Aqueous alteration of nuclear glass in its disposal environment
Exploitation, characterization and modeling of so-called "integral" experiments of glass alteration intended for the confinement of nuclear waste (SON68 and AVM4) in the presence of iron, cementitious material and argillite from the Bure site in two geometrical configurations: one simulating a disposal cell, the other intimately mixing the materials present. These tests were launched on behalf of ANDRA between 2017 and 2018 and their characterization started in the past two years.
Study of the decontaminating melting of end-of-life nuclear fuel claddings
Currently, in France, UOx fuel cladding is made of zirconium and tin or niobium based alloys. At the end of the use of nuclear fuels in the reactor, the fuel claddings contaminated with actinides (An), fission products (FP) and activation products (AP) are stored awaiting their storage in a geological site.
It is planned to decontaminate these claddings, once the spent fuel has been removed, to make them less radioactive, with the aim of decategorizing them.
Studies on radioactive sheaths have shown that the use of a fluoride-based slag allows decontamination of An and FP towards the slag. The scientific obstacle lies in the decontamination in AP, and more precisely in the preliminary stage of Zr/Nb separation.
In addition, the management of fluoride slags should be avoided due to the strong tendency of fluorine to corrosion. The use of oxide slags would be an alternative way to be privileged, constituting the second challenge of this research project.
The objectives of the post-doctorate will initially be to formulate slags. Then, Zr alloy decontamination, Zr/Nb separation and separation of activation products will be studied.
The experiments developed, in a non-radioactive laboratory, will be based on a literature review carried out by the post-doc and on the results of thermodynamic calculations performed at the LM2T of CEA Saclay.
The missions of the post-doc will be to develop slags according to the operating conditions that he/she will have defined (composition, temperature), to characterize them using physico-chemical analyzes (SEM/EDS, XRD, TDA/TGA) and to test them, in the presence of duct sections, for decontaminating melting. The post-mortem analysis will allow to assess their decontamination capacity and to optimize, if necessary, the interactions at the interfaces and/or their chemical composition.
Experimental and technological developments of a process for the mineralization of organic liquid waste by plasma
The ELIPSE process developed at the CEA allows the destruction of organic liquids by injection into a high-power plasma.
If the feasibility of destroying different organic components at flow rates of a few liters per hour has now been demonstrated, tests must now be further developed for reference organic liquids appropriately chosen according to existing deposits.
These studies, based on the characterization data of the chosen LORs, will aim to provide detailed process results obtained with the most representative operating conditions, to allow a complete and quantitative evaluation of the process. This will make it possible to establish operating, robustness and endurance data for the process.
This work will include the study of the behavior of radioelements in the process, which will be essential for the nuclearization study: this will involve studying the physico-chemical behavior of actinides during their processing via the use of inactive simulants.
Role of metal containers on the alteration of high-level waste confinement glasses in geological storage conditions: glass-iron interactions in hydrogen-tight reactors
Vitrified waste resulting from nuclear power plant fuel reprocessing, as well as their steel containers and overpacks, are intended for permanent storage in deep geological layers. Water will be the vector of glass alteration and potential migration of radioactive elements. The most advanced storage concept to date provides for the glass package to be protected for its thermal decay step from interaction with water by an unalloyed steel overpack. However, whether in the form of metallic iron or corrosion products of steels (oxides, carbonates, sulfides), iron plays a significant role in glass alteration.
The objective of this work is to understand and quantify the mechanisms of glass-iron interaction in order to strengthen the operational models for waste package performance. To this end, a bench of ten hydrogen-tight instrumented reactors has been developed in the laboratory. It has allowed the implementation of a first series of long-term experiments of several months, which concerned a non-radioactive model glass and a iron carbonate. The objective will be to carry out these interaction experiments using metallic iron this time, to characterize the sampled solutions and neoformed alteration products, and to interpret the experiments using the modeling tools available in the laboratory.
Hydrolysis energy distribtution in model glasses using molecular simulation and Machine Learning
The objective of the project is to develop a tool based on molecular simulations combined with Machine Learning to estimate rapidly the distributions of hydrolysis and reformation energies of the chemical bonds on the surface of alumino silicate glasses(SiO2+Al2O3+CaO+Na2O).
The first step will consist in validating the classical force fields used to prepare the hydrated SiO2-Al2O3-Na2O-CaO systems by comparison with ab initio calculations. In particular, metadynamics will be used to compare classical and ab initio elementary hydrolysis mechanisms.
The next step will consist in performing « Potential Mean Force » calculations using the classical force fields to estimate distributions of hydrolysis and reformation energies on large statistics in few glass compositions. Then by using Machine Learning and atomic structural descriptors, we will try to correlate local structural characteristics of the chemical bonds to the hydrolysis and reformation energies. Methods such as Kernel Ridge Regression, Random Forest or Dense Neural Network will be compared.
At the end, a generic tool will be available to rapidly estimate distributions of hydrolysis and reformation energies for a given glass composition.
Mitigation of Alkali Silica Reaction in concrete used for radwaste stabilization and solidification
Electricity production from nuclear power plants generates radioactive wastes, the management of which represents a major industrial and environmental concern. Thus, low- or intermediate - level radioactive aqueous waste streams may be concentrated by evaporation, and immobilized with a Portland cement, before being sent to disposal. Nevertheless, interactions may occur between some components of the waste and the cement phases or aggregates, and decrease the stability of the final waste forms. Thereby, the formation of a gel-like product has been recently observed on the surface of some cemented drums of evaporator concentrates which were produced in the 80’s in Belgium. This product results from a reaction between silica from the aggregates and the very alkaline pore solution of the concrete. However, its composition and rheological properties differ from those reported for alkali-silica gels in civil engineering. Extensive work has been performed to better understand the processes involved in the gel formation within the cement-waste forms and characterize its properties. Based on these results, the post-doctoral project will be focussed on the mitigation of alkali silica reaction in cement-waste forms. Two approaches will be more particularly investigated by decreasing the water saturation ratio of concrete and/or the pH of its pore solution using supercritical carbonation.
