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MontePy: a Python library for reading, editing, and writing MCNP input files.

The Monte Carlo N-Particle (MCNP) radiation transport code is a highly capable and accurate code with a long legacy. MCNP uses the Monte Carlo simulation process to simulate the path of particles (e.g., neutrons, photons, charged particles, etc.), and their interaction with materials. It is widely used in nuclear engineering, high-energy physics, and other fields. Its origins in the mid-twentieth century predate many modern software conventions. MCNP users provide an input file to MCNP, which it then uses to create an internal representation of the simulation problem. These input files originally had to be stored as punchcard decks, and the user manual still uses the terminology of cards and decks, despite moving beyond punchcards. MCNP predates nearly all modern human readable markup or data serialization languages, such as the extensible Markup Language (XML), the Standard Generalized Markup Language (SGML), YAML (YAML Ain’t Markup Language), and Javascript Object Notation (JSON). Due to this, MCNP uses an entirely custom defined syntax language for its input, making off-the-shelf libraries for XML, YAML, and JSON impossible to use for scripting various operations on MCNP input files (Kulesza et al., 2022).

97 - MATHEMATICS AND COMPUTING↗

Customer-Focused Key Performance Indicators for Electric Vehicle Charging

To systematically improve the public charging experience, EV charging industry stakeholders need to define and measure it precisely. Many stakeholders currently measure aspects of the charging experience, but they typically employ metrics that are either operational in nature, such as charger uptime and mean time between failures, or composite customer satisfaction indices. To improve the customer experience most effectively, the industry needs metrics that define the charging experience from the perspective of the customer, not business operations. Furthermore, industry practitioners need granular metrics to know what specific aspects of the charging experience need improvement. This report defines such customer-focused metrics, called key performance indicators (KPIs).

33 - ADVANCED PROPULSION SYSTEMS↗

Summary of INL Integrated Energy Systems Research for the Global National Laboratories Consortium on IES

The DOE Office of Nuclear Energy (DOE-NE) program on Integrated Energy Systems (IES) is led by researchers at Idaho National Laboratory (INL), and work is conducted in partnership with an array of other DOE laboratories, industry, and academia. IES research and development activities are additionally complimented by the DOE-NE Light Water Reactor Sustainability (LWRS) program, where work under the Flexible Plant Operations & Generation pathway supports analysis of opportunities for non-electric applications of current fleet nuclear plants and collaborates with multiple plants on near-term hydrogen production demonstration opportunities. The DOE-NE programs additionally partner with the Hydrogen and Fuel Cell Technologies Office under the DOE Office of Energy Efficiency and Renewable Energy to jointly fund the development of analysis tools, technologies, and nuclear-integrated hydrogen demonstration projects. This document provides a brief, high-level summary of IES work as contribution to the annual report for the Global National Laboratories Consortium on IES.

08 HYDROGEN↗

Entrapment Behavior of Solid Surrogate Fission Products at Engineered UN Nano‐Hetero‐Interfaces Within Metallic Nuclear Fuels

Nanometric hetero-interfaces provide a wealth of scientific and engineering opportunities due to their complex and often misunderstood properties that can differ from their respective bulk constituents. In this work, the ability for engineered nanostructures within a bulk U─Mo alloy to arrest simulant fission products is investigated experimentally and computationally. Nanostructured 90 wt% U/ 10 wt% Mo (U-10Mo) with 7.1 at% Nd is consolidated using spark-plasma- sintering (SPS) techniques and is heat-treated at 500 °C under vacuum for 24, 100, 500, and 1000 h. Analysis on the sintered and heat-treated U-10Mo reveals rapid kinetics in Nd diffusion to nanocluster sites, with evidence of Nd diffusion occurring during sintering and during the following heat-treatment. The segregation behavior of Nd at two different U─Mo/UN interfaces is computationally verified using density functional theory (DFT) to reinforce experimental data.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Challenges and Opportunities Specific to Microreactors: Compact and Light-Weight Shielding During Operation and Transportation

