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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Droplet Entrainment in Steam Supply System of Water-Cooled Small Modular Reactors: Experiment and Modeling Approaches

Droplet entrainment in steam-flow is a prominent phenomenon that needs adequate safety and risk analysis of postulated transient and accident scenarios—including experimental investigation and representative modeling and simulation (M&S)—for small modular reactor (SMR) system design and demonstration. This study identifies knowledge gaps by evaluating experimental and computational fluid dynamics modeling approaches to support early-stage reactor system design, testing, and model evaluation. Previous studies reported in the literature for steam-flow entrainment primarily focused on gigawatt capacity pressurized water reactor (PWR) systems. However, entrainment phenomena are even more prominent for PWR-type SMRs due to their more compact integrated designs, which need further research and development. To fill the research gaps, this study provides insight by specifying the phenomena of interest by leveraging the lessons learned from past research, adopting advanced M&S techniques and advanced instrumentation and control. The findings and recommendations are applicable for evaluating steam-flow entrainment models and for designing integral effect test and separate effect test facilities for gaining reactor design approvals.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

High-Fidelity and High-Performance Computational Simulations for Rapid Design Optimization of Sulfur Thermal Energy Storage

Industrial process heating (IPH) accounts for approximately 70% of US manufacturing energy use and is primarily produced by fossil fuel combustion. Approximately 1500 TWht (approximately 60%) of IPH demand is in the temperature range of 100-300. Industrial applications in this temperature range include drying, hydrothermal processing, thermal enhanced oil recovery, food and beverage, bioethanol production, etc. Cost-effective thermal energy storage (TES) that increases the utilization of waste and renewable heat (solar, geothermal, etc.) could provide significant energy savings and reliable heat sources, decrease emissions, and increase US manufacturing competitiveness through reductions in fuel consumption. TES development has historically been dominated by technologies suitable for deployment with concentrating solar power (CSP). State-of-the-art thermal storage deployed commercially with power tower CSP plants uses a 60%/40% NaNO3/KNO3 molten salt and operates between temperatures of approximately 280 degrees Celsius and 570 degrees Celsius using a two-tank configuration. However, these nitrate salts are unsuitable for operation outside of this temperature range due to a high freezing point of approximately 220 degrees Celsius, and limits on high-temperature salt stability and corrosion resistance of containment alloys. Other materials being investigated for TES include those based on: (1) sensible energy storage (various molten salt compositions, inert solid particles, rocks or pebble beds, sulfur, water, concrete, graphite, etc.), (2) latent energy storage in materials that undergo solid-liquid phase change at relevant temperatures (organic materials for low-temperature applications, inorganic salts and/or metals for high-temperature applications), or (3) thermochemical energy storage (hydrides, hydroxides, carbonates, metal oxides, etc.). The application temperature and challenges pertaining to storage material and/or containment cost, energy density, long-term thermal and cyclic stability, and charge/discharge heat transfer effectiveness drive material selection for a given IPH or electricity generation application. Sulfur is a cheap commodity at $80/ton compared to $1100 - 1300/ton for conventional salts. When using a metric of storage cost per kWh, sulfur costs around 2-3 $/kWh. Previous sulfur TES development focused on high temperature (>600 degrees) concentrated solar power applications with sulfur encapsulated in pipes and flow of gaseous HTF (air) in the shell side. However, for lower-temperature IPH applications in the range of approximately 100-300 degrees Celsius Element 16 adopted a compact and scalable TES design with molten sulfur in the shell and HTF pipes submerged in the molten sulfur bath. The low-cost molten sulfur TES for dispatchable IPH has deployment potential for broad applications. The spatial and temporal evolution of the HTF and sulfur temperature is critical to the TES system performance, and thus detailed modeling can improve understanding of the performance and facilitate design improvements. Using high performance computing and computational fluid dynamics (CFD) a low-cost molten sulfur thermal energy storage (TES) system for industrial process heating (IPH) applications was developed. The unique challenges in CFD modeling of sulfur TES are the sharp property changes of sulfur relevant to the working temperatures. Above 159, liquid sulfur undergoes polymerization, and the viscosity of sulfur rapidly increases by several orders of magnitude between 159 degrees Celsius and 188 degrees Celsius, followed by a decrease in viscosity beyond 188 degrees Celsius due to thermal bound dissociation. In addition, various concentrations of H2S impurities can also modify sulfur viscosity. This numerical challenge is especially relevant to transient simulation of the sulfur TES charging and discharging processes as the extreme property variations limit the applicability of traditional heat transfer correlations. Transient CFD simulations including the temperature-dependent sulfur properties and geometric complexity of the TES design were used to predict the effect of natural convection during charging and discharging on the heat transfer process, sulfur temperature uniformity, charge/discharge rates, and performance of the storage devices. The CFD model was validated with experimental results for a full charge and discharge cycle. The work will show 3D and 2D simulation comparisons aimed to facilitate rapid design iterations and a machine learning based design optimization approach.

