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DOE OSTI2020

Survey of Dynamic Mode Decomposition Methods

Dynamic mode decomposition (DMD) is a data-driven reduced order modeling (ROM) technique used for dynamic systems. The widely adopted algorithm was first introduced and demonstrated on fluid flow data by Schmid. In recent years, various other fields, such as nuclear engineering, have begun to adopt this method. For example, DMD has been used for estimating α-eigenvalues, as an ROM for pulsed neutron problems, for predicting isotopic composition in burnup calculations, as acceleration techniques for iterative methods, and in capturing dynamic behaviors in molten salt reactor transients. This report seeks to demonstrate the capabilities and limits of the standard DMD algorithm, and identify problem spaces where variants may be better suited. The primary variant this report considers is Multi-Resolution DMD (mrDMD). Because this serves as a survey, synthetically produced data is used in lieu of simulation results. The remainder of this report will go into detail on the DMD theory, outline the standard DMD and mrDMD algorithms, present test cases highlighting the applicability of each, and finally present a discussion on how to determine the best suited algorithm for a given problem. All calculations performed in this report are carried out using the open source DMD library, PyDMD.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Pu-238 Production Progress at Idaho National Laboratory From December 2022 to December 2023

Idaho National Laboratory (INL) has an ongoing effort to produce Pu-238 for NASA deep space missions. Recent work at INL has consisted of irradiation of Pu 238 production targets in the Advanced Test Reactor (ATR), generating more than an estimated 400 grams of Pu-238 heat source material between March and October 2023. Additionally, INL began qualifying Pu-238 production targets with a higher loading of Np-237 to further increase the production of Pu-238 production in later years. INL has also updated the analysis as a result of operational changes at ATR. One instance was updating the analysis to enable a single Pu-238 production target to be run in ATR’s South Flux Trap (SFT), rather than the previous seven production targets, to make use of a spare target from a discontinued design. Higher lobe powers in ATR were also analyzed due to potential changes in planned lobe powers.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2024

Pu-238 Production Progress at INL From December 2022 to December 2023

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2024

Human Factors Considerations in Artificial Intelligence Applications for Nuclear Power Plants

In recent years, there has been a wave of artificial intelligence (AI) technologies that offer to solve problems from shopping habits to mortgage approvals to critical systems operations. The rapidity of the development of these systems has led to both excitement and apprehension about the roles these systems should play in our modern societies. Furthermore, this paper focuses on the critical infrastructure industry, in general, and nuclear power generation, in particular, and seeks to scrutinize how we can leverage these novel technologies in human-centered ways to maintain or enhance the established high levels of reliability and resilience in these industries. First, we discuss the broader aspects of cognitive systems and activities that are critical to understanding the human-AI space. Then we explore different approaches to explainability in AI and the notions of trust. We then move on to discuss several human factors concepts and methods and how they can support the design of human-AI teams. We then explore recent research related to nuclear power that has been undertaken and evaluate the current industry and regulatory landscapes. Finally, we discuss identified research gaps and recommendations for solving these for the critical infrastructure space.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

A Tool Kit for Generating Simulated Radiation Measurements for Advanced Reactor Safeguards and Security

A tool kit was developed to simulate and analyze passive radiation measurements of molten salt reactor (MSR) operations to support development of nuclear safeguards approaches for this emerging reactor technology. A Transient Simulation Framework of Reconfigurable Modules (TRANSFORM) multiphysics simulation of an MSR produces time-dependent isotopic inventories at user-selected locations within the model. The tool kit implements the Gamma Detector Response and Analysis Software (GADRAS) application programming interface to inject the TRANSFORM isotopic inventories extracted/processed by a Python pipeline into GADRAS models of user-defined geometries. The TRANSFORM inventories are the source terms used to obtain synthetic measurements from GADRAS-defined detectors. The speed of TRANSFORM and GADRAS simulations enables surveying the large design space of MSRs (e.g., fuel type, fuel salt composition, number of loops) and the plethora of measurements (e.g., location, detector type, and collimation) within the reactor. This has enabled timely assessment of the various measurement locations and detectors to identify the most effective and efficient safeguards approach for a specific MSR design. Lastly, the tool kit also simulates extracted samples that can be aged to a desired dose, enabling stakeholders to optimize a measurement plan to use sample analysis as an element within a broader material accountancy plan.

