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DOE OSTI2025

Exploring the Utility-Privacy Trade-Off: Impacts of Semantic and Visit Types Ambiguities on Human Mobility Simulation

Humans are in perpetual movement, constantly traversing buildings, cities, waters, oceans, and countries. Mobility stands out as a major driving force shaping our modern societies. Capturing and explaining human behavior in a world of eight billion distinct mobility agendas is a complex challenge. With the rise of interconnected devices and platforms, such as smartphones, wearables, and point-of-interest data, largescale behavioral data has become more accessible, enabling rich insights into mobility patterns. However, the widespread availability of such data introduces significant ethical challenges. Detailed mobility data can inadvertently reveal sensitive personal information, including individuals' locations, habits, social interactions, and even political or religious affiliations. Beyond privacy breaches, the ethical implications of uncovering and potentially manipulating underlying behavioral patterns demand attention. Striking a balance between the utility of mobility models and the protection of individual privacy is therefore paramount. This paper explores the utility-privacy trade-offs in human mobility modeling, focusing on the impacts of introducing semantic and visit type ambiguities. By systematically examining how these ambiguities affect the fidelity of simulated trajectories and privacy risks, we provide a framework for evaluating ethical and privacy-conscious modeling practices. Our findings emphasize the need for methods that safeguard privacy without undermining the usefulness of mobility models, contributing to the responsible advancement of mobility science in alignment with ethical standards and societal expectations.

Amichi, Licia [ORNL] (ORCID:0000000177631394)↗

DOE OSTI2026

SAM Code Enhancements for Fission Product Tracking of Noble Gases and Metals in MSRs

This report documents fiscal year 2026 enhancements to the System Analysis Module (SAM) for modeling fission product transport in liquid-fueled molten salt reactors (MSRs). The work advances three principal areas: noble gas transport, noble metal deposition, and user interface improvements. The noble gas transport capability integrates drift-flux gas transport, Henry’s law two-film interphase mass transfer with pressure-based nucleation suppression, Knudsen-regime pore diffusion into porous graphite with a conjugate salt-graphite interface constraint, built-in material properties, five Sherwood-number mass transfer correlations including three derived from high-fidelity NekRS simulations, and xenon-135 reactivity feedback through SAM’s point-kinetics model. This work also presents a comprehensive verification test suite, including new analytically verified cases for pressure-dependent onset of interphase gas transfer in a stagnant vertical pipe, a postulated FLiBe-graphite Xe extraction permeator, a gravity riser with a fission-product source, and a descending pipe with gas redissolution driven by hydrostatic pressure. A machine learning framework for bubble rise velocity prediction in molten salt systems is developed and benchmarked on molten-salt and diverse aqueous bubble datasets. The best-performing fine-tuned transfer-learning networks achieve an 82% reduction in RMSE relative to the Clift correlation, and is implemented directly in SAM. The noble metal transport capability is developed, including a liquid-wall deposition model and a gas-surface flotation mechanism that transfers insoluble particles entrained by sparging gas to wetted structures. Verification tests and demonstration cases cover the surface deposition, flotation efflux, and flotation shedding. Finally, a new [SpeciesTransport] input structure replaces positional global vectors with selfcontained, order-independent, named species blocks, simplifies the specification of multiphase species and decay chains, and remains fully compatible with existing SAM input files. Together, these developments improve the physical fidelity, verification basis, and usability of SAM for system-level analyses of fissionproduct behavior in MSRs.

Mui, Travis (ORCID:0000000303736470)↗

DOE OSTI2024

Data-Driven Surrogate Modeling with Microstructure-Sensitivity of Viscoplastic Creep in Grade 91 Steel

