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Salvato, Daniele

Publications and source records attributed to Salvato, Daniele.

17 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Characterization of Fuel Cladding Chemical Interaction on a High Burnup U-10Zr Metallic Fuel via Electron Energy Loss Spectroscopy Enhanced by Machine Learning

Fuel cladding chemical interaction (FCCI) is one of the main performance limiting factors for metallic nuclear fuels. The interaction destabilizes the martensitic microstructure and deteriorates mechanical properties of HT-9 cladding. The detection of low atomic number elements (Z<10) and overlapping of elemental peaks can be problematic in interpreting energy dispersive X-ray spectroscopy (EDS) data. Electron energy loss spectroscopy (EELS) provides precise elemental edge energy values and can detect elements with a low atomic number. This work utilizes EELS to study the distribution of lanthanides and light elements at the interaction region. The sample was prepared from the FCCI region of a U-10Zr (wt.%) solid fuel with HT-9 cladding, irradiated to a burnup of 13.2 at.%. Processing the EELS data included three major steps: 1) enhance the signal to noise ratio by denoising the spectrum with principal component analysis (PCA) method, removing background and performing deconvolution; 2) identify chemical elements with core energy loss edges; 3) confirm different phases using a popular machine learning method, K-means. This work presents qualitative assessment of lanthanides and light elements like carbon (C) and oxygen (O) enhanced by the application of machine learning algorithms. By comparing with EDS elemental maps, EELS provides higher resolution chemical maps, reveals the distribution of carbon at the interaction region supporting the formation of zirconium carbide, a rind-like microstructure feature that was proposed to mitigate the chemical interaction. Furthermore, the plasmon peak map was also found to indicate an energy shift associated with the formation of phases/compounds. K-means clustering method was used on the processed electron energy loss (EEL) spectrum to automatically reveal different phases. The resulting clustered maps from K-means clustering align well with elemental maps confirming certain phases, especially Fe-Ce and Zr-C, in the FCCI region.

EELS↗
DOE OSTI2024

Segmentation and Classification of Fission as Pores in Reactor Irradiated Annular U–10Zr Metallic Fuel Using Machine Learning Models

Metallic fuels, particularly U—10Zr, are promising candidates for next-generation sodium-cooled fast reactors. Irradiation of nuclear fuels in reactors can lead to the formation of solid and gas fission product which subsequently forms microstructural pores, deteriorating fuel performance. Due to the massive amount of pores and complex phases formed, a quantitative description of fission gas pores is not yet available, preventing the development of microstructure-informed fuel performance modeling for fuel qualification. This paper applied a pre-trained deep learning model to ~10,260 high magnification scanning electron microscopy images. This method increased the accuracy of fission gas pore segmentation and allows statistical features to be extracted which cannot be achieved manually. A pre-trained decision tree model worked on the segemenation results and further classified the pores into different categories to produce a correlation between the pores, movement of lanthanides, and temperature gradient during irradiation. Finally, this paper emphasizes the potentials of machine learning models to accelerate fuel research, development, and qualification for advanced reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mechanical Properties of Irradiated U-10 wt. %Mo Alloy Degraded by Porosity Development

In this study, a plate-type nuclear fuel consisting of a solid monolithic foil of U-10 wt. %Mo is under development for use in the United States' high-performance research reactors. In support of developing this fuel, the fuel has been fabricated for the first time by a commercial fuel vendor and subsequently irradiated in a test reactor. This provides an opportunity to evaluate postirradiation mechanical properties of the commercially fabricated fuel. Four-point bend testing was conducted on the irradiated U-10Mo samples to generate the fuel material properties, including the modulus of elasticity and the bending strength. Although the material behaves in a brittle manner due to the accumulated porosity, a general trend of strength and modulus reduction was found as fission density increases. The data produced was evaluated using both Weibull statistics and a modulus degradation model with recommendations provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Analysis of radially resolved thermal conductivity in high burnup mixed oxide fuel and comparison to thermal conductivity correlations implemented in fuel performance codes

The thermal diffusivity and thermal conductivity of high burnup (19 % FIMA) mixed oxide (U, Pu)O 2 nuclear fuel has been measured along the radial direction using a thermoreflectance-based method. Measured thermal conductivity exhibits a notable radial variation consistent with the expectations that a large temperature gradient across the annular fuel pellet leads to a heterogeneous microstructure. A common fuel performance model of thermal conductivity, the Lucuta-Inoue model, is used to analyze the measured thermal conductivity profile. Further, this model adequately captures the radial dependence of thermal conductivity except in the periphery. The analysis suggests that the characteristic radial shape of the thermal conductivity profile follows the burnup profile within the fuel pin. In the periphery, the high burnup structure is formed and the conductivity model, not capturing this effect, likely overestimates the thermal conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effect of heat treatment on the microstructure of medium burn-up U-Mo monolithic fuel foils

