Building a new effective nuclear interaction model and propagating statistical errors
At the very heart of any « many-body » method used to describe the fundamental properties of an atomic nucleus, we find the effective nucleon-nucleon interaction. Such an interaction should be capable of taking into account the nuclear medium effects. In order to obtain it, one has to use a specific fitting protocol that takes into account a variety of nuclear observables such as radii, masses, the centroids of the giant resonances or the properties of the nuclear equation of state around the saturation density.
A well-known model of the strong interaction is the Gogny model. It is a linear combination of coupling constants and operators, plus a radial form factor of the Gaussian type [1]. The coupling constants are determined via a fitting protocol that typically uses the properties of spherical nuclei such as 40-48Ca, 56Ni, 120Sn and 208Pb.
The primary goal of this thesis is to develop a consistent fitting protocol for a generic Gogny interaction in order to access some basic statistical information, such as the covariance matrix and the uncertainties on the coupling constants, in order to be able to perform a full statistical error propagation on some selected nuclear observables calculated with such an interaction [2].
After having analysed the relations between the model parameters and identified their relative importance on how well observables are reproduced, the PhD candidate will explore the possibility of modifying some terms of the interaction itself such as the inclusion of a real three-body term or beyond mean-field effects.
The PhD candidate will work within a nuclear physics group at CEA/IRESNE Cadarache. The work will be done in close collaboration with CEA/DIF. Employment perspectives are in academic research and nuclear R&D labs.
[1] D. Davesne et al. "Infinite matter properties and zero-range limit of non-relativistic finite-range interactions." Annals of Physics 375 (2016): 288-312.
[2] T. Haverinen and M. Kortelainen. "Uncertainty propagation within the UNEDF models." Journal of Physics G: Nuclear and Particle Physics 44.4 (2017): 044008.
Online analysis of actinides surrogates in solution by LIBS and AI for nuclear fuel reprocessing processes
The construction of new nuclear reactors in the coming years will require an increase in fuel reprocessing capacity. This evolution requires scientific and technological developments to update process monitoring equipment. One of the parameters to be continuously monitored is the actinide content in solution, which is essential for process control and is currently measured using obsolete technologies. We therefore propose to develop LIBS (laser-induced breakdown spectroscopy) for this application, a technique well suited for quantitative online elemental analysis. As actinide spectra are particularly complex, we shall use multivariate data processing approaches, such as several artificial intelligence (AI) techniques, to extract quantitative information from LIBS data and characterize measurement uncertainty.
The aim of this thesis is therefore to evaluate the performance of online analysis of actinides in solution using LIBS and AI. In particular, we aim to improve the characterisation of uncertainties using machine learning techniques, in order to strongly reduce them and to meet the monitoring needs of the future reprocessing plant.
Experimental work will be carried out on non-radioactive actinide simulants, using a commercial LIBS equipment. The spectroscopic data will drive the data processing part of the thesis, and the determination of the uncertainty obtained by different quantification models.
The results obtained will enable publishing at least 2-3 articles in peer-reviewed journals, and even to file patents. The prospects of the thesis are to increase the maturity level of the method and instrumentation, and gradually move towards implementation on a pilot line representative of a reprocessing process.
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).
Microscopic nuclear structure models to study de-excitation process in nuclear fission
The FIFRELIN code is being developed at CEA/IRESNE Cadarache in order to provide a detailed description of the fission process and to calculate all relevant fission observables accurately. The code heavily resides on the detailed knowledge of the underlying structure of the nuclei involved in the post-fission de-excitation process. When possible, the code relies on nuclear structure databases such as RIPL-3 that provide valuable information on nuclear level schemes, branching ratios and other critical nuclear properties. Unfortunately, not all these quantities have been measured, nuclear models are therefore used instead.
The development of state-of-the-art nuclear models is the task of the newly-formed nuclear theory group at Cadarache, whose main expertise is the implementation of nuclear many-body solvers based on effective nucleon-nucleon interactions.
The goal of this thesis is to quantify the impact of the E1/M1 and E2/M2 strength functions on fission observables. Currently, this quantity is estimated using simple models such as the generalized Lorentzian. The doctoral student will be tasked with replacing these models by fully microscopic ones based on effective nucleon-nucleon interaction via QRPA-type techniques. A preliminary study shows that the use of macroscopic (generalized Lorentzian) or microscopic (QRPA) has a non-negligible impact on fission observables.
Professional perspectives for the student include academic research as well as theoretical and applied nuclear R&D.
Seismic analysis of the soil-foundation interface: physical and numerical modelling of global tilting and local detachment
Rocking foundations offer a potential mechanism for improving seismic performance by allowing controlled uplift and settlement, but uncertainties in soil-foundation interactions limit their widespread use. Current models require complex numerical simulations, which lack accurate representation of the soil-foundation interface.
The main objective of this thesis is to model the transition from local effects (friction, uplift) to the global response of the structure (rocking, sliding, and settlement) under seismic loads, using a combined experimental and numerical approach. Hence, ensure reliable numerical modeling of rocking structures. Key goals include:
• Investigating sensitivity of physical parameters in seismic response of rocking soil-structure systems using machine learning and numerical analysis.
• Developing and conducting both monotonic and dynamic experimental tests to measure the soil-foundation-structure responses in rocking condition.
• Implementing numerical simulations to account for local interaction effects and validate results with experimental results.
Finally, this research aims to propose a reliable experimental and numerical framework for enhancing seismic resilience in engineering design. This thesis will provide the student with practical engineering, along with expertise in laboratory tests and numerical modeling. The results will be published in international and national journals and presented at conferences, advancing research in the soil and structure dynamics field.
