Simulation of ultrasonic waves interaction phenomena with metal microstructure for imaging and characterisation purposes

The interaction of waves with matter is highly dependent on the frequency of these waves and the scale of their wavelengths in relation to the properties of the medium under consideration. In the context of ultrasound imaging applications, particularly concerning metals, the scales considered are generally on the order of a millimeter (ranging from a tenth to several tens of millimeters). However, depending on the manufacturing processes used, metallic materials, often anisotropic, can also have a microstructure with heterogeneities of similar dimensions. Consequently, ultrasonic waves propagating through metals may, under certain circumstances, be significantly influenced by their microstructures. This can either pose limitations to certain ultrasonic techniques (e.g., attenuation, structural noise) or provide an opportunity to estimate local properties of the inspected metal.
The general objective of the proposed thesis is to gain a deeper understanding of the link between microstructure and ultrasonic wave behaviour for large classes of material by benefiting from the combined knowledge of LEM3 for the generation of virtual microstructure and of the CEA for the simulation of ultrasonic wave propagation.
This work will combine the acquisition and analysis of experimental data (material and ultrasound), the use of simulation tools, and the statistical processing of data. This will enable an analysis of behaviors based on material classes, and possibly the implementation of inversion procedures to characterize a microstructure from a set of ultrasonic data. The combination of these methods will enable a holistic approach, contributing to significant advances in this field.

Virtual neutron scattering experiments from the moderation to the neutron detection.

The French neutron scattering community is proposing to build a new High-Current Accelerator-driven Neutron Source (HiCANS). Such a source would use a low-energy proton accelerator, a few tens of MeV, to produce thermal and cold neutrons and power an instrumental suite of around ten spectrometers. The aim of the thesis project is to build a multi-scale description of the operation of a neutron scattering spectrometer, ranging from the description of microscopic neutron moderation processes and neutron interactions with atomic structure and sample dynamics, to the propagation of neutrons through advanced optical elements and the production of background by secondary particles. The ultimate aim is to be able to carry out virtual neutron scattering experiments and accurately predict instruments performances on the future ICONE source.

Development of a numerical model of the POSEIDON irradiator for qualification in Co-60 radiosterilisation

CEA/Saclay research centre has several 60Co irradiation facilities dedicated to gamma irradiation for both CEA and industrials R&D needs in various fields such as electronuclear, defence, electronics, space as well as health applications.

In the more specific field of health, an irradiator is used to radiosterilise, i.e. to neutralise microbiological contaminants (such as bacteria, viruses, microbes, spores) using ionising radiation, for medical devices such as hip prostheses, orthopaedic screws or plates, on behalf of their suppliers. The great advantage of gamma radiation sterilization, compared with other sterilization alternatives (gas or cold immersion in liquid chemicals), is that medical devices do not have to be removed from their sealed pouches; they are processed directly through their packaging.

Radiosterilization of medical devices is a highly demanding process, in line with the requirements of ISO 13485 and ISO 11137. Firstly, the doses delivered must be neither too low, to ensure product sterility, nor too high, to avoid altering their integrity. Secondly, three qualification stages are required to guarantee validation of irradiation sterilization processes. The first two, known as installation and operational qualification, are respectively designed to demonstrate that the sterilization equipment has been installed in accordance with its specifications and is operating correctly, delivering appropriate doses within the limits of defined acceptance criteria. In particular, operational qualification consists in characterizing the irradiator in terms of dose distribution and reproducibility, by considering the volumes to be irradiated filled with a homogeneous material, with envelope densities representative of the products to be treated. Finally, the third qualification stage, known as performance qualification, must demonstrate, specifically for the medical products to be treated, that the equipment operates consistently, in accordance with predetermined criteria, and delivers doses within the specified dose range, thus producing a product that meets the specified requirement for sterility.

Depending on the supplier, irradiation packaging cartons are generally filled with a variety of different medical products, corresponding to a wide range of sizes and weights. The effects on spatial dose distribution of all possible product loading configurations should therefore be examined, including for different fill rates of the cartons on the irradiator's dynamic conveyor. Finally, it should be noted that the qualification processes must be repeated following any modification likely to affect dose or dose distribution, and therefore each time the sources are restocked. These processes are currently carried out exclusively by measurement, using a multitude of dosimeters appropriately distributed within and on the surface of the packages.

The Laboratoire des Rayonnements Appliqués (DRMP/SPC/LABRA), in charge of the POSEIDON gamma irradiator dedicated to the radiosterilization of medical equipment at CEA/Saclay would like to have a digital tool enabling these validation processes to be carried out by simulation. One of the major benefits expected from the use of this tool is to considerably reduce the downtime of the POSEIDON irradiator, imposed by the experimental validation phases.

