Mesoscopic simulations and development of simplified models for the mechanical behaviour of irradiated concrete
In nuclear power plants, the concrete biological shield serves as a support for the reactor vessel and as a protective shield against radiation. Over the long term, prolonged exposure to neutron radiation can cause the concrete aggregates to expand through amorphisation, leading to micro-cracking and degradation of its mechanical properties. This is an important issue in studies aimed at extending the life of power plants. At the mesoscale, these phenomena can be modelled by separating the behaviour of the aggregates, the cementitious matrix and the interfacial transition zones. However, it is difficult to describe the initiation and propagation of microcracks in such complex heterogeneous multi-cracked systems. The aim of this thesis, carried out as part of a Franco-Czech ANR project, is to develop a high-performance numerical simulation tool for analysing the effects of neutron irradiation on concrete at the mesoscopic scale. A coupled thermo-hydro-mechanical approach will be used in which the behaviour of the matrix will take into account shrinkage, creep and micro-cracking. The simulations will be validated using experimental data obtained on tested samples, and the numerical tool will then be used to estimate the impact of various factors on the behaviour and performance of concrete subjected to neutron irradiation.
This research project is aimed at a PhD student wishing to develop their skills in materials science, with a strong focus on multiphysical and multiscale modelling and numerical simulations.
Ultrasound-assisted decontamination of Hg-bearing solids
Mercury is one of the most dangerous pollutants. Yet, it has been widely used in the industry, in particular in electrolysers (chlor-alkali process), resulting in many contaminated facilities. Existing methods to stabilise or decontaminate are either energy-consuming or limited in terms of speciation. The aim here is to develop a new method combining leaching and ultrasonic irradiation, to decontaminate porous solids (e.g. mortar). The characterisation of solids and liquids before/after decontamination will be performed using SEM-EDX, XRD and XRF.
The PhD study will be performed in Marcoule centre, located 30 minutes from Avignon. The two host laboratories are the Laboratory of Supercritical Processes and Decontamination (DMRC/STDC/LPSD) and the Laboratory of Sonochemistry in Complex Fluids (ICSM//LSFC). Marcoule site is served by bus and hosts many PhDs and post-docs. The candidate should hold a master degree with a chemical engineering background and desirable skills in analytical chemistry and inorganic chemistry. The candidate will gain initial experience in the field of decontamination, which is one of the major problems associated with the circular energy economy. Depending on the focus of the thesis, they will be able to pursue a career in academia or industry.
Cohesive powder simulation: link between atomic and grain scale
Nuclear fuel is produced through a powder metallurgy process that involves several stages of the granular medium preparation (grinding, mixing, pressing and sintering). The powders used during these stages exhibit strong cohesion between the grains, making their flow behavior complex. Predicting powder behavior is a critical industrial challenge to quickly adapt to raw material changes, optimize product quality, and enhance production rates.
This thesis aims to establish a link between the properties of powders and their behavior during flow and pressing. Grain cohesion is a key factor that influences both the flow and densification of granular materials. This cohesion is governed by several interparticle forces, such as van der Waals forces, capillary interactions, and electrostatic forces. Understanding these interactions at the atomic scale is essential for accurately predicting and modeling powder behavior. The thesis seeks to address two central questions: How do the surface properties of grains at the atomic level influence the cohesive forces at the grain scale? And how can we scale up from the atomic level to the grain scale to simulate powders more realistically?
Multi-scale simulation approaches are crucial for bridging the gap between microscopic phenomena and the macroscopic behavior of granular materials. Current Discrete Element Method (DEM) simulations rarely incorporate fundamental interactions, such as van der Waals forces, electrostatic forces, and capillary effects, into their contact models. Recent research (1) (2) has explored the impact of cohesion using a simplified approach, treating it as an attractive force or cohesive energy. Simulation methods like Molecular Dynamics (MD) or Coarse-graining enable the modeling of material behavior at finer scales, based on these local structural and chemical properties. A deeper understanding of cohesion at small scales will enhance the predictive capabilities of DEM simulations and clarify the relationship between powder properties and their overall behavior.The main goal of this thesis is to better understand the relationships between atomic-scale interactions and grain-scale cohesion and to assess the consequences for simulations of powder pressing and flow.
The primary goal of this thesis is to make connections between the atomic-scale interactions and grain-scale cohesion and to simulate the powder flow and compaction processes.
One of the main challenges in this project is the development of DEM contact laws that incorporate complex atomic-scale interactions. This will require close collaboration between experts in atomic-level simulations and those working on DEM modeling. Additionally, validating these models through experimental comparisons is essential to ensure their accuracy and relevance for industrial applications.
