Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “IDAHO NATIONAL LABORATORY”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

TEM characterization of two variants of fuel cladding chemical interaction in a HT-9 Clad U-10Zr Fuel. Variant 1: FCCI with a Zr Rind

Here, this study investigated the fuel cladding chemical interaction (FCCI), a key factor that limits operational temperature and burnup, in an HT-9 clad U-10Zr nuclear fuel sample irradiated to a high burnup of 13.1 at.% at a time-averaged peak inner cladding temperature (PICT) of 530 °C. Previous results showed this fuel sample exhibited two distinct levels of FCCI at d. This paper analyzed the FCCI at an azimuthal position showing an interdiffusion layer of <10 µm using transmission electron microscopy to examine chemical and crystallographic nature of phases at the fuel-cladding interface at the nanoscale level. A ZrC layer and a Zr 3 Si phase were identified at the interface; these, along with the relatively low local temperature, potentially contributed to limit interdiffusion, behaving as inhibitors for deleterious interactions. Lanthanides (Ln) partially consumed the ZrC layer and interacted with Fe, forming a Zr-Ln compound and a (Zr,Ce)Fe 2+x phase while also infiltrating up to 4 µm into the cladding. Neither U nor Zr were observed in the cladding, whereas Fe diffused up to 3–5 µm in the fuel. Fe infiltration formed a ternary U-Zr-Fe ε-phase and likely promoted the precipitation of a Cr-rich α’ phase on the cladding interface. Additionally, a Cr-rich χ-phase, likely formed by the dissociation of pre-existing M 23 C 6 carbide precipitates, was identified about 2–5 µm from the fuel-cladding interface. Irradiation-induced nano-voids were also observed in the HT-9 bulk. These findings provide critical insights into FCCI mechanisms at representative irradiation conditions, essential for developing models simulating in-pile metallic fuel behaviors for next-generation reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Improving Dose Modeling With Dynamic Modeling Tools [Slides]

Utilities aiming for higher fuel enrichment for power uprates or extended operation times before refueling must conduct a new dose analysis. Current conservative dose estimation standards may cause utilities to exceed regulatory limits for proposed increased fuel enrichment. A more accurate modeling of doses from reactor accidents can lower these conservative assumptions. Prescott et al. (2022) demonstrated that the Event Modeling Risk Assessment using Linked Diagrams (EMRALD) software tool, developed at Idaho National Laboratory (INL), can be coupled with the Modular Accident Analysis Program (MAAP5) for dynamic accident analysis in reactor plants. EMRALD forms models of potential accident scenarios, while MAAP5 simulates the accident progression and dose consequences. By integrating these software tools with utility-specific data, a more precise estimation of dose consequences from plant accidents can be achieved. Preliminary findings indicate that EMRALD provides accurate mean core damage frequencies for generalized accident scenarios. Future work includes expanding the model to account for plant-specific data and mitigation factors.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Unattended Monitoring of Uranium Holdup with Scintillating Fibers

This work evaluated the use of scintillating fiber (SciFi) radiation sensors as a cost-effective, unattended monitoring technique for uranium holdup accumulation in reprocessing equipment. With ruggedized packaging and an outer diameter of less than 1 cm, scintillating fibers offer deployment flexibility. Additionally, plastic scintillating fibers coupled with standard optical fibers provide an affordable option to monitor locations kilometers away from a localized control room or data acquisition (DAQ) system. These combinations of characteristics along with their relatively low manufacturing costs make scintillating fibers ideal for installation at key measurement points such as pipes, valves, and filtration systems.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Material Characterization Report of EBR II Mark IV Fuel Element

The focus of this report is the characterization of an unirradiated as-built fuel element from the Experimental Breeder Reactor II (EBR-II) Mark IV driver fuel design. The fuel in this element is a metallic uranium-zirconium alloy, and the cladding material is HT9 stainless steel. Both the metallic fuel and cladding materials are characterized, including chemical composition, grain size, morphology, phase composition, precipitate composition, crystallography, density, and hardness.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Predicting the evolution of biomass bulk density through feedstock preprocessing: Discrete element modeling, regression analysis, and pilot-scale validation