The aim of the present thesis is to implement a numerical model of the POSEIDON irradiator, enabling the validation phases to be reproduced by simulation, as quickly as possible, while ensuring the accuracy of the results, to the desired precision. This work will be carried out at the DM2S/SERMA/CP2C laboratory (CEA/Saclay) with regular exchanges with the LABRA laboratory. CP2C is specialized, among other things, in radiation protection studies using numerical simulations.

Thus, the subject of the thesis, divided into three stages, will explore an alternative validation approach to that, carried out experimentally:

• The first stage will involve the development of a numerical model of the POSEIDON irradiator, integrating the dynamic nature of radiosterilization treatments. This numerical model will be based on a calculation methodology to be decided during the thesis (Monte-Carlo or deterministic method), with a compromise between the quality of the results obtained and the speed of calculation execution. For this stage, the radiation transport Monte Carlo code TRIPOLI-4® will be used as a reference, with comparisons made using other numerical tools such as MCNP®, PENELOPE, GEANT4, NARMER-1, etc.;

• The second stage will successively involve validation of the selected numerical model by comparison with experimental measurements, to be defined and carried out during the thesis, and its application to the calculation of operational qualification processes and performances for different families of supplier cartons. As regards validation of the calculations, the instrumentation used for gamma dose measurements will be numerically modelled and analysed, taking into account all the physical phenomena involved in absorbed dose (photon and electron doses). The aim is to consolidate calculation/measurement comparisons for experiments carried out during the thésis;

• The final step will be to analyze the contribution of the numerical model in relation to the experimental approach. This computational approach will nevertheless need to be optimized in terms of calculation time, in order to facilitate the sensitivity analyses to be carried out.

During the thesis, various directions of research will be investigated, such as improving the modelling of reflections during photon transport in a closed environment (PAGURE irradiator casemate; use of deep learning techniques for deterministic codes), implementing stochastic geometries to model the contents of the packaging to be irradiated, and improving algorithms to reduce computation times.

Stabilizer-universal graph states for robust quantum networks and quantum error correction

The last years have seen notable advances in quantum technologies, consolidating the development of basic requirements for the deployment of future quantum networks. Such networks are essential to distributed quantum information applications, and may serve various purposes, e.g., enabling the transmission of quantum states between physically distant parties, or improving the computational capabilities of quantum computers by combining multiple quantum processors. When only local operations and classical communication (LOCC) are allowed, the initial quantum state shared between the parties plays a key role, and may both enable specific applications, or provide the means to answer unsettled theoretical questions.
This PhD project aims at exploring k-stabilizer universal quantum states, that is, n-qubit quantum states that allow inducing any stabilizer state on any subset of k qubits, by using LOCC protocols only. Stabilizer states can be described, up to local unitaries, by the formalism of graph states, representing one of the most important classes of multipartite entanglement, and a powerful resource for many multipartite quantum protocols. The goal of the thesis is threefold. A first objective is to develop deterministic methods to construct k-stabilizer universal graph states on a number of qubits n quadratic in k (theoretical bound), thus improving the scalability and efficiency with respect to current state of the art. A second objective is to investigate the robustness of the derived protocol, for preparing a desired quantum stabilizer state on a subset of k qubits, to potential threats posed by malicious parties or qubit losses. Finally, the last objective of the thesis is to identify connections and implications between k-stabilizer universal graph states, robustness, and quantum error correction, as a way to devise new constructions of quantum error correcting codes of independent interest, or to increase the reliability of quantum networks.

Topology reconstruction of a ramified network by multisensor reflectometry

Smart Grids aim at monitoring and controlling electric power networks. Many parameters have to be monitored such as production and consumption units, and the integrity of the structure of the interconnection netwotk itself.

Smart grids aim at enhancing the quality of service while protecting people and infrastructures. In this area of research, most algorithms are deployed for taking the human out of the retroaction loops in order to maximize the availability and the reactivity. For that reason, artificial intelligence based algorithms are increasingly incorporated in decision loops.

In that industrial context, we are interested in methods that aim at estimating electrical network topologies. The topology of a network includes the length of the cable lines and their electrical properties, so as the characterictics of the loads that are connected to the networks (production and consumption units), and also potential faults in the network. In the end, the accurate estimation of the topology may be used to monitor the network with more accuracy with the help of a more accurate a priori information.

In order to characterize the topology, we propose to deploy either a single or a distributed set of electric reflectometers. These devices inject signals in the network under test and the study of the reflections gives information back which can be used to reveal the structure of the network. More precisely, every impedance discontinuity along the line wil cause partial reflections of the waves.

