On the fluid distribution for liquid thermocline - From experimental work to reduction of models
The proposed doctoral research builds upon the PhD work of Alexis Ferré and the postdoctoral research of Martin Rudkiewicz, which focused on the modeling and characterization of liquid thermocline thermal energy storage systems. These studies led to the development and validation of a comprehensive physical model implemented in ANSYS Fluent, enabling detailed investigation of the physical phenomena governing the formation and subsequent transport of the thermocline within a storage tank.
A partially validated CFD numerical model, together with a fully operational experimental facility, will therefore constitute the foundation of this PhD project. The main objectives are:
To further advance the experimental characterization of liquid thermocline storage behavior, with particular emphasis on the influence of flow distribution (including distributor type and design parameters), thermal cycling, and initial conditions on storage performance;
To validate the CFD physical model against newly acquired experimental data;
To reduce the high-fidelity CFD model to a comprehensive system-level model incorporating the distributor, the storage tank, and the extraction process;
To provide the scientific and industrial communities with currently unavailable datasets that are essential for model validation under varied and realistic operating conditions.
Heat Transfer Enhancement by Convective Boiling in Microchannels applied to the Cooling of Computing Units in Data Centers
The proposed PhD thesis aims to improve the understanding and modeling of convective boiling phenomena in microchannels for new low-environmental-impact refrigerants. The candidate will adopt a combined experimental and multi-scale modeling approach, including the design of a test bench simulating the behavior of a micro-evaporator, the implementation of CFD simulations (ANSYS Fluent, CATHARE) to describe two-phase flow regimes, and the evaluation of various eco-friendly alternative fluids. The expected outcomes include, for each of these new fluids, the characterization of confined boiling mechanisms, the development of a predictive heat transfer model, and the proposal of innovative cooling solutions.
The growing demand for high-performance computing, driven by artificial intelligence and cloud technologies, leads to a significant increase in power dissipation in electronic chips. Current single-phase cooling technologies are reaching their limits when dealing with heat fluxes exceeding 100 W/cm². Two-phase cooling, based on fluid boiling to remove heat, can achieve much higher heat transfer performance than single-phase systems while reducing overall energy consumption. The results of this research will contribute to the development of more efficient and sustainable cooling solutions for future data centers, helping to reduce the digital sector’s energy footprint and strengthen European technological sovereignty in advanced cooling technologies.
Development of Machine Learning algorithm to optimize the control of absorption machines
The Thermal and Solar Technologies Laboratory (L2TS) and the Energy Systems for Territories Laboratory (LSET), located at the CEA LITEN site in Le Bourget-de-Lac, are offering a cross-disciplinary PhD thesis combining thermodynamics and optimization using Artificial Intelligence.
Specifically, this doctoral research project involves developing a machine learning algorithm to optimize the control of absorption machines. These machines are thermodynamic cycles able to produce heat or cold from an intermediate heat input; thus, offering potential valorization of industrial waste heat or renewable energies, such as solar thermal. Heat exchange is made possible by the absorption and desorption reactions of a gaseous refrigerant in a fluid. Specifically, the NH3-H2O mixture will be used. The dynamic operation of these cycles is extremely complex because the operational variables, physical parameters, and hydrodynamic aspects are highly intertwined. Thus, the use of a neural network is particularly relevant for establishing an adaptive control strategy for these machines.
The thesis will have a theoretical aspect, involving the study and selection of the most suitable algorithm to address the problem, and an experimental aspect of validation on a prototype absorption machine. The project will also involve the design of a controller for implementation.
The thesis will take place in a CEA laboratory in Bourget du Lac.
Mechanical degradation of Solid Oxide Cells: impact of operating and failure modes on the performances
Solid oxide cells (SOCs) are electrochemical devices operating at high temperature that can directly convert fuel into electricity (fuel cell mode – SOFC) or electricity into fuel (electrolysis mode – SOEC). In recent years, the interest on SOCs has grown significantly thanks to their wide range of technological applications that could offer innovative solutions for the transition toward a renewable energy market. However, despite of all their advantages, the large-scale industrialization of this technology is still hindered by the durability of SOCs. Indeed, the SOCs remain limited by various degradation phenomena including mechanical damage in the electrodes. For instance, the formation of micro-cracks in the so-called ‘hydrogen’ electrode is a major source of degradation. However, the precise mechanism and the full impact of the micro-cracks on the electrode performances are still unknown. By a multi-physic modelling approach, it is proposed in this thesis (i) to simulate the damage in the microstructure of the electrode and (ii) to calculate its impact on the loss of performances. Once the model validated on dedicated experiments, a sensitivity analysis will be conducted to provide relevant guidelines for the manufacturing of improved robust and performant electrodes.
Thermodynamic and experimental approach of the reactivity in multi-constituted Silicon-Metal-Carbon systems for ceramic brazing
The development of ceramic-based material assemblies plays a fundamental role in technological innovation in many engineering fields. The choice of materials and joining process must ensure a functional, reliable and durable assembly, whose properties comply with the specifications of the application.
The PhD thesis is part of the development of brazing alloys optimized for the joining of ceramics (primarily silicon carbide) considered for various applications in harsh environments, particularly in the field of energy. Indeed, the design of these materials requires a good knowledge of the reactivity at the liquid alloy / ceramic interface. In this context, the thesis will contribute to the development of a thermodynamic and experimental approach to predict and understand the reactivity in multi-constituted Si-Metal-Carbon systems. This work includes a study of the wetting and interfacial reactivity of selected alloys (wetting and brazing experiments, fine characterization of the interfaces by different techniques such as FEG-SEM, X-ray diffraction, TEM, XPS) with the support of thermodynamic modelling using the CALPHAD method. This highly experimental work will be carried out in a dynamic and collaborative environment.