The PhD candidate will be based at the IRESNE Institute (CEA-Cadarache) within the Laboratory of Numerical Methods and Physical Components on the PLEIADES platform, part of the Department of Fuel Studies. They will collaborate with the Fuel Behavior Modeling Laboratory and will have access to state-of-the-art modeling and simulation tools, as well as a collaborative environment with the Mechanics and Civil Engineering Laboratory at the University of Montpellier.
Bibliography
1. Sonzogni, Max. Modélisation du calandrage des électrodes Li-ion en tant que matériau granulaire cohésif : des propriétés des grains aux performances de l'électrode. s.l. : Thèse, 2023.
2. Tran, Trieu-Duy. Cohesive strength and bonding structure of agglomerates composed. 2023.
Study of the corrosion behaviour in NaCl-MgCl2-CeCl3 of a nickel-based alloy in the presence of fission products (Te, S) for molten salt reactor
Access to clean and affordable energy seems more crucial than ever in the current context of climate emergency. Several avenues have been explored for years, but many technological barriers remain to be overcome in order to realise them, as they represent significant technological breakthroughs. Whether it's for energy storage or 4th generation nuclear reactors, the molten salt medium used as a heat transfer fluid and/or fuel is highly corrosive, making the choice of structural materials very complex.
The objective of the proposed PhD project within the Service of Corrosion and Material Behaviour (S2CM) is the comprehensive study of the behaviour of promising nickel-based alloys in the NaCl-MgCl2-CeCl3 ternary system, representative of the salt used in the French molten salt reactor concept, at 600°C. By "comprehensive", this refers to everything from specimen preparation to the multi-scale and multi-technique characterisation of corrosion products. This topic has therefore a strong experimental character and focuses on understanding corrosion mechanisms. The influence of fission products, such as tellurium or sulphur, on corrosion mechanisms will be specifically studied.
Predicting thermodynamic properties of defects in medium-entropy alloys from the atomic scale through statistical learning
The properties and behaviour of materials under extreme conditions are essential for energy systems such as fission and fusion reactors. However, accurately predicting the properties of materials at high temperatures remains a challenge. Direct measurements of these properties are limited by experimental instrumentation, and atomic-scale simulations based on empirical force fields are often unreliable due to a lack of precision.This problem can be solved using statistical learning techniques, which have recently seen their use explode in materials science. Force fields constructed by machine learning achieve the degree of accuracy of {it ab initio} calculations; however, their implementation in sampling methods is limited by high computational costs, generally several orders of magnitude higher than those of traditional force fields. To overcome this limitation, two objectives will be pursued in this thesis: (i) to improve active statistical learning force fields by finding a better accuracy-efficiency trade-off and (ii) to create accelerated free energy and kinetic path sampling methods to facilitate the use of computationally expensive statistical learning force fields.
For the first objective, we improve the construction of statistical learning force fields by focusing on three key factors: the database, the local atomic environment descriptor and the regression model. For the second objective, we will implement a fast and robust Bayesian sampling scheme to estimate the anharmonic free energy, which is crucial for understanding the effects of temperature on crystalline solids, using an adaptive bias force method that significantly improves convergence speed and overall accuracy.We will apply the methods developed to the calculation of free energy and its derivatives, physical quantities that give access to the thermo-elastic properties of alloys and the thermodynamic properties of point defects. To do this, we will use algorithmic extensions that allow us to sample a specific metastable state and also the transition paths to other energy basins, and thus to estimate the free energies of formation and migration of vacancy defects. The thermodynamic quantities calculated will then be used as input data for kinetic Monte Carlo methods, which will make it possible to measure the diffusion coefficients in complex alloys as a function of temperature.
One aim will be to try to relate the atomic transport properties to the complexity of the alloy. Since our approach is considerably faster than standard methods, we will be able to apply it to complex alloys comprising the elements W, Ti, V, Mo and Ta at temperatures and compositions that have not been studied experimentally.
