Use and extension of the Alien solver library with the proto-application Helix
First, the post-doc candidate will have to integrate the solver Library Alien into Helix to carry out performance and usability assessments in iterative or direct solver configuration. These assessments will be done on different computer architecture from desktop computer to national supercomputer with thousands of cores.
In a second time, the candidate will deal with the possibility to add new functionalities in the Alien library to solve non-linear systems composed with equations and inequations to be able to solve, in an HPC context, mechanical problems like phase field problem or contact problems, problems often still opened in the community. The results will be compared to the classical test cases and benchmarks of the state of the art in the domain.
The candidate will join the Helix development team, formed by 3/4 developers for the moment in the laboratory LM2S (15 persons). A transversal program between CEA directions finances the post-doc and the candidate will collaborate with the Alien library developers at the DAM of CEA.
Modelling of valley winds by statistical downscaling
To model and monitor atmospheric emissions in an area with significant relief, it is essential to represent the winds at the scale of this relief. Cadarache's operational meteorological model only has a horizontal resolution of 1km, which does not allow it to resolve the orographic effects of the valley.
However, obtaining simulation results with a high resolution model requires calculation times that are still incompatible with the constraints of operational weather forecasting (6 hours of calculation on our servers for 1 hour of forecast for Cadarache in 2020). This constrains the horizontal resolution of the calculations and does not make it possible to resolve the orographic valley effects.
The object of the post-doc is therefore to develop a downscaling model applied to a 3D mesh of the valley, with a sufficient resolution to, at the same time, model the aerology of the valley and follow a pollution plume using an atmospheric dispersion model. It will be implemented through the use of an artificial neural network, the learning of which will be based on measurements of local climatology and aerology, supplemented by synthetic data using a local high-resolution model.
The candidate will work within a small, attentive and benevolent CEA team while remaining connected to university research via the Toulouse Aerology Laboratory. He will be able to both become a specialist in applied research in the meteorological field and acquire digital and scientific skills that can be used in business.
Optimization of energy transition scenarios through a dynamic Life Cycle Assessment approach
The modelling of the energy transition, with a projection until 2050 and adaptable to different countries or strategies, is complex in terms of LCA because it involves many parameters:
- a dozen possible energies, with evolutionary inventories of construction of electricity generation/storage infrastructure
- a difficulty to estimate the future of technologies for a given sector
- electricity generation in connexion with national consumption
- very contrasting scenarios, including more or less rapid increases in renewables and a decrease in nuclear power, offset or not by gas-fired combined cycle power plants
- a need to provide for several forms of electricity storage depending on the size of the unmanageable energy stock, with power levels depending on the storage time
- the correlation or not of storage power with the level of interconnection of European electricity networks.
The work will consist of analysing the inventories available in the Ecoinvent database linked to Simapro, modifying them according to the foreseeable technologies for the medium term, continuing modelling in Python language to include all the parameters.
The objective is to determine the best possible environmental trajectories for the French energy transition.
Modelling of uranium precipitation kinetics as a function of pH. Application to fluidized bed reactor
The Orano plant in Niger (Somaïr) precipitates its uranium concentrate in a fluidized bed reactor by adding sodium hydroxide. The concentrate obtained contains around 6% sodium which leads to converter penalties. Orano carried out tests at the end of 2019 on a fluidized bed in the laboratory to change the operating point of precipitation and preferentially form UO3 via a change in pH. To refine the management of the industrial unit, it is necessary to model the precipitation reactions of uranium. The candidate will have to propose and calibrate a competitive precipitation model for Na2U2O7 and UO3 based on the equilibrium constants and reaction kinetics, as a function of the pH within the reactor. In particular, the model should make it possible to understand the impact of pH on the distribution of the two main species identified in the concentrate: Na2U2O7 and UO3. This chemical model should serve as input to an existing physical model of the fluidized bed reactor. An extension of the model to other precipitation reagents, in particular magnesia, could also be studied.
Synthesis and structural analysis of reference uranium minerals for the identification of uranium-bearing phases in mining environment by TRLFS.
In the frame of the collaborative project between the ICSM , CEA and Orano, a study is conducted in order to detect and identify minerals containing uranium (VI) by Time-Resolved Laser Fluorescence Spectroscopy (TRLFS). This technique showed its efficiency in order to identify the presence of uranyl in natural assemblies through the probing of the local environment of uranium. However, it requires the establishment of a database from synthetic and natural samples fully characterized. Therefore, in order to achieve this goal, we intend to synthesis, and thoroughly characterize a variety of compounds containing uranyl groups within the crystal structure. We can cite the families of oxi-hydroxide, sulfate, and silicates based compounds. Then, TRLFS spectra will be collected in order to complete the database and to evidence the impact of the local structure of uranyl cation on the intensity and the position of the emission bands. The obtained data will be also compared to a collection of natural samples.