Bulk density is an important material property of biomass feedstocks, influencing handling, storage, transport costs, and conversion efficiency. In this study, predictive regression models for loose and tapped bulk densities of Alamo and Cave-in-Rock switchgrass are developed using a comprehensive dataset generated via calibrated bonded-sphere discrete element method (DEM) simulations. Here, a key contribution of this study is the use of a DEM-based approach, which correlates density with moisture content and particle size distribution parameters and enables analysis across a continuous particle size range, overcoming limitations of purely experimental data. For comparison, regression models are also developed using only experimental data from pilot-scale runs at the Biomass Feedstock National User Facility at Idaho National Laboratory. Validation against pilot-scale data showed reasonable prediction accuracy for both model types, particularly for smaller particle sizes (post-secondary grinding). While the experimental model showed slightly better performance matching the validation data in some cases, the DEM-based model benefits from a much larger dataset, reduced predictor multicollinearity, and continuous parameter coverage, highlighting the utility of validated simulation models for developing robust predictive tools for biomass preprocessing applications.

09 - BIOMASS FUELS↗
DOE OSTI2025

Behavior of the Cadmium Pool in the INL Mk-IV Electrorefiner

The Mk-IV electrorefiner has been in service since 1996 recovering uranium from spent fuels from the Experimental Breeder Rector II and Fast Flux Test Facility sodium-cooled fast reactors. The electrorefiner vessel includes a cadmium pool beneath the salt. The voltage signal between the cadmium pool and reference electrode (Ag/AgCl type) provides information about the chemical condition of the cadmium pool with respect to uranium and zirconium saturation. This information is used to guide process control and sampling decisions. This paper describes how the voltage signal is related to chemistry by the analyses of data from Mk-IV operations and confirmatory experimentation.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

The Radiation-Induced Fate of Fission Product Iodine in Molten Salts

Understand and Predict Radiation-Induced Iodine Speciation, Chemistry, and Transport in High-Temperature Molten Salts Award Number: DE-AC07-05ID1451 Gregory P. Holmbeck (Gregory.Holmbeck@inl.gov), Center for Radiation Chemistry Research, Idaho National Laboratory, 1955 N. Fremont Avenue Idaho Falls, ID, 83415, USA. Project Scope The goal of this Chemical and Materials Sciences to Advance Clean Energy Technologies and Low-Carbon Manufacturing project is to understand and predict the radiation-induced speciation, chemistry, and transport of fission product iodine in the triumvirate extremes of high-temperature, ionizing radiation, and corrosive molten salts. This missing fundamental information is critical for the accelerated development and deployment of safe, clean nuclear energy based on molten salt reactor (MSR) and pyrochemical reprocessing technologies. The central hypothesis driving this research is, the radiation-induced conversion of iodide will yield an extensive suite of transient and steady-state iodine radiolysis products that will alter the bulk chemical and physical properties of the irradiated molten salt system—the speciation, distribution, and chemical transport of which will be dictated by the composition and the availability of multivalent metal cations and metal alloy interfaces. To test this hypothesis, this project initiated three synergistic Research Objectives: (1) determine how the inclusion of iodine/iodide influences the chemical and physical properties of complex molten salt mixtures; (2) elucidate the speciation and fundamental chemical behavior of transient and steady-state iodine/iodide species formed by the irradiation of molten and solid salt mixtures; and (3) understand the influence of interfacial processes on determining the final disposition of iodine in high temperature molten salts, notably the structure and chemical speciation of iodine at metal-salt interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Microreactor Optimization Using Simulation And Economics (mouse)