Oxide-clad joint and internal corrosion layer modelling in GERMINAL using experimental data provided by different characterisation techniques
This work will be done in the frame of studies on the thermo-mechanical and physico-chemical behaviour behaviour of the « uranium and plutonium mixed oxide fuel » during irradiation currently considered for the future reactors of 4th generation. Because of its particularly hight thermal level during irradiation this kind of fuel is subject to several physical and chemical phenomena duringf its stay in reactor. Those one can have a strong impact on the behaviour of the whole fuel element (pellet and clad), but we can focus on two specific phenomena that take place at middle and high burnup :
- the formation by evaporation-condensation of a fission products layer between the external surface of the fuel pellet and the inner surface of the cladding material at middle burnup, designed as JOG for Joint Oxyde-Gaine;
- the formation of a corrosion layer on the internal surface of the clad, containing fission products and elements constituting the cladding material at high burnup, and resulting from the FCCI (Fuel-Cladding Chemical Interaction),
The occurence of this two phenomena is a limiting factor for increasing the burnup. Thus it is important de be able to estimate quite precisely the chemical composition of the fuel pellet and of the fuel-to-clad gap during irradiation. Previous experimental work had shown that the JOG consisted mainly of caesium, molybdenum and oxygen, with the presence of other elements such as tellurium and barium. Observations have also shown the presence of chromium, iron and nickel, along with other volatile fission products (VFP), in areas of ROG. These observations were backed up by thermodynamic calculations, which led to the assumption that the JOG consisted mainly of caesium molybdate Cs2MoO4. However, until recently, there had been no direct evidence of the presence of this compound. Recently, more detailed characterisation methods carried out as part of a current thesis on (U,Pu)O2 fuel samples confirmed quantitatively that the JOG was mainly made up of Cs, Mo and O, but also of I and Ba distributed in several phases. Other elements were detected and measured in localised areas, namely Te, Zr as well as U and Pu. With regard to corrosion, phases based on Fe, Te and Pd were observed, as well as the joint presence of Cr and O.
At the same time, work was started on modelling the axial redistribution of caesium, with a view to improving the description currently used in GERMINAL. The chemical element inventory at a given axial dimension has a first-order effect on the calculated JOG thickness and ROG thickness.
The aim of this thesis is to improve the description and modelling of JOG and ROG formation in the GERMINAL scientific calculation tool (OCS), which is dedicated to calculating the thermo-mechanical and physico-chemical behaviour of 4th generation reactor fuel irradiated under nominal and/or incidental conditions.
To this end, research will be developed in three areas:
- Further development of the radial migration methodology adopted in the GERMINAL code through comparison with existing and recently obtained experimental results. This is based on a coupling with a thermochemistry module in which several hypotheses for the release of volatile fission products created in the pellet towards the pellet-cladding gap can be considered.
The aim of this PhD subject consists in improving the JOG and FCCI modeling into the fuel performance code (FPC) GERMINAL, dedicated to the calculation of the thermo-mechanical and physico-chemical behaviour of the 4th generation reactors’ fuel irradiated in normal and off-normal conditions. For that purpose, an acurrate experimental caractherization of some irradiated fuel samples, to which the PhD student will contribute, will be elaborated and coupled to a thermodynamic approach. The research will be based on the two items :
- Determination and experimental identification of the chemical elements and phases located into the fuel pellet, into the gap and at the fuel-to-clad interfaces at the end of the irradiation using the implementation of microprobe-SIMS-SEM/FIB techniques, by combining elemental and isotopic analysis results with microscopic observations.
- Comparison of the results with thermodynamic calculations: type and local quantities of the chemical phases formed in the fuel pellet as well as the phases constituting the JOG and those resulting from the FCCI.
Thus, based on those results, it will be possible to evaluate precisely the chemical composition of the irradiated fuel, of the JOG and of the corrosion compounds by using the FPC GERMINAL, from which the input inventory in chemical elements will be estimated in function of burnup at the different radial and axial localisations.
The PhD student will be attached both to a multi-scale modeling group and to an experimental team having sophisticated tools. Furthermore, academic or international collaborations are possible, in particular in the frame of the OECD/NEA with the development of the TAFID database. The student will have the opportunity to enhance the skills learned in the field of nuclear materials characterisation as well as in the field of thermodynamic calculations and irradiated fuel behaviour simulation.
To this end, the research will be developed along three lines:
- Further development of the radial migration methodology adopted in the GERMINAL code through comparison with existing and recently obtained experimental results. This is based on a coupling with a thermochemistry module in which several hypotheses for the release of volatile fission products created in the pellet towards the pellet-cladding gap can be considered.
- Further development of a [simplified] model for the axial redistribution of caesium and, by extension, of volatile fission products, leading to an initial implementation in the GERMINAL code for testing and preliminary validation of the axial inventories estimated by calculation by comparison with experimental results,
- Finally, thermodynamic calculations to determine the nature and local quantity of the chemical phases formed in the fuel pellet and the constituent phases of the JOG and ROG will be carried out on the basis of the axial inventories estimated by the GERMINAL code.
This will enable a more accurate assessment of the chemical composition of the irradiated fuel, the JOG and the ROG products as a function of the burn-up rate using the GERMINAL OCS as a function of time at the various radial and axial locations.
