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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Assessment of ITER radiation environment during the remote-handling operation of In-Vessel components with D1SUNED

During ITER operational life, a remote-handled cask will be used to transfer In-Vessel components to the Hot Cell for maintenance, storage and decommissioning purposes. Due to the distribution of penetrations for system allocation in the facility, the radiation field of each transfer operation presents a high spatial variability; all operations must be studied independently for workers and electronics protection. In this paper, we present a fully representative approach to describe the radiation environment during the complete remote-handling scenario of In-Vessel components in the ITER facility. The impact of all relevant radiation sources during different stages of the operation is addressed. As-built structures and 2020 baseline designs are considered to produce the most detailed neutronics model of the Tokamak Complex, the 400,000-tonne civil structure hosting the tokamak, up to date. Novel capabilities of the D1SUNED code have allowed to compute the integral dose, the dose rate and the photon-induced neutron flux of both moving and static radiation sources. Time bins are included in the simulations to compute the dose rate caused by In-Vessel components at all positions along the transfer. The time evolution of the dose rate is built in video format with a 1-m resolution, especially valuable for hot-spots identification.

42 ENGINEERING↗
DOE OSTI2024

A Computational Review of Privacy-Preserving Mechanisms for the Smart Grid

Smart grid technologies have rapidly become one of the largest and most comprehensive sources of data for the modern utility. For the most part, data streams are seen as an essential tool that enable utilities to carry their day-to-day business operations, but they also create the need for efficient and secure data management strategies. In the context of the smart grid, ensuring data privacy is becoming an increasing concern due to a combination of factors that range from shifts in operational paradigms and rapid technology evolution to changes in legislation. Furthermore, researchers have highlighted the risks associated with improperly protected energy records. For example, energy consumption data from homes could be used to infer the behaviors and habits of home occupants through activity recognition or user profiling (Fan, 2017), which may lead to unfair service pricing, targeted advertising, or other personal security violations. Similarly, Electric Vehicles’ (EVs) charging metadata could be used to reveal private information about the owner such as their payment methods, preferred charging stations, and other locational and timing information that could be used to reconstruct the vehicle owner’s behaviors. The privacy of user data, even when used for statistical analysis or machine learning training processes, also needs to be carefully considered, as an individual’s private traits may still be vulnerable if their inclusion/exclusion greatly impacts the result or could be linked to a public dataset through cross-reference. The breach of user privacy also has severe impacts for organizations that store, transmit, or work on the data in the form of diminishing the public’s trust in them while potentially incurring legal consequences (e.g., fines and suspensions under the European Union General Data Protection Regulation, Health Insurance Portability and Accountability Act, etc.). Because of these risks, several privacy-preserving mechanisms are available to help organizations comply with privacy legislations and prevent the unauthorized and malicious use of user data. In light of these concerns, this report focuses on performing a computational review of privacy-preserving mechanisms that have received a significant amount of interest in literature. It specifically focuses on 1) homomorphic encryption, 2) zero-knowledge proofs, 3) differential privacy, and 4) federated learning. It is worth noting that although many of the methods presented in this document rely on cryptographic primitives, their intent is not to provide perfect secrecy, but rather to enable users to maintain privacy, and thus they shall not be compared or equated to other constructs that are aimed to address cybersecurity constructs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Progress Towards Treating the Sludges Produced During Spent Fuel Processing - 19546

As a consequence of over 50 years of Magnox reprocessing, Sellafield site is in possession of significant quantities of Magnox sludge. This sludge material is the by-product of corrosion of the magnesium based Magnox metal that clads the Magnox fuel elements. Retrievals and processing of this material poses a significant challenge as corrosion of Magnox metal has occurred under a variety of conditions and over a significant period of time, in a variety of locations. Devising processes to treat heterogeneous materials offers a significant challenge to identify technologies with robust envelopes of acceptance, to effectively operate together. This is further compounded by difficulties defining test programmes and materials for testing that will provide assurance that nonradioactive testing is suitably representative or bounding. An overview of the significant body of work undertaken to process Sellafield's Magnox sludge is provided, from the thousands of commercially sensitive reports generated over the past five decades. This covers the sampling, characterisation, strategy and process evolution, technology development and test materials. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Predicting Geologic Behavior in Carbon Storage Projects Using Graph Neural Network