Abstract To support the development of advanced steel alloys tailored to withstand extreme conditions, it is imperative to account for the mechanical performance of components, while considering the influence of local microstructure on the macroscopic response. To this end, this study focuses on the development of microstructure-sensitive constitutive models for the mechanical response of Grade 91 steel exposed to extreme thermo-mechanical environments. Polynomial chaos expansion (PCE) surrogates are used to emulate high-fidelity polycrystal simulations of the viscoplastic response of Grade 91 steel as a function of the microstructure fingerprint (e.g., dislocations and precipitates). To cover a wide temperature–stress domain, two separate PCE surrogates—one that captures softening and the other that captures hardening behavior—are combined using another (sparse) Gaussian process regression model. The resulting constitutive creep surrogate model is integrated within the MOOSE finite element framework to simulate the intricate effects of microstructure, in particular MX-phase precipitates, on a component with a graded microstructure. Surrogate sensitivity analysis is applied to quantify the relevant impact of spatially varying microstructure on the creep response in a test-case involving a Grade 91 alloy with a prototypical weld.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Development of a Griffin model of the advanced test reactor

In the pursuit of a higher fidelity deterministic simulation capability of the Advanced Test Reactor, it is important to have a fast yet accurate deterministic neutronics model. Here, to achieve this, we employed an advanced two-step method. The first step involves generating homogenized cross sections using OpenMC, a cutting-edge Monte Carlo neutron transport code. OpenMC offers excellent modular capabilities, allowing for easy component integration and flexibility in incorporating new designs into the model. The second step involves deterministic transport calculations, which are performed using Griffin, a reactor physics application based on the Multiphysics Object-Oriented Simulation Environment (MOOSE). To ensure the accurate spatial resolution and assignment of material cross sections, a Cubit-generated mesh for the Advanced Test Reactor is utilized as an intermediate step between the OpenMC and Griffin models; Griffin utilizes the mesh for its finite element solution, while OpenMC material identifications are written to the mesh file to be used in Griffin material assignments. Additionally, a Python-based script converts the cross sections generated by OpenMC into the ISOXML format required by Griffin. Initial comparisons using the Griffin diffusion solver indicated good agreement between the neutron multiplication factors obtained from the standalone OpenMC model and the Griffin model, with differences of less than 10 pcm in the 2D geometry configuration; it was later determined that this agreement was likely due to compensating effect and was more likely on the order of –700 pcm relative to the OpenMC solution. However, in three-dimensional calculations, an unacceptably large error (almost 8,000 pcm) was found in the Griffin solution with the diffusion solver. Subsequent calculations using Griffin’s discrete ordinates solver demonstrated substantially improved agreement, within 116 pcm of the OpenMC solution used to generate the cross sections for Griffin. Building on this capability, future work will seek to perform more detailed validation calculations. The ultimate goal is to evaluate both transient and multiphysics simulations of the reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2026

MFC 5.0: An exascale many-physics flow solver

Many problems of interest in engineering, medicine, and the fundamental sciences rely on high-fidelity flow simulation, making performant computational fluid dynamics solvers a mainstay of the open-source software community. Previous work MFC 3.0 was made a published, documented, and open-source solver via Bryngelson et al. Comp. Phys. Comm. (2021) with numerous physical features, numerical methods, and scalable infrastructure. MFC 5.0 is a significant update to MFC 3.0, featuring a broad set of well-established and novel physical models and numerical methods, as well as the introduction of GPU and APU (or superchip) acceleration. Here, we exhibit state-of-the-art performance and ideal scaling on the first two exascale supercomputers, OLCF Frontier and LLNL El Capitan. Combined with MFC’s single-accelerator performance, MFC achieves exascale computation in practice, and achieved the largest-to-date public CFD simulation at 200 trillion grid points as a 2025 ACM Gordon Bell Prize finalist. New physical features include the immersed boundary method, N-fluid phase change, Euler–Euler and Euler–Lagrange sub-grid bubble models, fluid-structure interaction, hypo- and hyper-elastic materials, chemically reacting flow, two-material surface tension, magnetohydrodynamics (MHD), and more. Numerical techniques now represent the current state-of-the-art, including general relaxation characteristic boundary conditions, WENO variants, Strang splitting for stiff sub-grid flow features, and low Mach number treatments. Weak scaling to tens of thousands of GPUs on OLCF Summit and Frontier and LLNL El Capitan achieves efficiencies within 5% of ideal to over 90% of their respective system sizes. Strong scaling results for a 16-times increase in device count show parallel efficiencies over 90% on OLCF Frontier. MFC’s software stack has undergone further improvements, including continuous integration, which ensures code resilience and correctness through over 300 regression tests; metaprogramming, which reduces code length while maintaining performance portability; and code generation for computing chemical reactions