Microreactor Optimization Using Simulation and Economics (MOUSE) is a tool that integrates both nuclear microreactor design and reactor economics to provide comprehensive evaluations and optimizations. This tool enables stakeholders to explore the interplay between technical and economic variables, guiding them towards effective and competitive microreactor solutions. For the reactor core simulations, MOUSE leverages the OpenMC Monte Carlo Particle Transport Code to perform detailed core simulations for various microreactor designs. The included OpenMC models are 2D core designs of a Liquid Metal Thermal Microreactor (LMTR), a Gas-Cooled TRISO-Fueled Microreactor (GCMR), and a Heat Pipe Microreactor. Beyond core design, MOUSE includes simplified calculations for: - Calculating the masses of heat exchangers within the system. - Mechanical power of pumps. - Estimating the area occupied by various buildings within the nuclear plant. For the economic analysis, MOUSE provides detailed bottom-up cost estimates, encompassing a wide range of costs including preconstruction costs, direct costs, indirect costs, training costs, financial costs, operation & maintenance (O&M) costs, and fuel costs. These cost estimations are developed using data from the MARVEL project and additional literature sources, enabling the calculation of total capital costs and levelized cost of energy for both first-of-a-kind and nth-of-a-kind microreactors. MOUSE also enables analysis of the cost drivers and competitiveness in the electricity market. MOUSE allows users to modify a wide array of technical and economic parameters to evaluate different scenarios and their impacts. Examples of these parameters include: Fuels, coolants, or reflector materials Enrichment levels Control drum materials and geometry Fuel pin geometry and materials Moderator pin geometry and materials Reactor core and reflector dimensions Packing factor for the TRISO particles Nuclear reactor power and reactor burnup Number of sensors Shielding thickness Reactor vessel and guard vessel dimensions Operational staff requirements Number of emergency shutdowns Levelization period Interest rate Construction duration Since MOUSE is powered by the WATTS toolkit, it supports optimization studies, parametric analyses, and uncertainty calculations/propagation. The optimization techniques enable users to identify optimal design and economic configurations. The parametric analysis tools allow users to explore the sensitivity of various parameters, while uncertainty propagation helps quantify the impact of uncertainties on overall performance and cost. User Interface and Workflow: Currently, MOUSE is a command-line-based tool. Users can input various reactor design or economic parameters, modify the designs, run simulations, and visualize results through comprehensive data visualization and reporting capabilities. The typical workflow involves setting up the reactor model, defining economic parameters, running simulations, and analyzing the results to make informed decisions. By combining advanced design calculations with detailed economic modeling, MOUSE provides a robust framework for optimizing nuclear microreactor technologies, enhancing their competitiveness, and guiding stakeholders towards innovative and cost-effective solutions.

Hanna, Botros [Idaho National Laboratory (INL), Id↗
DOE OSTI2024

Fracture behavior of irradiation induced nanocrystalline UO 2 studied by in-situ mechanical testing in transmission electron microscopy

Uranium Dioxide (UO 2 ) is widely used as a fuel in current light water reactors (LWRs). Upon accumulation of radiation damage, LWR UO 2 fuel pellets start to develop a different microstructure at the pellet periphery when fuel burnup exceeds 45–50 GWd/tHM. The resulting porous, nanocrystalline microstructure is one of the most prominent microstructural changes occurring in such fuel. Its fracture mechanisms, which causes fuel fine fragmentation, could impact safety limits when the cladding breaches. Direct measurements of these properties are challenging, therefore a surrogate obtained via ion irradiation can be used. In this study, multiple microcantilevers were fabricated by focused ion beam from both fresh UO 2 and UO 2 irradiated with 84 MeV Xe 26+ ions to a peak dose of 1357 displacements per atom (dpa). Further, the irradiation produced a pseudo high burnup structure approximately 2 µm below the surface. In-situ nano-mechanical bending tests were conducted to investigate the fracture behavior and the effect of the surrogate UO 2 high burnup structure on local fracture properties. Fresh UO 2 fuel was observed to fracture in transgranular mode without nucleation or movement of dislocations. However, the Xe-irradiated nanocrystalline microcantilevers fractured along the grain boundaries, with no influence from the pre-existing micro-cracks in the microcantilever. Fracture toughness for this type of surrogate high burnup UO 2 structure is reported for the first time in literature. Both the fracture stress and toughness show degradation for UO 2 as a result of Xe-irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Data Management for Digital Twin Implementation: Enhancing Existing SCADA Architecture for INL's CITRC Test Distribution System

