Rosa Lo Frano

Tritium breeding blanket is a key component of future fusion power plants, and its performance depends on the selection, fabrication, and qualification of lithium-based ceramic material. Among the proposed lithium ceramics materials, the main candidates for ceramic breeders are lithium orthosilicate (Li₄SiO₄) and lithium metatitanate (Li₂TiO₃). These advanced ceramics and their biphasic composites are the leading candidates due to their high lithium density, favorable tritium breeding ratio (TBR ≈ 1.15–1.25 with Be₁₂Ti multiplier and 90% ⁶Li enrichment), and robust thermo-mechanical behavior within the 200–900 °C operational window of helium-cooled pebble bed (HCPB) blankets. This review provides an engineering-oriented assessment covering fabrication routes (solid-state, hydrothermal, melt-based, drip casting, powder injection molding, microwave sintering, and digital light processing additive manufacturing); microstructure–property relationships and performance under neutron irradiation; and tritium generation, retention, and release as functions of chemical composition, defect structure, and operating temperature. Induced radioactivity of Li-based ceramics and key impurity elements is quantified using activation formalisms applied to WWR-K reactor conditions, providing guidance for raw-material selection and waste-management assessment. Authors’ original contributions include (i) an empirical model of pebble crush load vs. biphasic composition (R² > 0.99); (ii) two universal semi-empirical kinetic models (exponential growth and non-linear strength degradation, R² = 0.97–0.99) for nine structural and mechanical parameters of Li₂TiO₃ under He²⁺ and H⁺ irradiation; (iii) a consolidated table of Arrhenius tritium diffusion parameters from reactor experiments and DFT; and (iv) an induced radioactivity calculation for the biphasic system with two-exponential post-irradiation decay analysis. The review identifies biphasic Li₄SiO₄–Li₂TiO₃ composites with ~30 ± 5 mol.% Li₂TiO₃ as particularly promising and formulates specific data gaps and modeling needs for the reliable deployment of ceramic breeder pebbles in helium-cooled fusion blanket systems. It should be specifically noted that Li₄SiO₄ pebbles fabricated via the melt method, as an example, typically exhibit exceptionally high densities, generally exceeding 90% of the theoretical density (TD). Building on the calculation of induced radioactivity, it is crucial to consider the microstructural distribution of highly radioactive nuclides (e.g., Co, Mn) within the ceramic matrix. If these impurities segregate at grain boundaries rather than being homogeneously distributed, there is a potential pathway to develop targeted wet-chemical methods, such as selective acid leaching, to remove these impurities post-irradiation, thereby lowering the waste disposal classification.

Using the edge plasma code package SOLPS-ITER, we study the four types of Snowflake (SF) divertors for an ITER-size tokamak, with toroidal magnetic field B _T ∼ 5 T, major radius R ∼ 5 m and plasma current I _p ∼ 10 MA. Our aim is to provide insights into SF divertor design for future devices. In this work, the impacts of magnetic geometry and divertor target geometry in the four types of SF configurations on plasma behavior and power exhaust performance are investigated in detail. Low-recycling regime, high-recycling and detachment in the four types of SF divertors are obtained through an upstream density scan. The secondary X-point positions of SF divertors are systematically varied to examine their impact. For Low-Field-Side (LFS) SF− and High-Field-Side (HFS) SF− divertors the observed power splitting, induced by the secondary X-point, is consistent with experimental observations. The effect of target geometry is studied by comparing the flat target plates with the ITER-like divertor shape. The overall simulation results reveal a notable consequence of the LFS SF− divertor: a closed structure of the inner target with highly inclined plate can compress recycling neutrals originating from the HFS divertor region towards the LFS Scrape-Off Layer (SOL) and Private Flux Region regions. This results in considerable volumetric dissipation through strong ionization and recombination, causing the connected outer target region to detach. This feature can be considered in the design of the LFS SF− divertor for future devices. For the LFS and HFS SF+ divertors, the region between the two X-points exhibits strong ionization and recombination sources which are close to the primary X-point. This feature might be beneficial for the formation of X-Point Radiator (XPR) but would require further impurity seeding simulation study.