Computational fluid dynamics↗

DOE OSTI2026

Validation of SPH code Spheral to model interacting solid bodies in a supersonic flow

Contemporary discussions of planetary defense involve analyzing the risks posed by smaller sized, 20 to 200 m diameter, asteroids which are capable of breaking up in the atmosphere and generating a blast wave. Consequence assessments for this size class of asteroids are performed through fast-running analytic or semi-analytic models which are informed by high-fidelity hydrocode simulations of asteroid entry and breakup. However, insufficient historical data necessitates validating the independent physical processes which dominate airburst events. Here, the Fluid Solid Interface Smoothed Particle Hydrodynamics solver was previously used by Pearl et al. in 2023 to model the Chelyabinsk airburst and is used here to perform a series of validation simulations. The first effort involves modeling a cylinder in a hypersonic flow and comparing the bow shock geometry to that predicted by analytic theory. The second effort involves modeling the separation of two spherical bodies in supersonic flow and validating against experimental footage. Combined, these exercises demonstrate the ability of the code to model the flight-path of interacting solid bodies in a hypersonic flow.

Airburst↗

DOE OSTI2026

Continuum Correlations from CFD-DEM Modeling of Conduction Heat Transfer in Granular Flows

Heat transfer between a surface and flowing particles is analyzed to improve the accuracy of continuum models for wall-to-bed heat transfer in a fluidized bed. Discrete element modeling (DEM) is used to model a fluidized bed heat exchanger where heat enters the system through a heated wall. The DEM heat transfer predictions are validated against published experimental work (Brewster et al., 2024) with less than 15% error. In previous work by Morris et al. (2015), a continuum model was developed using data from high-fidelity DEM simulations of chute flows. In the current study, the continuum model is extended and validated for fluidized beds. The sensitivity of the continuum heat transfer model parameters, which was not quantified in previous studies, is also investigated. It is observed that for a given particle with specific properties, e.g. the particle size, roughness, and conduction lens radius, the continuum correlation developed for heat transfer from a heated boundary to the particle bed depends mainly on the solid fraction or porosity of the particle bed for a given fluid. The new continuum heat transfer model is then validated over a wide range of superficial velocities via comparisons to both discrete element and experimental data. It is shown that this correlation is valid for a large range of particle flow conditions from chute flows to fluidized beds with less than 10% error as compared to DEM predictions.

14 SOLAR ENERGY↗

DOE OSTI2024

Response of a high-pressure 4 He scintillation detector to nuclear recoils up to 9 MeV

Helium-4-based scintillation detector technology is emerging as a strong alternative to pulse-shape discrimination-capable organic scintillators for fast neutron detection and spectroscopy, particularly in extreme gamma-ray environments. The 4 He detector is intrinsically insensitive to gamma radiation, as it has a relatively low cross-section for gamma-ray interactions, and the stopping power of electrons in the 4 He medium is low compared to that of 4 He recoil nuclei. Consequently, gamma rays can be discriminated by simple energy deposition thresholding instead of the more complex pulse shape analysis. The energy resolution of 4 He scintillation detectors has not yet been well-characterized over a broad range of energy depositions, which limits the ability to deconvolve the source spectra. In this work, an experiment was performed to characterize the response of an Arktis S670 4 He detector to nuclear recoils up to 9 MeV. The 4 He detector was positioned in the center of a semicircular array of organic scintillation detectors operated in coincidence. Deuterium–deuterium and deuterium–tritium neutron generators provided monoenergetic neutrons, yielding geometrically constrained nuclear recoils ranging from 0.0925 to 8.87 MeV. The detector response provides evidence for scintillation linearity beyond the previously reported energy range. Finally, the measured response was used to develop an energy resolution function applicable to this energy range for use in high-fidelity detector simulations needed by future applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Mechanistic understanding of carbon mineralization in fracture systems using microfluidics

