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.
Digital reconstruction of an industrial tank for the improvement of real-time monitoring instrumentation
In the context of industrial digitalization and real-time monitoring, accessing 3D fields (velocity, viscosity, turbulence, concentration, etc.) in real time can be crucial, as local sensor networks are sometimes insufficient to provide a comprehensive view of the system's dynamics. This PhD project aims to investigate a methodology for the real-time reconstruction of fields within an instrumented industrial tank equipped with a mixing system. The proposed approach relies on finite element modeling of the relevant physics within the tank (e.g., fluid dynamics, thermal processes) and model reduction techniques such as physics-based Machine Learning (virtual sensor approach). A key focus of this thesis will also be the development of the tank instrumentation and its associated acquisition chain, both to validate the models and to generate a database for applying the proposed methodology.
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
Design and optimization of an innovative breeding blanket concept for a compact high heat flux nuclear fusion reactor
Skills:
Technical: heat transfer, structural mechanics, hydraulics, materials, numerical simulation
Non-technical: writing, interpersonal skills, English
Prerequisites: this thesis will be preceded by a 6-month internship. Contact the supervisor for more details about the topic.
Context:
This PhD focuses on the design and optimization of an innovative breeding blanket for compact nuclear fusion reactors. Nuclear fusion offers a promising solution to produce clean and sustainable energy. However, it requires the continuous production of tritium, a rare isotope, through breeding blankets surrounding the plasma. These blankets must also extract the generated heat. In compact reactors, technical constraints are increased due to extremely high heat fluxes and severe thermal and neutron conditions.
The PhD will take place within the Design, Calculations, and Realizations Office at CEA Saclay, a recognized player in the development of breeding blankets at the European level. This office has designed several concepts, such as HCLL (Helium Cooled Lithium Lead) and BCMS (Breeder and Coolant Molten Salt), two types of blankets based on helium or molten salt cooling systems.
PhD description:
The research program will take place over three years. The first year will focus on studying existing blankets, identifying the constraints of compact reactors, selecting appropriate materials and heat transfer fluids, and developing a preliminary design of the blanket. The following years will be dedicated to multiphysics modelling (thermal, mechanical, neutron), followed by iterative optimization of the concept to improve its performance.
Perspectives:
The results of this PhD will have a significant impact on the development of compact fusion reactors by ensuring tritium production and structural integrity. This work could also open new avenues for future research on even more advanced breeding blankets, contributing to the growth of sustainable and commercially viable fusion energy.
Understanding and Modeling Laser Cutting Mechanisms for Dismantling
For over 30 years, the Assembly Technologies Laboratory (LTA) at CEA Saclay has been conducting research to develop innovative tools for the dismantling of nuclear facilities, by designing laser cutting processes to work in hostile environments. This technology is suitable to cut thick materials, either in air or underwater, and has proven particularly effective for dismantling operations due to its precision and ability to limit aerosol generation. Today, this technology is considered safe and reliable, thanks to the efforts achieved through the European project "LD-SAFE".
However, technical challenges remain, particularly the management of residual laser energy, which, by propagating beyond the cut piece, can damage surrounding structures.
Initial studies, including a PhD thesis, have made it possible to develop numerical models to predict and control this energy, yielding significant advancements. Nevertheless, technological challenges remain, such as handling thicker materials (>10 mm), cutting multi-plate configurations, and considering the addition of oxygen to improve cutting efficiency.
The objective of the PhD is to address these challenges and to gain a better understanding of the laser cutting process and the propagation of residual laser energy. The doctoral student will refine the numerical model to predict its impact on background structures, particularly for thick materials and multi-plate configurations. The work will include the development of a multiphysics model, validated by experiments, with a particular focus on the effect of oxygen, the creation of simplified models, and adaptation for use by operators.
The PhD will be conducted in collaboration between the Assembly Technologies Laboratory (LTA) at CEA Saclay and the Dupuy de Lôme Research Institute (IRDL - UMR CNRS 6027) at the University of South Brittany (Lorient).
Measurement and evaluation of the energy dependence of delayed neutron data from 239Pu
This PhD proposal aims to measure and characterize the delayed neutron emissions from the fission of 239Pu. This actinide is involved in various reactor concepts, and the nuclear data available remains insufficient, particularly with fast neutrons. The project has a strong experimental focus, with multiple measurement campaigns at the MONNET electrostatic accelerator from JRC Geel, in which the candidate will actively participate.
The first phase focuses on the intercomparison of the neutron flux measurement methods (dosimetry, fission chamber, long-counter detector and recoil proton scintillator) which will be confronted to Monte-Carlo simulations of neutron emission from charged particle interactions (D+T, D+D, p+T). This work will ensure proper neutron flux characterization, a crucial step for the project.
Next, the candidate will replicate the delayed neutron measurements for ²³8U using an existing target in order to verify the results from a 2023 experimental campaign.
