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.
Influence of battery system disassemblability on their environmental impacts
With the rise of electric mobility and Energy storage, the demand for batteries is rapidely increasing. But this growth raises a crucial question: how can we design batteries that are both high-performing, durable, and more environmentaly friendly ?
Without focusing on cell Chemistry, one promising approach lies in disassembly-oriented designs: making battery packs easier to disassemble could facilitate their repair, reuse, or recycling. However, a more easily dismantled design may also increase its mass or reduce the system's reliability, potentially affecting its overall lifetime.
This PhD aims to tackle this challenge by developing an analytical method to link the design of dismountable battery systems with their actual environmental impacts, while explicitly accounting for reliability aspects.
The PhD candidate will assess the ease of disassembly of different battery systems, quantify the environmental gains and losses compared to conventional designs, and help develop a decision-support tool to guide design choices. The proposed research will involve, among other tasks, Life Cycle Assessment (LCA) modelling coupled with battery performance and ageing models, as well as failure probabilities analysis.
This project takes place in a technological context driven by the growing need for resource circularity, the automation of disassembly processes, and the implementation of new European regulations on batteries. If offers a unique opportunity to contribute to the design of the next generation of sustainable battery systems.
Simulation of flow in centrifugal extractors: the impact of viscous solvents on operation
Within the framework of nuclear spent fuel reprocessing, the CEA co-developed with ROUSSELET-ROBATEL liquid/liquid extraction (ELL) devices aimed at bringing two immiscible liquids into contact, one of which contains the valuable metals to be recovered and the other an extractant molecule. The multi-stage Centrifugal Extractor is one of the devices used to perform ELL at the La Hague plant. The future use of solvents potentially more viscous than current industrial standards may pose performance issues that need to be studied in advance in the laboratory to provide the necessary recommendations to restore the expected performance levels for the plant. The nuclear environment in which these devices operate makes in situ studies nearly impossible, thus depriving R&D of valuable information that is nevertheless essential for a deep understanding of the physicochemical mechanisms at the heart of the issues involved. To address this, the proposed study will rely on a numerical approach that will have been previously validated by comparison with either historical experimental data or data acquired from more recent ad hoc pilot systems. Thus, following a phase of literature review and capitalization of recent measurements, it is proposed to first create test cases that will be used to validate the numerical models. Based on this validation and in light of the knowledge acquired from previous theses concerning the effect of viscosity on flows, it is proposed to numerically explore the impact of an increase in solvent viscosity on centrifugal extractors. This will pave the way for a better understanding of the operation of the devices as well as operational or geometric improvements. The student will work at CEA Marcoule, in a research environment at the crossroads between a team of experimentalists and a team of numerical simulators. This experience will enable the student to acquire important skills in modeling liquid-liquid flows as well as solid knowledge on the development of liquid-liquid contactors.
Investigation of geopolymer durbility for radioactive wastewater treatment
The reprocessing of spent nuclear fuel generates radioactive effluents that require appropriate treatment. To meet industrial and regulatory challenges, the CEA is developing geopolymer-based adsorbent materials that are robust, cost-effective, and efficient for capturing Cs-137 and Sr-90. Their performance can be enhanced through the incorporation of selective adsorbents (such as zeolites) and through innovative shaping processes (3D printing, beads, foams) optimized for column adsorption.
The durability of these materials remains a critical issue, as their leaching and ageing mechanisms in column systems are still poorly understood. This PhD project will focus on studying these phenomena in order to assess the impact of effluent chemistry on the stability and efficiency of geopolymers. The work will include material synthesis, batch and column sorption tests, and the use of modelling tools to interpret alteration mechanisms. The scientific challenge is to identify the key physicochemical markers of geopolymer degradation in the targeted liquid effluents and to link them with column sorption performance.
The PhD candidate will join the Laboratory for Supercritical Processes and Decontamination (LPSD), renowned for its expertise in column-based ion extraction and adsorbent characterization. He/she will collaborate with specialists at CEA Marcoule and with the laboratory teams, and will regularly present project progress to the industrial partner. Upon completion of the PhD, the candidate will have developed recognized expertise at the interface of materials science, chemistry, and column adsorption processes. This work will open a wide range of opportunities: R&D positions in the nuclear sector, waste management, and functional materials; academic pathways (postdoctoral research, academia, teaching); or contributions to major energy and environmental challenges.