The problem of designing a shield for a mobile microreactor has been addressed. The principal challenges encountered in this endeavor are the dual goals of increasing radiation protection and decreasing weight. It is recognized that these two goals are contradictory. Increasing shielding naturally increases weight. Conversely, decreasing weight naturally calls for decreasing material inventory, including possibly decreasing shield mass. The operational and regulatory drivers for shielding and transportation constraints are identified and summarized. The main constraints pertain to volume, mass, radiation dose, material feasibility and availability, and decommissioning expectations. The latter are limits on residual contamination and dose rates after the reactor is removed. Progress toward solving the challenge of shielding a transportable microreactor is made by considering a tungsten tetraboride (WB4) shell surrounding the reactor vessel. The shield and a generic microreactor were modeled using the MCNP code. It was determined that the presence of a 16-cm-thick WB4 shield reduces the dose equivalent rate during operations to 3.6 mrem/h just outside of a concrete vault and dome and soil berm surrounding the reactor, which is very near the occupational dose rate limits. Without the WB4 layer, the dose rate at the same location outside the berm would be 120 mrem/h. Most importantly, the presence of the WB4 shield substantially protects the surrounding concrete and soil from activation, thus decreasing the duration of administrative control for the site following removal of the reactor from 16 to 3.4 years. At that point, the site may be decommissioned and returned to unrestricted public access. A limitation on the incorporation of a WB4 shield as an intrinsic component of a microreactor is that it results in a design that is transportable only by using the largest road conveyances and that the load would require special permits for transit through the U.S. highway system. New directions for further improvements and possibly more effective solutions to the shielding problem of a mobile microreactor are discussed in the conclusion section.

Microreactor↗

idaholab/cape2stix

This software allows for the conversion, extraction, and transformation of malware behavior data from "Malware Configuration And Payload Extraction" (CAPEv2) sandbox reports, to Structured Threat Information eXpression (STIX). This allows for further analysis to be performed, sharing of threat data, and transit to a graph database.

Cutshaw, Michael [Idaho National Laboratory (INL),↗

Plant Reload Optimization (prlo)

The PRLO framework is built on a modular and extensible architecture that tightly couples advanced evolutionary optimization algorithms with nuclear fuel depletion solvers (i.e., nuclear physics neutronics code). It supports exploring complex, high-dimensional design spaces constrained by user-specified operational, safety, and economic constraints. Objectives such as minimizing fresh fuel enrichment, flattening radial and axial power distributions, and maximizing discharge burnup are evaluated. PRLO’s equilibrium cycle optimization capability enables the identification of core configurations that maintain fuel cycle sustainability over extended planning horizons. Its integration with the RAVEN platform facilitates optimization of loading patterns or fuel shuffling schemes across multiple cycles. The interface with SIMULATE, a licensed industry-standard nodal code developed by Studsvik, ensures accurate neutronic and thermal-hydraulic feedback for reactor core design. PRLO’s automated workflow engine supports iterative design refinement, enabling utilities to streamline core design processes and meet evolving performance and regulatory targets.

Kim, Junyung [Idaho National Laboratory] (00090005↗

Predictive Modeling and Uncertainty Quantification in Condition Monitoring of Active Components: A Reactor Coolant Pump Use Case

This work develops data-driven models for onset of thermal barrier leakage in reactor coolant pumps. It incorporates uncertainty quantification to enhance the reliability and robustness of pre- dictions. Using synthetic data generated by the Generic Pressurized Water Reactor simulator, realistic degradation scenarios were simulated across lifecycle stages—beginning, middle, and end of life. Key variables, including differential pressure, flow rate, vibration, and temperatures, were analyzed using machine learning framework. The fully connected neural network models demonstrated exceptional performance, achieving R2 scores exceeding 0.99 and root mean square errors as low as around 8.23 × 10-2 gallon per minute (gpm) for the three stages of the lifecy- cle. UQ analysis further validated the model’s robustness, with narrow uncertainty bounds during steady-state operations and appropriately wider bounds during transitional phases, reflecting the physical behavior of the system. This work addresses important gaps in real-time condition moni- toring and regulatory compliance by integrating advanced condition monitoring technologies with UQ into IST programs. The ability to detect thermal barrier leakage early and quantify prediction reliability supports optimizing maintenance strategies while ensuring nuclear power plants’ safe and reliable operation.