This study was invited to presented at NVIDIA's GTC conference to highlight the potential of Graph Neural Network as a novel and promising methodology for predicting pressure and saturation evolution in carbon storage projects. Carbon capture and storage (CCS) technology plays a pivotal role in mitigating greenhouse gas emissions, facilitating the transition to a low-carbon future. Effective management of subsurface reservoirs is essential to ensure the safe and efficient storage of captured carbon dioxide (CO₂). Accurate predictions of pressure and saturation over time are critical for evaluating the long-term performance and integrity of CCS projects. In recent years, Graph Neural Network (GNN) has emerged as a powerful framework for analyzing complex data in graph-structured domains. This abstract explores the application of GNN to forecast pressure and saturation evolution in carbon storage projects. Traditional numerical simulations of subsurface reservoirs have proven successful in providing pressure and saturation forecasts. However, these simulations involve massive amounts of computational effort and require extensive domain expertise for proper model calibration and validation. Graph Neural Operator offers an alternative approach that harnesses the inherent graph structure of reservoirs, where nodes represent reservoir grid cells and edges represent the geological connectivity between them.

Shih, Chung Yan↗
DOE OSTI2022

Runaway electron deconfinement in SPARC and DIII-D by a passive 3D coil

The operation of a 3D coil—passively driven by the current quench (CQ) loop voltage—for the deconfinement of runaway electrons (REs) is modeled for disruption scenarios in the SPARC and DIII-D tokamaks. Nonlinear magnetohydrodynamic (MHD) modeling is carried out with the NIMROD code including time-dependent magnetic field boundary conditions to simulate the effect of the coil. Further modeling in some cases uses the ASCOT5 code to calculate advection and diffusion coefficients for REs based on the NIMROD-calculated fields, and the DREAM code to compute the runaway evolution in the presence of these transport coefficients. Compared with similar modeling in Tinguely et al (2021 Nucl. Fusion 61 124003), considerably more conservative assumptions are made with the ASCOT5 results, zeroing low levels of transport, particularly in regions in which closed flux surfaces have reformed. Of three coil geometries considered in SPARC, only the n = 1 coil is found to have sufficient resonant components to suppress the runaway current growth. Without the new conservative transport assumptions, full suppression of the RE current is maintained when the thermal quench MHD is included in the simulation or when the RE current is limited to 250kA, but when transport in closed flux regions is fully suppressed, these scenarios allow RE beams on the order of 1–2 MA to appear. Additional modeling is performed to consider the effects of the close ideal wall. In DIII-D, the CQ is modeled for both limited and diverted equilibrium shapes. In the limited shape, the onset of stochasticity is found to be insensitive to the coil current amplitude and governed largely by the evolution of the safety-factor profile. In both devices, prediction of the q-profile evolution is seen to be critical to predicting the later time effects of the coil.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Quantum algorithms for systems of linear equations inspired by adiabatic quantum computing

We present two quantum algorithms based on evolution randomization, a simple variant of adiabatic quantum computing, to prepare a quantum state |x⟩ that is proportional to the solution of the system of linear equations $A\overrightarrow{x} = \overrightarrow{b}$. The time complexities of our algorithms are O(κ 2 log(κ)/ε) and O(κ log(κ)/ε), where κ is the condition number of A and ε is the precision. Both algorithms are constructed using families of Hamiltonians that are linear combinations of products of A, the projector onto the initial state |b⟩, and single-qubit Pauli operators. The algorithms are conceptually simple and easy to implement. They are not obtained from equivalences between the gate model and adiabatic quantum computing. They do not use phase estimation or variable-time amplitude amplification, and do not require large ancillary systems. We discuss a gate-based implementation via Hamiltonian simulation and prove that our second algorithm is almost optimal in terms of κ. Like previous methods, our techniques yield an exponential quantum speed-up under some assumptions. Our results emphasize the role of Hamiltonian-based models of quantum computing for the discovery of important algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Screening aqueous organic redox couples for spontaneous hydrogen generation on catalysts