This project is intended for a post-doctoral fellow wishing to develop skills in materials science, with an interest in advancing the field of cement chemistry and improving the conditioning of radioactive waste. It will be performed in collaboration with ONDRAF-NIRAS, the Agency in charge of radioactive waste management in Belgium, and will build upon the expertise of two laboratories at CEA Marcoule: the Cements and Bitumen for Waste Conditioning Laboratory for materials elaboration and characterization, and the Supercritical and Decontamination Laboratory.
Rhelogical properties of molten crystallized glass
Formulation of nuclear waste conditioning glass results from a compromise between waste loading, glass technological feasibility and its long-term behavior. Up to now borosilicate glasses formulated at CEA and elaborated at La Hague plant by Orano to condition nuclear waste are homogeneous when molten. That means that today glass formulation is determined such as solubility limits of each constituting elements of waste aren’t exceeded in order to avoid phase separation (implying typically Mo, S, P) and/or crystallization (implying typically Fe, Ni, Cr, Zn, Al, Ce, Cs, Ti…) leading to a two-phase molten glass (liquid-liquid or liquid-solid).Today CEA would like to explore the impact of solid particles in suspension in the molten glass and in the final glass canister on respectively the glass technological feasibility and its long-term behaviour.
The proposed study focuses on the molten glass technological feasibility. The presence of solid heterogeneities in the melt is known to lead to a modification of some of its physical properties – notably its rheology, as well as thermal and electrical conductivities, and can generate settling phenomena. Yet these properties are in the heart of vitrification process control and modelling. This study will then investigate the impact of crystals in the molten glass on vitrification process control and modelling.
Synthesis by 3D printing of functionnalized geopolymer membrane for the treatment of complex radioactive effluents.
In the field of the treatment of liquid radioactive wastes on solid supports, the development of new composite materials synthetized by 3D printing under filtre shape is of primary of importance to decontaminate some radioactive effluents.
In this phD proposal, we propose to develop a membrane allowing to produce, from effluent containing somes traces of micronic solids in suspension and ionic species, a clarified effluent compatible with a nuclear outlet pipe. The challenge is to study the shaping of a material in a form of a filtration membrane allowing to trap in a single step an effluent containing some solids in suspension and some ionic species. In order to develop both functionnalities, 3D printing will be used to synthetise multiscale porous ceramic composites such as some geopolymers functionnalized by a selective adsorbants. The candidate, mainly based at CEA/ISEC Marcoule, could first formulate a functionnalized geopolymer paste with suitable rheological properties compatible with the constraints of the 3D printing process. A cross-flow filtration membrane with a controled macroporous network will be then printed by optimizing the geometry of the mesh. Finally, some sorption and cross-flow filtration tests will be performed on some model effluents containing calibrated solid in suspension and ions of interest such as Cs and Sr. The relevance of the printed membrane architecture will be assessed in relation to the capture of the solids and radioelements.
The candidate must have skills in the field of rheology, process and modeling. From this research work, job opportunities either in the field og 3D printing of materials or in the field of liquid waste treatment and depolution are potential options.
Robotics Moonshot : digital twin of a laser cutting process and implementation with a self-learning robot
One of the main challenges in the deployment of robotics in industry is to offer smart robots, capable of understanding the context in which they operate and easily programmable without advanced skills in robotics and computer science. In order to enable a non-expert operator to define tasks subsequently carried out by a robot, the CEA is developing various tools: intuitive programming interface, learning by demonstration, skill-based programming, interface with interactive simulation, etc.
Winner of the "moonshot" call for projects from the CEA's Digital Missions, the "Self-learning robot" project proposes to bring very significant breakthroughs for the robotics of the future in connection with simulation. A demonstrator integrating these technological bricks is expected on several use cases in different CEA centers.
This post-doc offer concerns the implementation of the CEA/DES (Energy Department) demonstrator on the use case of laser cutting under constraints for A&D at the Simulation and Dismantling Techniques Laboratory (LSTD) at the CEA Marcoule.
Development of a digital twin of complex processes
The current emergence of new digital technologies is opening up new opportunities for industry, making production more efficient, safer, more flexible and more reliable than ever. The application of these technologies to the vitrification processes could improve the knowledge of the processes, optimise their operation, train operators, help with predictive maintenance and assist in the management of the process.
The SOSIE project aims at providing a first proof of concept for the implementation of digital technologies in the field of vitrification processes, by integrating virtual reality, augmented reality, IoT (Internet of Things) and Artificial Intelligence.
This project, carried out in collaboration between the CEA and the SME GAMBI-M, is a READYNOV project. GAMBI-M is a company specialised in the reconstruction of complex environments and in digital engineering. The work will be carried out in close collaboration with the CEA teams developing the vitrification processes for nuclear waste.
The project consists of developing a digital twin of 2 vitrification processes, and will be implemented on 2 platforms in parallel, one in a conventional zone, the other in a high activity zone. The first step will be to develop a visual digital twin, the virtual 3D model of each cell, which will allow the user to visit the cells and access any point virtually. Based on this reconstructed model, an "augmented" twin will be developed and connected to the supervisory controller. Finally, the last step will be to develop the "intelligent twin" by exploiting existing databases on the operation of the process. By training machine learning algorithms on these data, a predictive model of nominal operation will be generated.
Publications are expected on the implementation of virtual reality and augmented reality tools on shielded chain operations, as well as on the development of deep learning methods for the assistance to the control of such complex processes.