Modeling the impact of defects in Steel–Concrete Structures. Identification of critical defects through metamodeling and optimization algorithms
To meet growing constructability challenges, steel–concrete (SC) structures are emerging as a promising alternative to conventional reinforced concrete structures. These elements are composed of infill concrete, two external steel plates, and steel shear studs that ensure composite action. While such structures present a clear interest due to their overall mechanical behavior, the presence of the steel plates prevents visual inspection of the concrete casting quality. It is therefore essential to characterize the impact of possible defects. This is the context of the proposed PhD research. Building upon recent results obtained in the laboratory, the goal is to develop a numerical framework to account for defects in steel–concrete structures. The thesis will be structured in several stages: validation of a modeling strategy for the mechanical behavior of defect-free SC structures, introduction of defects in the simulations and assessment of the applicability of the numerical approach, development of a metamodel and sensitivity analysis, and identification of critical defect configurations through optimization algorithms. One of the operational objectives of this doctoral work is to provide a tool capable of identifying critical defect configurations (size, position, and number) with respect to a given target quantity of interest (such as loss of strength or reduction in average stiffness). The research will therefore rely on the use and further development of state-of-the-art numerical tools in the fields of finite element modeling, optimization techniques, sensitivity analysis, and metamodeling. The thesis will be carried out within a rich collaborative environment, notably in partnership with EDF.
Integrated optical functions on microbolometer focal planes for uncooled infrared imaging
Thermal infrared imaging (wavelengths 8-14 µm) is a growing field, particularly in industry, transportation, and environment. It relies on a detection technology, microbolometers, for which CEA-Leti is at the forefront of the global state of the art. Integrating advanced optical functions directly onto the detectors is a very promising approach for improving performance, compactness, and cost in future infrared cameras.
The optical functions under consideration include spectral filtering, polarimetry, wavefront correction, and more. Some aim to enrich the image with information essential for applications such as absolute thermography (temperature and emissivity measurement), identification for automated scene interpretation (machine vision), gas detection, and others.
The proposed work will include the design, fabrication, and electro-optical characterization of functionalized microbolometer arrays. Using 3D electromagnetic simulation tools, the design of these optical functions will take into account the compatibility with our microbolometer technologies and the capabilities of our microfabrication facilities. Fabrication will take place in the CEA-Leti cleanrooms by dedicated personnel, but the candidate will participate in defining and monitoring the work. Finally, optical and electro-optical characterizations will be performed in our laboratory, if necessary with the development of dedicated characterization benches.
Effects of structural heterogeneities on air flow through reinforced concrete walls
The containment building represents the third barrier to confinement in nuclear power plants. Its role is to protect the environment in the event of a hypothetical accident by limiting releases to the outside. Its function is therefore closely linked to its tightness. Traditionally, the estimation of the leakage rate is based on a sound knowledge of transfer properties (such as permeability), combined with a chained (thermo-)hydro-mechanical simulation approach. While the mechanical behavior of the structure is now broadly well understood, progress is still needed in the comprehension and quantification of fluid flow. This is particularly true in the presence of heterogeneities (cracks, honeycombs, construction joints, reinforcements, cables, etc.), which represent situations that can locally disturb permeability. This is the context of the present PhD topic.
The work will consist, through a methodology combining experimental testing and numerical simulation, in improving the representation of fluid flow by explicitly accounting for the impact of heterogeneities. An initial analysis will define an experimental plan, which will then be carried out. The results will be analyzed in order to empirically characterize the influence of each type of heterogeneity tested on transfer properties. A simulation approach, exploiting the experimental findings, will then be developed using finite element and discrete methods. Finally, the applicability of the methodology to a real-scale structure will be assessed, while explicitly accounting for uncertainties regarding the presence and impact of such heterogeneities (probabilistic approach).The PhD will therefore rely on state-of-the-art experimental and numerical tools and methods, and will be conducted in a rich collaborative context (CEA, ASNR, EDF).
Hydrodynamic simulations of porous materials for ductile damage
The mechanical behavior of metallic materials under highly dynamical loading (schock) and especially their damage behavior is a topic of interest for the CEA-DAM. For tantalum, damage is ductile : by nucleation, growth and coalescence of voids within the material. Usual ductile damage models have been developed using the simplifying assumption that voids are isolated in the materials. However, recent studies by direct simulations explicitly describing a void population in the material (and experimental observations after failure) have shown the importance of void interaction for predicting ductile damage. Yet, the microscopical mechanisms of this interaction remain little known.