Carbon mineralization in mafic and ultramafic rocks presents an opportunity for permanent carbon storage in the Earth's subsurface. However, due to their lower permeability, pre-existing fracture networks are key for mineralization to occur. Therefore, to fully develop this technology, a mechanistic understanding of the mineralization behavior in fractures with the consideration of hydrodynamic components is required. We use high-pressure microfluidics to investigate key mechanisms influencing dissolution–precipitation in a fracture network. The experiments were conducted in micromodels made of natural rocks with a comb-shaped flow channel to mimic a fracture network. This enabled studying the effect of injection rate on coupled dissolution–precipitation in advection and diffusion-dominated flow paths. We used gypsum carbonation as an analog reaction to allow for realistic experimental time frames due to its rapid reaction kinetics. The experimental work is coupled with high-fidelity numerical simulations to enhance our understanding of the parameters affecting the mineralization reaction. Our results demonstrate the importance of flow rate on the rate and nature of the gypsum carbonation reaction revealing that higher flow rates enable deeper penetration of the mineral precipitation front into the dead-end channels. This is an important finding since for sustained mineralization in a fracture network, precipitation in dead-ends while still allowing for flowing fractures is critical. Detailed characterization of the precipitates showed that lower flow rates led to porous and loose precipitates in the form of aragonite while higher flow rates mimicked supersaturation behavior leading to the formation of calcite. The reactive transport simulations further demonstrated the significance of flow velocity in advection-dominated channels to influence the efficiency of carbon mineralization in diffusion-dominated channels, potentially clogging of dead-end channels. These findings highlight the need for coupling chemical, mechanical, and hydrodynamic processes to evaluate the nature and extent of carbon mineralization in fractured media critical for permanent storage in mafic and ultramafic formations. This research further highlights the need for more investigation in potential subsurface fracture generation techniques to aid carbon mineralization.

25 ENERGY STORAGE↗

DOE OSTI2024

MeV x-ray production from a petawatt laser in the regime of a relativistically transparent preplasma, with applications to radiography

Bright sources of mega-electron volt (MeV) x-rays have many unique applications, including nuclear physics, radiation oncology, and imaging high areal density systems. High intensity lasers (>1018 W cm−2) incident on mm-thick metal targets can deliver MeV x-rays via the bremsstrahlung process, providing sources with ultrashort duration (∼ps) and small source size (∼100 μm). Here, we report on a reproducible regime of laser-driven MeV x-ray sources, where the x-ray dose can be further increased by 60% by coating the metal target with micrometers of plastic. High fidelity numerical simulations indicate that the interaction is a result of relativistic transparency in the preplasma. Though relativistic transparency is present in both cases, the greater sound speed and smaller ion inertia of the plastic target allow the laser to more deeply penetrate and couple more efficiently to electrons. Radiography with this system demonstrates a resolving power < 300 μm, important for imaging applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

WEST L-mode record long pulses guided by predictions using Integrated Modeling

A new record was set on the WEST Tokamak, designed to operate long duration plasmas in a tungsten (W) environment, with an injected energy of 1.15 GJ and a plasma duration 364s. Scenario development was supported by integrated modeling using the High Fidelity Plasma Simulator (HFPS), the European IMAS-coupled version of JETTO/JINTRAC, which integrates physics-driven modules into a unified framework. In particular, a reduced model for Lower-Hybrid heating and Current-Drive (LHCD) and the quasi-linear turbulent transport model TGLF are crucial for long pulses predictions up to the Last Closed Flux Surface (LCFS). Using this workflow, a 100 s reference discharge was modeled and plasma kinetic profiles and loop voltage were quantitatively well matched. In preparation for the recent long duration experiments, non-inductive current-drive actuators (I P , n e , P LHCD ) were varied to determine the operational domain going towards fully non-inductive discharges. In particular, decreasing the plasma current is shown to ease the access to such conditions, with a careful monitoring of (n e , P LHCD ) to avoid machine limitations. In addition, post-prediction experiments conducted within the investigated parameter range validated the predicted dependencies and were shown to be in quantitative agreement. Exploratory work on the use of ECCD for MHD stability purpose is also introduced.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Closed-Loop Wind Turbine Controllers for Active Wake Mixing Strategies