Control & optimization of fuel cell temperature
Proton exchange membrane fuel cells (PEMFC) represent a key technology for the development of clean and sustainable energy systems, particularly for heavy-duty transport applications where their energy density is very attractive. However, in order to represent a viable industrial alternative, a number of obstacles still need to be overcome, including operating costs and, above all, the durability of the systems under real-world conditions. Among the levers for action, optimizing operating conditions is a promising avenue for limiting the degradation phenomena occurring within the cell. The operating temperature is a particularly key parameter because it affects all aspects of the system, from the kinetics of degradation mechanisms to the thermal capacity that the system can dissipate, including the water balance within the fuel cell. Despite the influence of this parameter on durability, it is generally only optimized at the system level to achieve the best performance, the shortest possible response time and to limit the size of the thermal management system.
The aim of this thesis is to work on optimizing the temperature management of a fuel cell within a system, taking into account not only performance but also sustainability criteria. To do this, the impact of operating temperature on degradation mechanisms will be analyzed using various simulation tools already available at LITEN and the teams' fifteen years of experience in studying PEMFC fuel cell degradation. Various thermal architectures will be proposed and evaluated in conjunction with the work on temperature control optimization. The latter will be implemented on a real fuel cell system in order to demonstrate the relevance of the proposed solution using concrete experimental data.
Innovative techniques for evaluating critical steps and limiting factors for batteries formation
The battery manufacturing sector in Europe is currently experiencing strong growth. The electrical formation step that follows battery assembly and precedes delivery has received little academic attention, despite being crucial for battery performance (lifespan, internal resistance, defects, etc.). It is an essential time-consuming and costly step in the process (>30% of the cell manufacturing cost, and 25% of the equipment cost in a Gigafactory) that would greatly benefit from optimization.
In this thesis, we propose studying battery formation using innovative, complementary, operando non-intrusive techniques. The goal is to identify the limiting mechanisms of the electrolyte impregnation step (filling electrode pores) and of the initial charge. The candidate will implement experimental methods to monitor and analyze these mechanisms. He will also establish a methodology and protocols for studying these steps, combining electrochemical measurements with non-intrusive physical characterizations under operating conditions. The research will focus on optimizing formation time and quality control during this stage.
From angstroms to microns: a nuclear fuel microstructure evolution model whose parameters are calculated at the atomic scale
Controlling the behavior of fission gases in nuclear fuel (uranium oxide) is an important industrial issue, as fission gas release or precipitation limit the use of fuels at extended burn-ups. The gas behavior is strongly influenced by the material’s microstructure evolution due to the aggregation of irradiation-induced defects (gas bubbles, dislocation loops and lines). Cluster dynamics (CD) (a kind of rate theory model) is relevant for modelling the nucleation/growth of the defect clusters, there gas content and the gas release. The current model has been parameterized following a multiscale approach, based on atomistic calculations (ab initio or empirical potentials). This model has been successfully applied to annealing experiments of UO2 samples implanted with rare gas atoms and has emphasized the impact of the irradiation damage on gas release. The aim of this PhD thesis is now to improve the model, particularly the damage parameterization, and to extend its validation domain through in depth comparison of simulation with a large set of recently obtained experimental results, such as gas release measurement by annealing of sample implanted in ion beam accelerator, bubble and loop observation by transmission electrons microscopy of implanted or in-pile irradiated samples. This global analysis will finally yield an improved parameterization of the CD model.
The research subject combines a “theoretical” dimension (improving the model) with an “experimental” one (interpreting existing experiments or designing some new ones). The variety of techniques will introduce you into the experimental world and thus broaden your scientific skills. You will be welcomed at the Fuel Behavior Modeling Laboratory (part of the Institute for Research on Nuclear Systems for Low-Carbon Energy Production, IRESNE, CEA Cadarache), where you will benefit from an open environment rich in academic collaborations. You also have to manage collaborations for the experiments analysis, for the model development and for the specification of additional atomistic calculations. You will be at the interface of atomistic techniques, large-scale simulation and various experimental techniques. Therefore, You will develop a broad view of irradiation effects in materials and of multi-scale modelling in solids in general.
This project is an opportunity to contribute to the overall development of numerical physics applied to multi-scale modeling of materials, occupying a pivotal position and adopting a global viewpoint. This will allow experiencing yourself the way computed fundamental microscopic data finally helps solving complex practical issues.
Further readings:
Skorek et al. (2012). Modelling Fission Gas Bubble Distribution in UO2. Defect and Diffusion Forum, 323–325, 209.
Bertolus et al. (2015). Linking atomic and mesoscopic scales for the modelling of the transport properties of uranium dioxide under irradiation. Journal of Nuclear Materials, 462, 475–495.
Study of the behaviour of mixed oxide fuels with degrade isotopy at the beginning of life.