CFD↗
DOE OSTI2025

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Recent Improvements in Pronghorn for Advanced Reactor Modeling

Pronghorn is a thermal-hydraulics computational tool developed using the Idaho National Laboratory's Multiphysics Object-Oriented Simulation Environment (MOOSE). It is designed to support Computational Fluid Dynamics (CFD) modeling, ranging from subchannel and porous media analysis to Reynolds Averaged Navier-Stokes (RANS) turbulence modeling. As an integral part of the MOOSE-based suite of tools, Pronghorn seamlessly couples with other MOOSE-based applications to simulate a variety of physical phenomena. This article highlights recent significant enhancements to Pronghorn's CFD modeling capabilities and demonstrates their application to advanced nuclear reactor designs. The recent improvements in Pronghorn primarily focus on modifications to its turbulence modeling capabilities, near-wall corrections and numerical schemes. In terms of turbulence modeling, the two-equation $k-\epsilon$ and $k-\omega$ SST models have been implemented and validated with both equilibrium and non-equilibrium wall treatments. Additionally, corrections for wall roughness, and curvature, and wall-channeling in pebble beds have been introduced in the near-wall modeling. These developments enable more accurate simulations of advanced nuclear reactors. Two case studies are presented in this work: a pool-type Molten Chloride Reactor and a salt-cooled Pebble-Bed High Temperature Reactor. In both cases, the previous models in Pronghorn are compared with the new implementations, demonstrating the improved accuracy achieved with the updated models.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer Based Hydrogen Production Facility

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at NREL's Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗
DOE OSTI2026

Seawater Acidification and Bubble Plume Dispersion from Accidental Subsea CO 2 Pipeline Rupture: A Multiphase CFD Study

If a CO 2 reservoir or transmission pipeline were to leak, both the surrounding ecology and maritime traffic safety could be put at risk. To better understand and prepare for this risk, multiphase Computational Fluid Dynamics (CFD) models were built in ANSYS Fluent to capture the behavior of a leak once it enters the water. A 3D Eulerian–Eulerian model was used for validation, while a simplified 2D model was applied to simulate conditions at a 50-m depth. The models integrate bubble dynamics, gas holdup, CO 2 dissolution, dissolved species transport, and seawater acidification into a unified CFD framework. Mass transfer was calculated using the Hughmark correlation, and local seawater temperature and salinity were factored in to determine dissociation behavior and the relevant Henry’s Law constant. To confirm the 3D model’s accuracy, results were checked against two experimental datasets: the QICS field study and the Hauser Tank experiments. The team also modeled a hypothetical release scenario at the High Island 10L site and compared the results with earlier published work. The results show that at a depth of 50 m, the surrounding water column can completely absorb a CO 2 release at a rate of 35 kg/s, since the gas dissolves into the seawater as it rises toward the surface. Beyond confirming this mitigation capacity, the simulations shed light on how a leak would actually unfold in the environment, including the shape and movement of the rising bubble plume, how much CO 2 dissolves along the way, and the resulting shifts in seawater pH and pCO 2 . Together, this provides a practical framework for assessing how CO 2 leaks could affect marine environments in the Gulf of Mexico.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Prototype Modeling for a Light-Trapping Planar-Cavity Enclosed Particle Solar Receiver