Wind turbine active wake mixing (AWM) is an exciting new field of research where dynamic actuation, usually on the blade pitch angles, is used to increase wind farm-wide power production. From a controls perspective, the current state-of-the-art AWM strategies are very simple: a dynamic, usually periodic, reference signal is prescribed to actuators in an open-loop (OL) fashion. The actuation is then presumed to have a certain desired effect on the system, i.e., the wind turbine and the flow it affects. However, this system is highly nonlinear and experiences disturbances in the form of wind variations that are not known a priori. As a result, the OL approach might not yield optimal results. In this article, a novel approach is presented, which closes the loop on AWM controllers. A feedback loop is implemented, which uses measurements of the individual blade bending moments that are widely available on modern wind turbines to determine the individual blade pitch angles. A proof of concept of this implementation is presented in this article, and a thorough comparison with the OL method is executed using high-fidelity flow simulations. These simulations show that the novel closed-loop controller does not substantially increase wake mixing but achieves similar performance as the OL controller while reducing fatigue loads on the controlled turbine.

17 WIND ENERGY↗

DOE OSTI2025

Moltensaltpropnet

MoltenSaltPropnet is a physics-informed machine learning framework that aims to predict the thermophysical properties of molten fluoride and chloride salt mixtures, which are crucial for the design and safety of Generation IV molten salt reactors. The code processes data from the Molten-Salt Thermal Properties Database (MSTDB-TP) and the Janz compendium, converting critically evaluated correlations into fast, differentiable surrogate models for density, viscosity, thermal conductivity, and heat capacity across 448 distinct salt systems. The implementation consists of several key components: 1. Data Curation: The code parses and cleans the raw data, normalizing elemental mole fractions and extracting relevant regression coefficients for various thermophysical properties. 2. Feature Engineering: It generates fixed-length numerical descriptors that encapsulate the composition and temperature, incorporating polynomial interaction terms and dimensionality-reduction techniques to optimize model performance. 3. Coefficient Learning: Four different machine learning architectures are employed: a deep residual network (ResNet), a Kolmogorov–Arnold network (KAN), a sparsity-inducing neural network (SNN), and classical regression models. Each model learns to predict coefficients that define the temperature-dependent correlations for the thermophysical properties. 4. Property Reconstruction: The predicted coefficients are used to compute temperature-dependent property values, ensuring positivity and monotonic trends through a composite loss function that enforces physical constraints. 5. User Interface: An open-source web application enables users to filter the database, train task-specific models, and visualize the results, allowing for rapid exploration of candidate salt mixtures. MoltenSaltPropnet bridges the gap between limited experimental data and high-fidelity reactor simulations, providing a powerful tool for researchers in the field of molten salt reactors and advanced nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗

DOE OSTI2024

Addressing Experimental Challenges in Probing Dark Energy with Accuracy and Precision with the Rubin Observatory Legacy Survey of Space & Time (LSST)