Finally, the candidate will measure the delayed neutron yields and group abundances for ²³?Pu in a neutron energy range from 1 to 8 MeV. The objective is to produce an energy-dependent evaluation, integrated into an ENDF file, to be tested on reactor calculations (beta-eff, power transients, absorber efficiency calibration, etc.). These measurements will complement a thermal spectrum study conducted at ILL in 2022, forming a coherent model for ²³?Pu from 0 to 8 MeV.
This project will contribute to the OECD/NEA's JEFF-4 nuclear data file, addressing a strong demand from the nuclear industry (highlighted by the IAEA) to improve the precision of multiplicity measurements and delayed neutron kinetic parameters, thus enhancing reactor safety and reducing safety margins.
Very high energy electrons radiotherapy with beams from a wakefield accelerator
Research objectives:
Use numerical modelling to optimize the properties of laser-plasma accelerators in the 50 MeV-200 MeV range for VHEE radiotherapy:
(i) optimize the properties of a laser-plasma accelerator (energy spread, divergence) with electron beams injected from a plasma-mirror injector using the WarpX and HiPACE++ codes.
(ii) Study the impact of such electron beams on DNA using Geant4DNA.
This numerical modelling will then be used to guide/design/interpret experiments of radiobiology on in-vitro biological samples that are planned at our in-house 100 TW laser facility at CEA during the project. This will be carried out in the context of research project FemtoDose funded by the French National Research Agency.
The researcher will benefit from a large variety of training available at CEA on HPC and computer programming as well as training at our industrial partners (ARM, Eviden) and Université Paris Saclay, which has MSc courses in radiobiology and also hosts a research centre (INanoTherad) dedicated to novel radiotherapy treatments, gathering physicists, radiobiologists and medical doctors. The activities will be carried out in the framework of the Marie Sklodowska Curie Action Doctoral Network EPACE (European compact accelerators, their applications, and entrepreneurship)
Numerical twin for the Flame Spray Pyrolysis process
Our ability to manufacture metal oxide nanoparticles (NPs) with well-defined composition, morphology and properties is a key to accessing new materials that can have a revolutionary technological impact, for example for photocatalysis or storage of energy. Among the different nanopowders production technologies, Flame Spray Pyrolysis (FSP) constitutes a promising option for the industrial synthesis of NPs. This synthesis route is based on the rapid evaporation of a solution - solvent plus precursors - atomized in the form of droplets in a pilot flame to obtain nanoparticles. Unfortunately, mastery of the FSP process is currently limited due to too much variability in operating conditions to explore for the multitude of target nanoparticles. In this context, the objective of this thesis is to develop the experimental and numerical framework required by the future deployment of artificial intelligence for the control of FSP systems. To do this, the different phenomena taking place in the synthesis flames during the formation of the nanoparticles will be simulated, in particular by means of fluid dynamics calculations. Ultimately, the creation of a digital twin of the process is expected, which will provide a predictive approach for the choice of the synthesis parameters to be used to arrive at the desired material. This will drastically reduce the number of experiments to be carried out and in consequence the time to develop new grades of materials
Simplified modelling of calcination in a rotating tube
As part of the reprocessing of uranium oxide spent fuel, the final high-level liquid waste is packaged in glass using a two-stage process, calcination followed by vitrification. Calcination gradually transforms the liquid waste into a dry residue, which is mixed with preformed glass in a melting furnace. The calciner consists of a rotating tube heated by a resistance furnace. The calcined solutions consist of nitric acid and compounds in their nitrate form or insolubles in the form of metal alloys. In order to improve control of the calciner, it is proposed to model it.
The modelling will consist of creating and then coupling three models:
- A thermodynamic model to represent the transformations undergone by the material. This part will almost certainly involve ATD and ATG measurements, coupled with a design of experiments type approach (1st year).
- A material flow model. The literature already contains very simplified principles for representing the flow in a rotating tube calciner, but we will have to be innovative, in particular by defining tests to characterise the flow of the material during the calcination process (2nd year).
A thermal model that will take into account exchanges between the furnace and the calciner tube as well as exchanges between the material and the tube. The exchange coefficients will have to be characterised (1st year).
Combining these three models (3rd year) will give rise to an initial simplified calcination model. This model will be used to help control the calcination stage and also to train operators to control this apparatus.
You will be working in the LDPV, a multidisciplinary team (process, chemistry, fluid mechanics, modelling, mechanics, induction) comprising 16 engineers and technicians. A team with 30 years' experience in vitrification processes, recognised both nationally and internationally.
Plasma Mirrors: towards extreme intensity light sources and high-quality compact electron
Research objectives:
expand the capabilities of the WarpX Partice-In-Cell code for lower cost-to-convergence using mesh refinement.
Devise a high-charge high quality injector for laser-plasma accelerators.
Determine feasibility of the proposed scheme on a 100-TW-class laser system.
The researcher will benefit from a large variety of training available at CEA on HPC and computer programming as well as training at our industrial partners (ARM, Eviden) and Université Paris Saclay. The activities will be carried out in the framework of the Marie Sklodowska Curie Action Doctoral Network EPACE (European compact accelerators, their applications, and entrepreneurship)