The objective of the PhD is to study the growth and coalescence phases of ductile damage through direct numerical simulations of a porous material undergoing dynamic loading. Hydrodynamic simulations, in which voids are explicitly meshed within a continuous matrix, will be used to study relevant scales of length and time. Monitoring the void population throughout the simulation will provide valuable information on the influence of void interaction during ductile damage. Firstly, the bulk behavior will be compared to the one predicted by usual models of isolated voids, showing the macroscopic effect of void interaction. Secondly, the evolution of the size distribution in the void population will be monitored. The last objective will be to understand microscopic void-to-void interaction. In order to take advantage of the wealth of simulation results, approaches based on artificial intelligence (neural networks on the graph associated with the pore population) will be used to learn the link between a void's neighborhood and its growth.
The doctoral student will have the opportunity to develop their skills in shock physics and mechanics, numerical simulations (with access to CEA-DAM supercomputers), and data science.
Modelling of Thermo-Fluid Phenomena in the Plasma Nozzle of the ELIPSE Process
The ELIPSE process (Elimination of Liquids by Plasma Under Water) is an innovative technology dedicated to the mineralization of organic effluents. It is based on the generation of a thermal plasma fully immersed in a water-filled reactor vessel, enabling extremely high temperatures and reactive conditions that promote the complete decomposition of organic compounds.
The proposed PhD research aims to develop a multiphysics numerical model describing the behavior of the process, particularly within the plasma nozzle, a key zone where the high-temperature gas jet from the torch interacts with the injected liquids.
The approach will rely on coupled thermo-aerodynamic modeling, integrating fluid dynamics, heat transfer, phase change phenomena, and turbulence effects. Using Computational Fluid Dynamics (CFD) tools, the study will characterize plasma–liquid interaction mechanisms and optimize the geometry and operating conditions of the process. This modeling will be compared and validated against complementary experimental data obtained from the ELIPSE setup, providing the necessary input for model calibration and validation.
This work will build upon previous research that has led to the development of thermal and hydraulic models of both the plasma torch and the reactor vessel. Integrating the new model within this framework will yield a comprehensive and coherent representation of the ELIPSE process. Such an approach represents a decisive step toward process optimization and industrial scale-up.
The ideal candidate will be a Master’s or final-year engineering student with a background in process engineering and/or numerical simulation, demonstrating a strong interest in physical modeling and computational approaches.
During this PhD, the candidate will develop and strengthen skills in multiphysics numerical modeling, advanced CFD simulation, and thermo-aerodynamic analysis of complex processes. They will also acquire solid experience in waste treatment, a rapidly expanding field with significant industrial and environmental relevance. These skills will provide strong career opportunities in applied research, process engineering, energy, and environmental sectors.
AI Enhanced MBSE framework for joint safety and security analysis of critical systems
Critical systems must simultaneously meet the requirements of both Safety (preventing unintentional failures that could lead to damage) and Security (protecting against malicious attacks). Traditionally, these two areas are treated separately, whereas they are interdependent: An attack (Security) can trigger a failure (Safety), and a functional flaw can be exploited as an attack vector.
MBSE approaches enable rigorous system modeling, but they don't always capture the explicit links between Safety [1] and Security [2]; risk analyses are manual, time-consuming and error-prone. The complexity of modern systems makes it necessary to automate the evaluation of Safety-Security trade-offs.
Joint safety/security MBSE modeling has been widely addressed in several research works such as [3], [4] and [5]. The scientific challenge of this thesis is to use AI to automate and improve the quality of analyses. What type of AI should we use for each analysis step? How can we detect conflicts between safety and security requirements? What are the criteria for assessing the contribution of AI to joint safety/security analysis?
CORTEX: Container Orchestration for Real-Time, Embedded/edge, miXed-critical applications
This PhD proposal will develop a container orchestration scheme for real-time applications, deployed on a continuum of heterogeneous computing resources in the embedded-edge-cloud space, with a specific focus on applications that require real-time guarantees.
Applications, from autonomous vehicles, environment monitoring, or industrial automation, applications traditionally require high predictability with real-time guarantees, but they increasingly ask for more runtime flexibility as well as a minimization of their overall environmental footprint.
For these applications, a novel adaptive runtime strategy is required that can optimize dynamically at runtime the deployment of software payloads on hardware nodes, with a mixed-critical objective that combines real-time guarantees with the minimization of the environmental footprint.