Previous works were conducted by our team of researchers on that topology reconstruction topic, by exploiting optimization algorithms coupled to a simulator. We would like to extend these works in two directions. First, we would like to explore a machine learning regressor-based approach in a mono sensor version. Second, we would like to estimate the topology by combining the measurements from multiple sensors, either with already available optimization-based approachs, or by the new machine learning-based approach.

Signal processing in cybersecurity: development of frequency tools for side-channel attacks and application to voice biometrics

Embedded cryptography on smartcards can be vulnerable to side-channel attacks, based on the interpretation of the information retrieved during the execution of the algorithm. This information leak is generally measured at the hardware level thanks to a consumption signal or electromagnetic radiation. Many methods, based mainly on statistical tools, exist to exploit these signals and to find secret elements.
However, the information used during this process is partial, because the current methods mainly exploit the signal in the time space. The signals being more and more complex, noisy and out of sync, and also very variable from one component to the other, the application of signal processing methods, in particular a time / frequency analysis, makes it possible to obtain additional information from the frequency space. The use of this information can lead to improved attacks. The state of the art presents several methods around side-channel attacks in frequency domain, but they are currently sparsely exploited.
As a first step, the PhD student will be able to use the existing signals and tools to become familiar with the side-channel attacks. He will then be able to rely on the existing literature around frequency attacks, in particular works of G. Destouet [1-2-3] which explore new techniques for filtering, compression, but also pattern detection for the purpose of optimal resynchronization, or for cutting signals in the context of so-called "horizontal" attacks.
These researches will be analyzed deeply and the Phd Student will be able to explore new techniques, for example new wavelet bases, and will test his algorithms on suitable signal bases.
Moreover, the "machine learning" method applied to side-channel attacks is currently studied, and the contribution of frequency data is also a way of improving the use of neural networks. The doctoral student will be able to rely on the different methods already existing in time and expand them thanks to wavelet transforms, in order to improve learning.
These different methods are applicable to signals analysis in voice biometrics. The Phd student will be able, among other things, to study neural networks using frequency data, adapted to audio signals obtained in biometrics, also using wavelets or so-called “cepstral” analysis.

At CEA-Leti Grenoble the student will be in a reference laboratory in the evaluation of high security devices(

[1] Gabriel Destouet Ondelettes pour le traitement des signaux compromettants. (Wavelets for side-channel analysis)
[2] Gabriel Destouet et al. Wavelet Scattering Transform and Ensemble Methods for Side-Channel Analysis". In : Constructive Side-Channel Analysis and Secure Design. Sous la dir. de Guido Marco Bertoni et Francesco Regazzoni. T. 12244. Series Title : Lecture Notes in Computer Science. Cham : Springer International Publishing, 2021, p. 71-89. isbn : 978-3-030-68772-4 978-3-030-68773-1. doi : 10 . 1007 / 978 - 3 - 030 -68773-1_4.
[3] Gabriel Destouet et al. Generalized Morse Wavelet Frame Estimation Applied to Side-Channel Analysis. ICFSP 2021: 52-57

Analysis, compensation and use of beam-squint for wideband mmWave/sub-Thz communications

The ever-increasing demand for data traffic pushes communication systems to upgrade, networks to densify and thus being more and more power-hungry. How to satisfy this need of high connectivity while limiting the carbon footprint of telecommunication systems?

To this end, the combination of the rise in frequency into the upper spectrum (mmWave/sub-Thz) and hybrid (analog/digital) MIMO architectures has emerged from recent research topics. However, with the rise in frequency and bandwidth enlargement, unwanted effect, such as beam squinting, appears and limits the performance of communication systems. Their characterisation and compensation is a trendy topic with a growing number of scientific publications.
The proposed thesis subject aims at first properly modelling to propose innovative compensation techniques. In a second time, we will investigate the possibilities to control side beams for tracking or sensing purposes. The proposed study is on the border between antenna design and digital signal processing. Pioneering antenna systems and innovative signal processing modules will be considered.

At Grenoble (France), we are about to join a dynamic “Telecom” team with a large set of competences ranging from propagation analysis, RF circuit and antenna design and modem/DSP specifications and optimisations. Beside, the thesis is 100% funded by “France 2030” and the national research program “PEPR-Réseaux du futur” which gives the ph.d students the chance to share and present their results to major French research laboratories. The position is available for autumn 2024.