Using scanning electron microscopy (SEM), this study evaluates the microstructure evolution of U-Mo fuel foils made with and without heat treatment at medium burn-up (of approximately 5 x 10 21 f/cm 3 ). The impact of annealing treatments on critical microstructural properties of the U-Mo fuel foils, including porosity, grain structure, Mo homogeneity, and fuel interaction with the Zr interlayer, was examined using large area lift outs (LALOs). The heat-treated specimens presented less grain refining at these burnups when compared to the un-heated specimens. Grain refinement was associated with porosities and fission products precipitation. Heat treatment can reduce fuel swelling during irradiation. Chemical inhomogeneity (Mo banding) was found to persist in the un-heated samples but was not present in the heat-treated samples. Thus, heat-treated U-Mo foils allows for more predictable fuel behavior under irradiation with respect to un-heated foils. The U-Mo and Zr interaction layer appears to be thicker and more continuous in the heat-treated sample which has been associated with stronger interface integrity during irradiation, as also observed in previous studies. These observations may indicate an overall improved performance of heat-treated fuel foil in a reactor. Further, the effect of local burn-up on grain size/refinement and porosities in each LALO specimen, sampled from different positions in the fuel foil, was difficult to analyze due to the large standard deviation of these parameters. Finally, evidence of grain refinement by polygonization may be present in these specimens.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

The effect of temperature and burnup on U-10Zr metallic fuel chemical interaction with HT-9: A SEM-EDS study

The fuel cladding chemical interaction (FCCI) between Uranium-Zirconium-based metallic fuel and cladding materials during in-pile service is one of the most constraining phenomena affecting the performance of this fuel system. In this study, we investigated the effect of temperature and burnup on the FCCI development in two U-10 wt.% Zr (U-10Zr) fuel samples with HT-9 cladding irradiated as part of the MFF-3 irradiation test in the Fast Flux Test Facility (FFTF). One sample achieved a burnup of 13.1 at.% and operated with an average inner cladding temperature of 530°C, while the other achieved a burnup of 8.5 at.% and was subjected to an average inner cladding temperature of 615°C. Automated scanning electron microscopy (SEM) back-scattered electron (BSE) imaging of entire fuel cross-sections and SEM energy dispersive x-ray spectroscopy (EDS) analysis on specific fuel-cladding interface regions successfully provided a comprehensive characterization of the depth and type of interaction happening under different irradiation conditions. Further, our analysis shows that FCCI development on both fuel and cladding side is strongly influenced by the inner cladding temperature and, to some extent, the formation and integrity of Zr-rich layers between the fuel and cladding, while the impact of burnup and power is negligible. Measured FCCI thicknesses were compared to BISON simulations using both an empirical model based upon legacy data from the Experimental Breeder Reactor II (EBR II) irradiations and a mechanistic model currently under development for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, showing satisfactory agreement. Nonetheless, this comparison supports the need for additional microstructural characterization in intermediate ranges of temperature, power, and burnups in prototypic-length pins.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

An efficient instance segmentation approach for studying fission gas bubbles in irradiated metallic nuclear fuel

Abstract Gaseous fission products from nuclear fission reactions tend to form fission gas bubbles of various shapes and sizes inside nuclear fuel. The behavior of fission gas bubbles dictates nuclear fuel performances, such as fission gas release, grain growth, swelling, and fuel cladding mechanical interaction. Although mechanical understanding of the overall evolution behavior of fission gas bubbles is well known, lacking the quantitative data and high-level correlation between burnup/temperature and microstructure evolution blocks the development of predictive models and reduces the possibility of accelerating the qualification for new fuel forms. Historical characterization of fission gas bubbles in irradiated nuclear fuel relied on a simple threshold method working on low-resolution optical microscopy images. Advanced characterization of fission gas bubbles using scanning electron microscopic images reveals unprecedented details and extensive morphological data, which strains the effectiveness of conventional methods. This paper proposes a hybrid framework, based on digital image processing and deep learning models, to efficiently detect and classify fission gas bubbles from scanning electron microscopic images. The developed bubble annotation tool used a multitask deep learning network that integrates U-Net and ResNet to accomplish instance-level bubble segmentation. With limited annotated data, the model achieves a recall ratio of more than 90%, a leap forward compared to the threshold method. The model has the capability to identify fission gas bubbles with and without lanthanides to better understand the movement of lanthanide fission products and fuel cladding chemical interaction. Lastly, the deep learning model is versatile and applicable to the micro-structure segmentation of similar materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A fine pore-preserved deep neural network for porosity analytics of a high burnup U-10Zr metallic fuel

