Modeling of Critical Heat Flux Using Lattice Boltzmann Methods: Application to the Experimental Devices of the RJH
The Lattice Boltzmann Methods (LBM) are numerical techniques used to simulate transport phenomena in complex systems. They allow for the modeling of fluid behavior in terms of particles that move on a discrete grid (a "lattice"). Unlike classical methods, which directly solve the differential equations of fluids, LBM simulates the evolution of distribution functions of fluid particles in a discrete space, using propagation and collision rules. The choice of the lattice in LBM is a crucial step, as it directly affects the accuracy, efficiency, and stability of the simulations. The lattice determines how fluid particles interact and move within space, as well as how the discretization of space and time is performed.
LBM methods exhibit natural parallelism properties, as calculations at each grid point are relatively independent. Although classical CFD methods based on the solution of the Navier-Stokes equations can also be parallelized, the nonlinear terms can make parallelism more difficult to manage, especially for models involving turbulent flows or irregular meshes. Therefore, LBM methods allow, at a lower computational cost, to capture complex phenomena. Recent work has shown that it is possible, with LBM, to reproduce the Nukiyama cooling curve (boiling in a vessel) and thus accurately calculate the critical heat flux. This flux corresponds to a mass boiling, known as the boiling crisis, which results in a sudden degradation of heat transfer.
The critical heat flux is a crucial issue for the Jules Horowitz Reactor, as experimental devices (DEX) are cooled by water in either natural or forced convection. Therefore, to ensure proper cooling of the DEX and the safety of the reactor, it is essential to ensure that, within the studied parameter range, the critical heat flux is not reached. It must therefore be determined with precision.
In the first part of the study, the student will define a lattice to apply LBM methods on an RJH device in natural convection. The student will then consolidate the results by comparing them with available data. Finally, exploratory calculations in forced convection (from laminar to turbulent flow) will be conducted.
Portable GPU-based parallel algorithms for nuclear fuel simulation on exascale supercomputers
In a context where the standards of high performance computing (HPC) keep evolving, the design of supercomputers includes always more frequently a growing number of accelerators or graphics processing units (GPUs) that provide the bulk of the computing power in most supercomputers. Due to their architectural departures from CPUs and still-evolving software environments, GPUs pose profound programming challenges. GPUs use massive fine-grained parallelism, and thus programmers must rewrite their algorithms and code in order to effectively utilize the compute power.
CEA has developed PLEIADES, a computing platform devoted to simulating nuclear fuel behavior, from its manufacture all the way to its exploitation in reactors and its storage. PLEIADES can count on an MPI distributed memory parallelization allowing simulations to run on several hundred cores and it meets the needs of CEA's partners EDF and Framatome. Porting PLEIADES to use the most recent computing infrastructures is nevertheless essential. In particular providing a flexible, portable and high-performance solution for simulations on supercomputers equipped with GPUs is of major interest in order to capture ever more complex physics on simulations involving ever larger computational domains.
Within such a context the present thesis aims at developing and evaluating different strategies for porting computational kernels to GPUs and at using dynamic load balancing methods tailored to current and upcoming GPU-based supercomputers. The candidate will rely on the tools developed at CEA such as the thermo-mechanical solver MFEM-MGIS [1,2] or MANTA [3]. The software solutions and parallel algorithms proposed with this thesis will eventually enable large 3D multi-physics modeling calculations of the behavior of fuel rods on supercomputers comprising thousands of computing cores and GPUs.
The candidate will work at the PLEIADES Fuel Scientific Computing Tools Development Laboratory (LDOP) of the department for fuel studies (DEC - IRESNE, CEA Cadarache). They will be brought to evolve in a multidisciplinary team composed of mathematicians, physicists, mechanicians and computer scientists. Ultimately, the contributions of the thesis aim at enriching the computing platform for nuclear fuel simulations PLEIADES.
References :[1] MFEM-MGIS - https://thelfer.github.io/mfem-mgis/[2]; Th. Helfer, G. Latu. « MFEM-MGIS-MFRONT, a HPC mini-application targeting nonlinear thermo-mechanical simulations of nuclear fuels at mesoscale ». IAEA Technical Meeting on the Development and Application of Open-Source Modelling and Simulation Tools for Nuclear Reactors, June 2022, https://conferences.iaea.org/event/247/contributions/20551/attachments/10969/16119/Abstract_Latu.docx, https://conferences.iaea.org/event/247/contributions/20551/attachments/10969/19938/Latu_G_ONCORE.pdf; [3] O. Jamond et al. «MANTA : un code HPC généraliste pour la simulation de problèmes complexes en mécanique », https://hal.science/hal-03688160
Study of the amorphous intermediate states during the precipitation of actinides oxalate
Growing energy needs and the climate emergency require a rapid transition to completely carbon-free energy, by mixing renewable energies and sustainable nuclear power. In this context, the precipitation of plutonium and uranium in the form of oxalate constitutes a key step in the industrial process of recycling spent fuel. A detailed understanding of the crystallization mechanisms of these oxalates thus constitutes a major challenge for better management of these operations.
