Development of a Metal Supported Cell for Hydrogen production by High Temperature Steam Electrolysis
The development of Metal Supported Cells (MSC) for High Temperature Steam Electrolysis (HTSE) constitutes an interesting innovation able to reduce the degradation of this component under operation. An increase in the cell life time would be a valuable contribution to cost reduction and is able at positioning HTSE as an alternative process to other hydrogen production technologies. However, some progresses in the elaboration of MSCs are still required. Within the current process, functional ceramic layers of the MSC are joined to the metallic substrate at elevated temperature (> 1000 °C). Mismatch of the mechanical properties of the materials as well as the reducing conditions fixed by the metal substrate during sintering lead to MSCs having insufficient electrochemical performances. The post-doctorate aims, on the one hand, at obtaining a better understanding of the mechanisms that occur in the multilayer structure during sintering and, on the other hand, at proposing and testing technological solutions able to improve to reliability of MSC elaboration.
Development of numerical tools for the simulation of ultrasonic nondestructive inspection.
The CEA LIST develops the CIVA software platform (http://www-civa.cea.fr), in position of global leader for the simulation and expertise of non-destructive testing (ultrasonic and electromagnetic methods, radiography, X tomography). In the context of extending and improving capabilities of the CIVA platform, the post-doc fellow will contribute to the development of numerical methods for the ultrasonic testing (UT) simulation module.
The semi-analytical models of CIVA are based on physical simplifying hypotheses for the propagation of the ultrasonic beam and its interaction with defects. These methods provide efficient computational performances with accurate results in a wide range of realistic applications. However, configurations for which these models are not valid. The so called “numerical models” including finite element method (FEM), finite difference method (FDM) or boundary element method (BEM) enable to deal with these configurations without any simplifying hypotheses. However, the computation time is prohibitive in an industrial context, especially for 3D applications. The approach adopted in the CIVA platform consists in hybridizing semi analytical models with numerical ones in order to benefit of both the numerical efficiency of the former and the capability of simulating complex phenomena of the later.
The tasks associated to the post include the development of numerical methods themselves, in collaboration with academic partners, the integration in CIVA of a meshing solution enabling the data formatting for the numerical solving and specific developments for the coupling with semi analytical methods. Multi-boxes solutions, enabling for example the optimization of configurations with several defects or a coupling around the source and the defect, will be studied.
Compensation methods (for magnetic perturbation) for shape capture via orientation sensors
Our laboratory works for several years on shape capture (curves, surfaces) in static and moving positions, via inertial sensors - e.g. accelerometers ans magnetometers - able to provide information about their own orientation. In fact, in real conditions, sensors do not exactly provide their orientation, the measure is disturbed with external contributions (own motion acceleration, vibrations, magnetic perturbations). This work consists in analysing these disturbances, proposing preprocessing to clean data to obtain "denoised" tangential information to allow the reconstruction of these curves and surfaces.
First, we study the case of the reconstruction of a metallic pipe: we want to reconstruct a curve with magnetic sensors disturbed (the surface reconstruction will be explored afterwards). This work consists in finding the best methods allowing to extract the needed information from these "noised" signals (data fusion, source separation, model of perturbations, adding a new sensor modality,... are domains to explore). In this goal, a bibliographic study will be done firstly by the Post Doc student, then he will have to implement the different methods found, and test the performances with real signals acquired with our system of shape capture in a disturbed environment.
Model reduction in dynamics : application to earthquake engineering problems
The complexity and refinement of the numerical models used to predict the behavior of structures under seismic loading often impose computation times of several days for solving the partial differential equations of the reference problem.
Furthermore, in the context of optimization , model identification, or parametric and stochastic analyses, the aim is not to predict the response of a unique model but of a family of models.
To reduce the computation time, model reduction techniques (Proper Orthogonal/Generalized Decomposition) may be considered. This post-doctoral study proposes to define and implement (especially in the FE code CAST3M) a technique suitable for the reduction of reinforced concrete type models subjected to seismic loading.
Unsupervised Few-Shot Detection of Signal Anomalies
Our laboratory, located at Digiteo in CEA Saclay, is looking for a postdoc candidate working on the subject of anomaly detection in manufacturing processes, for a duration of 18 months starting from Feburary 2022. This postdoc is part of HIASCI (Hybridation des IA et de la Simulation pour le Contrôle Industriel), a CEA LIST project in an internal collaboration which aims at building a platform of AI methods and tools for manufacturing applications, ranging from quality control to process monitoring. Our laboratory contributes to HIASCI by developping efficient methods of anomaly detection in acoustic or vibrational signals, operating with small amounts of training data. In this context, the detection of signal anomalies (DSA) consists of extracting from data the information about the physical process of manufacturing, which is in general too complex to be fully understood. Moreover, real data of abnormal states are relatively scarce and often expensive to collect. For these reasons we privilege a data-driven approach under the framework of Few-Shot Learning (FSL).