99 - GENERAL AND MISCELLANEOUS↗

Microstructural Characterization of AGR-2 TRISO-coated Particle Buffer, IPyC, and Buffer-IPyC Interfaces

Investigating the microstructural, mechanical, and chemical behaviors of Tristructural Isotropic (TRISO) fuel particles is vital for its qualification and use in advanced reactors. Central to the study of TRISO particles is understanding the silicon carbide (SiC) layer's ability to confine fission products, with failure mechanisms linked to chemical degradation following mechanical degradation of the buffer and IPyC layers. Research has been done to quantify the micro-tensile properties of the buffer, inner pyrolytic carbon (IPyC), and buffer-IPyC interlayer regions and their interactions within both irradiated and un-irradiated TRISO particles. Techniques such as atom probe tomography (APT) and transmission electron microscopy (TEM) have also been deployed to examine microstructural defects and fission product distribution in detail. The goal is to understand layer delamination, establish connections between microstructure and mechanical attributes, and inform computational predictions of fuel performance. This work may help refine predictive models of TRISO fuel behavior and facilitating its certification for use in advanced reactors.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Impacts of molecular architecture on the radiation-induced degradation and reaction kinetics of hydrophobic diglycolamides with the solvated electron and the dodecane radical cation

Given their proposed use as trivalent actinide–lanthanide separation ligands, the role of molecular architecture on the radiation robustness of diglycolamide (DGA) molecules has been investigated. This study examined three prototypical molecules with differences in their aliphatic chain architecture: N,N,N′,N′-tetra(n-octyl)diglycolamide (TODGA), N,N,N′,N′-tetra(2-ethylhexyl)diglycolamide (T2EHDGA), and N,N′-dimethyl-N,N′-dioctyldiglycolamide (DMDODGA). Rate coefficients and activation parameters are reported for the reactivity of each DGA with the solvated electron (e solv − ) and the corresponding dodecane radical cation (RH˙ + ) over the temperature range of 10.0 to 44.1 °C. These measurements indicate that DMDODGA is the most chemically reactive with both transient radicals, which may be attributed to this molecule's more accessible backbone. Complementary gamma dose accumulation studies (≤ 600 kGy) under envisioned process conditions—50 mM DGA in n-dodecane solvent—afforded dose constants for the loss of DGA of d = (3.41 ± 0.07) × 10 −3 , (4.19 ± 0.09) × 10 −3 , and (4.65 ± 0.09) × 10 −3 kGy −1 for T2EHDGA, DMDODGA, and TODGA, respectively. These dose constants indicate that varying DGA architecture affords subtle differences in chemical reactivity, leading to varying rates of radiolytic degradation under envisioned actinide–lanthanide separation conditions. However, more ambitious DGA frameworks, such as modifying the backbone, branching of the aliphatic chains, and/or changing the size of the chain may be required for larger gains in radiolytic longevity while optimizing actinide–lanthanide selectivity.

Arrhenius parameters↗

Infrastructure and resource development needs to support a significant expansion of US nuclear capacity

In December 2023, the United States pledged at a United Nations conference to triple nuclear energy by 2050. In May of 2025 a new administration announced plans to quadruple nuclear energy by 2025, setting a new target that requires understanding the key infrastructure and resources needed to achieve large-scale deployment. This study attempts to quantify “what it takes” to deploy an additional 200 GWe of nuclear capacity. It projects demand levels for workforce, fuel, uranium mining and enrichment, waste management, supply chain, land, licensing, and water. Demand growth is also contextualized. For example, the peak number of construction workers required is approximately 215,000, a 37 % increase in the current US utility construction workforce. Up to 80,000 MT/year of mined uranium will be needed, necessitating a 60-fold increase in US mining production or a doubling of global mining if sourced externally. Advanced reactor fuels, uranium mining, and nuclear-grade equipment production would need substantial expansion. Operational workforce, enrichment needs, and licensing submissions also face significant increases. Although water consumption may see relatively lower increases, securing water rights poses unique challenges. This study consolidates various demand metrics in a broad context, highlighting the necessity of early preparations, such as workforce training, to support a tripling of nuclear energy. While it outlines the demand-side requirements, it does not assess the difficulties of ramping up or other supply-side issues. The findings also shed light on the impact of reactor size and reactor technology on various demand metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Integrated Molten Salt Reactor Modeling Capabilities in NEAMS Thermal Hydraulics Tools

The DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad range of advanced reactor concepts. The research and development approach under the thermal fluids technical area synergistically combines three length and time scales in a hierarchical multi-scale approach. To enable multi-scale thermal fluids capability using these codes, a key joint effort has been underway to develop an integrated system- and engineering-scale thermal fluids analysis capability, through integration of SAM and Pronghorn codes, both based on the MOOSE framework.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

RU-net for automatic characterization of TRISO fuel cross sections

During irradiation, phenomena such as kernel swelling and buffer densification may impact the performance of tristructural isotropic (TRISO) particle fuel. Post-irradiation microscopy is often used to identify these irradiation-induced morphologic changes. However, each fuel compact generally contains thousands of TRISO particles. Manually performing the work to get statistical information on these phenomena is cumbersome and subjective. Here, to reduce the subjectivity inherent in that process and to accelerate data analysis, we used convolutional neural networks (CNNs) to automatically segment cross-sectional images of microscopic TRISO layers. CNNs are a class of machine-learning algorithms specifically designed for processing structured grid data. They have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we generated a large irradiated TRISO layer dataset with more than 2,000 microscopic images of cross-sectional TRISO particles and the corresponding annotated images. Based on these annotated images, we used different CNNs to automatically segment different TRISO layers. These CNNs include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net performs best in terms of Intersection over Union (IoU). Using CNN models, we can expedite the analysis of TRISO particle cross sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Multi-species electrolyte migration kinetics with directed flow

Here, this paper investigates an electrochemical process designed to control mixing kinetics in liquid electrolytes. The process utilizes an electrochemical cell with anode and cathode chambers connected by a channel without a membrane. This configuration depletes multiple electroactive species in the cathode chamber while selectively replenishing them in the anode chamber. A key application is the removal of impurity species from the cathode chamber electrolyte and the selective replenishment of primary electroactive species in the anode chamber. Aqueous cell experiments were conducted to validate the theoretical model, and simulations were performed for molten salt electrolytes. This approach minimizes waste by reducing the need for additional electrolyte supplies and extends the utilization of anion species, contributing to environmentally sustainable electrochemical materials processing.

Electrochemical Process↗

Experimental results of conductive inserts to reduce nuclear fuel temperature during nuclear volumetric heating

Advanced fuel designs that incorporate thinner fuel UO2 pellets interspaced by high thermal conductivity inserts have been proposed, with the primary goals of reducing peak centerline temperatures and temperature gradients across fuel pellets and enhancing heat transfer from the fuel to the coolant. An initial series of experiments has been performed on this design, including laboratory experiments and a series of experiments using the Idaho National Laboratory (INL) Transient Reactor Test (TREAT) Facility, the latter of which compared thermal gradient driven fracture of standard pellet designs with that in the proposed advanced fuel design. Although reducing fracture is not the primary objective of the new fuel design, the lower thermal gradients are expected to reduce fracture, so it can serve as an indicator of the thermal behavior of this fuel in the reactor. The in-reactor tests were conducted at multiple linear heat generation rates and confirm the expected result that fracture in both the standard and advanced fuel pellets occurs during the first ramp to power in standard light-water reactor conditions. Post-irradiation examination of the experiment material was performed and included quantification of the extent of fracture in the fuel pellets. It was found that the advanced-design pellets reduce the extent of fracture in a statistically significant way. This confirms the expected behavior predicted by two-dimensional axisymmetric models of this experiment. Here in this study is an important first experimental confirmation of the efficacy of the proposed inserts for achieving their desired effect on the thermal behavior of the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

