Assimilation of heterogeneous data in simulations of atmospheric dispersion of radionuclides at regional scale
Modeling and simulation provide essential knowledge on the aerial dispersion of gases and particles and the resulting environmental marking. This applies in particular to the releases that were generated by atmospheric nuclear tests carried out in the past by France in Polynesia. While regional-scale meteorological and dispersion calculations are reasonably reliable, their results have a degree of uncertainty and present discrepancies with heterogeneous measurements of activities or dose rates in the air, on the ground and in biological compartments. The thesis will aim to develop inversion methods, based on data assimilation, in order to reduce errors and uncertainties in simulations of regional dispersion of radionuclides. The application will concern certain nuclear tests in the atmosphere. However, the methods developed during the thesis, such as Monte Carlo sampling by Markov chains, will have a more general field of implementation. After a literature review on nuclear testing and data assimilation methods, original inverse modeling algorithms will be programmed, tested, and applied to the simulation of the dispersion of aerial releases from tests. This will allow us to estimate the anticipated important role of measurement assimilation in improving simulations.
Can we predict the weather or the climate?
According to everyone's experience, predicting the weather reliably for more than a few days seems an impossible task for our best weather agencies. Yet, we all know of examples of “weather sayings” that allow wise old persons to predict tomorrow’s weather without solving the equations of motion, and sometimes better than the official forecast. On a longer scale, climate model have been able to predict the variation of mean Earth temperature due to CO2 emission over a period of 50 year rather accurately.
In the late 50’ and 60’s, Lewis Fry Richardson, then Edward Lorenz set up the basis on the resolution of this puzzle, using observations, phenomenological arguments and low order models.
Present progress in mathematics, physics of turbulence, and observational data now allow to go beyond intuition, and test the validity of the butterfly effect in the atmosphere and climate. For this, we will use new theoretical and mathematical tools and new numerical simulations based on projection of equations of motion onto an exponential grid allowing to achieve realistic/geophysical values of parameters, at a moderate computational and storage cost.
The goal of this PhD is to implement the new tools on real observations of weather maps, to try and detect the butterfly effect on real data. On a longer time scale,, the goal will be to investigate the “statistical universality” hypothesis, to understand if and how the butterfly effect leads to universal statistics that can be used for climate predictions, and whether we can hope to build new “weather sayings” using machine learning, allowing to predict climate or weather without solving the equations.
Alteration mechanisms study of MOX spent fuel in the presence of cimentious bentonitic material (MREA). Experimental and modeling approaches
In France, the reference way remains the reprocessing of spent fuel and the recovery of certain materials such as uranium and plutonium through the elaboration of MOX fuels and its recycling. However, the direct storage of fuels (UOX and MOX) in deep geological repository is also being studied in order to ensure that French storage concepts (Cigéo) are suitable for spent fuels as requested and included in the National Plan for the Management of Radioactive Materials and Waste (PNGMDR). Therefore, it is essential to study the alteration mechanisms of the spent fuel matrices in the presence of environmental materials that are similar, on a laboratory scale, to the current storage concept of radioactive waste in deep geological disposal: HA cells dug in the Callovo-Oxfordian (COx) clay whose low-alloy steel liner is isolated from the clay by a cimentious bentonitic grout called MREA. There is various objectives : on the one hand, to determine the impact of the environment on the alteration mechanisms of the fuel matrix as well as on the radionuclides release, and on the other hand, to develop a geochemical model to account for the main physicochemical processes involved. These studies are carried out at the ATALANTE facility (DHA) of the CEA Marcoule, where leaching experiments and characterizations of MOX fuels are achievable. This work is performed as part of the COSTO project and is supported by Andra and EDF.
Development of a transport chemistry model for spent fuel in deep geological disposal under radiolysis of water
The direct storage of spent fuel (SF) represents a potential alternative to reprocessing as a means of managing nuclear waste. The direct storage of spent fuel in a deep geological environment presents a number of scientific challenges, primarily related to the necessity of developing a comprehensive understanding of the processes involved in the dissolution and release of radionuclides. The objective of this thesis is to develop a comprehensive scientific model that can accurately describe the intricate physico-chemical processes involved, such as the radiolysis of water and the interaction between irradiated fuel and its surrounding environment. The objective is to propose an accurate reactive transport model to enhance long-term predictions of storage performance. This thesis employs a back-and-forth process between modeling and experimentation, with the goal of refining the understanding of alteration mechanisms and validating hypotheses with experimental data. Based on existing models, such as the operational radiolytic model, the work will propose improvements to reduce the current simplifying assumptions. The candidate will contribute to major industrial and societal issues related to nuclear waste management and will help to provide solutions to the associated safety issues.