Westphal, Greg↗

DOE OSTI2020

Nuclear Thermal Propulsion Scoping Analysis of Fuel Plate Core Configurations

Nuclear thermal propulsion (NTP) engines use a nuclear reactor to heat up hydrogen to high temperatures. Thrust is generated as the hydrogen is ejected at high velocity through a nozzle. NTP has the potential of reducing travel times for deep space missions, such as to Mars. The United States studied NTP early in the space age and the National Aeronautics and Space Administration (NASA) is currently revisiting the potential of the technology to enable its missions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Phase Relationships in the Carbon–Titanium–Uranium System for Ultra-High Temperature Nuclear Fuels

Carbides of uranium have attracted interest as fuels for nuclear thermal propulsion (NTP) to drive deep-space exploration owing to their attractive thermal and neutronic properties. Optimization of NTP technology, however, requires ultra-high temperature reactor environments to maximize the ratio of thrust to propellant to achieve peak rocket engine efficiency. Incorporation of transition metals into uranium carbides offers a pathway to increase the melting point of carbide fuels to address the operational challenges posed by NTP. Here, a thermodynamic model has been developed to examine the phase relationships in the C–Ti–U system at NTP conditions. Calculated phase relationships at ultra-high temperatures predict a stable (U, Ti)C solid solution. Additionally, experimental work on C–Ti–U synthesis via arc melting has been carried out, providing data on phase constitution and compositions that can be used to further refine the thermodynamic model that has been developed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Engineered $\mathrm{Ru}$ on $\mathrm{HY}$ zeolite catalyst for continuous and selective hydrodeoxygenation of lignin phenolics to cycloalkanes under moderate conditions

Here we report a continuous selective hydrodeoxygenation (HDO) process of guaiacol conversion to cycloalkanes under 180 °C/1 MPa, which results in improved HDO chemistry for lignin-based jet fuel production. The incipient wetness impregnation method was modified to prepare an HY zeolite-supported Ru catalyst with better metal dispersion and acid site uniformity, which overcomes the low conversion and selectivity of previous literature. The modified catalyst (Ru-HY-60-MI) was tested in a continuous fixed bed reactor, resulting in increased HDO conversion of guaiacol to cycloalkanes compared to the unmodified catalyst. Pressure, temperature, and weight hourly space velocity-dependent tests validate guaiacol HDO over Ru-HY-60-MI catalyzed ring hydrogenation of guaiacol to 2-methoxycyclohexanol, acid-catalyzed demethoxylation and dehydration to cyclohexene, and further hydrogenation of cyclohexene to cyclohexane. These experiments enable exploring a continuous HDO process, demonstrate effectiveness for other ß-ß and a-O-4 lignin representatives and real lignin bio-oil, and pave the way towards commercialization of lignin-based jet fuel

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Self-Organization and Nitrogen Incorporation in Diamond-Like Carbon Microstructures Synthesized by Nonthermal Plasma

Nonthermal plasma activation of light alkanes is an encouraging decarbonization strategy to produce chemicals or fuels from abundant and/or flared carbon sources. However, prolific carbon growth on both the catalyst and electrode has limited its practicality, requiring additional knowledge of the carbon structure and growth mechanism before breakthroughs are realized. Furthermore, visual evidence is provided for nonuniform diamond-like carbon (DLC) microstructures that materialize in a coaxial dielectric barrier discharge (DBD) reactor flowing ethane and He at 278 K. Through a connection to known behaviors of DBD microdischarge patterns, the microstructure spacing was controlled by altering the applied voltage (ΔV) of the plasma or the burning voltage (U b ). Additionally, carbon valorization through nitrogen incorporation from N 2 was explored as an orthogonal solution to carbon mitigation, with N/C values >0.25 achieved and both sp 2 and sp 3 C–N bonding observed in the microstructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