Concentrating solar thermal (CST) systems present a promising avenue for affordable and reliable energy production. Solar receivers are key components that determine the efficiency and longevity of these systems. Particle-based solar receivers have emerged as a compelling alternative to traditional technologies, offering several advantages that address limitations in current CST systems. This is especially true as next-generation CST technologies target applications including electricity generation, thermochemical processes, and industrial process heat, many of which necessitate higher operating temperatures than current commercial molten salt systems. Molten-salt thermal energy storage (TES) systems, commonly used in CSP, face challenges related to freezing and corrosion. Particle-based TES systems, in contrast, do not experience these issues, as particles are stable at high temperatures, exceeding 1000 degrees Celsius. This capability allows for a wider range of applications, including those requiring higher temperatures for industrial processes and efficient electricity generation. A novel innovation in particle-based solar receiver technology is the light-trapping planar cavity receiver (LTPCR) configuration developed by NREL. The LTPCR design consists of small cavity-like structures using opaque planar surfaces, enabling efficient capture and absorption of solar energy. A high incident flux concentration at the cavity aperture is absorbed on the receiver walls, and subsequently transferred to particles on the inside of cavities. The particles flow through the system, forming a fluidized bed inside of the receiver panels, effectively capturing the absorbed solar heat. Air is used as a fluidizing medium in this process to enhance particle heat transfer and mixing. The effectiveness of this design lies in its ability to manage solar flux conditions and ensure high solar-to-thermal receiver efficiency. A 100-kW prototype is currently being tested at the King Saud University in Saudi Arabia to assess the receiver performance. A range of modeling analyses for the optical, thermal, and mechanical effects were conducted to assess the performance of the receiver under on-sun conditions. The solar flux resulting from the KSU heliostat field was modeled using NREL SolTrace software and produced up to 600 kW/m2 at the receiver aperture. The solar flux absorbed on the receiver walls was then used within a computational fluid dynamics (CFD) model to predict wall temperature distributions along with radiation and convection loss. A two-phase CFD model was developed for the fluidized bed of silica sand inside the receiver panels to predict local wall-to-particle heat transfer coefficients, particle temperature distributions, and outlet temperature of the particles. We have also conducted analyses to understand the thermomechanical behavior of these innovative enclosed light-trapping solar receivers optimized for particle heating. We used finite element analysis (FEA) to predict the receiver's performance using temperature distributions obtained from CFD and based on the resulting stress profiles, evaluated creep-fatigue damage with a goal of achieving a 30-year service life. Analysis showed a significant impact of the particle-to-wall heat transfer coefficients (HTCs) on receiver performance, with higher HTCs resulting in reduced stress and increased lifespan. For instance, when using Inconel 740H, increasing the HTC from 800 W/m2 K to 1400 W/m2 K increased the creep life from 4,000 hours to over 100,000 hours. This highlights the importance of understanding and optimizing heat transfer in the design of high-efficiency receivers.