Characterization methods for LMJ’s layered cryogenic targets

Inertial Fusion on the Laser Megajoule facilty requires to form a spherical DT layer at cryogenic temperature. A major topic of interest for fusion experiments is the characterization of the layer quality and thickness. The characterization will be done using two technics : optical shadowgraphy and X-ray phase contrast analysis. A cryostat developed by CEA is already available to work on future target designs and layer characterization.
The objectives of the PhD are to understand and model (theorically and numerically) the physics of the layer observation and to develop the characterization test bench in the cryostat’s environment and the image analysis for the 3D description of the layer.
The student will have to learn to use the cryostat, its command system and its simple actual characterization system. After a bibliography research, he will have to study the physics governing the characterization (multiple reflections, refractions, phase contrast, …) and develop the acquisition and image analysis system allowing the 3D description of the layer using images obtained during experiments with the cryostat. Lastly, the coupling between the command of the cryostat and the characterization will be developed. For all these developments, the student will have access to extensive bibliographical data and the expertise of the host team

Multiphysics coupling algorithms for black-box solvers in an HPC framework

This research work is proposed as part of the NumPEx (from French, Numerical Methods for Exascale) research priority program and equipment (PEPR). It belongs with the Exa-MA Project (Methods and Algorithms for Exascale) and is jointly proposed by researchers from CEA (IRESNE Institute, Cadarache center) and Inria (Bordeaux). It takes place in a work package dedicated to discretization methods and aims to build efficient numerical methods for solving Multiphysics problems, i.e., problems in which different physics interact.
Numerical simulation of phenomena involving different physics can be carried out using either a monolithic or partitioned approach.
The monolithic approach consists in representing the different physics by solving a single matrix system containing all the unknowns. This system is often ill-conditioned and requires adapted techniques to be solved. It is also important to note that the algebraic system to be solved is often very large, reaching or even exceeding the maximum capacity of current solvers.
The partitioned approach relies on efficient solvers already developed and adapted to each of the Physics considered separately. The difficulty then lies in coupling these different solvers to obtain the converged Multiphysics solution.
The aim of this thesis is to develop an efficient and generic numerical method for coupling different physics solvers used in black-box way. In addition, this approach needs to be scalable to Exascale.
The relevance and generalizability of the proposed approach will be verified on electromagnetic/acoustic/seismic and thermo-mechanical couplings. In addition, the efficiency of the numerical method will be compared with that of a monolithic resolution considered as a reference numerical approach, but including physical modeling that is often degraded. Experimental validations will also be possible.

HPC Parallel Integrodifferential Solver for Dislocation Dynamics

Context : Understanding the behavior of metals at high deformation rate [4] (between 104 and 108 s-1) is a huge scientific and technologic challenge. This irreversible (plastic) deformation is caused by linear defects in the crystal lattice : these are called dislocations, which interact via a long-range elastic field and contacts.
Nowadays, the behavior of metals at high deformation rate can only be studied experimentally by laser shocks. Thus, simulation is of paramount importance. Two approaches can be used : molecular dynamics and elastodynamics simulations. This thesis follows the second approache, based on our recent works [1, 2], thanks to which the first complete numerical simulations of the Peierls-Nabarro Equation (PND) [5] was performed. The latter equation describes phenomena at the scale of the dislocation.
PND is a nonlinear integrodifferential equation, with two main difficulties : the non-locality in time and space of the involved operators. We simulated it thanks to an efficient numerical strategy [1] based on [6]. Nevertheless, the current implementation is limited to one CPU –thus forbidding thorough investigations on large-scale systems and on long-term behaviors.

Thesis subject : There are two main objectives :
- Numerics. Based on the algorithmic method of [1], implement a HPC solver (High Performance Computing) for the PND equation, parallel in time and space, with distributed memory.
- Physics. Using the solver developped, investigate crucial points regarding the phenomenology of dislocations in dynamic regime. For exploiting the numerical results, advanced data-processing techniques will be employed, potentially enhanced by resorting to AI techniques.
Depending on the time remaining, the solver might be employed for investigating dynamic fractures [3].

Candidate profile : The proposed subject is multidisciplinary, between scientific computing, mechanics, and data-processing. The candidate shall have a solid background in scientific computing applied to Partial Differential Equations. Mastering C++ with OpenMP and MPI is recommended. Moreover, interest and knowledge in physics –especially continuum mechanics- will be a plus.
The PhD will take place at the CEA/DES/IRESNE/DEC in Cadarache (France), with regular journeys to Paris, for collaboration with CEA/DAM and CEA/DRF.

[1] Pellegrini, Josien, Shock-driven motion and self-organization of dislocations in the dynamical Peierls model, submitted.
[2] Josien, Etude mathématique et numérique de quelques modèles multi-échelles issus de la mécanique des matériaux. Thèse. (2018).
[3] Geubelle, Rice. J. of the Mech. and Phys. of Sol., 43(11), 1791-1824. (1995).
[4] Remington et coll., Metall. Mat. Trans. A 35, 2587 (2004).
[5] Pellegrini, Phys. Rev. B, 81, 2, 024101, (2010).
[6] Lubich & Schädle. SIAM J. on Sci. Comp. 24(1), 161-182. (2002).