Abstract U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel system to design future fast reactors. To address the above issues, we introduce a workflow to process and analyze multi-source Scanning Electron Microscope (SEM) image data. Moreover, an encoder-decoder-based, deep fully convolutional network is proposed to segment pores accurately by integrating the residual unit and the densely-connected units. Two SEM 250 × field of view image datasets with different formats are utilized to evaluate the new proposed model’s performance. Sufficient comparison results demonstrate that our method quantitatively outperforms two popular deep fully convolutional networks. Furthermore, we conducted experiments on the third SEM 2500 × field of view image dataset, and the transfer learning results show the potential capability to transfer the knowledge from low-magnification images to high-magnification images. Finally, we use a pre-trained network to predict the pores of SEM images in the whole cross-sectional image and obtain quantitative porosity analysis. Our findings will guide the SEM microscopy data collection efficiently, provide a mechanistic understanding of the U-10Zr fuel system and bridge the gap between advanced characterization to fuel system design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mechanical Properties of Irradiated U-10wt%Mo Alloy Degraded by Porosity Development

A plate-type nuclear fuel consisting of a solid monolithic foil of U-10wt%Mo is under development for use in the United States’ high performance research reactors. In support of developing this fuel, the fuel has been fabricated for the first time by a commercial fuel vendor and subsequently irradiated in a test reactor. This provides an opportunity to evaluate post-irradiation mechanical properties of commercially fabricated fuel. Four-point bend testing was conducted on the irradiated U-10Mo fuel and the data produced includes bending strength and Young’s modulus. Although the material behaves in a brittle manner due to the developed porosity, a general trend of strength and modulus reduction are found as fission density increases. The data produced is evaluated using both Weibull statistics and a modulus degradation model with recommendations provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Contributions to the mechanistic understanding of the microstructural evolution in irradiated U-Mo dispersion fuel

Here, advanced microstructural characterization techniques, such as scanning electron microscopy (SEM) and scanning transmission electron microscopy - energy dispersive x-ray spectroscopy (STEM-EDS), were used to interpret the fuel microstructure evolution and fission products behavior in U-Mo dispersion fuel irradiated in the Advanced Test Reactor (ATR) as part of the European Mini-Plate Irradiation Experiment (EMPIrE) test. The larger as-fabricated fuel grain size achieved by heat-treating the U-Mo powder resulted in slower high burnup structure (HBS) development and reduced fission gas porosity. Slower HBS kinetics was observed at the fuel kernels’ periphery, which contained smaller and less fission gas bubbles at all fission densities (FDs) investigated and was attributed to a locally reduced damage density and fission products concentration, as corroborated with Monte Carlo simulations. The non-refined grains at the fuel kernel periphery hosted a perfectly ordered fission Gas Bubble Superlattice (GBS) up to 6.3 × 10 21 fissions/cm 3 . Nano-scale STEM-EDS analysis presented in this study provided useful information on the GBS characteristic morphology and evolution in U-Mo fuel. The concentration of fission gas in the GBS progressively increased with FD, pointing to an evolution of the nanobubble pressure status with irradiation. A possible connection between the GBS collapse and HBS onset is proposed for which there exists a threshold in the misorientation of the refined sub-grains above which the GBS stability during irradiation is no longer preserved, resulting in the GBS collapse.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Advanced characterization-informed machine learning framework and quantitative insight to irradiated annular U-10Zr metallic fuels

Abstract U-10Zr Metal fuel is a promising nuclear fuel candidate for next-generation sodium-cooled fast spectrum reactors. Since the Experimental Breeder Reactor-II in the late 1960s, researchers accumulated a considerable amount of experience and knowledge on fuel performance at the engineering scale. However, a mechanistic understanding of fuel microstructure evolution and property degradation during in-reactor irradiation is still missing due to a lack of appropriate tools for rapid fuel microstructure assessment and property prediction based on post irradiation examination. This paper proposed a machine learning enabled workflow, coupled with domain knowledge and large dataset collected from advanced post-irradiation examination microscopies, to provide rapid and quantified assessments of the microstructure in two reactor irradiated prototypical annular metal fuels. Specifically, this paper revealed the distribution of Zr-bearing secondary phases and constitutional redistribution across different radial locations. Additionally, the ratios of seven different microstructures at various locations along the temperature gradient were quantified. Moreover, the distributions of fission gas pores on two types of U-10Zr annular fuels were quantitatively compared.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The role of UC inclusions in the development of fission gas bubble superlattice neutron-irradiated monolithic U-10Mo fuels