However, it is now widely accepted that ions in solution assemble into crystals via a series of non-crystalline transient states, which fundamentally contradicts all classical nucleation theories used in precipitation models. In particular, we have demonstrated in recent years that rare earth oxalate crystals (Eu, Nd, Ce, Tb), some used to experimentally simulate the recycling of uranium and plutonium, form via liquid, reagent-rich nanodroplets which separate from the aqueous solvent. This behavior modifies the view hitherto retained for the precipitation of these oxalates and leads us to question the behavior of actinide oxalates.
The aim of this thesis is to confirm or refute that transient mineral droplets also form during the formation of uranium and plutonium oxalates, and to determine whether crystallization transients impact the precipitation models used to calibrate the recycling process of nuclear fuel. This study will not only impact precipitation processes used in recycling, but will also advance a fundamental question about long-debated “non-classical” crystallization.
Thermomechanical behaviour at high temperature of an irradiated nuclear ceramic
This thesis is part of the studies on pellet-cladding interactions in nuclear fuel rods used in NPP. The operator must ensure and demonstrate the integrity of rods in any situations. The mechanical stresses on the clad, the first safety barrier, are linked to the viscoplastic properties of the fuel. It is therefore necessary to know these behaviors and their evolution in operation.
The topic proposed will focuse on the characterization, in hot lab, of an irradiated fuel. One of the main difficulties is that the irradiated fuels in a reactor are multi-cracked, which makes their mechanical characterization particularly complex. However, an ongoing thesis (2022-25) has reached different steps: (i) the design of a specific thermomechanical testing machine, (ii) the partial qualification of this device, (iii) the implementation of tools and cracked sample extraction method, (iv) and a whole system model (digital twin).
The thesis will be the continuation of this work and will be built in four stages on three experimental platforms available at the CEA:
1. Getting the knowledge and improving existing digital and experimental tools,
2. Implementation of the device in hot-cell on an existing furnace,
3. Thermomechanical testing on irradiated fuel, a world first time in these conditions.
The tests will require dedicated post-processing based on simulation-experiments comparisons. Once the experimental base is sufficiently developed and interpreted, it will then be possible to confirm or revise the irradiated fuel behaviour laws. A link with the microstructure of materials could be addressed.
Throughout these stages, the PhD student will draw on skills and expertise of laboratories of the Fuel Research Department (IRESNE Institute, CEA Cadarache) and on a academic collaboration. This thesis also fits into the framework of the European project OPERA HPC and is a major issue.
The PhD student should have a strong taste for the experimental approach and some facilities for the use of digital tools. Knowledge of materials science is the minimum required. During the three years, the PhD student will improve his multiphysical skills in experimental device design and high-temperature material behavior, as well as in numerical simulation, which will facilitate his professional integration.
Bottom-up study of Ionic Transport in Unsaturated Hierarchical Nanoporous Materials : application to cement-based materials
Ion transport is critical in determining the durability of cement-based materials and, therefore, the extension of service life of concrete (infra)structures. Transport phenomena determine the containment capacity of concrete, which is crucial in the design and asset management of concrete infrastructures for energy production. Under most service conditions, concrete exists in unsaturated conditions. Anomalous transport has been associated with cement-based materials, and the reasons behind such deviations from the expected behavior of other porous materials may stem from nanoscale processes.
Research efforts have aimed to correlating material composition and microstructure to transport properties and durability. However, to date, the majority of predictive modeling of durability does not explicitly account for nanoscale processes, which are fundamental in determining transport properties. Recent advances have been made in quantifying the behavior of confined water in various phases present in cement systems. Calcium silicate hydrates (C-S-H) are the main hydrated phase in cement-based materials and present nanopores in the micro and mesopore range. The effects of desaturation remain however to be fully worked out. A fundamental understanding of transport processes requires a multiscale framework in which information from the molecular scale reverberates across other relevant scales (in particular, the mesoscale associated with C-S-H gel porosity (~nm), capillary porosity, and interfacial transition zone (~µm) up to the macroscopic scale of industrial application in cement-based materials).
