Methodology Development for Proliferation Resistance Optimization of Advanced Reactors and Fuel Cycles
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11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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Prediction of Silicon Content in a Blast Furnace via Machine Learning: A Comprehensive Processing and Modeling Pipeline
Silicon content plays an important role in determining the operational efficiency of blast furnaces (BFs) and their downstream processes in integrated steelmaking; however, existing sampling methods and first-principles models are somewhat limited in their capability and flexibility. Current data-based prediction models primarily rely on a limited set of manually selected furnace parameters. Additionally, different BFs present a diverse set of operating parameters and state variables that are known to directly influence the hot metal’s silicon content, such as fuel injection, blast temperature, and raw material charge composition, among other process variables that have their own impacts. The expansiveness of the parameter set adds complexity to parameter selection and processing. This highlights the need for a comprehensive methodology to integrate and select from all relevant parameters for accurate silicon content prediction. Providing accurate silicon content predictions would enable operators to adjust furnace conditions dynamically, improving safety and reducing economic risk. To address these issues, a two-stage approach is proposed. First, a generalized data processing scheme is proposed to accommodate diverse furnace parameters. Second, a robust modeling pipeline is used to establish a machine learning (ML) model capable of predicting hot metal silicon content with reasonable accuracy. The method employed herein predicted the average Si content of the upcoming furnace cast with an accuracy of 91% among 200 target predictions for a specific furnace provisioned by the XGBoost model. This prediction is achieved using only the past shift’s operating conditions, which should be available in real time. This performance provides a strong baseline for the modeling approach with potential for further improvement through provision of real-time features.
Chemistry↗
Core plasma fueling by fast inward particle transport after hydrogen pellet injection in Wendelstein 7-X
A large database of more than 1000 individual cryogenic hydrogen pellets injected into Wendelstein 7-X for plasma fueling was analyzed to improve the understanding of the three phases of the process: the ablation, deposition and transport of the pellet material. Kilohertz-sampled electron density and temperature measurements revealed a more complex drift behavior than predicted by numerical code simulation. It could be explained by the poloidal plasma E r x B- drift rotation, which plays a significant role in stellarators, but was not previously considered in pellet injection codes like HPI2. The drift results in a fast poloidal rotation of the pellet material around the plasma core, leading to an almost homogeneous deposition over the involved flux surfaces regardless of magnetic high and low field side injection geometry. Additionally, a novel fast inward directed transport mechanism (‘FIT-effect’) was observed. The effect occurs on timescales of tens of milliseconds and cannot be explained by neoclassical transport or diffusion. It might be linked to the turbulence pinch recently found in Wendelstein 7-X. When the FIT-effect occurs, the pellet particles are rapidly transferred from the deposition flux surfaces to the plasma core, causing the plasma density profile to peak, which is beneficial for confinement in Wendelstein 7-X. The large pellet injection database was statistical analyzed with regard to pellet and plasma parameters, which delivered some starting points towards developing an understanding of the physics behind the FIT-effect. The results indicate, that plasma core fueling via pellet injection is largely independent of the injection geometry in stellarators under certain conditions, reducing the technical complexity of the injection system.
Wendelstein 7-X↗
Revealing Phase Heterogeneity in Vertically Aligned Nanocomposites via Plan-View Electron Energy Loss Spectroscopy
Hydrogen utilization in clean energy technologies is challenged by limited storage and transport within materials, owing to the complex hydrogen kinetics at interfaces [1]. Understanding these interfacial mechanisms at the nanoscale is crucial for developing improved materials for hydrogen applications, particularly proton-conducting fuel cells (PCFCs). Vertically aligned nanocomposites (VANs) grown by pulsed laser deposition (PLD) offer a unique platform for investigating the interfacial effects on hydrogen transport due to their well-defined interfaces parallel to the direction of charge transport [2-4]. To investigate hydrogen transport, the two phases within the VANs were chosen as BaZr 0.9 Y 0.1 O 3-x (BZY), a known proton conductor, and Pr 0.1 Ce 0.9 O 2-x (PCO), a mixed ionic-electronic conductor [5]. This PCO-BZY VANs architecture allows the investigation of how the interface between a proton conductor and a mixed conductor influences hydrogen transport. However, because of the small size of hydrogen, it is difficult to discern the nature of its interactions with interfaces from bulk measurements at the macroscale, thus necessitating nanoscale measurements [6]. Electron energy loss spectroscopy (EELS) allows for nanometer-resolution probing of the local atomic structure and chemistry at the BZY/PCO interface. In this study, plan-view analysis of PCO-BZY VANs films was employed to characterize the structure and phase distribution of the VANs and investigate the interface between the nanostructures. The films were imaged using scanning electron microscopy (SEM) in the Hitachi S-4800 SEM, collecting secondary electron images using mixed upper and lower detectors. Then, plan-view transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) EELS were employed using a JEOL ARM300 microscope operated at 300kV with a Gatan K3 GIF Continuum detector to study the distribution of the BZY and PCO phases through the film. As a result, spectrum images were acquired at a dispersion of 0.18eV per channel and denoised afterward by principal component analysis (PCA) method.
