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.

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.

Staggered schemes for the Navier-Stokes equations with general meshes

The simulation of the Navier-Stokes equations requires accurate and robust numerical methods that
take into account diffusion operators, gradient and convection terms. Operational approaches have
shown their effectiveness on simplexes. However, in some models or codes
(TrioCF, Flica5), it may be useful to improve the accuracy of solutions locally using an
error estimator or to take into account general meshes. We are here interested in staggered schemes.
This means that the pressure is calculated at the centre of the mesh and the velocities on the edges
(or faces) of the mesh. This results in methods that are naturally accurate at low Mach numbers .
New schemes have recently been presented in this context and have shown their
robustness and accuracy. However, these discretisations can be very costly in terms of memory and
computation time compared with MAC schemes on regular meshes
We are interested in the "gradient" type methods. Some of them are based on a
variational formulation with pressure unknowns at the mesh centres and velocity vector unknowns on
the edges (or faces) of the cells. This approach has been shown to be effective, particularly in terms of
robustness. It should also be noted that an algorithm with the same degrees of freedom as the
MAC methods has been proposed and gives promising results.
The idea would therefore be to combine these two approaches, namely the "gradient" method with the same degrees of freedom as MAC methods. Initially, the focus will be on recovering MAC schemes on regular meshes. Fundamental
questions need to be examined in the case of general meshes: stability, consistency, conditioning of
the system to be inverted, numerical locking. An attempt may also be made to recover the gains in
accuracy using the methods presented in for discretising pressure gradients.
During the course of the thesis, time will be taken to settle the basic problems of this method (first and
second years), both on the theoretical aspects and on the computer implementation. It may be carried
out in the Castem, TrioCFD, Trust or POLYMAC development environments. The focus will be on
application cases that are representative of the community.

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.

Modeling of Wall Condensation Phenomena and Liquid Film Interactions

In this thesis, we focus on modeling mass and energy transfer associated with wall condensation in a turbulent flow of a vapor–noncondensable gas mixture. The flow is two-phase and turbulent, where forced, mixed, and natural convection modes may occur. The framework of this work relies on the RANS approach applied to the compressible Navier–Stokes equations, in which wall condensation is described using semi-analytical wall functions developed in a previous doctoral study cite{iziquel2023}. These functions account for the different convection modes as well as suction and species interdiffusion effects, but neglect the presence of a liquid film.
In the literature, the influence of film formation and flow on mass and heat transfer is often neglected, since it is generally assumed that, in the presence of noncondensable gases, the resistance of the gaseous layer to vapor diffusion is much greater than the thermal resistance of the liquid film.
The objective of this thesis is to improve the prediction of heat and mass transfer by investigating, beyond the thermal resistance of the condensate, the dynamic effect of the liquid and its interaction with the gaseous diffusion layer during wall condensation. The study will first consider laminar film flow, and then attempt to extend the analysis to the turbulent regime.
In the gas phase, the wall-function model developed in cite{iziquel2023} for a binary mixture of vapor and a single noncondensable gas will be extended to mixtures of vapor and $n>1$ noncondensable gases (N2, H2, …), in order to address hydrogen risk issues.
The validation of the implemented models will be carried out using results from separate-effect (SET) and coupled-effect (CET) experiments available in the literature (Huhtiniemi cite{huhti89}, COPAIN, ISP47-MISTRA, ISP47-TOSQAN, RIVA). Comparisons at the CFD scale, using wall functions for condensation neglecting the film, will be performed on benchmark cases from the literature and condensation experiments (COPAIN) to assess the impact of this assumption as well as the improvement provided by the new model in terms of accuracy and computational cost.

Design of asynchronous algorithms for solving the neutron transport equation on massively parallel and heterogeneous architectures

This PhD thesis work aims at designing an efficient solver for the solution to the neutron transport equation in Cartesian and hexagonal geometries for heterogeneous and massively parallel architectures. This goal can be achieved with the design of optimal algorithms with parallel and asynchronous programming models.
The industrial framework for this work is in solving the Boltzmann equation associated to the transportof neutrons in a nuclear reactor core. At present, more and more modern simulation codes employ an upwind discontinuous Galerkin finite element scheme for Cartesian and hexagonal meshes of the required domain.This work extends previous research which have been carried out recently to explore the solving step ondistributed computing architectures which we have not yet tackled in our context. It will require the cou-pling of algorithmic and numerical strategies along with programming model which allows an asynchronousparallelism framework to solve the transport equation efficiently.
This research work will be part of the numerical simulation of nuclear reactors. These multiphysics computations are very expensive as they require time-dependent neutron transport calculations for the severe power excursions for instance. The strategy proposed in this research endeavour will decrease thecomputational burden and time for a given accuracy, and coupled to a massively parallel and asynchronousmodel, may define an efficient neutronic solver for multiphysics applications.
Through this PhD research work, the candidate will be able to apply for research vacancies in highperformance numerical simulation for complex physical problems.

