out in mixer-settler batteries. However, depending on the operating conditions, these finished products may be contaminated by impurities. This contamination results from the combination of several factors:
-Hydrodynamic: Entrainment in the solvent of non-decanted aqueous drops containing impurities
-Chemical: the impurity separation factor is low (less than 10-3)
-Process: the entrainment of drops is amplified with the increase in the rate (reduction of the residence time of the drops)
This thesis aims to increase the understanding of the different phenomena responsible for these phase entrainments in order to estimate optimal operating parameters and to guarantee a contamination of the finished products below a fixed threshold. The aim will be to develop a macroscopic model to predict the flow rate of non-decanted droplets as a function of the operating conditions in the mixer-settler batteries. It will have to be based on hydrodynamic simulations coupling the resolution of a droplet population balance to a continuous phase flow. A coupling will be carried out between this hydrodynamic model and the PAREX or PAREX+ code to size the process diagrams. The qualification of the proposed models will have to be done by comparisons with experimental measurements (based on previous or future test campaigns).
The Monte Carlo method is considered to be the most accurate approach for simulating neutron transport in a reactor core, since it requires no or very few approximations and can easily handle complex geometric shapes (no discretisation is involved). A particular challenge for Monte Carlo simulation in reactor physics applications is to calculate the impact of a small model change: formally, this involves calculating the derivative of an observable with respect to a given parameter. In a Monte-Carlo code, the statistical uncertainty is considerably amplified when calculating a difference between similar values. Consequently, several Monte Carlo techniques have been developed to estimate perturbations directly. However, the question of calculating perturbations induced by a change in reactor geometry remains fundamentally an open problem. The aim of this thesis is to investigate the advantages and shortcomings of existing geometric perturbation methods and to propose new ways of calculating the derivatives of reactor parameters with respect to changes in its geometry. The challenge is twofold. Firstly, it will be necessary to design algorithms that can efficiently calculate the geometric perturbation itself. Secondly, the proposed approaches will have to be adapted to high-performance computing environments.
Over the past twenty years, molten salt reactors (MSRs) have been the focus of renewed interest in the international nuclear community (national programs, start-ups, including one from the CEA). Modern MSR concepts feature a system for evacuating fission gases, which accumulate in the expansion tank. Some of these gases will consist of radionuclides that are delayed neutron precursors, which will therefore be lost for the fission chain reaction. This should further reduce the effective fraction of delayed neutrons in these reactors, already reduced by the circulation of the fuel salt outside the critical zone. The aim of this thesis is to assess the extent of this reduction, and its influence on reactor dynamics.
Such an assessment may involve numerical simulations that take into account 1) a differentiation of delayed neutron precursor groups into “liquid phase groups” and “gas phase groups”, and 2) two-phase flow models (where each type of group joins its corresponding phase). In order to differentiate the groups, we need to evaluate the “liquid” and “gas” fractions for each of them, based for example on the branching ratios of the nuclear evaluations and knowledge of the chemical elements joining each of the phases. Once this has been done, simulations can be carried out with the CATHARE “system” code (already able to use two-phase models) and the TRUST-NK “core” code (whose two-phase calculation functions may require further development) to assess the influence of precursor loss on reactor dynamics.
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. Densification induces macroscopic shrinkage of the pellet. If the compact (powder obtained by pressing, manufacturing step before sintering) is highly heterogeneous density, a difference in densification within the pellet may occur, leading to differential shrinkage and the appearance of defects.
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.