Griffin, Elizabeth [Northwestern University, Evans↗
Microgravity Combustion Science and Fluid Physics Experiments and Facilities for the ISS
At the NASA Glenn Research Center, the Microgravity Science Program supports both ground-based and flight experiment research in the disciplines of Combustion Science and Fluid Physics. Combustion Science research includes the areas of gas jet diffusion flames, laminar flames, burning of droplets and misting fuels, solids and materials flammability, fire and fire suppressants, turbulent combustion, reaction kinetics, materials synthesis, and other combustion systems. The Fluid Physics discipline includes the areas of complex fluids (colloids, gels, foams, magneto-rheological fluids, non-Newtonian fluids, suspensions, granular materials), dynamics and instabilities (bubble and drop dynamics, magneto/electrohydrodynamics, electrochemical transport, geophysical flows), interfacial phenomena (wetting, capillarity, contact line hydrodynamics), and multiphase flows and phase changes (boiling and condensation, heat transfer, flow instabilities). A specialized International Space Station (ISS) facility that provides sophisticated research capabilities for these disciplines is the Fluids and Combustion Facility (FCF). The FCF consists of the Combustion Integrated Rack (CIR), the Fluids Integrated Rack (FIR) and the Shared Accommodations Rack and is designed to accomplish a large number of science investigations over the life of the ISS. The modular, multiuser facility is designed to optimize the science return within the available resources of on-orbit power, uplink/downlink capacity, crew time, upmass/downmass, volume, etc. A suite of diagnostics capabilities, with emphasis on optical techniques, will be provided to complement the capabilities of the subsystem multiuser or principal investigator-specific experiment modules. The paper will discuss the systems concept, technical capabilities, functionality, and the initial science investigations in each discipline.
Lauver, Richard W.↗
Microwave and Millimeter Wave Nondestructive Evaluation of the Space Shuttle External Tank Insulating Foam
The Space Shuttle Columbia s catastrophic failure has been attributed to a piece of external fuel tank insulating SOFI (Spray On Foam Insulation) foam striking the leading edge of the left wing of the orbiter causing significant damage to some of the protecting heat tiles. The accident emphasizes the growing need to develop effective, robust and life-cycle oriented methods of nondestructive testing and evaluation (NDT&E) of complex conductor-backed insulating foam and protective acreage heat tiles used in the space shuttle fleet and in future multi-launch space vehicles. The insulating SOFI foam is constructed from closed-cell foam. In the microwave regime this foam is in the family of low permittivity and low loss dielectric materials. Near-field microwave and millimeter wave NDT methods were one of the techniques chosen for this purpose. To this end several flat and thick SOFI foam panels, two structurally complex panels similar to the external fuel tank and a "blind" panel were used in this investigation. Several anomalies such as voids and disbonds were embedded in these panels at various locations. The location and properties of the embedded anomalies in the "blind" panel were not disclosed to the investigating team prior to the investigation. Three frequency bands were used in this investigation covering a frequency range of 8-75 GHz. Moreover, the influence of signal polarization was also investigated. Overall the results of this investigation were very promising for detecting the presence of anomalies in different panels covered with relatively thick insulating SOFI foam. Different types of anomalies were detected in foam up to 9 in thick. Many of the anomalies in the more complex panels were also detected. When investigating the blind panel no false positives were detected. Anomalies in between and underneath bolt heads were not easily detected. This paper presents the results of this investigation along with a discussion of the capabilities of the method used.