Uranium Carbide (UC) inclusions are the most prevalent impurities in Uranium-Molybdenum (U-Mo) fuel and are considered undesirable because they could potentially affect fuel performance. This work revealed that, like grain boundaries (gBs), UC inclusions could help facilitate the formation of the fission gas bubble superlattice (GBS). The GBS is a highly organized complex defect structure that can effectively store fission gases, thereby inhibiting fuel swelling. Transmission electron microscopy (TEM) showed that GBS self-organization can initiate at the UC/U-Mo interfaces in U-10Mo fuel irradiated to low fission density. Furthermore, this study also revealed that the UC boundary in U-10Mo irradiated to low fission density is wavy and periodic in morphology and that GBS formation is semi-coherent with the UC boundary. Because the initiation of GBS occurs at gBs and UC/U-Mo interfaces, the fission gas inventory is always highest at those regions compared to the U-Mo grain interior. Consequently, at higher fission densities, it is likely that high burnup structure (HBS) development via grain refinement will begin at gBs and UC/U-Mo interfaces.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Microstructure and phase evolution in the U-10Zr fuel investigated by in situ TEM heating experiments

The development of U-Zr metallic nuclear fuel for fast spectrum reactors is impacted by a lack of mechanistic understanding of the fuel behavior evolution under thermal irradiation conditions, despite previous works providing substantial fuel performance data. This work uses in-situ transmission electron microscopy heating experiments to study phase and microstructural evolution in several unirradiated U-10Zr specimens during rapid heating ramps (from room temperature to 1000 °C). The starting a-U + bcc-(Zr, U) eutectic microstructure began to decompose above 600 °C. The decomposition initiated from the bcc (U,Zr) phase. Similar results were observed for all specimens even when fabricated by different routes (e.g., cold rolled or annealed). As a result, the impact of observed microstructure and phase evolutions at high temperatures on fuel fabrication and in-pile fuel transient test was also discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Annular Metallic Nuclear Fuel Informatics at 50 nm Resolution

U-10wt.% Zr (U-10Zr) based metallic fuel is the leading candidate for next-generation sodium cooled fast reactor in United States. Advanced post-irradiation characterization (from sub-nanometer to micrometer) helps to understand fuel microstructure and property change during irradiation, benefiting fuel qualification for commercial application. With high velocity image data generating method, an automatic way to extract the microstructural information quantitively can better serve the needs from post irradiation characterization. A trained machine learning model, named Decision Tree, is employed to categorize pores caused by fission gas release and to aid phase identification. This work presents a showcase of this approach on different irradiated U-10Zr metallic fuels. This quantitative data offers insights into the fission product migration and potentially thermal conductivity degradation. This information from machine learning will be fed into fuel design code for better prediction of fuel performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Early self-organization of fission gas bubble superlattice formation in neutron-irradiated monolithic U-10Mo fuels

Self-organization of defect superlattices in far-from-equilibrium systems presents a promising way to mitigate swelling concerns in nuclear materials. The gas bubble superlattice (GBS) is a highly ordered, three-dimensional complex defect structure that can retain fission gasses in Uranium-Molybdenum (U-Mo) fuels. Transmission electron microscopy (TEM) investigation of monolithic U-10Mo fuel irradiated to 1.15 × 10 21 fissions/cm 3 and 1.30 × 10 21 fissions/cm 3 revealed that early-stage ordering preferentially occurs at the grain boundaries (GB) and that the critical bubble size for complete ordering is ~3 nm. Once formed at the GB, the GBS extends towards the grain interior; however, the spread in distance from the GB varies likely depending on the type and strength of the GB sink. TEM results also showed a possible correlation between the growth and evolution of the intragranular disordered bubbles and large dislocation networks. The fission product distribution in and outside of the GBS was also investigated confirming the presence of xenon in the GBS, as well as other fission products including cesium, barium, lanthanum, and cerium.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Microstructural and phase changes in alpha uranium investigated via in-situ studies and molecular dynamics

A deeper knowledge of thermally induced microstructural and phase evolution in nuclear metallic fuel can be obtained using novel in-situ microscopic analyses. Such studies can provide information on the dynamics of phase transitions which is not possible with conventional postmortem characterization (post-irradiation examination). In this work, the behavior of alpha uranium (α-U) was investigated via in-situ heating tests in a transmission electron microscope. Here, the main objective is to understand the microstructural and phase changes, such as defect annihilation and ß phase formation and retention, observed in reactor in-pile transient studies at the Transient Reactor Test facility. Indeed, defect migration and rearrangement were observed within the α phase starting at 673 K; α→ß phase transition was observed between 773 K and 1,073 K during the heating ramp (which is in the temperature window reported for α→ß transition temperatures). Recrystallization and formation of nano grains was observed at high temperatures (over 1,073 K). Such recrystallization was possibly related to the formation of the γ phase. Finally, it was indeed observed that the ß phase (but not γ phase) was retained at room temperature upon rapid cooling. Molecular dynamics studies support these experimental results and shows that the γ phase of pure uranium cannot be retained at room temperature if not stabilized with the addition of an alloying element.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