The PhD student will be integrated into the fuel behaviour study and simulation group(IRESNE Institute, CEA CAdarache) which has or is developing various simulation tools, and will also be able to interact with a characterisation laboratory with cutting-edge experimental tools. Academic and international collaborations are also possible, particularly within the OECD/NEA framework with the development of TAFID database. These will enable the PhD student to make the most of the skills he or she has acquired in the field of characterisation of nuclear materials, as well as in thermodynamic calculations and simulation of the physico-chemical behaviour of irradiated nuclear fuel.
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.
Nucleation, Growth, and Multi-Scale Structural Properties of Colloidal Nanoparticles of Actinide Oxides (Pu, U, Th)
Nanocrystalline oxides possess unique physicochemical properties, modulated by their size and local structure, making them promising for various technological applications. However, actinide oxide nanoparticles remain underexplored due to their radioactivity and toxicity. Nonetheless, studies dedicated to these species are growing, driven by environmental and industrial considerations, particularly for their involvement in current and future nuclear fuel cycles. This thesis focuses on plutonium, a key element in nuclear reactors. Its behavior in solution is complex, particularly due to hydrolysis reactions that lead to the formation of highly stable colloidal PuO2 nanoparticles. Although these species are now better described, the mechanisms leading to their formation remain largely unexplored.
The ambitious goal of this thesis is to uncover the fundamental mechanisms involved in the formation of these nanoparticles by adopting a systematic approach that combines a wide range of experimental parameters. These include the synthesis medium, temperature, reactant concentration, reaction time, and the contribution of sonochemistry. The focus will be on studying the nucleation and growth stages of these nanoparticles, as well as their structural properties in relation to the physicochemical conditions that influence their formation. Studies will be conducted at ICSM with Th, U, and Zr as analogs, and at the Atalante facility for Pu. In addition to standard laboratory techniques necessary for characterizing these systems, complementary experiments will be carried out on synchrotron lines (SOLEIL and ESRF) to thoroughly investigate the structural and reactive properties of these species and their precursors.
Superlattices for the characterization of diffusion under irradiation at the atomic scale
Metal alloys used in nuclear applications are subjected to relatively low temperatures (below 450°C) for long periods of time (more than 10 years). At these temperatures, the kinetics of the diffusion-controlled microstructure transformations are slow. The appearance of certain undesirable phases, likely to embrittle the material, can occur after several years of service. Therefore, diffusion coefficients play a crucial role as input data for modeling the evolution of these microstructures using phenomenological models. However, experimental determination of diffusion coefficients at low temperatures (T < 600°C) is extremely tricky, especially because of the need to characterize nanometric diffusion lengths, a difficulty made all the more difficult in the presence of irradiation.
With the development of chemical analysis by transmission electron microscopy (TEM) and atom probe tomography (APT), it is now possible to experimentally access very small diffusion lengths and thus determine low-temperature diffusion coefficients using superlattices, which consist of stacking nanometric layers of different chemical compositions. We can even characterize the effect of irradiation on diffusion by performing ion irradiations, enabling us to simulate the changes caused by neutron irradiation without activating the materials. The aim of this thesis is to develop a methodology and characterize diffusion under and outside irradiation in a ternary system of interest (Ni-Cr-Fe), representative of the steels and high-entropy considered in the nuclear industry.
This thesis is an opportunity to work with cutting-edge experimental techniques, in close collaboration with a team of theoretician in the same department, as well as with teams specializing in the development of superlattices at UTBM in Belfort and CINAM in Marseille.
Deterministic neutron calculation of soluble-boron-free PWR-SMR reactors based on Artificial Intelligence
In response to climate challenges, the quest for clean and reliable energy focuses on the development of small modular reactors using pressurized water (PW-SMR), with a power range of 50 to 1000 MWth. These reactors aimed at decarbonizing electricity and heat production in the coming decade. Compared to currently operating reactors, their smaller size can simplify design by eliminating the need for soluble boron in the primary circuit water. Consequently, control primarily relies on the level of insertion of control rods, which disturb the spatial power distribution when control rods are inserted, implying that power peaks and reactivity are more difficult to manage than in a standard PWR piloted with soluble boron. Accurately estimating these parameters poses significant challenges in neutron modeling, particularly regarding the effects of the history of control rod insertion on the isotopic evolution of the fuel. A thesis completed in 2022 explored these effects using an analytical neutron model, but limitations persist as neutron absorbers movements are not the only phenomena influencing the neutron spectrum. The proposed thesis seeks to develop an alternative method that enhances robustness and further reduces the calculation biases. A sensitivity analysis will be conducted to identify key parameters, enabling the creation of a meta-model using artificial intelligence to correct biases in existing models. This work, conducted in collaboration with IRSN and CEA, will provide expertise in reactor physics, numerical simulations, and machine learning.