Shrestha, S.↗
Final Technical Report: Transport of Complex Mixtures in Ion-Containing Polymer Membranes
Permselective ion-containing membranes are an integral component for many applications from water treatment, fuel cells, and solar fuels devices where the selective transport of molecules and ions is desired. In solar fuels devices, ion-containing polymer membranes are responsible for permitting selective transport of ions between electrodes to maintain overall charge neutrality yet limit transport of reaction products produced at the electrodes. While the transport of single solutes through such membranes has been fairly well described, binary and multicomponent transport is poorly understood due to the myriad of interactions that occur in these systems (i.e. between co-permeants and between permeants and the membrane). Solar fuels devices are just one example of an application where understanding the transport of multiple simultaneous species is critically important to improving device performance as product crossover leads to reductions in overall device performance. The objectives of this research was to improve our understanding of the complex array of factors that influence transport behavior of multiple solutes within ion-containing polymer membranes. This experimental project addressed the lack of fundamental understanding of multicomponent transport behavior by synthesizing ion exchange membranes with varied incorporation of comonomers (ionic and neutral moieties) to investigate fundamental relationships between membrane structure, membrane physiochemical properties, and transport behavior of solutes and complex solute mixtures through dense, hydrated membranes.
25 ENERGY STORAGE↗
The search for high-entropy fuel-cell catalysts using disorder descriptors
The transition to a hydrogen economy depends on efficient, affordable catalysts for fuel cells. Platinum—the industry standard for fuel-cell electrodes—is costly and scarce, highlighting the need for practical alternatives. High-entropy alloys offer vast compositional diversity and tunable properties that can mitigate these issues, yet their chemical complexity and configurational disorder have hindered rational discovery. Here, we introduce a data-driven framework that couples machine learning with first-principles disorder descriptors—including the entropy forming ability, disordered enthalpy-entropy descriptor, and electronic-structure similarity metrics to platinum—to predict alloy synthesizability and catalytic performance. These descriptors are applied for the first time in the context of fuel-cell catalyst discovery. The workflow rapidly screens more than 20 000 compositions and identifies several platinum-free candidates that are economically viable, readily scalable, and exhibit promising predicted activity. These results demonstrate that disorder descriptors are reliably predicted by machine learning models and can be effectively integrated into materials-discovery pipelines, accelerating innovation across complex compositional spaces.
fuel-cell catalysts↗
3D TRISO particle-explicit compact meshing
The TRI-structural ISOtropic (TRISO) layered fuel particle is a robust nuclear fuel form offering enhanced safety and performance for advanced reactor concepts, including high-temperature gas-cooled reactors and other Generation IV designs. These poppy-seed-sized particles are embedded in a graphite matrix to form fuel elements that must withstand elevated temperatures and high burn-up levels. The heterogeneous nature of these fuel elements — comprising thousands of randomly distributed TRISO particles — produces complex stress fields and thermal gradients that one- and two-dimensional models cannot accurately capture. While three-dimensional modeling has improved predictions of dimensional changes, internal pressure buildup, and fission product transport under irradiation, current approaches rely on homogenized material properties that are known to have considerable divergence from experimental observations. This work presents a methodology for optimized random packing of TRISO fuel compacts and full three-dimensional mesh generation within the BISON fuel performance code, with each particle coating layer individually discretized. The resulting mesh was demonstrated through heat conduction simulations under representative in-reactor operating conditions, showing strong agreement with expected behavior. This capability enables detailed analysis of particle-to-particle interactions, matrix cracking mechanisms, and the statistical distribution of coating layer failures — all of which directly govern fuel performance and safety margins.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Actively cooled airframe structures for high-speed flight
An assessment of forced convectively cooled aircraft structures is presented based on recent and on-going studies. Particular emphasis is given to contractual efforts in which large panels of three different concepts are being designed and fabricated for cyclic thermal-structural tests at the Langley Research Center. Results of ambient temperature fatigue tests of small specimens of these concepts are reviewed. Aspects of conceptual and detail designs, material selection, fabrication, reliability, and heat-load/hydrogen fuel heat-sink matching are discussed. Results to date indicate that active cooling significantly impacts the structural design process, and, despite the use of conventional aluminum materials, advanced complex fabrication processes are required.
Nowak, R. J.↗
Analysis of a Landing System for Planetary Payloads Utilizing Passive Energy Absorbing Composite Structure
Delivery of a payload from space to a planetary surface currently requires the development of an application specific landing system to protect the payload from forces imparted during impact with the planet surface. Often, active energy attenuating systems such as retro-rockets, deployable parachutes, and airbags are utilized within these landing systems to reduce landing impact energy. Unfortunately, these active systems come at a cost; active energy attenuating systems are susceptible to system faults which may limit or completely negate their energy attenuating capability. Additionally, components needing to be stowed such as fuel, parachutes, and airbags increase design complexity, cost, and weight. To overcome these limitations, this study examines the potential of passive energy attenuation through energy absorbing structural design and composite materials to mitigate landing loads for small payload planetary delivery. Researchers at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) have conducted extensive research into developing energy absorbing structures and components for the attenuation of impact energy under various loading conditions including aircraft crash and spacecraft impact. The current study leverages this research to design a lightweight planetary delivery system which utilizes unique outer mold line (OML) geometry and passive energy absorbing structural design to limit landing loads across potential planetary surface environments. The OML geometry is designed to control impact orientation and provide self-righting capabilities for slopped impact surfaces. The internal structure is composed of composite material structures arranged to provide energy absorption which is robust to impact angle and impact velocity. The developed planetary delivery design concept will be evaluated using finite element (FE) model analysis. Simulations of landing impacts with representative soil surface environments will be used to characterize the energy absorbing capabilities of the landing system. Sensitivity of predicted impact force to landing environment, impact angle, and impact velocity will be assessed to identify capabilities and limitations of the initial structural design. Results will be used to determine the feasibility of a lightweight composite structure to passively absorb landing energy for robust planetary payload delivery.