MARVEL Instrumentation, Control, and Software Considerations

This paper details the various I&C considerations and design decisions made throughout the MARVEL (Micro-reactor Applications Research Validation and Evaluation) project, including sensor and actuator selection, safety-related functionality, digital control hardware and software, and testing methodologies. Key challenges such as managing radiation, temperature, and space constraints are discussed, along with the trade-offs between using standard equipment and custom solutions. The successful integration of off-the-shelf components, the emphasis on minimizing safety-related instrumentation, and the lessons learned from prototyping and testing are highlighted. The authors aim to provide insights that can benefit future micro-reactor designs and emphasize the importance of real-world testing in advancing reactor technology.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2022

High Flux Isotope Reactor Low Enriched Uranium U-10Mo Fuel Design Parameters

Activities to convert the HFIR from HEU to LEU are ongoing as part of the US Department of Energy (DOE) National Nuclear Security Administration (NNSA) nuclear nonproliferation mission. Design activities to study the conversion of HFIR from HEU to LEU fuel explored different fuel design features and shapes with a uranium-molybdenum (U-10Mo) monolithic alloy fuel. This high-density alloy contains 90 wt % uranium and 10 wt % molybdenum and has a uranium density of 15.318gU/cm 3 . The goal of these studies is to generate several candidate HFIR LEU fuel designs of varying fuel fabrication complexity that meet the current HEU performance metrics and safety requirements. Recent advancements in modeling and simulation tools and design methods enabled a thorough analysis of the available design space with U-10Mo fuel. A surrogate model used this analysis as training data to quickly determine the performance of a design given specific design parameters. An optimization module used this surrogate model to quickly search this multidimensional search space given specific desired performance characteristics. This approach was made possible by the large available design space with U-10Mo fuel. Shift, a Monte Carlo tool optimized for high-performance computing (HPC) architectures, was used for faster calculation and better data management for reactor physics simulations. Once most of these design studies were complete, a new suite called the Python HFIR Analysis and Measurement Engine (PHAME) was developed to connect all fuel design analysis steps, making design studies more efficient and reproducible. The post-processing capabilities of these new tools are leveraged for the information provided herein. Leveraging these tools, several candidate fuel designs were selected with varying levels of feature complexity and reactor performance. This report provides design feature details for four selected HFIR LEU U-10Mo fuel designs and their corresponding performance and safety metrics. Nominal best-estimate design parameters and irradiation conditions, including fission rate densities, power densities, heat fluxes, and cumulative fission densities, are provided. Simulations show that the high uranium density of U-10Mo fuel provides a large potential design space that enables various LEU designs to meet HEU core performance metrics and safety requirements with a power increase from 85 MW (HEU) to 95 MW or 100 MW (LEU).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Data-Driven Model Predictive Control for Temperature Management of Heat Pipe Microreactor

To enable the self-regulating capability of heat pipe (HP) microreactors, an anticipatory control strategy through model predictive control (MPC) could proactively respond to potential disturbances and deviations in operating setpoints. However, a key factor prohibiting the widespread adoption of MPCs in nuclear applications is the effort and computational costs associated with learning and calibrating first-principles-based process models when the target system is complex and when there are gaps between modeled and target reactor systems. In this paper, we demonstrate data-driven MPC using three approaches for modeling the system dynamics, including a linear state-space model, feedforward neural network, and recurrent neural networks long short-term memory. We present the development and validation process of each model and compare the performance of data-driven MPCs in controlling the temperatures of selected HPs at the evaporator and condenser regions in a 37-HP-monolith system. Our results show that, qualitatively, all data-driven MPCs are producing similar control actions, while quantitatively, with artificial neural nets (especially feedforward neural nets), MPC can better follow drastic changes in setpoints with smallest errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