14 SOLAR ENERGY↗
DOE OSTI2024

CFD simulations of Molten Salt Fast Reactor core cavity flows

Computational Fluid Dynamics (CFD) has become increasingly important in the research and development of advanced nuclear reactors. Here, in the current study, extensive CFD simulations were conducted for the coolant flow in Molten Salt Fast Reactor (MSFR) core models using the state-of-the-art spectral element flow solver Nek5000 and multiscale coarse-mesh thermal-hydraulic software Pronghorn. The underlying motivation is to seek an in-depth understanding of how the internal velocity distribution can be influenced by the MSFR core cavity shape, the Reynolds number, turbulence modeling options and the inlet boundary conditions. The CFD techniques involved in this investigation range from coarse-mesh CFD, RANS modeling, to the high-fidelity LES calculations. Specifically, a series of RANS simulations were performed for the 2-D axisymmetric core model and 3-D wedge domains to study the flow distribution inside the MSFR core. It is observed that a proper representation of the MSFR inlet channel duct is important for the prediction of internal flow distribution. It is also showcased here how researchers can leverage the Nek5000 CFD results to calibrate more efficient coarse-mesh CFD tools, like Pronghorn, for the actual MSFR design needs. Moreover, this paper highlights a 3-D LES model for an entire MSFR core using the spectral element method and demonstrates the feasibility of this modeling approach. The readiness and potential limitations of the RANS approach are examined with respect to the high-fidelity LES simulations. The present investigation lays a solid foundation as we are leveraging the high-fidelity CFD capabilities to inform MSFR design efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

THERMAL MODELING OF HANFORD CESIUM AND STRONTIUM CANISTERS DURING SIMULATED LOADING

A computational fluid dynamics (CFD) model was built to simulate planned testing of heater assemblies within a canister and overpack for the Hanford Lead Canister (HLC) project. The HLC is a canister storage system that will contain heaters to simulate the decay heat of nuclear material and provide the canister storage system with environmental conditions equivalent to the operating conditions on a dry storage pad. The HLC will be equipped with long-term data collection and monitoring systems to provide an early warning of corrosion, pitting, cracking, or other signs of canister degradation that might threaten the integrity of the containment boundary over the potentially long term of dry storage. An important part of the HLC development is to make pretest numerical predictions for the behavior of the heated canister during the simulated radiolytic decay heat testing, which simulates the dry storage system during loading operations. The simulated radiolytic decay heat test is planned for mid-2024 in a configuration that includes the heater assembly, overpack, and canister, but with the lids removed to allow loading cesium and strontium capsules into the canister. One of the goals of the test is to evaluate the thermal behavior of the canister and overpack assembly in the ambient air of the test facility, which will provide data critical to validating the thermal models and understanding how the HLC will perform as a system once deployed. To best approximate real-world conditions, the CFD model includes the full air volume of the mock-up truck bay the heated canister test will be performed in, enabling detailed investigation of how the heated canister affects airflow around it. Rigorous pre-deployment testing of the complete HLC cask and canister system is intended to be completed before the HLC is deployed in the 2028 timeframe. This study presents the pre-test temperature predictions of the simulated radiolytic decay heat test. A description of the heater assembly, canister, and overpack system is presented. The model was developed with the commercial CFD software STAR-CCM+. An uncertainty analysis was run with the CFD model to determine the uncertainty in the temperature predictions and provide a range over which the predicted temperatures are expected to vary. The uncertainty analysis was preformed by coupling STAR-CCM+ with the software Dakota, which provides advanced parametric analyses, including quantification of margins and uncertainty with computational models. This work is expected to provide insight into SNF canister behavior.

