Influence of delayed neutron precursors losses resulting from fission gas evacuation on molten salt reactors dynamics
Over the past twenty years, molten salt reactors (MSRs) have been the focus of renewed interest in the international nuclear community (national programs, start-ups, including one from the CEA). Modern MSR concepts feature a system for evacuating fission gases, which accumulate in the expansion tank. Some of these gases will consist of radionuclides that are delayed neutron precursors, which will therefore be lost for the fission chain reaction. This should further reduce the effective fraction of delayed neutrons in these reactors, already reduced by the circulation of the fuel salt outside the critical zone. The aim of this thesis is to assess the extent of this reduction, and its influence on reactor dynamics.
Such an assessment may involve numerical simulations that take into account 1) a differentiation of delayed neutron precursor groups into “liquid phase groups” and “gas phase groups”, and 2) two-phase flow models (where each type of group joins its corresponding phase). In order to differentiate the groups, we need to evaluate the “liquid” and “gas” fractions for each of them, based for example on the branching ratios of the nuclear evaluations and knowledge of the chemical elements joining each of the phases. Once this has been done, simulations can be carried out with the CATHARE “system” code (already able to use two-phase models) and the TRUST-NK “core” code (whose two-phase calculation functions may require further development) to assess the influence of precursor loss on reactor dynamics.
Methodology for studying the deployment of a fleet of innovative nuclear reactors driven by grid needs and constraints
Power grids are to a society what the blood system is to the human body: the providers of electrical energy essential to the daily life of all the organs of society. They are highly complex systems that have to ensure balance at all times between consumer demand and the power injected onto its lines, via mechanisms on different spatial and temporal scales.
The aim of this thesis is to develop a methodology for optimizing the deployment of innovative nuclear reactors in power grids, adapted to their specific needs and constraints. This approach should be applicable to a wide variety of grids, from island to continental scale, and to various levels of penetration and technologies of Variable Renewable Energies (VREs). Network constraints will need to reflect stability requirements in the short term (location and capacity of inertial reserves, participation in ancillary services), medium term (controllability and load following), and long term (seasonal availability and load factor of generation resources). Innovative nuclear reactors can be of any technology, and are characterized by macroscopic parameters such as load ramp-up/down kinetics, partial power levels, time before restart, cogeneration capacities, etc., as well as the technical and economic data required for dispatching. The aim is then to be able to draw up a profile (i.e. location, power, kinetics) of nuclear reactor fleets guaranteeing stabilized operation of power grids despite a high VREs penetration rate. Two main contributions are expected:
- Academic contribution: to propose an innovative methodology for optimizing the deployment of large-scale energy systems comprising innovative nuclear reactors, by integrating both the physics of power grids and their operational constraints;
- Industrial contribution: develop recommendations for the optimal deployment of innovative nuclear reactors in power systems incorporating VREs, taking into account aspects such as reactor power and inertia, location, reserve requirements for system services, load-following capability and availability.
The PhD student will be based in an innovative nuclear systems research unit. At the intersection of the study of nuclear reactor dynamics, power system physics and optimization, this energetics thesis will offer the PhD student the opportunity to develop in-depth knowledge of tomorrow's energy systems and the issues associated with them.
Impact of power histories on the decay heat of spent nuclear fuel
Decay heat is the energy released by the disintegration of radionuclides present in spent fuel. Precise knowledge of its average value and range of variations is important for the design and safety of spent fuel transport and storage systems. Since this information cannot be measured exhaustively, numerical simulation tools are used to estimate the nominal value of decay heat and quantify its variations due to uncertainties in nuclear data.
In this PhD, the aim is to quantify the variations in decay heat induced by reactor operating data, particularly power histories, which are the instantaneous power of fuel assemblies during their residence in the core. This task presents a particular challenge as the input data are no longer scalar quantities but time-dependent functions. Therefore, a surrogate model of the scientific computing tool will be developed to reduce computation time. The global modeling of the problem will be carried out within a Bayesian framework using model reduction approaches coupled with multifidelity methods. Bayesian inference will ultimately solve an inverse problem to quantify uncertainties induced by power histories.
The doctoral student will join the Nuclear Projects Laboratory of the IRESNE institute at CEA Cadarache. He/she will develop skills in neutron simulation, data science, and nuclear reactors. He/she will be given the opportunity to present his/her work to various audiences and publish it in peer-reviewed journals.
Low temperature selective epitaxial growth of SiGe(:B) for pMOS FD-SOI transistors
As silicon technologies for microelectronics continue to evolve, processes involved in device manufacturing need to be optimized. More specifically, epitaxy, a crystal growth technique, is being used to fabricate 10 nm technological node FD-SOI (Fully Depleted-Silicon On Insulator) transistors as part of CEA-Leti's NextGen project. Doped and undoped Si and SiGe semiconductor epitaxy is being developed to improve the devices' electrical performances. The thesis will focus on selective SiGe(:B) epitaxy for channels and source/drains of pMOS transistors. A comparison of SiGe and SiGe:B growth kinetics will be made between growth under H2, the commonly used carrier gas, and N2. Innovative cyclic deposition/etching (CDE) strategies will also be evaluated, with the aim of lowering process temperatures.