With support from this award, the Stanford group under the leadership of PI Patricia Burchat focused on pixel-level algorithms that are key to the investigation of dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The work was carried out through strong engagement in the DOE-supported LSST Dark Energy Science Collaboration (DESC), for which the PI served as Deputy Spokesperson (07/2019 - 07/2021) and Technical Coordinator (07/2021 - 07/2023). Members of the Burchat group are Full DESC members and are among scientists who have been accepted to join the Rubin Observatory System Integration, Test, and Commissioning (SIT-Com) effort. The specific intellectual focus of the group was the optimization of gravitational lensing as a probe of the evolution of the distribution of dark matter in space and time to learn about the nature of dark energy. The Stanford group pursued an integrated research program to understand in detail, and then remediate or calibrate, systematic effects that could limit the sensitivity of the LSST to cosmic shear as a dark energy probe -- particularly those related to our understanding of the atmospheric point spread function (PSF), challenges associated with blended galaxy images, and impacts of residual camera artifacts. Key to this work was developing, enhancing, and validating the fidelity of simulations that play a key role in the development of our understanding of subtle systematic biases and then using these simulations to develop techniques to characterize and mitigate biases, and associated algorithms for implementation in the LSST or DESC science pipelines. The group’s work included contributions to the open-source GalSim simulation package, which is widely used in the community; simulations and studies of spatial correlations of atmospheric PSFs; studies of temporal correlations of the atmospheric PSF; impacts of chromatic PSFs on cosmic shear calibration; continued studies of anisotropic Gaussian process interpolation of PSF models across the focal plane; and measuring and mitigating impacts of residual camera artifacts on cosmic shear. A primary impact of this work is that it increases the scientific discovery potential of the DOE and NSF investments in the Rubin Observatory Legacy Survey of Space \& Time, by addressing challenges in interpreting astronomical images through more accurate descriptions of the blurring of images due to the atmosphere. Specifically, this work impacts our ability to understand the fundamental nature of dark energy.

Burchat, Patricia Rose↗

DOE OSTI2024

MOSCATO Development and Integration in Fiscal Year 2024

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Enabling Low-Temperature (LTP) Ignition Technologies for Multi-Mode Engines through the Development of a Validated High-Fidelity LTP Model for Predicative Simulations Tools

The goal of multi-mode engine architectures is to extend current lean-burn dilution limits with renewable fuels, which requires spark plugs to deposit high energies (hundreds of mJ) in order to initiate ignition and complete combustion. At elevated energy deposition rates, spark plugs experience increased electrode erosion and thermal losses, which ultimately shortens the spark-plug lifetime and lowers ignition efficiency. As such, in order to safeguard the efficiency gains of multi-mode concepts, new and improved ignition technologies are required. Recently, non-equilibrium low-temperature plasmas (LTP) have been shown to promote energy-efficient ignition via quenching and transport of electronically excited atoms and molecules, selective radical production and fast heating of hydrocarbon/air mixtures [1-2]. Thus, LTP is seen as a technology that can potentially improve the energy extraction efficiency of fuels, while enabling kinetically controlled combustion modes towards fuel leaner conditions to realize current DOE VTO goals of improving the sustainability of future mobility [3]. Although many previous studies have demonstrated the efficacy of plasma-assisted ignition to enhance combustion, the detailed enhancement mechanisms remain largely unknown, especially for oxygenated fuels and at elevated pressures that are most relevant to practical engine conditions. These barriers hinder the development of accurate and comprehensive numerical models that seek to describe LTP-based ignition in existing engine design software tools and methods. Current state-of-the-art simulation capabilities for LTP ignition systems are in need of improvements since they deliver qualitative results only due to important limitations of existing approaches. Firstly, validated kinetic models with elementary steps for plasma discharges in oxygenated fuel/air mixtures of relevance to the transportation sector are required. Such kinetic models do not exist at present and will be developed and validated within this project. Secondly, plasma discharges and reactive mixture ignition are multi-scale, unsteady processes requiring high-performance numerical methods and software that execute efficiently on DOE supercomputers. Such software does not exist at present and will be developed and applied to practical LTP ignition scenarios as part of this project. Thirdly, experimental databases that are tailored to serve as benchmark in support of the development of predictive computational models of LTP ignition do not exist and will be part of this project.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

MOSCATO Development and Integration in Fiscal Year 2025: Implementation of Multiphase, Multiphysics Modeling Capabilities for Molten Salt Systems