Carpenter-Graffy, Dina E.↗
DOE OSTI2026

Numerical Modeling of a Two-Stage Ocean Current Turbine

The Equinox Ocean Turbines (EQOT) current energy converter has a unique design with power generation in two small-diameter turbines attached to the tips of a large-diameter passive rotor. This configuration offers some key advantages for capturing ocean currents. With no centrally placed generator, almost no reaction torque is required at the nacelle of the main large-diameter rotor, and the small-diameter tip turbine generators operate at a higher speed and lower torque. The physics that determine the performance and loads on the turbine are also unique. The interactions of the flow field between the two stages and the general architecture of the system cannot be captured with traditional mid-fidelity modeling tools. For design iterations and large sets of load cases, it is important to have mid-fidelity models that can capture the important phenomenon with enough accuracy to identify global trends. This work uses a limited set of high-fidelity computational fluid dynamics (CFD) simulations to help inform the selection of and construction of a custom mid-fidelity model. Mid-fidelity modeling approaches were verified by comparing key turbine performance quantities to those found with the CFD model. Hydrodynamic interactions of the two-stage rotor were identified through high-fidelity CFD modeling. This highlighted the impact of the main rotor tip vortex and wake on the secondary rotor apparent inflow. This results in a relative flow rotation and sharp deficit, that change the optimal secondary rotor rotation speed and adds unsteadiness to the blade loading respectively. Multiple mid-fidelity approaches were evaluated for their ability to capture these effects. A simple approximation of the combined-stage performance based on single-stage BEM provides a reasonable rough prediction, especially near the peak TSR values, with some larger discrepancy at higher TSRs. Predicting the combined-stage performance based on single-stage CFD data improves this prediction across the TSR range. Although the combined-stage modeling in OLAF was not successful in this stage of the project, it showed promise as a mid-fidelity method, assuming the parameters can be tuned to account for the significant differences in time and length scales between the main and secondary rotors. This may be addressed through code changes in future work. A significant finding from the OLAF work was the agreement between the vortex core radius values found independently via a parameter space search and via CFD. The technique of using single-stage secondary rotor BEM, with a custom inflow taken from single-stage main rotor CFD or OLAF, provides an efficient method to capture one-way coupled flow interactions. This method provided generally good predictions of the impact of the flow rotation on the secondary rotor but struggled to accurately predict the peaks of the unsteady load progression. Future work could include some superposition of a tuned main rotor trailing edge viscous wake into the custom inflow to better predict this interaction.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Development of fiber orientation in injection molding: Comparison of glass fiber, carbon fiber and their hybrid composites

Fiber orientation distribution (FOD) in injection-molded panels with respect to distance from the gate was analyzed using X-ray computed tomography (X-CT) for glass fiber (GF), carbon fiber (CF), and hybrid CF/GF (CGF) reinforced nylon 66. To understand the reason behind the FOD with different fiber types, computational fluid dynamics (CFD) and rheology were performed. Samples were extracted at three locations: near the gate, center, and opposite end. Thickness of the layers of typical skin-shell-core type FOD varied with fiber type and location. GF achieved flow direction alignment (in shell) earlier than viscous CF and CGF near the gate, whereas CF showed the highest flow-direction alignment at the center due to shear induced orientation. At the opposite end, GF experienced more backflow than others indicating faster mold filling owing to its lower viscosity. Hybrid CGF exhibited GF-dominated center and CF-dominated end region. The numerical model used to obtain FOD and rheological predictions for the CF and GF composites served to corroborate the trends observed in the experimental trials. The FOD responses across fiber types and location were reflected in their longitudinal and transverse properties. Only GF showed higher longitudinal modulus over transverse modulus near the gate attributed to rapid alignment, whereas CF and CGF exhibited opposite trend. However, fountain flow enhanced the longitudinal modulus over transverse modulus with the distance for all, particularly for CF. This study offers insights into mold filling behavior of different fibers which are critical in optimizing injection molding conditions for tailored final properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Software Quality Assurance for the MOOSE-Based Open-Source Multiphysics Code Cardinal - An Expanded CI Testing Suite

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing and, maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program has been initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as a safety analysis tool. These gaps have been captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents a snapshot of the verification test cases currently available for Cardinal and NekRS in their assimilation into a Continuous Integration (CI) platform. Following the CI practice permits the integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. It should be noted that the SQA program itself, including the program plans, procedures, configuration management, and testing strategies, need to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Progress Towards NQA-1 for Cardinal in FY25