First Report of the Nuclear Data Subcommittee of the Nuclear Science Advisory Committee

Accurate, reliable nuclear data is essential for the success of Federal missions such as nonproliferation, nuclear forensics, homeland security, national defense, space exploration, clean energy generation, and scientific research. Data access is also key to innovative commercial developments such as new medicines, automated industrial controls, energy exploration, energy security, nuclear reactor design, and isotope production. The United States Nuclear Data Program (USNDP) is the domestic custodian of nuclear data. In its April 2022 meeting, the DOE/NSF Nuclear Science Advisory Committee was charged with preparing two reports on nuclear data. In this first report, we review recent accomplishments of the USNDP and discuss complementary and collaborative international efforts. Detailed descriptions of nuclear data needs for basic science, nonproliferation, national security, nuclear energy together with medical and space applications are also presented. Lastly, a set of specific cross-cutting nuclear data needs with relevance for multiple applications areas are also identified for further discussion in a follow-on report planned for release at the end of January 2023.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

MOOGLE: A Multi-Objective Optimization tool for three-dimensional nuclear fuel assembly design

MOOGLE is a new genetic algorithm methodology for the three-dimensional design of nuclear fuel assemblies. MOOGLE uses common fuel rod types as the decision variable to develop a suite of three-dimensional fuel assemblies to provide optimized solutions to the design problem. Pressurized Water Reactor (PWR) fuel assemblies were optimized using IFBA and gadolinium (Gd 2 O 3 ) as burnable poisons in order to compare how burnable poison choice affects optimization results. Boiling Water Reactor (BWR) fuel bundles were also optimized using three unique fuel rod palettes to study how the size of the design space affects optimization results. Burnable poison analysis showed that utilizing IFBA and Gd 2 O 3 as burnable poisons produced the best and widest range of optimized solutions. Further, BWR fuel bundle optimization results indicate that the inclusion of additional fuel rod types produced a wider solution space but did not improve optimization results for regions explored using fewer unique fuel rods. These tests demonstrate MOOGLE's ability to analyze the tradeoffs between the inclusion of different fuel elements and their effects on assembly performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Overview of Wendelstein 7-X high-performance operation

The Wendelstein 7-X (W7-X) stellarator has completed two consecutive experimental campaigns OP 2.2 (Sep.-Dec. 2024) and OP 2.3 (Feb.-May 2025) under a new operational strategy enabling more than one year of uninterrupted device availability. This approach, supported by exceptionally high subsystem reliability, allowed sustained high-efficiency plasma operations with up to 80–100 discharges per day across a broad range of magnetic configurations. Several key technical upgrades-most notably the first operation of a 1.5 MW class steady-state gyrotron, a new steady-state pellet injector, and advanced real-time feedback control systems significantly enhanced heating, fueling, and plasma control capabilities. Together, these improvements enabled major advances in long-pulse performance, high-β operation, and confinement optimization. Long-pulse discharges achieved 1.8 GJ of injected energy under fully detached divertor conditions, while reduced-field scenarios facilitated record volume-averaged β values approaching 3%. High-performance plasmas with centrally peaked density profiles, created via neutral beam injection (NBI) or sustained pellet fueling, demonstrated strongly reduced turbulent transport and stellarator-record fusion triple products. Complementary studies of power exhaust and divertor heat loads revealed the role of scrape-off-layer drift physics in shaping strike-line patterns under attached conditions. Together, the results from OP 2.2 and OP 2.3 significantly expand the operational space of W7-X and strengthen its role as a leading platform for steady-state stellarator research and reactor-relevant plasma scenarios.