High-temperature steam oxidation study of irradiated FeCrAl defueled specimens

Post irradiation examinations (PIE) were performed on irradiated iron-chromium-aluminum (FeCrAl) specimens. These FeCrAl specimens were fabricated at the US Department of Energy's Oak Ridge National Laboratory (ORNL). The experimental setup involved subjecting FeCrAl cladding, along with UO 2 pellets, to irradiation in the Idaho National Laboratory Advanced Test Reactor (ATR). In parallel, the FeCrAl alloy tubing without UO 2 pellets was irradiated at ORNL's High Flux Isotope Reactor (HFIR). After irradiation, the ATR-irradiated rodlet was transported to an ORNL hot cell, where it was sectioned into multiple samples for the PIE and severe-accident testing. The sectioning process revealed that the fuel was not bonded to the cladding and could be easily detached from sectioned cladding slices. Microstructural analysis of the fuel cross sections demonstrated no significant interaction between the fuel and the cladding. Additionally, high-temperature steam oxidation tests on defueled cladding segments showed minimal oxygen uptake even at 1200 °C. Here, the ATR-irradiated specimens began to exhibit signs of enhanced oxidation upon reaching a temperature of 1300 °C. Furthermore, enhanced oxidation was observed on the inner surface of the ATR-irradiated FeCrAl specimen, which had been subjected to 1300 °C for a duration of 1 min. By contrast, high-temperature steam oxidation experiments indicated that the HFIR-irradiated FeCrAl cladding provided good thermal stability when exposed to 1300 °C for up to 4 h. Comparative analysis encompassing the oxidation behavior of the ATR-irradiated fueled FeCrAl, HFIR-irradiated unfueled FeCrAl, and unirradiated FeCrAl suggests that the fuel–cladding interaction, although not visible via standard microscale electron microscopy measurements, may accelerate the deterioration of FeCrAl cladding in beyond-design-basis accident scenarios.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Cracking in first ramp to power of standard versus high thermal conductivity UO2 pellets via internal nuclear heating

Advanced fuel designs that incorporate thinner fuel UO2 pellets interspaced by high thermal conductivity inserts have been proposed, with the primary goals of reducing peak centerline temperatures and temperature gradients across fuel pellets and enhancing heat transfer from the fuel to the coolant. An initial series of experiments has been performed on this design, including laboratory experiments and a series of experiments using the Idaho National Laboratory (INL) Transient Reactor Test (TREAT) Facility, the latter of which compared thermal gradient driven fracture of standard pellet designs with that in the proposed advanced fuel design. Although reducing fracture is not the primary objective of the new fuel design, the lower thermal gradients are expected to reduce fracture, so it can serve as an indicator of the thermal behavior of this fuel in the reactor. The in-reactor tests were conducted at multiple linear heat generation rates and confirm the expected result that fracture in both the standard and advanced fuel pellets occurs during the first ramp to power in standard light-water reactor conditions. Post-irradiation examination of the experiment material was performed and included quantification of the extent of fracture in the fuel pellets. It was found that the advanced-design pellets reduce the extent of fracture in a statistically significant way. This confirms the expected behavior predicted by two-dimensional axisymmetric models of this experiment. This study is an important first experimental confirmation of the efficacy of the proposed inserts for achieving their desired effect on the thermal behavior of the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Lowering the barrier to access information-rich transient kinetic data for machine learning methods

Transient kinetic data contain a wealth of information about intrinsic features of a catalyst as well as the reaction mechanism. Currently, high volume transient data is underutilized, and data science methods could both increase the value of information that can be extracted from this data, integrate experimental with theoretical data sources, and accelerate the pace of catalyst technology advancement. Transient kinetic characterizations with simple probe molecules exhibiting reversible adsorption, irreversible adsorption and bulk-surface diffusion are presented as training components for similar experiments with more complex surface reactions. In conclusion, by increasing the availability and accessibility of transient kinetic data through details of its structure and acquisition, we aim to decrease the barrier for data scientists to apply machine learning methods to this valuable data source.

Catalysis↗