Two low-cost redox couples with near neutral or alkaline pH - 7,8-dihydroxyphenazine-2-sulfonic acid (DHPS) and chrome chelated ethylenediaminetetraacetic acid (Cr-EDTA) with ammonia – are identified to generate hydrogen evolution spontaneously on Pt/C catalysts. Cr-EDTA redox couple has two times higher hydrogen evolution rate than that of DHPS, and the charged Cr-EDTA molecules are fully utilized to generate hydrogen gas, while ~ 50% of DHPS molecules are utilized to produce hydrogen spontaneously on Pt/C catalysts. The Cr-EDTA electrolyte enables cost reduction by allowing cheap raw material of Cr and corrosion resistant alloy instead of costly superalloy for catalytic reactor systems. Furthermore, the Cr-EDTA with ammonia as a negolyte for flow batteries was validated to suppress hydrogen evolution side reaction, reach 99% of coulombic efficiency in flow cell operation paired with Fe(CN)6 redox couple near neutral pH.

08 HYDROGEN↗
DOE OSTI2016

CFD and X-ray Analysis of Gaseous Direct Injection from an Outward Opening Injector

Using natural gas in an internal combustion engine (ICE) is emerging as a promising way to improve thermal efficiency and reduce exhaust emissions. In the development of such engine platforms, computational fluid dynamics (CFD) plays a fundamental role in the optimization of geometries and operating parameters. One of the most relevant issues in the simulation of direct injection (DI) gaseous processes is the accurate prediction of the gas jet evolution. The simulation of the injection process for a gaseous fuel does not require complex modeling, nevertheless properly describing high-pressure gas jets remains a challenging task. At the exit of the nozzle, the injected gas is under-expanded, the flow becomes supersonic and shocks occur due to compressibility effects. These phenomena lead to challenging computational requirements resulting from high grid resolution and low computational time-steps. In this paper, the simulation of gaseous injection from an outward opening injector was carried out with the commercial CFD software CONVERGE. Argon was injected into a quiescent chamber filled with Nitrogen. Two free-jet cases with injection pressure of 15 and 10 bar, and ambient pressure of 1 and 2 bar respectively, were tested. For the 15 bar injection pressure and 1 bar ambient pressure, a jet impinging on a barrier case was performed as well. The numerical results were validated against experimental mass measurements using X-ray radiography. The results, presented in terms of 2D maps and transverse sections of equivalent path length of argon, showed good agreement between modeling and experiments in terms of jet penetration, shape and gas mass distribution. These emphasized the significant impact of mesh size on the results for the simulation of this type of injector. Due to the small geometrical dimensions a fine mesh is required in order to deliver an accurate description of the mixture formation. Numerical results were discussed with a particular emphasis on the application to engine simulations, where a trade-off between accuracy and computational time is a necessity.

Bartolucci, Lorenzo↗
DOE OSTI2023

Availability Estimates of Low-Cost, Dispatch-Constrained Electricity (LDE)

This dataset accompanies the report "Potential Availability of and Supply Curves for Low-Cost, Dispatch-Constrained Electricity", which provides initial estimates of the quantity and availability of the potential low-cost, dispatch-constrained electricity (LDE) resource in the United States under scenarios with high variable renewable energy (VRE) penetrations. The analysis also estimates supply curves that can be used in subsequent analysis of the opportunity to use the LDE. The estimated LDE resource could be used for various applications that value low-cost electricity and can operate at reduced capacity factors, including electrolytic hydrogen production and carbon capture. The analysis accompanying this dataset was performed in 2018-2019 to support an analysis of "The Technical and Economic Potential of the H2@Scale Concept within the United States" ( https://www.nlr.gov/docs/fy21osti/77610.pdf ). This dataset includes the quantity of estimated LDE resource for each hour of the year in 2050, aggregated to both the national level and the ReEDS balancing area level. As described in the accompanying report, the ReEDS model was used to project the evolution of the power sector over time. Links to the mapping of ReEDS balancing areas to states and ReEDS balancing area shape files are provided. This dataset also includes the report figure data.