The United States power grid will continue to experience stress from aging infrastructure, extreme weather, and increasing loads. In order to strengthen resiliency, researchers need to run tests and simulations that model real-life infrastructure. Idaho National Laboratory (INL) is creating a digital twin of its Critical Infrastructure Test Range Complex (CITRC). CITRC is an at-scale grid testbed which can be configured in utility-realistic distribution scenarios for a variety of tests, such as advanced grid protection and control. A digital twin of this infrastructure would support in-depth tests/simulations without risking physical consequences, before trialing devices under test at-scale. This project focuses on the data acquisition part of constructing a digital twin. It investigates the Supervisory Data Acquisition and Control (SCADA) system of CITRC and explores ways to utilize this system for the twin. Future “ideal” at-scale implementations such as upgraded equipment, modern communication protocols, and automation applications are also explored.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Effect of particle size and moisture on flow performance of loblolly pine anatomical fractions: Experimental findings and model predictions

The rising energy demand has highlighted biomass as a promising next-generation energy source. However, commercializing biomass-derived energy faces challenges, particularly in handling biomass feedstock. Factors like particle size, shape, moisture content, and surface roughness significantly impact biomass flowability. This study addresses a crucial knowledge gap by examining the effects of particle size and moisture content on the flow behavior and shear properties of different anatomical fractions of loblolly pine (Pinus taeda). The bulk shear behavior was examined using a Schulze ring shear tester, while flow performance was tested through gravity-driven flow experiments in a variable wedge-shape hopper. Results were incorporated into empirical and machine learning-based flow prediction models to evaluate their accuracy and limitations. The study found that samples with higher moisture content show higher unconfined yield strength. The critical arching distance increased with particle size, e.g., from approximately 13 and 33 mm for 2- and 6-mm whole chips, respectively at a 32-degree inclination angle. Conversely, the flow rate decreased for a given hopper opening as particle size increased. For instance, at a 60-mm hopper opening and a 32-degree inclination angle, the mass flow rates for 2- and 6-mm whole chips were 7.83 and 6.42 tonne/h, respectively. The empirical model consistently overpredicted the mass flow rate for all anatomical fractions, while the machine learning model more accurately predicted the central tendency of flow rate but was insensitive to varying tissue proportions. These novel findings provide comprehensive characterization of anatomical fractions, reveal significant combined effects of particle size and moisture content on biomass flow behavior, and demonstrate a better predictive accuracy of a machine learning model, all of which are useful for optimizing material handling strategies and biomass utilization technologies in the industry.

09 - BIOMASS FUELS↗
DOE OSTI2025

Decayheatml

This code is designed to predict and analyze the decay heat generated in molten salt reactors (MSRs) using a hybrid approach that combines machine learning and segmented polynomial fitting. The accurate prediction of decay heat is essential for reactor safety and the optimization of spent fuel storage. The code operates through several key components: 1) Data Architecture: It incorporates a modular data architecture that handles various MSR-specific operational parameters such as power density, humidity content, and air ingress. These parameters are sampled using Sobol sequences to ensure comprehensive coverage of operational uncertainties. 2) Machine Learning Framework: The code employs a diverse set of machine learning models, including polynomial regression, decision trees, random forests, gradient boosting, support vector regression, k-nearest neighbors, multi-layer perceptrons, and symbolic regression. These models are trained to predict decay heat over a wide temporal range, from immediate shutdown up to 10,000 years. 3) Region-Optimized Training: The temporal domain is divided into multiple regions, each modeled separately to capture distinct decay heat characteristics across different time scales. This approach significantly improves the accuracy and interpretability of predictions. 4) Segmented Polynomial Interpretation (SPI): The SPI method translates machine learning predictions into piecewise polynomial equations. These equations are physically interpretable and can be directly integrated into existing engineering workflows and safety analyses. 5) Front-End Interfaces: The code includes both a Jupyter notebook interface for research development and a Streamlit web application for operational deployment. These interfaces allow users to interactively explore decay heat predictions, adjust operational parameters, and visualize results in real-time. 6) Applications: The framework supports various applications, including safety system validation and spent fuel container optimization. It enables real-time evaluation of worst-case decay heat scenarios, informing the design of passive safety systems and optimizing container designs for long-term storage. Overall, this code provides a robust, accurate, and user-friendly tool for predicting decay heat in MSRs, enhancing reactor safety, and optimizing spent fuel management.