Design of a high-energy phase contrast radiography chain
As part of hydrodynamic experiments carried out at CEA-DAM, the laboratory is seeking, using pulsed X-ray imaging, to radiograph thick objects (several tens of mm), made of low-density materials (around 1 g/cm3), inside which shock waves propagate at very high speeds (several thousand m/s). For this type of application, it is necessary to use energetic X-ray sources (beyond 100 keV). Conventional X-ray imaging, which provides contrast due to variations in absorption cross sections, proves insufficient to capture the small density variations expected during the passage of the shock wave. A theoretical study recently carried out in the laboratory showed that the complementary exploitation of the information contained in the X-ray phase should enable better detectability. The aim of the post-doctorate is to provide experimental proof of concept for this theoretical study. For greater ease of implementation, the work will mainly focus on the dimensioning of a static X-ray chain, where the target is stationary and the source emits continuous X-ray radiation. Firstly, the candidate will have to characterize in detail the spectrum of the selected X-ray source as well as the response of the associated detector. In a second step, he (she) will design and have manufactured interference gratings adapted to high-energy phase measurements, as well as a representative model of the future moving objects to be characterized. Finally, the student will carry out radiographic measurements and compare them with predictive simulations. The student should have a good knowledge of radiation-matter interaction and/or physical and geometric optics. Proficiency in object-oriented programming and/or the Python and C++ languages would be a plus.
Automatic driving of a finite element software based upon a domain decomposition strategy. Application to ultrasonic non-destructive testing.
One the most important field of activity at the DISC (Department of Imaging and Simulation for Control) of CEA - LIST is to provide a comprehensive set of tools for modeling and simulation for Non-Destructive Testing (NDT). These tools are gathered within the computational platform CIVA. Most of the ultrasound models -- elaborated by the LSMA (research laboratory for Simulation and Modeling in Acoustics) -- are based upon semi-analytical methods. Although very efficient, these methods suffer from a loss of precision as soon as some critical phenomena (e.g. head waves or caustics) or some particular features of the material (e.g. flaws or heterogeneities ) appear in the control experiment. To circumvent these limitations, one of the field of research in the LSMA is to build coupling schemes between semi-analytical and numerical methods. Following this strategy, a computational software based upon high-order finite elements combined with domain decomposition strategies is developped in order to address 3D configurations. The work proposed here focuses on increasing the complexity of the configurations reachable within this coupling strategy. A typical example being the fluid-structure interaction in the case of flaws reaching the bottom of the material to control.
Simulation of silicon solar cells based on n-type material : modelling and architecture optimisation.
INES is actually developping new fabrication technologies for n-type silicon solar cells. Working on simulation of photovoltaic solar cells enables the speed-up of the developement of new technologies: physical interpretation of characterisation results, support to device design, optimisation of processing steps and evaluation of original designs.
This subject open for post-doc position is focused on the study of semi-empirical models for materials and process steps for n-type solar cells. These basic road-blocks will be assembled in a complete model by using a multi-scale simulation tool. In the end, this global model will allow optimising of the p-type emitter geometrical structure, the efficiency of carrier collection on the back side or the geometry of metallisation for electrical contacts.
Multiscale Modeling of the Degradation Mechanisms in Polymer Electrolyte Fuel Cells
In an attempt to provide a rigorous physical-based description of the physicochemical phenomena occurring in the PEFC environments, the Modeling Group at CEA-Grenoble/LCPEM has developed a novel physical multi-scale theory of the PEFC electrodes electro-catalysis,the MEMEPhys model, based on a combined non-equilibrium thermodynamics/electrodynamics approach. This postdoctoral research position will consist on actively contributing on the development of the model, including the implementation of a physical-based description of water transport phenomena and water condensation in the PEFC. Heterogeneities on the electrochemical and aging processes, induced by water transport, will be in particular addressed. The candidate will strongly combine theoretical and experimental data, obtained in our laboratory, in order to establish MEA microstructure-performance relationships and to elucidate the main MEA degradation and failure mechanisms. From a fundamental point of view, this work will provide a deeper understanding of the electrochemical mechanisms responsible of the PEFC active layers aging at different spatiotemporal scales.
Global offshore wind turbines monitoring using low cost devices and simplified deployment methods
This project follows previous work focused on on-shore wind turbine instrumentation with inertial sensors networks whose dataflows allows the detection of vibration modes specific to the wind turbine components, in particular the mast and the real-time monitoring of these signals.
The objectives of this project are manyfolds: to bring this work to offshore wind turbines; search for signatures in wider frequency bands; study the behavior of offshore platforms and their anchorages.
One of the challenges is to find the signatures of rotating elements (blades) without direct instrumentation. Instrumentation of these elements is indeed more expensive and more impacting on the structure.
In addition, the sensor technology will be suitable for monitoring the fatigue life cycle of moving wire structures (dynamic electrical connection cable and anchoring) in the case of an off-shore wind turbine. The ultimate goal is to propose a global method for offshore wind turbine health monitoring.