Validation of a Model-Free Data Driven Identification approach for ductile fracture behavior modeling
This research proposes a shift from traditional constitutive modeling to a Data-Driven Computational Mechanics (DDCM) framework which has been recently introduced [1]. Instead of relying on complex constitutive equations, this approach utilizes a database of strain-stress states to model material behavior. The algorithm minimizes the distance between calculated mechanical states and database entries, ensuring compliance with equilibrium and compatibility conditions. This new paradigm aims to overcome the uncertainties and empirical challenges associated with conventional methods.
As a corollary tool for simulations DDCM, Data-Driven Identification (DDI) has emerged as a powerful standalone method for identifying material stress responses [2, 3]. It operates with minimal assumptions about while being model-free, this making it particularly suitable for calibrating complex models commonly used in industry.
Key objectives of this research include adapting DDCM strategies for plasticity [4] and fracture [5], enhancing DDI for high-performance computing, and evaluating constitutive equations. The proposed methodology involves collecting full-field measurement maps from an heterogeneous test, utilizing High-Speed cameras and Digital Image Correlation. It will adapt DDCM for ductile fracture scenarios, implement a DDI solver in a high-performance computing framework, and conduct an assessment of a legacy constitutive model without uncertainties. The focus will be on 316L steel, a material widely used in nuclear engineering.
This thesis is the result of a collaboration between several labs at CEA ans Centrale Nantes which are prominent in computational and experimental mechanics, applied mathematics, software engineering and signal processing.
[1] Kirchdoerfer, Trenton, and Michael Ortiz. "Data-driven computational mechanics." Computer Methods in Applied Mechanics and Engineering 304 (2016): 81-101.
[2] Leygue, Adrien, et al. "Data-based derivation of material response." Computer Methods in Applied Mechanics and Engineering 331 (2018): 184-196.
[3] Dalémat, Marie, et al. "Measuring stress field without constitutive equation." Mechanics of Materials 136 (2019): 103087.
[4] Pham D. et al, Tangent space Data Driven framework for elasto-plastic material behaviors, Finite Elements in Analysis and Design, Volume 216, 2023, https://doi.org/10.1016/j.finel.2022.103895.
[5] P. Carrara, L. De Lorenzis, L. Stainier, M. Ortiz, Data-driven fracture mechanics, Computer Methods in Applied Mechanics and Engineering, Volume 372, 2020, https://doi.org/10.1016/j.cma.2020.113390.
Rheology of concentrated mineral-filled suspensions
As a research organization in the nuclear field and alternative energies, the CEA participates in fundamental studies involving dense suspensions. Inorganic particles (glass, zeolite, sludge, salts, or cement/sand) suspended in fluids, sometimes with very high viscosity like bitumen, are part of the systems under study for various applications. These include optimizing the filling of glass packages (Dem N' Melt process) or cement packages, where flow properties need to be optimized to ensure homogeneity of waste drums. Besides to addressing the recovery (historical sludges), treatment, and conditioning of waste in glass or bituminous matrices, concentrated suspensions of glass grains are being studied for high-temperature electrolysis production of dihydrogen.
In this optic, the research will initially focus on model concentrated suspensions, characterizing their flow properties under shear and compression. This latter type of mechanical test can trigger the appearance of frictional regimes, liquid/solid phase separation, and various non-linear responses that will need to be modeled. After this first stage, the topology, particle size distribution, and polydispersity of the solid particles will be varied to be as close as possible to the suspensions encountered in industry.
Activated conductive materials for energy conversion and energy storage through capacitive effect
Energy production from renewable sources requires efficient storage systems to address imbalances between supply and demand. This project aims to develop cost-effective supercapacitors using composite electrodes derived from industrial by-products. Mineral binders, such as geopolymers or Alkali Activated Materials (AAM), made conductive by dispersing carbon black, are being studied for energy storage or heat generation applications. Based on a recently filed patent, we propose a detailed study of these conductive composites. Their performance will be evaluated depending on formulation and shaping parameters. Additionally, the porous network and the dispersion of conductive charges in the material will be thoroughly characterized. Finally, material shaping tests will be conducted, and supercapacitors will be assembled to study the impact of the process (3D printing) and geometries.
Study of the synthesis and thermodynamic properties of the (An,Zr)O2 and (Zr,An)SiO4 compounds
In the event of a serious nuclear accident, the fuel in the reactor core may melt, resulting in the formation of a compound known as corium. Cases of major accidents and prototypical corium formation experiments have identified the formation of key compounds such as mixed oxides (U,Zr)O2 formed by interaction of the fuel with the zircaloy cladding and silicates (Zr,U)SiO4 formed by interaction of the corium with structural materials. In the case of MOx, (U,Pu)O2 fuels, corium formation could lead to the formation of equivalent phases with significant plutonium contents. However, experimental thermodynamic data on such compounds, which would enable their behaviour to be assessed, are currently non-existent. In this context, determining the conditions for synthesising such compounds with a good degree of purity is essential for acquiring such data. The synthesis of (Zr,Pu)O2 and (Zr,Pu)SiO4 solid solutions is therefore an essential first step before studying (Zr,U,Pu)O2 and (Zr,U,Pu)SiO4 systems.
The aim of this PhD thesis will be to determine the conditions suitable for the synthesis of these compounds, to carry out a series of characterisations enabling their purity to be assessed and their thermodynamic properties to be established. To achieve this, experiments will be carried out on the ATALANTE facility and a multi-technique characterisation approach will be chosen (XRD, Raman and infrared spectroscopies, SEM, synchrotron characterisation techniques, etc.). Solubility tests in a controlled environment will then be set up and calorimetric measurements carried out as part of international collaborations.
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.