The goal of this PhD work is to evaluate the ionic transport of chlorides, a critical species for the durability of concrete, under non-saturated conditions by combining small-scale simulations, multiscale modelling and experimentation in a bottom-up approach. The work will focus on the C-S-H. The project aims to characterize the effects of desaturation on the nanoscale processes driving transport of chlorides.
Modeling of complexation equilibria of actinides in nitric medium. Application to the PUREX process
The PAREX+ code is a major tool in the field of separation chemistry. It allows for the modelling and simulation of separation processes base on solvent extraction. In this code, the distribution of interest species between the aqueous and organic phases is calculated at every point in the process, both in steady and transitory states. The aim of this thesis is to improve this distribution model. To achieve this, a better understanding of the phenomena involved in the organic and aqueous phases is necessary, as well as a new approach to incorporate them into the model. This thesis thus combines experimental work and modeling. The student will join a supervisory team composed of experts in separation chemistry and modeling. His work will be valued through the publication of papers and participation in international conferences. At the end of this thesis, the student will have solid knowledge in the field of solvent extraction and its modeling, which he can leverage with industry or research organizations in the nuclear field or in other areas of separation chemistry (separation of rare earths or hydrometallurgy).
Thermo-chemo-mechanical modeling of sintering : effect of atmosphere and the differential densification on pellet shrinkage
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.
Innovative modeling for multiphysics simulations with uncertainty estimates applied to sodium-cooled fast reactors
Multiphysics modeling is crucial for nuclear reactor analysis, yet uncertainty propagation across different physical domains—such as thermal, mechanical, and neutronic behavior—remains underexplored due to its complexity. This PhD project aims to address this challenge by developing innovative methods for integrating uncertainty quantification into multiphysics models.
The key objective is to propose optimal modeling approaches tailored to different precision requirements. The project will explore advanced techniques such as reduced-order modeling and polynomial chaos expansion to identify which input parameters most significantly impact reactor system outputs. A key aspect of the research is the comparison between "high-fidelity" models, developed using the CEA reference simulation tools, and "best-estimate" models designed for industrial use. This comparative analysis will highlight how these errors propagate through different models and simulation approaches.
The models will be validated using experimental data from SEFOR, a sodium-cooled fast reactor. These experiments provide valuable benchmarks for testing multiphysics models in realistic reactor conditions. This research directly addresses the growing need for reliable, efficient modeling tools in the nuclear industry, aiming to improve reactor safety and performance.
The candidate will work in a dynamic environment at the CEA, benefiting from access to advanced simulation resources and opportunities for collaboration with other researchers and PhD students. The project offers the possibility of presenting results at national and international conferences, with strong career prospects in nuclear reactor design, safety analysis, and advanced simulation.
oxygen ordering in zirconium: mechanisms, kinetics and associated mechanical properties
The aim of this work is to study the properties of binary zirconium-oxygen (Zr-O) alloys, particularly in the context of nuclear applications. Traditionally, oxygen is considered to be in solid solution in the zirconium matrix, without the formation of ordered compounds such as Zr6O or Zr3O. However, recent studies suggest that at temperatures below 600°C, ordered compounds can form, affecting the solubility limit of oxygen. These compounds, observed after heat treatments, could modify the mechanical properties of Zr-O alloys, particularly at room temperature and up to 350°C. The proposed thesis seeks to understand these mechanisms through X-ray diffraction and electron microscopy experiments, in order to study the arrangement of oxygen, the thermal stability of the compounds and their impact on plastic deformation. The aim is to optimise the use of these alloys in nuclear reactors.
SIMULATION-BASED PREDICTION OF VIBRATION IN CENTRIFUGES
Rotating machinery is a critical piece of equipment in many industrial plants, and its operation is regularly accompanied by balancing problems that result in potentially dangerous vibrations for operators and equipment. The centrifugal decanter, for example, is sometimes subject to vibrations that force the operator to slow down the production rate. The nuclear environment in which this equipment operates makes it impossible to carry out the measurements and observations required for a purely experimental study. The aim is therefore to carry out modelling with limited data in order to gain a detailed understanding of the phenomena involved. The aim of this work is to combine Euler-Euler type CFD simulations of the mass distribution in the rotating bowl with mass-spring modelling of the mechanical connections in order to get closer to the vibration signals measured industrially. Such a numerical tool would be a valuable aid in investigating the various potential sources of mass imbalance without the need for experimental replication. Combined with deep learning methods, this type of model would also make it possible to build an unbalance predictor from short vibration signals, opening the door to active control of the decanter