08 HYDROGEN↗
DOE OSTI2025

Time at Temperature Abstract and Intern Poster

Current NRC regulations for BWR operations dictate that any occurrence reaching the point of Departure from Nucleate Boiling (DNB) disqualifies the use of the fuel rod for further reactor operation. That criteria does not account for duration of rate of the power increase, the corresponding effects on material properties or rewetting that may occur. Previous Anticipated Operational Occurrences (AOOs) show short durations power increase that may require limited amounts of heat removal. Industrial experience has shown evidence that fuel can reach dryout yet continue to safely operate in regular reactor conditions. The gap in research into such occurrences is the motivation for a series of experiments, including this current work. Time-at-Temperature experiments aim to identify and characterize the microstructural changes in Zircaloy-2 under oxygen-free high temperatures. This work uses the FlashDSC instrument to rapidly ramp up and down the temperature of a focus ion beam (FIB) prepared large area lift-out (LALO) of Zircaloy-2 at a rate of 10,000 K/s to desired values. The focus is to characterize the microstructure evolution, if any, of Zircaloy-2 that may impact its performance under typical BWR conditions. This characterization includes analyzing grain structure and size, secondary phase particle (SPPs) size, shape, composition, and location using Transmission Electron Microscopy (TEM). Further data collection and analysis is in progress including diffraction pattern indexing and 4D STEM processing. While current results focus on the testing and characterizing unirradiated material, future plans include expansion to irradiated material to explore the effects of rapid transition rates seen in DNB and dryout conditions on irradiationg damage and defect annealing.

36 - MATERIALS SCIENCE↗
DOE OSTI2018

Implementation of ANL’s Mechanics Based Evolutionary Fatigue Modeling Through ABAQUS-WARP3D Based High-Performance Computing Framework

This report presents an update on the environmental fatigue research that is being conducted at Argonne National Laboratory in support of the Department of Energy’s Light Water Reactor Sustainability (LWRS) program. Argonne is developing a fully mechanistic fatigue evaluation approach without using empirical fatigue (S~N) curves. This approach is based on the fundamental concept of the time evolution of progressive fatigue damage rather than on the conventional S~N curve approaches using end-of-life data. In FY 2017, we performed extensive validation of this approach with respect to fatigue test data for 316 stainless steel [1]. This validation was performed for different loading cases, including constant, variable, and random amplitude. In the present FY 2018 semi-annual report, we present the further advances of Argonne’s environmental fatigue research work in the context for more practical applications. In this report, we discuss a methodology for fully mechanistic (i.e., not using S~N curves) fatigue life evaluation of reactor components subjected to realistic loading cycles, namely, design-basis loading cycles. The loading cycles include plant heat-up, full-power, and cool-down operations. As a test case, we considered a typical pressurized water reactor surge line, which is made of 316 SS. To perform the fatigue simulation for thousands of fatigue cycles in a computationally cost effective way, we modified our previous desktop-based finite element (FE) modeling approach to work in a high-performance computing (HPC) framework. For the HPC implementation, we developed a hybrid framework based on commercial FE software (ABAQUS), open-source FE software (WARP3D), and Argonne-developed evolutionary cyclic-plasticity modeling methods. We validated this HPC-based cycle-by-cycle damage model for the entire fatigue life of a Pressurized Water Reactor (PWR) surge line (SL) pipe with respect to assumed loading cycles. The simulated fatigue life was found to be 5855 cycles, which is 85% accurate as compared to the corresponding small-specimen-based experimental fatigue life (6914 cycles). Also, the simulated stress history captures the cyclic hardening and softening behavior of the material for entire fatigue cycles. The FE simulation of the PWR SL pipe was conducted in a reasonable time of 12.5 days. These results show the promise that a fully mechanistic (not using S~N curves) fatigue life evaluation of a safety-critical nuclear reactor component (or even other safety critical components like those in aircraft, aero-engines, etc.) is possible. We anticipate that this type of methodology will drastically reduce the uncertainly associated with conventional fatigue life estimates based on empirical S~N curves. We also proposed an FE model that is based on a hybrid full-component and single-element approach and that can readily be used by industry if HPC resources are not available. In this approach, a single-cycle FE simulation has to be performed first for the required loading cycle. Then, the resulting strain/stress profile at the hotspot (highest strain/stress location) is used as input strain/stress loading to the single-element FE model. The single-element FE model is run under multiple fatigue cycles as long as the failure criteria are achieved. The cycle number at failure gives the fatigue life of the component in question. This cost-effective framework does not require expensive HPC hardware and can be performed in a reasonable time by using a desktop computer. We demonstrated this approach with respect to PWR SL fatigue evaluation under two realistic design-basis loading cycles (simple and detailed). The associated results were validated with respect to test data obtained through fatigue testing of uniaxial specimens under the in-air condition at 300 °C. The approach is in the development stage and requires further improvement and validation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