Simulation of flow in centrifugal extractors: the impact of viscous solvents on operation
Within the framework of nuclear spent fuel reprocessing, the CEA co-developed with ROUSSELET-ROBATEL liquid/liquid extraction (ELL) devices aimed at bringing two immiscible liquids into contact, one of which contains the valuable metals to be recovered and the other an extractant molecule. The multi-stage Centrifugal Extractor is one of the devices used to perform ELL at the La Hague plant. The future use of solvents potentially more viscous than current industrial standards may pose performance issues that need to be studied in advance in the laboratory to provide the necessary recommendations to restore the expected performance levels for the plant. The nuclear environment in which these devices operate makes in situ studies nearly impossible, thus depriving R&D of valuable information that is nevertheless essential for a deep understanding of the physicochemical mechanisms at the heart of the issues involved. To address this, the proposed study will rely on a numerical approach that will have been previously validated by comparison with either historical experimental data or data acquired from more recent ad hoc pilot systems. Thus, following a phase of literature review and capitalization of recent measurements, it is proposed to first create test cases that will be used to validate the numerical models. Based on this validation and in light of the knowledge acquired from previous theses concerning the effect of viscosity on flows, it is proposed to numerically explore the impact of an increase in solvent viscosity on centrifugal extractors. This will pave the way for a better understanding of the operation of the devices as well as operational or geometric improvements. The student will work at CEA Marcoule, in a research environment at the crossroads between a team of experimentalists and a team of numerical simulators. This experience will enable the student to acquire important skills in modeling liquid-liquid flows as well as solid knowledge on the development of liquid-liquid contactors.
Exploration and optimization of RAID architectures and virtualization technologies for high-performance data servers
Given the ever-increasing demands of numerical simulation, supercomputers
must constantly evolve to improve their performance and thus maintain a
high quality of service for users. These demands are reflected on storage
systems, which, to be performant, reliable, and capacitive, must contain
cutting-edge technologies concerning the optimization of data placement
and the scheduling of I/O accesses. The objective of this thesis is to
study these technologies such as GPU-based RAID and I/O virtualization,
to evaluate them, and to establish optimizations that can improve the
performance of HPC storage systems.
A theoretical framework for the task-based optimal design of Modular and Reconfigurable Serial Robots for rapid deployment
The innovations that gave rise to industrial robots date back to the sixties and seventies. They have enabled a massive deployment of industrial robots that transformed factory floors, at least in industrial sectors such as car manufacturing and other mass production lines.
However, such robots do not fit the requirements of other interesting applications that appeared and developed in fields such as in laboratory research, space robotics, medical robotics, automation in inspection and maintenance, agricultural robotics, service robotics and, of course, humanoids. A small number of these sectors have seen large-scale deployment and commercialization of robotic systems, with most others advancing slowly and incrementally to that goal.
This begs the following question: is it due to unsuitable hardware (insufficient physical capabilities to generate the required motions and forces); software capabilities (control systems, perception, decision support, learning, etc.); or a lack of new design paradigms capable to meet the needs of these applications (agile and scalable custom-design approaches)?
The unprecedented explosion of data science, machine learning and AI in all areas of science, technology and society may be seen as a compelling solution, and a radical transformation is taking shape (or is anticipated), with the promise of empowering the next generations of robots with AI (both predictive and generative). Therefore, research can tend to pay increasing attention to the software aspects (learning, decision support, coding etc.); perhaps to the detriment of more advanced physical capabilities (hardware) and new concepts (design paradigms). It is however clear that the cognitive aspects of robotics, including learning, control and decision support, are useful if and only if suitable physical embodiments are available to meet the needs of the various tasks that can be robotized, hence requiring adapted design methodologies and hardware.
The aim of this thesis is thus to focus on design paradigms and hardware, and in particular on the optimal design of rapidly-produced serial robots based on given families of standardized « modules » whose layout will be optimized according to the requirements of the tasks that cannot be performed by the industrial robots available on the market. The ambition is to answer the question of whether and how a paradigm shift may be possible for the design of robots, from being fixed-catalogue to rapidly available bespoke type.
The successful candidate will enrol at the « Ecole Doctorale Mathématiques, STIC » of Nantes Université (ED-MASTIC), and he or she will be hosted for three years in the CEA-LIST Interactive Robotics Unit under supervision of Dr Farzam Ranjbaran. Professors Yannick Aoustin (Nantes) and Clément Gosselin (Laval) will provide academic guidance and joint supervision for a successful completion of the thesis.
A follow-up to this thesis is strongly considered in the form of a one-year Post-Doctoral fellowship to which the candidate will be able to apply, upon successful completion of all the requirements of the PhD Degree. This Post-Doctoral fellowship will be hosted at the « Centre de recherche en robotique, vision et intelligence machine (CeRVIM) », Université Laval, Québec, Canada.