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DOE OSTI2025

Identifying preferential flow from soil moisture time series: Review of methodologies

Abstract Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods to highlight important information for readers who want to identify PF from soil moisture data and to inform those who aim to develop new methods or improve existing ones. Core Ideas Soil moisture data can be used to identify the occurrence of preferential flow (PF) and its initiating conditions. Various data‐analysis methods to identify PF differ in susceptibility to error, bias, and subjectivity. These methods can utilize vast amounts of data from soil moisture monitoring networks to develop understanding of when, where, and under what conditions PF occurs. Newly developed methods may lead to better accuracy and reliability, and reduce the need for subjective judgments. Plain Language Summary Preferential flow through soil occurs when a large amount of water is suddenly available, as during an intense storm. This type of flow moves rapidly through the soil in distinct narrow pathways rather than moving evenly throughout the body of soil, with major consequences for groundwater resources, ecosystems, spreading of contaminants, and other vital concerns. Methods of detecting preferential flow have been developed that utilize measurements of soil water content made by sensors installed at various depths. This measurement technology has been widely implemented, many locations now having datasets years in length, and various methods have been developed for using these to identify preferential flow. The various methods are based on different features in the soil moisture records and vary in their advantages and shortcomings. In this review, we explain and evaluate these methods, highlighting important information for their implementation to identify preferential flow from soil moisture data and for efforts to develop new methods or improve existing ones.

Nimmo, John R↗

DOE OSTI2020

The Sealing Mechanisms of a Fracture in Opalinus Clay as Revealed by in situ Synchrotron X-Ray Micro-Tomography

The detailed mechanisms of the sealing of a single fracture, from hydration to almost complete closure by increase of confining pressure, as monitored from in situ synchrotron X-ray microtomography during the flow of carbonated water, is here shown for the first time. Different mechanisms play the key role at different stages in the evolution of the fracture. Hydration mechanically weakens the surfaces of the fracture and induces a first closure due to microcracking at the asperity contacts, increasing their size and creating choke points. Increase in confining stress promptly hydraulically seals the fracture by closing the main choke point, with a relative small deformation of the sample. Finally, the more pervasive mechanical deformation observed at higher stresses almost completely seals the whole fracture. The evolution of the sample has been described and quantified using 4D image processing, focusing on the evolution of aperture and digital volume correlation. Hydraulic properties of the sample at different stages have been modeled via Stokes flow simulation, and the results compared to the morphometric analysis, finding positive correlations with the average fracture aperture variation along the flowpath in function of confining pressure. Opalinus Clay is found to be a rock markedly prone to sealing in case of flow with carbonated water; this behavior is the result of the large fraction of clays and of its microstructure, lacking both cementing phases and large stiff particles. CO2 in this sample has no evident role in the evolution of the fracture; chemically induced weathering on the surface has not been detected, in contrast with the behavior observed in samples with carbonates as cementing phase.

58 GEOSCIENCES↗

DOE OSTI2022

Correlating Time-Resolved Pressure Measurements With Rim Sealing Effectiveness for Real-Time Turbine Health Monitoring

Purge flow is bled from the upstream compressor and supplied to the under-platform region to prevent hot main gas path ingress that damages vulnerable under-platform hardware components. A majority of turbine rim seal research has sought to identify methods of improving sealing technologies and understanding the physical mechanisms that drive ingress. While these studies directly support the design and analysis of advanced rim seal geometries and purge flow systems, the studies are limited in their applicability to real-time monitoring required for condition-based operation and maintenance. As operational hours increase for in-service engines, this lack of rim seal performance feedback results in progressive degradation of sealing effectiveness, thereby leading to reduced hardware life. To address this need for rim seal performance monitoring, this study utilizes measurements from a one-stage turbine research facility operating with true-scale engine hardware at engine-relevant conditions. Time-resolved pressure measurements collected from the rim seal region are regressed with sealing effectiveness through the use of common machine learning techniques to provide real-time feedback of sealing effectiveness. Two modeling approaches are presented that use a single sensor to predict sealing effectiveness accurately over a range of two turbine operating conditions. Here, the results show that an initial purely data-driven model can be further improved using domain knowledge of relevant turbine operations, which yields sealing effectiveness predictions within 3% of measured values.