High-pressure pipelines in nuclear power plants (NPPs) are prone to structural failures, and the study of their failure behavior is essential to analyze and minimize damage to the surrounding structures and components. The prediction of the extent of damage is also a key parameter when designing the surrounding structures. This prediction holds significant importance, since a substantial number of NPPs globally are approaching the 60-year mark in their operational lifespan. Consequently, it becomes imperative to formulate sophisticated methodologies for assessing damage behavior of structures and components under dynamic loading conditions with a more realistic representation of the behavior. This study investigates the damage response resulting from the pipe whip phenomenon in high-pressure pipelines of nuclear power plants through numerical simulations that incorporate damage models for both concrete and steel. The proposed modeling approach was also verified with the results of a ballistics impact study. The finite element modeling (FEM) of the pipe-on-wall-impact (POWI) scenario using ABAQUS helps to implement the damage models of Johnson–Cook (J–C) and Cowper–Symonds (C–S) to steel and the Concrete Damaged Plasticity (CDP) model to concrete using a damage-based approach to determine the extent of damage and failure possibilities. The maximum stresses of the pipe attained 450 MPa for the C–S model and 387 MPa for the J–C model, with the C–S model predicting higher stresses due to its high strain rate sensitivity at extreme loads. By incorporating the damage parameters for the POWI model, a better understanding of the mechanical behavior under impact conditions can be attained.

The rapid increase in global warming requires that sustainable energy choices aimed at achieving net-zero greenhouse gas emissions be implemented as soon as possible. This objective, emerging from the European Green Deal and the UN Climate Action, could be achieved by using clean and efficient energy sources such as hydrogen produced from nuclear power. “Renewable” hydrogen plays a fundamental role in decarbonizing both the energy-intensive industrial and transport sectors while addressing the global increase in energy consumption. In recent years, several strategies for hydrogen production have been proposed; however, nuclear energy seems to be the most promising for applications that could go beyond the sole production of electricity. In particular, nuclear advanced reactors that operate at very high temperatures (VHTR) and are characterized by coolant outlet temperatures ranging between 550 and 1000 °C seem the most suitable for this purpose. This paper describes the potential use of nuclear energy in coordinated and coupled configurations to support clean hydrogen production. Operating conditions, energy requirements, and thermodynamic performance are described. Moreover, gaps that require additional technology and regulatory developments are outlined. The intermediate heat exchanger, which is the key component for the integration of nuclear hybrid energy systems, was studied by varying the thermal power to determine physical parameters needed for the feasibility study. The latter, consisting of the comparative cost evaluation of some nuclear hydrogen production methods, was carried out using the HEEP code developed by the IAEA. Preliminary results are presented and discussed.

This study investigates the mechanical and microstructural performance of three alkali-activated geopolymer formulations, constituted of metakaolin (MK), blast furnace slag (BFS), and a ternary blend of MK, BFS, and fly ash (MIX), for the immobilization of simulated radioactive liquid organic waste (RLOW). Thermal ageing tests were performed to evaluate geopolymer durability, including fire exposure (800 °C) and climatic chamber cycles (from −20 to 40 °C). Characterization through thermogravimetric analysis (TGA), compression tests, and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS) was carried out to assess material degradation after thermal ageing. Preliminary results showed substantial strength and microstructural degradation in oil-loaded specimens after cyclic climatic ageing, while fire-exposed blank matrices retained partial mechanical integrity. BFS matrices exhibited the best thermal resistance, attributable to the formation of Ca-Al-Si-hydrate (C-A-S-H) gels. These findings support the use of optimized geopolymer formulations for safe RLOW immobilization, while contributing to the advancement of knowledge on sustainable and regulatory-compliant direct conditioning technology.

Tritium is a radioisotope that is extremely mobile in the biosphere and that can be transferred to the environment and to humans mainly via tritium oxide or tritiated water. Moreover, as is widely known, it is extremely difficult to detect in the environment. In the last decade, many studies and research activities have been performed to fill the knowledge gap on this radionuclide, the amount of which is expected to be increasingly released into the environment from nuclear installations in the near future. Considering this and the fact that the biological and environmental effects produced by tritium have been examined mainly from a medical and detection monitoring point of view, it is considered important to propose in this study a review of the critical aspects of tritium from the environmental, engineering, and waste management points of view. Identifying sources and effects of tritium, tritium materials and wastes containing tritium in the environment is also fundamental for planning the specific and necessary actions required for an effective waste management approach under, e.g., disposal conditions. The critical analysis of the published recent studies has allowed to evaluate, for example, that the expected rate of tritium generation in a fusion reactor is four orders of magnitude higher than that of LWRs, and the environmental release from a fusion reactor is 1.4–2.2‱, which is twice as much as from a heavy water reactor and more than two orders of magnitude higher than from a LWRs. Furthermore, with reference to the waste management strategy, it is emphasized, e.g., that the condensation of moisture inside vaults and the interaction of H₂O with the disposal body determine the formation of tritiated water, which is filtered through the concrete and eventually released into the environment. Consequently, in the selection of engineered barrier materials for repositories/disposal facilities, the use of a mixture of a framework and layered silicates is proposed to improve its absorption and filtering properties.