Wendelstein 7-X↗

DOE OSTI2026

Computational Thermal Hydraulics of a High-Performance Low-Enriched-Uranium Annular Target for HFIR Irradiation

Molybdenum-99 has historically been generated via isolation from fissioned highly enriched uranium (HEU) targets. Here, this isotope is in high demand due to its daily use across the world in radiopharmaceutical medical procedures. The primary objective of this work was to design and analyze an experimental target assembly containing one low-enriched-uranium (LEU) annular target for irradiation at the High Flux Isotope Reactor (HFIR). Efforts included incorporating spatially dependent energy sources from neutron and gamma interactions, quantifying thermal contact conductance at material interfaces, performing grid-independent studies, comparing turbulence models, and simulating various steady-state and transient scenarios relevant for irradiation qualification and eventual insertion. These models provide velocity, pressure, and temperature distributions in both space and time. Such results enable the selection of an appropriate irradiation location, fission rate density, and flow-limiting orifice size and demonstrate compliance with HFIR safety requirements such that insertion into the reactor can be approved. This analysis shows that across all scenarios, wetted surface temperatures remain below the coolant saturation temperature with no net vapor formation in the coolant. In every scenario, all components stay below 30% of the aluminum 6061 melting temperature. Computational fluid dynamics and system-level models predict peak target temperatures that agree within 4%, though the predicted axial location of the peak differs by about 10% of the heated length due to differences in flow development length. These results de-risk the irradiation of LEU (annular targets) and strengthen a domestic, HEU-independent 99 Mo supply by providing important fuel performance data to form the foundation for a robust licensing basis.

Molybdenum-99↗

DOE OSTI2023

Characterization of Aluminum Metal Powders for Plutonium-238 Program

As part of radioisotope thermoelectric generator (RTG) production for power sources in deep space exploration, Oak Ridge National Laboratory (ORNL) produces plutonium-238 ( 238 Pu). To produce 238 Pu, neptunium-237 ( 237 Np) targets are fabricated at ORNL and subsequently irradiated at the High Flux Isotope Reactor (HFIR) at ORNL and the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). Specifically, current flowsheets utilize neptunium dioxide ( 237 NpO 2 ) targets. Aluminum (Al) powder is blended with 237 NpO 2 target material to improve thermal conductivity during irradiation. The current composition of 237 NpO 2 /Al pellets (i.e., cermets, or ceramic–metallics) is 20% 237 NpO 2 , 70% Al, and 10% void space. Al powders utilized by the 238 Pu program are high-fired under vacuum before blending into targets. The primary objective of this work is to measure the physical, chemical, and thermal properties of Al before and after the high-firing process. Properties of interest include the morphology, surface texture, particle size, crystal phase(s), and thermal conductivity of the material. These properties are measured with existing materials characterization equipment at ORNL, including powder x-ray diffraction (pXRD), scanning electron microscopy (SEM) with energy-dispersive spectroscopy (EDS), laser flash analysis (LFA), and thermogravimetric analysis (TGA). A secondary objective of this work is to compare the Al powders before and after the high-firing procedure to determine the effects of high-firing on chemical, physical, and thermal properties and to determine the efficacy of the high-firing process.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Additively manufactured strain sensors for in-pile applications

Accurate, real-time monitoring of strain in fuel, cladding, and structural components of nuclear reactors is critical to better understand radiation induced phenomena during reactor tests and operations. The data provided is crucial to verify physics-based, multiscale modeling and simulation efforts, which aim to shorten the timeline for the development of new nuclear materials. Resistive strain gauges have limited performance during in-pile experiments due to the harsh operating conditions and limited physical space between fuel and cladding components. In this work, aerosol jet printing using silver nanoparticle inks was used to fabricate interdigitated electrode capacitive strain gauges on aluminum alloy 6061 tensile specimens. Here to simulate the temperatures of a traditional light water reactor, the capacitive strain gauges were tested with a mechanical test frame up to 300 °C and compared to commercially available bondable resistive strain gauges. The printed capacitive strain gauges exhibited a gauge factor of 1.0 and showed higher reproducibility and predictability of strain sensing performance than the resistive strain gauge. The results demonstrate the potential of aerosol jet printing to fabricate strain sensors with predictable performance and reduced invasiveness for high-temperature applications with confined spacing.

36 MATERIALS SCIENCE↗