France has decided to adopt a 'closed' nuclear fuel cycle. This involves processing spent fuel to recover valuable materials such as uranium and plutonium, while other compounds such as fission products and minor actinides constitute final waste. UO2 fuel irradiated in pressurised water reactors (PWRs) is currently reprocessed to produce plutonium (PuO2), which is then reused in the form of mixed oxide (MOX) fuel. This fuel is then irradiated in PWRs, a process known as plutonium monorecycling. The CEA is currently studying the multi-recycling of materials using fuels containing Pu from the processing of spent MOX assemblies. However, this multi-recycled plutonium contains a higher proportion of highly alpha-active isotopes (Pu238, Pu240 and Pu241/Am241), resulting in more severe alpha self-irradiation than current MOX fuels experience [1]. This exacerbates certain physical phenomena [2-5], such as fuel swelling due to helium precipitation and the creation of crystal defects and decreased thermal conductivity [6-8], which can alter its behaviour in the reactor.
The proposed thesis will study the impact of these phenomena on the behaviour of MOX fuels at the beginning of the irradiation, using a combination of experimentation and modelling. Heat treatments will be employed to analyse the mechanisms of crystal defect healing and helium behaviour. Various experimental techniques will be employed to characterise the structure and microstructure (X-ray diffraction, scanning electron microscopy (SEM), Raman spectroscopy and microprobe analysis), defect densities (transmission electron microscopy (TEM)), helium release (KEMS), thermal gradient reproduction (CLASH laser) and thermal conductivity (LAF laser). The results will inform simulations modelling the microstructure and thermal properties.
This cross-disciplinary study will improve our understanding of the phenomena involved in the initial power-up of fuels damaged by alpha self-irradiation, particularly the impact of helium produced by decay.
You will be based at the Multi-Fuel Design and Irradiation Laboratory (LECIM) within the Research Institute for Nuclear Systems for Low-Carbon Energy Production at CEA/Cadarache. For the experimental part of the project, you will collaborate with the Chemical Analysis and Materials Characterisation Laboratory (LMAT) at CEA/Marcoule and the European Research Centre (JRC) in Karlsruhe. You will have the opportunity to publish your results through scientific publications and conference presentations. This role offers the chance to develop your expertise in a variety of techniques that can be applied across multiple fields of materials science and engineering.
[1]O. Kahraman, thésis, 2023.[2]M. Kato et al., J Nucl Mater, 393 (2009) 134–140.[3]L. Cognini et al., Nuclear Engineering and Design 340 (2018) 240–244.[4] T. Wiss et al., Journal of Materials Research 30 (2015) 1544–1554.[5]D. Staicu et al., J Nucl Mater 397 (2010) 8–18.[6] T. Wiss et al.,Front. Nucl. Eng. 4 (2025) 1495360.[7]E.P. Wigner, J. Appl. Phys. 17 (1946) 857–863.[8]D. Staicu et al., Nuclear Materials and Energy 3–4 (2015) 6–11.
Parallel simulation and adaptive mesh refinement for 3D solids mechanics problems
The challenge of this PhD thesis is to implement adaptive mesh refinement methods for non-linear 3D solids mechanics adapted to parallel computers.
This research topic is proposed as part of the NumPEx (Digital for Exascale) Priority Research Programs and Equipment (PEPR). It is part of the Exa-MA (Methods and Algorithms for Exascale) Targeted Project. The PhD will take place at CEA Cadarache, within the Institute for Research on Nuclear Energy Systems for Low-Carbon Energy Production (IRESNE), as part of the PLEIADES software platform development team, which specializes in fuel behavior simulation and multi-scale numerical methods.
In finite element simulation, adaptive mesh refinement (AMR) has become an essential tool for performing accurate calculations with a controlled number of unknowns. The phenomena to be taken into account, particularly in solids mechanics, are often complex and non-linear: contact between deformable solids, viscoplastic behaviour, cracking, etc. Furthermore, these phenomena require intrinsically 3D modelling. Thus, the number of unknowns to be taken into account requires the use of parallel solvers. One of the current computational challenges is therefore to combine adaptive mesh refinement methods and nonlinear solid mechanics for deployment on parallel computers.
The first research topic of this PhD thesis concerns the development of a local mesh refinement method (of block-structured type) for non-linear mechanics, with dynamic mesh adaptation. We will therefore focus on projection operators to obtain an accurate dynamic AMR solution during the evolution of refined areas.
The other area of research will focus on the effective treatment of contact between deformable solids in a parallel environment. This will involve extending previous work, which was limited to matching contact meshes, to the case of arbitrary contact geometries (node-to-surface algorithm).
The preferred development environment will be the MFEM tool. Finite element management and dynamic re-evaluation of adaptive meshes require assessing (and probably improving) the efficiency of the data structures involved. Large 3D calculations will be performed on national supercomputers using thousands of computing cores.
his will ensure that the solutions implemented can be scaled up to tens of thousands of cores.
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.