Impact of synthesis on the modeling of sodium storage mechanisms in hard carbon
Sodium-ion (Na-ion) batteries are attracting considerable interest as a credible alternative to the lithium-ion batteries widely used today. The abundance of sodium, together with the potential use of electrode materials without critical elements in their composition, has led to intensified research into Na-ion batteries. Hard carbon (HC) has been identified as the most suitable negative electrode for this technology. However, there is no consensus on the mechanisms for storing sodium in HC, because the many precursors and synthesis methods lead to singularly different HCs, which obviously do not function in the same way. A large database provides relationships between synthesis parameters (precursor, washing, pre-treatment, pyrolysis, grinding) and HC properties (porosity, structure, morphology, surface chemistry, defects), but it does not explain them. Consequently, the approach envisaged in this thesis is a multiphysics modeling of HC performance to understand the influence of precursor and synthesis method, exploiting the large existing characterization database.
Generation of Cesium silicate micro-particles from Fukushima
Microscopic in size, but large in environmental impact, cesium microparticles hold one of the keys to understanding the Fukushima nuclear accident. Following the Fukushima Daiichi accident, these cesium-rich silicate glass microparticles (CSMP) were discovered in the environment, carrying a significant portion of the radioactivity. Very poorly soluble in water, they differ from those observed at Chernobyl. A previous thesis demonstrated that these CSMPs could be the result of the interaction between corium and concrete during a severe accident, via small-scale experiments. The study made it possible to reproduce similar particles, made of amorphous silica with crystalline nano-inclusions. However, the results need to be refined, particularly with regard to the presence of zinc and calcium. The proposed thesis aims to explore the physicochemical mechanisms leading to the synthesis of these CSMPs. Laboratory experiments will recreate the corium-concrete interaction conditions, representative of Fukushima, in order to optimize the compositions and improve the modeling of the releases of these particles in current severe accident assessment tools.
Development of multiscale and multiview correlation techniques for monitoring large-scale dynamic tests
Experimental data obtained on large-scale specimens plays an important role in the study of structural integrity. Detailed interpretations of these tests require extensive instrumentation of the models. In addition to conventional data acquisition systems, digital image correlation (DIC) techniques can be used to measure displacement fields and extract quantities of interest (e.g. damage field). The aim of this thesis is to develop a multi-view, multi-scale digital image correlation (DI2M) technique for monitoring large-scale dynamic tests. We will focus on the behavior of reinforced concrete structures subjected to dynamic loading. The finite element model updating (FEMU) technique will be used to identify non-linear phenomena in the process zone around cracks. FEMU will be coupled with DI2M analyses, which can also be used to measure boundary conditions. The use of DI techniques to calculate acceleration fields will also be studied. A numerical framework will be proposed for performing modal analysis based on calculated fields. Ultimately, these tools could be integrated into a test/calculation dialogue procedure, providing precise information on the mechanical properties of structural elements and their evolution (e.g. damage) induced by seismic loading.
Analyzis and modelling of ions-catalyst-ionomer interactions in an AEM electrolyzer cell
CEA/Liten is a research organization on new energies. It offers a PhD on the production of green hydrogen by electrolysis of water using a new technology. The 3 types of water electrolysis to produce hydrogen from electricity are: high temperature electrolysis, low temperature alkaline electrolysis, low temperature PEM electrolysis (proton exchange membrane). All these types of electrolysis have their advantages and disadvantages. Very recently, a new type of electrolysis was born: low temperature electrolysis with AEM membrane (OH- anion exchange). It is a compromise between PEM and alkaline electrolysis to benefit from the advantages of these 2 technologies. First prototypes of such a device exist at the CEA and are studied at the cell or stack scale but the mechanisms involved in the electrochemical and chemical reactions at smaller scales within the electrodes are still poorly understood. In particular, the interactions (ion exchanges, ionic potentials) between the ionomer of the active layer, the membrane and the solution of water and diluted KOH are poorly understood. The objective of the thesis is 1/ to study these mechanisms and to quantify them by developing elementary experiments then, 2/ to model them and implement these models in an existing in-house electrolyzer code and finally 3/ to simulate polarization curves to validate all the models of the code including those developed by the doctoral student.
This thesis will span 2 laboratories: an experimental laboratory and a simulation laboratory in which the student will find all the skills necessary to achieve these objectives. This thesis is linked to several projects involving people from the CEA and other French university laboratories. The student will therefore be in a working environment where this theme is booming.
The candidate is required to have good knowledge of electrochemistry and polymer chemistry and to have notions of modeling and use of software such as Comsol.
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