W-band system-on-chip electron cyclotron emission imaging system on DIII-D

Monolithic, millimeter wave “system-on-chip” (SoC) technology has been employed in heterodyne receiver integrated circuit radiometers in a newly developed Electron Cyclotron Emission Imaging (ECEI) system on the DIII-D tokamak for 2D electron temperature profile and fluctuation evolution diagnostics. Here, a prototype module operating in E-band (72-80 GHz) was first employed in a 2 x 10 element array that demonstrated significant improvements over the previous quasi-optical Schottky diode mixer arrays during the 2018 operational campaign of the DIII-D tokamak. For compatibility with International Thermonuclear Experimental Reactor (ITER) relevant scenarios on DIII-D, the SoC ECEI system was upgraded with 20 horn-waveguide receiver modules. Each individual module contains a University of California at Davis designed W-band (75 -110 GHz) receiver die that integrates a broadband low noise amplifier (LNA), a double balanced down-converting mixer, and a x4 multiplier on the local oscillator (LO) chain. A x2 multiplier and two IF amplifiers are packaged and selected to further boost the signal strength as well as downconvert the signal frequency. The upgraded W-band array exhibits > 30 dB additional gain and 20x improvement in noise temperature comparing with the previous Schottky diode radio frequency (RF) mixer input systems; an internal 8 times multiplier chain is used to bring down the LO frequency below 12 GHz, thereby obviating the need for a large aperture for quasi-optical LO coupling and replacing it with coaxial connectors. The horn-waveguide shielding housing avoids out-of-band noise interference on each individual module. The upgraded ECEI system plays an important role for absolute electron temperature evolution and fluctuation measurements for edge and core region transport physics studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Secondary Ion Mass Spectrometry (SIMS) for Chemical Characterization of Metal Halide Perovskites

Metal halide perovskite (MHP) solar cells have attracted much attention due to the rapidly growing power conversion efficiency that has reached 25.2% in a decade, comparable to established commercial photovoltaic modules. Compositional engineering is one of the most effective methods to boost the performance of MHP solar cells. Further improving the efficiency and the stability of MHP solar cells necessitates good understanding of the chemical–efficiency correlation and the chemical evolution during the degradation of MHP solar cells. In this regard, time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful tool to investigate the chemical aspect of MHPs and has played an important role in advancing the development of MHP optoelectronics. However, up to date, a review that can guide future utilization of ToF-SIMS in the MHP development is missing. In this paper, the capabilities of ToF-SIMS in MHP investigations are summarized and analyzed from simple material synthesis and chemical distribution to more complicated device operation mechanism and stability. The strength of ToF-SIMS in resolving important issues in this field, such as interface composition, ion migration, and degradation in MHP is highlighted. Finally, an outlook with an emphasis on making the utmost of ToF-SIMS in developing MHP devices is provided.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Steam caps in geothermal reservoirs can be monitored using seismic noise interferometry

Harvesting geothermal energy often leads to a pressure drop in reservoirs, decreasing their profitability and promoting the formation of steam caps. While steam caps are valuable energy resources, they also alter the reservoir thermodynamics. Accurately measuring the steam fraction in reservoirs is essential for both operational and economic perspectives. However, steam content estimations are very limited both in space and time since current methods rely on direct measurements within production wells. Besides, these estimations normally present large uncertainties. Here, we present a pioneering method for indirectly sampling the steam content in the subsurface using the ever-present seismic background noise. We observe a consistent annual velocity drop in the Hengill geothermal field (Iceland) and establish a correlation between the velocity drop and steam buildup using in-situ borehole data. This application opens new avenues to track the evolution of any gas reservoir in the crust with a surface-based and cost-effective method.