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing,and maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program was initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as an analysis tool. These gaps were captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents the progress made towards NQA-1 for Cardinal in the Fiscal Year 2025 (FY25). All cases in the expanded Continuous Integration (CI) suite of NekRS are included in this report which test the solvers and modules available in NekRS exhaustively. The NekRS tests are integrated with the Cardinal CI suite and made available in publicly accessible Github documentation. Following the CI practice permits integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. Also in this report is a brief overview of the development of the Cardinal Software Quality Assurance Plan (SQAP) that was done in FY25, though it should be noted that the rest of the documentation for the SQA program needs to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

PowderJet: Spherical metal powder production via multi-orifice droplet-on-demand metal jetting

Leading metal additive manufacturing techniques, such as laser powder bed fusion and directed energy deposition, rely on high-quality spherical metal powders. However, traditional powder production methods like gas atomization face limitations, including low in-spec yield, asphericity, and internal porosity. We introduce PowderJet, a powder production platform that uses electromagnetic pulses to eject liquid metal droplets from a multi-orifice nozzle. Unlike stochastic methods, PowderJet tightly controls powder size, distribution, and purity through a droplet-on-demand approach. We detail the system’s design, operation, and performance using a combined experimental and computational fluid dynamics (CFD) framework. Initial results with Al4008 and Cu110 alloys demonstrate successful production, yielding unsieved aluminum powder batches with a mean diameter of 200 µm and a narrow size distribution (15 µm standard deviation). The produced powders are highly spherical, achieving a roundness > 0.95. PowderJet operates with a small melt volume (3 mL) and supports continuous refilling, enabling production rates between 30 and 140 cm³/hr depending on jetting frequency, number of orifices and particle size. CFD simulations show that future systems could achieve rates exceeding 1000 cm³/hr for particle sizes as small as 40 µm. PowderJet’s high yield of in-spec powder makes it ideal for producing precious or hazardous materials that are inefficient to manufacture using conventional methods. This platform offers a scalable, precise, and efficient solution for producing high-quality powders tailored for advanced manufacturing applications.

Atomization↗
DOE OSTI2026

Which way does the dendrite grow? Competition among epitaxy, preferred growth direction, and thermal gradients in powder bed fusion additive manufacturing

The as-processed microstructure of metal alloy parts manufactured through laser powder bed fusion (LPBF) is heavily derived from the cellular dendritic solidification. The growth direction of dendrites within the melt pool is determined through competition among epitaxial growth, preferred growth directions, and maximum thermal gradients. However, the dominant factor and the specific role of each in developing melt pool microstructures remain unknown. Here, in this study, we performed single laser track scans on an SS316L single crystal substrate and combined experimental characterization of microstructure and crystal orientations with Computational Fluid Dynamics simulations of thermal gradients to evaluate the role of each factor in determining dendritic growth direction and evolution. Our results reveal that epitaxial growth dominates microstructure development by preferentially growing along a single 〈100〉 variant of the single crystal substrate adjacent to the melt pool boundary. Under LPBF’s highly curved and rapidly evolving thermal field, this preferential dendrite variant selection and its continued growth from the melt pool boundary to the centerline are governed by the local temperature gradient magnitude at the solid-liquid interface, rather than by the instantaneous maximum temperature gradient direction alone. Using these findings, we successfully predict changes in the dendrite growth direction with changing laser scan direction on a single crystal substrate, and show that the geometric melt pool centerline can deviate from the microstructural centerline because asymmetric local temperature gradient magnitudes transiently limit growth, resulting in different dendrite travel distances on each side of the melt pool.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Toward integrating high-fidelity CFD approaches in the thermal-hydraulic analysis of turbulent dry cask systems

Nuclear power plants have been supplying resilient and reliable electricity for decades, contributing to energy independence of the U.S.. However, nuclear waste management remains one of the most significant challenges in the industry. The safety of dry cask storage systems relies heavily on their thermal-hydraulic performance. Computational Fluid Dynamics (CFD) simulations are often used to demonstrate this performance and ensure that the system design meets safety standards. This study presents reduced numerical models for various types of dry cask systems. These numerical models can produce efficient and fast results based on the employed modeling strategies. Additionally, the study uses a novel approach to high-fidelity simulations to evaluate modeling assumptions in dry cask modeling. Large Eddy Simulations (LES) are used for this purpose, particularly in regions where fluid velocity is relatively high and the turbulence characteristics become important. Furthermore, the results of these high-fidelity simulations will enhance the interpretation of outcomes produced from a lower-fidelity CFD model.