Crashworthiness↗
Developing Open-Source Tools for Increasing the Efficiency of Synthetic Aviation Turbine Fuel Certification Process
FuelLib is an open-source Python-based fuel library, developed by NREL, that leverages the group contribution method (GCM) of [1] to systematically estimate the thermodynamic and transport properties of hydrocarbon fuels. FuelLib predicts these properties based on the molecular structure of individual compounds or compound families, using weight percentages of a fuel's composition, typically measured using techniques such as gas chromatography (GC). FuelLib enables property estimation over a wide range of temperatures and pressures of multi-component fuels in the absence of detailed molecular composition data, making it particularly valuable for complex fuel mixtures where detailed experimental characterization of fuel composition is unavailable. These capabilities contribute directly to synthetic aviation turbine fuels (SATF) development, supporting the short-term American Society for Testing and Materials (ASTM) qualification of drop-in fuels while potentially expanding ASTM boundaries to certify a broader range of fuels.
33 ADVANCED PROPULSION SYSTEMS↗
SSME - Materials and Methods for Addressing High-Pressure Hydrogen Embrittlement
From the humid, corrosion-friendly atmosphere of KSC, to the extreme heat of ascent, to the cold vacuum of space, the Space Shuttle faced one hostile environment after another. One of those harsh environments the hydrogen environment existed within the shuttle itself. Liquid hydrogen was the fuel that powered the shuttle s complex, powerful, and reusable main engine. Hydrogen provided the high specific impulse the bang per pound of fuel needed to perform the shuttle s heavy lifting duties. Hydrogen, however, was also a potential threat to the very metal of the propulsion system that used it. The diffusion of hydrogen atoms into a metal can make it more brittle and prone to cracking a process called hydrogen embrittlement. This effect can reduce the toughness of carefully selected and prepared materials. A concern that exposure to hydrogen might encourage crack growth was present from the beginning of the Space Shuttle Program, but the rationale for using hydrogen was compelling. This paper outlines the material characterization, anomaly resolution, and path to understanding of hydrogen embrittlement on superalloys through the course of the SSME program. Specific examples of nickel alloy turbine housings and single crystal turbine blades are addressed. The evolution of fracture mechanics analytical methods is also addressed.
Matejczk, Daniel↗
Preparation of a uranium monocarbide anode and electrochemical characterization in molten LiCl-KCl-UCl 3
Porous uranium carbide (UC) pellets possessing moderate electrical conductivity were synthesized by reaction of UO 2 with graphite at temperatures up to 1550°C under rough vacuum. Conversions as high as 98% were achieved at soak times of 2-4 hours. The electrochemistry of the UC pellets in molten LiCl-KCl-6.5 wt% UCl 3 was explored using a variety of techniques including DC polarization methods, cyclic voltammetry, chronopotentiometry and bulk electrolysis. Here, the electrode reaction for anodic dissolution was found to be kinetically controlled by dissociation of UC to a transition state complex that was hypothesized to consist of a uranium atom partially complexed by chloride ions. Precise measurements of current efficiencies using chronopotentiometry indicated upper limits of 90.9 ± 3.4% and 98.3 +1.7/-3.7% for anode and cathode, respectively, when operating at anodic overpotentials near +300 mV. Bulk electrolysis of a UC pellet performed by passing 98% of the theoretical charge resulted in nearly complete recovery of its uranium content as highly pure metal at the cathode.
36 MATERIALS SCIENCE↗
Application of fuel cells with heat recovery for integrated utility systems
This paper presents the results of a study of fuel cell powerplants with heat recovery for use in an integrated utility system. Such a design provides for a low pollution, noise-free, highly efficient integrated utility. Use of the waste heat from the fuel cell powerplant in an integrated utility system for the village center complex of a new community results in a reduction in resource consumption of 42 percent compared to conventional methods. In addition, the system has the potential of operating on fuels produced from waste materials (pyrolysis and digester gases); this would provide further reduction in energy consumption.