58 GEOSCIENCES↗
DOE OSTI2020

Driven electrostatic phase space vortices in a 1D weakly dissipative Vlasov–Poisson system

In this paper, the effect of collisions on driven electrostatic phase space vortices is analyzed by means of Eulerian simulation for two different collision models. It was demonstrated recently that in the absence of collisions, at late times, steady state phase space vortices manifest to form a plateau in the resonant region of the particle velocity distribution function, due to trapping of particles supporting multiextrema giant phase space vortices (PSVs). In the presence of collisions, over long time, this multiextrema plateau are found to smooth out, since collisions drive the velocity distribution toward Maxwellian, irrespective of how weak the collisions are as long as they are non-zero. In these conditions, kinetic processes and collisionality are found to be in competition, and the evolution of the plasma is found, therefore, to be a result of nontrivial combination of these two effects. An attempt has been made by means of numerical simulations to study the effect of weak collisionality on the electrostatic driven phase space vortices with two types of collision operators: (1) Bhatnagar–Gross–Krook (Krook) collision operator, where the colliding particles can be treated as isolated pairs and, (2) Fokker–Planck (FP) type collision operator (Zakharov–Karpman) in one dimension, where many weak collisions lead to particle diffusion in velocity space. It is shown that depending on the collision model used, the nature of smoothing in velocity space of giant PSVs results in qualitatively very different phase space structures. However, irrespective of the collision model used, excess density fractions over 10% are retained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

de Sitter space as a tensor network: Cosmic no-hair, complementarity, and complexity

Here, we investigate the proposed connection between de Sitter spacetime and the multiscale entanglement renormalization ansatz (MERA) tensor network, and ask what can be learned via such a construction. We show that the quantum state obeys a cosmic no-hair theorem: the reduced density operator describing a causal patch of the MERA asymptotes to a fixed point of a quantum channel, just as spacetimes with a positive cosmological constant asymptote to de Sitter space. The MERA is potentially compatible with a weak form of complementarity (local physics only describes single patches at a time, but the overall Hilbert space is infinite dimensional) or, with certain specific modifications to the tensor structure, a strong form (the entire theory describes only a single patch plus its horizon, in a finite-dimensional Hilbert space). Furthermore, we suggest that de Sitter evolution has an interpretation in terms of circuit complexity, as has been conjectured for anti–de Sitter space.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Numerical Modelling of Radionuclide Migration in the Context of a Near-Surface LILW Disposal Facility - 18618

The reference solution for the management of low and intermediate level short-lived waste (LILW) in France consists in their emplacement in concrete vaults built at the near-surface. The corresponding disposal facility under operation by the French waste management organization (Andra), is located in North-eastern France and planned to be closed in 2060. The safety case developed by Andra has to show the evidence that, amongst other aspects, the radionuclide transfer through the confinement barriers will occur in such a way that the human and environmental exposure will be as low as reasonably achievable (ALARA) and in accordance with the dose constraints. For this purpose, modelling is used to integrate uncertainties about the characteristics of concrete components, waste and water table and their evolution in time and space. At last, modelling is finally used to investigate the radiological impact of specific scenarios in which the failure of safety barriers occurs. In the frame of its technical review of the safety assessment, the French Institute for Radiological Protection and Nuclear Safety (IRSN) also performs such kind of numerical modelling of radionuclide fate from the waste to the hydrogeological outlets, in order to check whether the assessment performed by Andra takes into account sufficiently conservative assumptions. The present work aims to evaluate the role of components of the vaults on radionuclide transport during the post-closure period over a few thousand years. For this purpose, IRSN carries out numerical calculations with MELODIE software, which simulates water flow and transport of species, in order to simulate radionuclide migration from waste packages emplaced in a concrete vault to the surrounding groundwater. The developed transport model focuses on 3-H radionuclide and integrates Andra's main assumptions (release model from the waste packages, chemical and hydraulic properties of the vault components, shrinkage and cracks in concrete components). An adaptive mesh method, based on an a posteriori error estimator, was used to model the cracks and the consideration of a strong heterogeneity in the hydraulic and transport parameters values in the different components of the model. This method shows an improvement of results of about 40 times, whereas the mesh size was increased by only 2%. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