CFD↗
DOE OSTI2025

The molten salt tritium transport experiment: A pumped fluoride salt loop for hydrogen isotope experimentation

Molten salt reactors (MSRs) and fusion reactors propose to use molten salts as coolants and breeder blanket materials, respectively. Tritium, however, poses safety concerns in both reactor types due to its ability to permeate through reactor materials and potential for environmental release. This manuscript addresses the tritium transport phenomena in molten salts and presents the design and analysis of the Molten Salt Tritium Transport Experiment (MSTTE). MSTTE is a forced-convection fluoride salt loop intended to measure hydrogen isotope permeation through structural materials in a flowing salt system. In the first phase, MSTTE will use FLiNaK salt and deuterium as surrogates for FLiBe and tritium, with future plans to utilize tritium and FLiBe. MSTTE couples a Copenhagen Atomics pumped salt loop with an external test section that introduces hydrogen isotopes into the loop and measures transport phenomena. The Hydrogen Injection System (HIS) controls hydrogen isotope introduction into the molten salt loop. Here, the permeation test section measures the permeation rate through stainless steel tubing in contact with flowing salt. Computational fluid dynamics (CFD) analysis ensures fully developed salt flow in the permeation test section. MSTTE is modeled with MELCOR-TMAP to predict the permeation rate as a function of experimental variables such as source term, salt flow rate, and salt temperature. Results indicate that the source term is the only parameter with a significant effect on the permeation rate. Pressure drop analysis suggests that the loop should operate below 200 LPM to maintain a pressure drop below 200 kPa. Additionally, finite-element analysis assesses thermal stress during loop operation to ensure the experiment's safe design. MSTTE will provide semi-integral data on tritium transport phenomena in molten salts and serve as a testbed for advancing molten salt technology.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Bringing solar to agriculture: An interdisciplinary design and analysis of a Concord grape agrivoltaic system

Agrivoltaics presents an opportunity to integrate solar photovoltaics (PV) with agricultural production, but crop-specific challenges and operational constraints remain underexplored. This study develops and evaluates a Concord grape agrivoltaic system in the Lake Erie American Viticulture Area, where vineyards face economic pressures and land use conflicts with solar development. Starting with vertical, tracking, and overhead PV systems, we model photosynthetic photon flux density (PPFD) reduction in grapevines and power generation losses from shading using the Agrivoltaic Radiation Tool (ART). Based on these results, which indicate 0.47 % annual grapevine PPFD loss for vertical designs, 1.6 % for tracking, and up to 25 % for the overhead systems, the vertical and tracking designs are selected for further computational fluid dynamics (CFD) analysis to evaluate airflow interactions. CFD results show that vertical panels do not significantly impact airflow through the grapevine canopy, and that tracking systems in horizontal position may enhance airflow compared to a vine-only scenario. Considering operational constraints for tracking systems, the vertical design is selected for an economic evaluation to reveal key financial outcomes for solar developers (14-year payback period) and growers ($408 reduction in financial losses per acre annually). A sensitivity analysis quantifies uncertainty in power generation (±8.8 %) and PPFD (±5.0 %), ensuring model robustness across different vineyard conditions. Furthermore, these findings provide quantitative evidence for the feasibility of Concord grape agrivoltaics, demonstrating a synergistic opportunity for dual-use solar while preserving cultural heritage in grape-growing regions.

14 SOLAR ENERGY↗