One-sided communication mechanisms for data decomposition in Monte Carlo particle transport applications

In the context of a Monte Carlo calculation for the evolution of a PWR (pressurized water reactor) core, it is necessary to compute a very large number of neutron-nucleus reaction rates, involving a data volume that can exceed the memory capacity of a compute node on current supercomputers. Within the Tripoli-5 framework, distributed memory architectures have been identified as targets for high-performance computing deployment. To leverage such architectures, data decomposition approaches must be used, particularly for reaction rates. However, with a classical parallelization method, processes have no particular affinity for the rates they host locally; on the contrary, each rate receives contributions uniformly from all processes. Access to decomposed data can be costly when it requires intensive use of communications. Nevertheless, one-sided communication mechanisms, such as MPI RMA (Message Passing Interface, Remote Memory Access), make these accesses easier both in terms of expression and performance.
The objective of this thesis is to propose a method for partial data decomposition relying on one-sided communication mechanisms to access remotely stored data, such as reaction rates. Such an approach will significantly reduce the volume of data stored in memory on each compute node without causing a significant degradation in performance.

Modelling of Thermo-Fluid Phenomena in the Plasma Nozzle of the ELIPSE Process

The ELIPSE process (Elimination of Liquids by Plasma Under Water) is an innovative technology dedicated to the mineralization of organic effluents. It is based on the generation of a thermal plasma fully immersed in a water-filled reactor vessel, enabling extremely high temperatures and reactive conditions that promote the complete decomposition of organic compounds.
The proposed PhD research aims to develop a multiphysics numerical model describing the behavior of the process, particularly within the plasma nozzle, a key zone where the high-temperature gas jet from the torch interacts with the injected liquids.
The approach will rely on coupled thermo-aerodynamic modeling, integrating fluid dynamics, heat transfer, phase change phenomena, and turbulence effects. Using Computational Fluid Dynamics (CFD) tools, the study will characterize plasma–liquid interaction mechanisms and optimize the geometry and operating conditions of the process. This modeling will be compared and validated against complementary experimental data obtained from the ELIPSE setup, providing the necessary input for model calibration and validation.
This work will build upon previous research that has led to the development of thermal and hydraulic models of both the plasma torch and the reactor vessel. Integrating the new model within this framework will yield a comprehensive and coherent representation of the ELIPSE process. Such an approach represents a decisive step toward process optimization and industrial scale-up.
The ideal candidate will be a Master’s or final-year engineering student with a background in process engineering and/or numerical simulation, demonstrating a strong interest in physical modeling and computational approaches.
During this PhD, the candidate will develop and strengthen skills in multiphysics numerical modeling, advanced CFD simulation, and thermo-aerodynamic analysis of complex processes. They will also acquire solid experience in waste treatment, a rapidly expanding field with significant industrial and environmental relevance. These skills will provide strong career opportunities in applied research, process engineering, energy, and environmental sectors.

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.

What mechano-thermal coupling is necessary for fast transients? Evaluation of the contributions of thermodynamics to irreversible processes.

The Laboratory for the Analysis of Radioelement Migration (LAMIR) at the Institute for Research on Nuclear Systems (IRESNE) of the CEA Cadarache has developed a set of measurement methods to characterize the release of fission products from nuclear fuel during transient thermal transients. For these transients, it is important to simulate the mechanical stresses associated with temperature changes that could lead to fracturing of the tested fuel samples . This thesis focuses on modeling hypothetical and very rapid accidental power transients. Its objective is to implement a new model based on the thermodynamics of irreversible processes (TIP).

The first part of this thesis will aim to validate the thermomechanical coupling model in TIP, which was proposed in our laboratory (https://www.mdpi.com/2813-4648/3/4/33). This will be an essentially analytical approach to establish the orders of magnitude of the various mechanisms involved. The second part will apply this formalism to experimental results obtained during rapid heating experiments using laser beams.

One of the main challenges of numerical simulation with TIP is calculating the temperature and stress fields simultaneously, rather than sequentially as in current models. We will start with a 1D program (in Python or another language) that will be progressively refined. Comparing the results obtained with TIP and with current models will help us identify situations in which TIP-specific couplings must be taken into account to achieve accurate predictions.

The PhD candidate will benefit from the support of experts in thermodynamics, mechanics, and programming. The research will lead to scientific publications and conference presentations. Owing to the diversity of the fields involved, this thesis topic offers excellent career prospects in both industry and academic research.

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