Shields, V.↗
A sensing material-free and simple readout MEMS sensor for detecting Helium
Abstract In this work, we report a method that enables a standard electrostatic MEMS device to perform complex sensing functionalities, such as detecting the presence of helium without a sensing material or a conditioning circuit. Helium is a noble, odorless, non-reactive gas that is very challenging to detect. It is used in critical applications such as storing nuclear fuel waste inside a dry cask. In these applications, its leakage from the dry cask may indicate the cask's safe operation's degradation. A departure from the common practice of exciting the MEMS around its mechanical resonance, the method is based on exciting the MEMS around its electrical resonance circuit. This method shows that the tiny difference between the air dielectric constant (1.00059) and helium (1.000067) corresponding to only a few Femtofarad level capacitances produces a 25 mV difference without a conditioning circuit. Simulation results confirmed those findings and explored the sensor response at different operation conditions. This method eliminates the need for a heated microstructure and the need for absorption material. This method is not limited to gas sensing. It can be applied to other sensing mechanisms, such as acceleration and pressure measurements, and eliminate the complex circuit to read small capacitance in these applications.
Mohaidat, Sulaiman↗
Advanced microfabrication technologies for microspacecraft
Advanced microfabrication technologies offer the prospect of reducing the weight and size of spacecraft through the use of lighter and stronger materials in conjunction with new mechanical/structural design concepts and design optimization methods. At the same time, electronic components have been scaled down while increasing functional utility. A two-fold benefit is derived for space applications through the use of less expensive components and the lower launch costs associated with lighter components. GE-CRD is actively pursuing research in these key technologies for a wide range of applications including satellites. These key technologies will be reviewed and an update on GE progress will be given. The need to reduce weight and lower cost, while maintaining product quality and reliability are primary drivers in the design of satellites, in general, and microsatellites in particular. For the structural subsystem, these requirements pose a complex design problem unless new mechanical design concepts and computer-aided design optimization methods are employed. Several new concepts, such as battery packs doubling as panel reinforcements and fuel tanks as integral structural members, need to utilized. In addition, new viscoelastic material damping concepts for spacecraft components provide for lighter weight/lower cost designs, while satisfying the structural dynamics requirements. High density interconnect (HDI) technology permits the use of bare IC's on a ceramic substrate with 90 percent active area utilization. A copper/polyimide multilayer structure is the backbone of the technology, which has demonstrated a size/weight reduction of greater than 10x compared to printed circuit board with performance up to the GHz level. HDI modules have exceptional mechanical robustness as evidenced by survival of 180 kg rapid acceleration tests. Microelectromechanical systems (MEMS) are redefining sensors and actuators by miniaturization through micromachining techniques. Sharing many fabrication steps with HDI, we have developed a new technique for surface micromachining of copper/polyimide structures using computer-aided laser patterning.
Ghezzo, M.↗
A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products
Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial radiation damage during fission. Traditionally, property evolution has been determined via empirical data collected following irradiation. However, these empirical correlations are limited in their applicability beyond the specific conditions in which they were obtained. This study explores a novel approach to address this challenge by applying materials informatics to develop a machine learning random forest (ML-RF) model that captures the effects of fission products on fuel compounds. The model predicts formation enthalpy (ΔH f ) by leveraging extensive quantum materials property data and correlating it with material descriptors such as composition, atomic and site features, and crystal lattice properties. This ML-RF model enables rapid interpolation across the compositional and structural spaces covered by the training data, thus supporting high-throughput screening and energetic ranking of candidate phases. The model demonstrates the ability to predict ΔH f with a mean absolute error (MAE) of approximately 0.1 to 0.2 eV/atom across a wide range of compounds, including key nuclear fuel systems (U-O, U-N, U-C, U-Si, and U-Mo). For example, it was used to assess shifts in stoichiometry for UO 2 (O/M) and UN (N/M) fuels, revealing their distinct tendencies in chemical potential variation and enabling preliminary convex hull analyses. Furthermore, the model provides insights into how individual fission products affect fuel properties. Results indicate that larger fission products (e.g., Nd, Pu, Ce) have a more pronounced impact on UO 2 , while lighter ones (e.g., Zr) strongly influence UN. Here, the model developed in this work can be used to support the Accelerated Fuel Qualification approach by facilitating preliminary evaluations prior to extensive materials modeling and experimentation. To this end, the trained model has been made available to the fuel community to support ongoing fuel development efforts.
Accelerated fuel qualification↗