Retamales, Mauricio Eduardo Tano [Idaho National L↗
DOE OSTI2026

FY27 Annual LDRD Call for Proposals - external release

Proposals are now being accepted for the fiscal year 2027 (FY-27) Laboratory Directed Research and Development (LDRD) call, the FY-27 Annual LDRD Call for Proposals. Idaho National Laboratory (INL) has renewed its research and development (R&D) portfolio to align with its strategy, and this call seeks high-quality proposals that address these renewed research priorities. The LDRD Office encourages proposals that offer the potential to achieve breakthroughs in the three science and technology (S&T) strategic initiatives: • Unleashing America’s Energy Abundance: Enabling the Quadrupling of Nuclear Power by 2050; • Securing America’s Future by Developing Domestic Supply Chains for Critical and Strategic Minerals and Materials (CSMM); and • Delivering Critical National Security Technology. Proposals that support INL’s four strategic thrust areas are also encouraged: • Enabling Future Fusion Energy Systems; • Delivering Small Nuclear Reactor Technology for Space Exploration and Defense Missions; • Accelerating Technologies for Hybrid Energy and Nuclear Applications; and • Securing America’s Energy Future Through Artificial Intelligence (AI).

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Synergistic torrefaction of plastic polymers and biomass

This study explores the synergistic torrefaction of biomass and plastics, aimed at enhancing bioenergy production and promoting a circular economy. By leveraging the unique properties of both materials, we investigated the thermochemical transformations occurring during the torrefaction process, from material preparation to the final characteristics of the torrefied product. The biomass used included corn stover (CS) and loblolly pine (LP), while various plastics were categorized from #1 to #7. Torrefaction was conducted at temperatures of 200, 225, and 250 °C, with subsequent extrusion of the torrefied materials and raw materials to produce composite filaments. The results show a consistent decrease in mass yield with increased torrefaction temperature, with notable variations among different biomass-plastic combinations. Co-torrefaction of biomass with polyvinyl chloride and polypropylene resulted in accelerated reaction kinetics, with an observed mass loss rate increase of 15 % at 250 °C compared to the expected rates for individual components. This synergy was quantified, indicating a 20.3 % increase in mass loss for the loblolly pine-polypropylene combination and 23.9 % for corn stover-polypropylene. In contrast, other plastics, including polyethylene terephthalate, high-density polyethylene, low-density polyethylene, polystyrene, and polycarbonate, did not exhibit significant synergistic effects. Mechanical testing indicated that the torrefaction process alters the strength and brittleness of the resulting materials, with implications for their application in bioenergy production and bio-renewable materials. Overall, this research highlights the potential of synergistic torrefaction as a viable strategy for co-processing biomass and plastics, paving the way for innovative solutions in waste management and renewable energy resource development.