MOSCATO (Molten Salt Chemistry and Transport) is a multiphysics code that provides high-fidelity, coupled simulations of fluid flow, heat transfer, mass transfer, chemistry, electrochemical phenomena, and alloy corrosion for molten salt systems. In FY25, significant developments were made to the code package, enhancing its capabilities for modeling all relevant phenomena within operating moltens salt reactors (MSRs). The developments and activities in FY25 included: 1. Implementation of Level-Set methods to enable modeling of single-bubble behavior in molten salts. In FY25, the Level-Set two-phase flow modeling implementation was improved to simulate single bubble behavior with molten salt media. The large density and viscosity ratios between typical gases and molten salt liquids present challenges for these types of numerical solvers. With enhancements to the pressure projection method, MOSCATO’s Level-Set solver was able to be successfully validated to experiments related to helium bubble rise in stagnant molten salt. The simulated bubble rising velocity showed reasonable good agreement with experimental measurements. The bubble shape and dynamics were also visually compared with experimental snapshots, demonstrating a good qualitative match. 2. Generation of mass transfer correlations for multiphase flow systems. To enable calculations of the tritium transport across the interface between gas bubbles and salt, we modeled high- Schmidt-number mass transfer around a sphere across a broad range of Reynolds numbers. The mesh near the sphere surface was highly refined to resolve steep concentration gradients caused by the low diffusion coefficient. Literature-based mass transfer correlations were compared with the numerical results, and modifications were proposed to improve agreement, particularly at higher Schmidt numbers. These mass transfer correlations were subsequently provided to other national laboratories to help enable high quality mass transfer simulations using lower-order solvers under development within the NEAMS program. 3. Preliminary implementation of a bubbly flow solver. To model bubbly flow in molten salt, we implemented a bubbly flow solver for void fractions less than 5%. To do so, an algebraic relative velocity model that assumes small bubbles with rapid momentum equilibration was added to MOSCATO to compute bubble velocities. Preliminary comparisons with experimental data showed reasonable agreement, and further improvements are underway. 4. Generation of mass transfer correlations for MSRE subchannel The Molten-Salt Reactor Experiment (MSRE) was a landmark historical project that demonstrated the feasibility of molten-salt reactor technology. The MSRE campaign also generated a significant body of experimental data and reports that continue to support molten-salt–related research. In this report, the MSRE core subchannel was used as the reference geometry for a mass transfer study performed with MOSCATO. The geometry and computational mesh were adapted from a previous study, providing adequate resolution for the relatively low Reynolds number in this case. Additional mesh refinement was applied to reach higher Schmidt numbers, enabling the derivation of a reliable mass-transfer correlation for the present scenario. 5. Simulations of oxygen ingressions into molten salt. In the previous fiscal year, we initiated a study to simulate oxygen ingression in stagnant salt. As oxygen enters the salt through its surface, it reacts with Ce 3+ to form solid CeO 2 and other reaction products. To more fully capture the complex diffusion-convection-reaction mechanisms, capabilities for modeling natural convection in the salt vessel were added. These were needed as the flow of the ingressed gas induced flow in the salt caused by surface shear and non-isothermal effects. With these updated physics in place, we were able to successfully reproduce the experimental results for the rate of change of CeCl 3 concentrations versus time. 6. Flow corrosion model validation. In FY24, MOSCATO’s corrosion model was validated against static corrosion experiments. In FY25, this work was extended to a flow corrosion experiment, where FLiNaK salt was driven by natural convection, with initial salt impurities to initiate corrosion. Despite uncertainties in parameters such as elemental diffusion coefficients in the alloy and unknown H + concentrations, the simulations achieved good agreement with experimental results, especially in predicting sample mass losses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Characterization of Neutron Emission Rates of Commercial 252 Cf Sources

Accurate knowledge of 252 Cf neutron emission rates is critical for modeling and fast-neutron experiments, yet commercial sources are often supplied without traceable calibration or uncertainty estimates. This report describes a method to characterize 252 Cf sources using a pulse-shape-discrimination (PSD) scintillator. The scintillator was efficiency-calibrated against a time-tagged 252 Cf fission chamber manufactured at ORNL over 40 years ago. Isotopic evolution of the calibration source was modeled using Bateman equations to account for changes in the effective average neutrons per fission at the time of measurement. The calibrated scintillator was then used to measure absolute emission rates of several commercial 252 Cf sources, revealing deviations of up to 12% from nominal manufacturer values. This methodology provides a practical approach for establishing uncertainty-quantified 252 Cf neutron emission rates, improving fidelity in simulations and supporting the accurate interpretation of measurements.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