Dynamic monitoring by light scattering of mass transfer between two phases in multiphase flows
The understanding and the modeling of recycling processes studied at CEA, require the measurement of both local and average properties of multiphase flows involved in chemical engineering devices. Moreover, as the R&D studies are generally conducted on small-scale experiments, access to these quantities is often difficult, especially considering that measurement methods should not disturb the observed system. In this context, optical methods, associated to extensive and rigorous physical simulations of light/particles interactions, are particularly relevant and, accordingly under specific developments since several years. Therefore, the DMRC/LGCI (CEA Marcoule), in collaboration with the laboratory IUSTI (CNRS and Aix-Marseille University), develops two optical interferometric techniques suitable for R&D studies: the Digital In-line Holography (DIH) and the Rainbow Refractometry (RR). Previous works have shown that DIH allows a simultaneous measurement of 3D-positions, shape and size of flowing particles, even considering astigmatic geometries, while RR gives access to the size and refractive index of each particle or of set of particles, which considering linear optics is directly linked to their composition. This study aims to go further in multiphase flows characterization with these two technics by following three main objectives: 1) propose original solutions for the characterization of materiel compositions thanks to DIH, 2) deepen inverse methods in RR to allow the study of clouds of particles with variable compositions and to take into account gradients of concentration around a sessile drop, 3) evaluate the relevance of these technics for lab on chip systems.
Optical sensor development for in-situ and operando Li-ion battery monitoring
To improve the battery management system, it is required to have a better knowledge of the physical and chemical phenomena inside the cells. The next generation of cells will integrate sensors for deepest monitoring of the cell to improve the performances, safety, reliability and lifetime of the battery packs. The main challenge is thus to measure relevant physico-chemical parameters in the heart of the cell to get a direct access to the real state of the cell and thus to optimize its management. To address this challenge, a research project will start at CEA at the beginning of 2020 to develop innovative optical sensors for Li-ion battery monitoring. He / She will participate, in a first step, to the development of optical probes and their integration on optical fibres. The work will focus on the synthesis of a photo-chemical probe (nanoparticle and/or molecule) as active part of the sensor. Then, theses probes will be put on the optical fibre surface to form the sensor. The candidate will also participate to the realization of an optical bench dedicated to the testing of the sensors. In a second step, he / she will work on integrating the sensors into the Li-ion cells and test them in different conditions. The objective is to demonstrate the proof of concept: validation of the sensors efficiency to capture the behaviour of the cell and correlate it to electrochemical measurements.
Time-resolved in-situ study, by X-ray diffraction under synchrotron radiation, of structural evolutions in a high temperature oxidized zirconium alloys
In certain hypothetical accident situations in pressurized-water nuclear reactors (PWRs), the zirconium alloy cladding of fuel pallets, which constitutes the first barrier for the containment of radioactive products, can be exposed for a few minutes to water vapor. at high temperature (up to 1200 ° C), before being cooled and then quenched with water. The cladding material then undergoes numerous structural and metallurgical evolutions. In order to study these structural evolutions in a precise way, a first experiment campaign was carried out on the BM02 line of the ESRF on a prototype furnace allowing to perfectly control the atmosphere and the temperature. Two tasks will be entrusted to the candidate: continue and finish the analysis of the first experiment(phase fraction determination, residual constraints ...) and prepare a new complementary experimental proposal by mid 2020.
Strudy and processing of C/SiC composites
For different applications, we are looking for materials having superior mechanical properties at high temperature (1000 ° C or higher) and that are resistant to oxidation. The family of ceramic matrix composite materials (CMC), especially C / SiC, seems the most relevant to our needs. However, it is necessary to conduct studies to determine the most efficient solutions among the wide variety of fibrous architectures and possible matrix microstructures, while taking into account the constraints related to available processes and targeted geometries. This work will be conducted in collaboration with other CEA laboratories.
Data science for heterogeneous materials
In order to predict the functional properties of heterogeneous materials through numerical simulation, reliable data on the spatial arrangement and properties of the constitutive phases is needed. A variety of experimental tools is commonly used at the laboratory to characterize spatially the physical and chemical properties of materials, generating "hyperspectral" datasets. A path to progress towards an improved undestanding of phenomena is the combination of the various imaging techniques using the methods of data science. The objectives of this post-doc is to enrich material knowledge by developping tools to discover correlations in the datasets (for exemple between chemical composition and mechanical behavior), and to increase reliability and confidence in this data by combining techniques and physical constraints. These tools will be applied to datasets of interest regarding cementitious materials and corrosion product layers from archaeological artifacts.