09 - BIOMASS FUELS↗
DOE OSTI2025

Refining NEAMS MARVEL Reactor Model Accuracy

This report outlines the progress of Idaho National Laboratory (INL) in improving the fidelity of the multiphysics model of the Microreactor Applications Research Validation and Evaluation (MARVEL) reactor developed in FY24. The multiphysics model firstly developed in FY24 leverages three single-physics models coupled via the MOOSE’s MultiApps and Transfer systems. The first single-physics model, that functions as the driver application, leverages Griffin to model the neutron transport in the core through the discontinuous finite element (DFEM) discrete ordinates solver (SN). The second single-physics model uses BISON to compute the solid temperature in the reactor. Finally, the System Analysis Module (SAM) was used to model the flow of the sodium-potassium eutectic in the primary loop. In this report we detail the following improvement and enhancements: • An updated mesh leveraging the latest feature in the reactor module (see Section 3.1.).

42 - ENGINEERING↗
DOE OSTI2024

Selection and Ranking of Experiments from the Halden Database in support of Multiscale Model Validation

Validating fuel performance codes, such as BISON, requires an extensive amount of experiments covering a wide range of operating conditions and fuel types. Within the light-water reactor (LWR) space, there have been several international experimental programs that have contributed to the wealth of available experimental data available for use. One of those international programs, the Halden Reactor Project (HRP), began in 1958 and utilized the Halden Boiling Water Reactor to conduct many highly instrumented experiments until the reactor closed in 2018. Idaho National Laboratory, through the U.S. Department of Energy, has utilized several Halden experiments to perform the initial validation of the BISON code based upon their inclusion in international modeling and simulation benchmarks. Recently, the HRP has provided member organizations a complete copy of all available data, reports, and presentations since the HRP began. This report provides an initial exploration of the data available in the database for use in validating the multiscale models under development in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program for LWR applications. Ranking tables that identify potential validation cases are provided for the high priority models of interest. It was found that some of the recommended high priority experiments correspond to additional rods in existing assemblies already available in the BISON validation suite. It is expected that several of these cases will be incorporated into future NEAMS milestones in the fuels technical area for increased validation of BISON.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

MegaWatt Mayhem: Grid Operator Challenges Center Loads

This report provides a summary of the challenges faced by United States electricity grid operators in accommodating and anticipating the rapid deployment of large loads, particularly data centers, based on academic literature and industry working groups. The report highlights the unique requirements and operational characteristics of data centers, which differ significantly from traditional industrial loads. Key issues addressed utility planning considerations, with emphasis on the implications for grid operators, impacts to normal operations for grid operators, reliability considerations during periods of grid stress, and resilience considerations for the changing operational paradigms based on data centers. Real-world examples are used to highlight these challenges and the changes that grid operators must address. The findings underscore the necessity for coordinated efforts and innovative solutions from both grid operators and regulatory bodies to ensure the stable integration of large loads into the grid. This report is the first in a series that will explore the challenges of data center deployments based on several key power system perspectives.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Advanced Transmission Technologies (ATTs) Supplier Cohort Workshops Cohort Summary [Slides]

This Summary slide deck summarizes the key outcomes of the Advanced Transmission Technologies (ATTs) supplier cohort, part of Idaho National Laboratory’s (INL) Technical Assistance for Digital Assurance (TADA) program. The program aimed to strengthen grid resilience through cybersecurity controls, supply-chain security, and Cyber-Informed Engineering (CIE) for advanced transmission technologies. The cohort brought together vendors representing the full range of Grid-Enhancing Technologies (GETs), including providers of Dynamic Line Ratings (DLR), Advanced Power Flow Control (APFC), Transmission Topology Optimization (TTO), and High-Performance Conductors (HPCs). Discussions focused on institutional, integration, and operational barriers limiting GET adoption; cybersecurity risks at EMS/SCADA, cloud, and network integration points; and supply-chain transparency issues such as semiconductor dependence and SBOM/HBOM expectations. Participants also addressed operator trust, human-in-the-loop requirements, and challenges with utility adoption, while exploring how CIE can support secure deployment of GETs. This deck represents a consolidated summary of challenges and risks identified by vendors, cross-cutting themes and technology-specific insights from three cohort workshops, and actionable mitigations to guide utilities, vendors, and the Department of Energy in advancing secure, trusted deployment of GETs.

24 - POWER TRANSMISSION AND DISTRIBUTION↗