Convolutional Neural Networks (CNNs) are proposed for use in the nuclear power plant domain as surrogate models to enhance the computational efficiency of finite element analyses in simulating nuclear fuel behavior under varying conditions. The dataset comprises 3D fuel pellet FE models and involves 13 input features, such as pressure, Young’s modulus, and temperature. CNNs predict outcomes like displacement, von Mises stress, and creep strain from these inputs, significantly reducing the simulation time from several seconds per analysis to approximately one second. The data are normalized using local and global min–max scaling to maintain consistency across inputs and outputs, facilitating accurate model learning. The CNN architecture includes multiple dense, reshaping, and transpose convolution layers, optimized through a brute-force hyperparameter tuning process and validated using a 5-fold cross-validation approach. The study employs the Adam optimizer, with a significant reduction in computational time highlighted using a GPU, which outperforms traditional CPUs significantly in training speed. The findings suggest that integrating CNN models into nuclear fuel analysis can drastically reduce computational times while maintaining accuracy, making them valuable for real-time monitoring and decision-making within nuclear power plant operations.

Dry systems are being employed worldwide as interim storage for Spent Nuclear Fuel (SNF). Despite not being designed as permanent repositories, the safe storage of SNF must still be ensured. In this framework, few experimental campaigns have been conducted in the past. However, their limited number has led to the necessity to exploit numerical simulations for the thermal characterization of the system. Since the majority of the degradation mechanisms are temperature-dependent, conducting a thermal analysis of a dry cask is essential to assess the integrity of the system itself, and of the SNF stored within it. In this regard, both heat production and heat removal mechanisms have to be taken into account. On this basis, the present paper addresses the variation in the system heat removal capacity when considering different backfill gas pressures. In particular, the analysis, carried out with the MELCOR code, investigates the thermal response of the ventilated, concrete-based HI-STORM 100S cask, currently employed for spent fuel elements of Light Water Reactors (LWRs), when imposing different initial pressures for the helium backfill gas. Results are reported primarily in terms of maximum temperature of the fuel cladding, which is the variable under regulatory surveillance. In addition, the adherence to the maximum design pressure for the canister is verified by evaluating the helium pressure as the steady state is reached. The analysis seems to suggest that the safe operation of the HI-STORM 100S cask is guaranteed only for a limited range of the initial helium pressure.

It is of meaningful importance to evaluate the performance of all the nuclear facilities, and particularly those part of such buildings where spent nuclear fuel (SNF) is stored to assess what kinds of consequences are anomalous/abnormal or to determine what types of accident events may occur. In this preliminary study, the strategies adopted for the management of SNF, and the risk related to them are discussed. The aim of this study is to evaluate the total radioactivity inventory characterising Ukrainian nuclear facilities, including storage facilities. The dataset used to calculate the total activity associated with nuclear fuel is provided and discussed. For the evaluation, it is considered that a SNF pool in VVER-1000 is designed to store 687 fuel assemblies, and 670 are in VVER-440. When it is half full, which is the case for 15 Ukrainian units, it will store about 2200 tU containing up to 1·10¹⁹ Bq of 137Cs, 7·10¹⁸ Bq of 90Sr, and 1·10¹⁹ Bq of TUE. This study focuses particularly on the total activity of the SNF stored at the Zaporozhye plant, the biggest nuclear plant in Europe, and the risk posed by the potential loss that cooling the plant could incur because of pond water level variation. The results of the analysis of the Zaporozhye NPP behaviour suggest that the water flow rate which keeps the SNF pool temperature constant is about 200,000 m³·day⁻¹. Therefore, the water level in the pond should not be lower than 1.5–2 m; otherwise, the plant will need an additional source of water of more than 200,000 m³ per day to guarantee safe storage of SNF.