42 ENGINEERING↗

DOE OSTI2021

Correlating Time-Resolved Pressure Measurements With Rim Sealing Effectiveness for Real-Time Turbine Health Monitoring

Purge flow is bled from the upstream compressor and supplied to the under-platform region to prevent hot main gas path ingress that damages vulnerable under-platform hardware components. A majority of turbine rim seal research has sought to identify methods of improving sealing technologies and understanding the physical mechanisms that drive ingress. While these studies directly support the design and analysis of advanced rim seal geometries and purge flow systems, the studies are limited in their applicability to real-time monitoring required for condition-based operation and maintenance. As operational hours increase for in-service engines, this lack of rim seal performance feedback results in progressive degradation of sealing effectiveness, thereby leading to reduced hardware life. To address this need for rim seal performance monitoring, the present study utilizes measurements from a one-stage turbine research facility operating with true-scale engine hardware at engine-relevant conditions. Time-resolved pressure measurements collected from the rim seal region are regressed with sealing effectiveness through the use of common machine learning techniques to provide real-time feedback of sealing effectiveness. Two modelling approaches are presented that use a single sensor to predict sealing effectiveness accurately over a range of two turbine operating conditions. Results show that an initial purely data-driven model can be further improved using domain knowledge of relevant turbine operations, which yields sealing effectiveness predictions within three percent of measured values.

Compressors↗

DOE OSTI2025

Multiscale Thermal-hydraulic analysis of the MARVEL micro-reactor using coupled MOOSE Subchannel (SCM) and SAM

MARVEL is a natural-convection-cooled sodium-potassium microreactor that is anticipated to generate 85 kilowatts of thermal energy. It will operate within Idaho National Laboratory’s Transient Reactor Test Facility and is being developed by the DOE Microreactor Program. MARVEL will be used to test microreactor applications, evaluate systems for remote monitoring, and develop autonomous control technologies. A thermal-hydraulic computational model of this facility is a valuable tool to study important transients and calculate the safety limits of the micro-reactor design. For this purpose, the authors have chosen to use a multiscale coupled simulation: SCM for modeling the reactor core and SAM for the reactor’s primary cooling system. SCM is MOOSE physics module for subchannel analysis, which was designed to model single-phase flows through liquid-metal cooled, wire-wrapped fuel pin sub-assemblies, ordered in a triangular lattice. The SCM code was modified to be able to model MARVEL’s unique geometry. SAM is a systems analysis module based on the MOOSE framework. It aims to provide fast-running, whole-plant transient analyses capability with improved-fidelity for various advanced reactor types. The coupling between the two SCM and SAM for MARVEL modeling is done implementing a domain over-lapping approach. The resulting coupled simulation can model transients such as reactor startup/shutdown and provide an intermediate fidelity picture of the temperature field and other variables, in the core. Results for the steady-state simulations are presented in the article as well as flow blockage transient.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Multiscale Thermal-hydraulic analysis of the MARVEL microreactor using a coupled SAM and SCM simulation. (PPTX)

This is .pptx document presenting a summary of the paper of the same name that has been submitted and accepted to NURETH-21: MARVEL is a natural-convection-cooled sodium-potassium microreactor that is anticipated to generate 85 kilowatts of thermal energy. It will operate within Idaho National Laboratory Transient Reactor Test Facility and is being developed by the DOE Microreactor Program. MARVEL will be used to test microreactor applications, evaluate systems for remote monitoring, and develop autonomous control technologies. A thermal-hydraulic computational model of this facility is a valuable tool to study important transients and calculate the safety limits of the micro-reactor design. For this purpose, the authors have chosen to use a multiscale coupled simulation: SCM for modeling the reactor core and SAM for the reactor's primary cooling system. SCM is MOOSE physics module for subchannel analysis, which was designed to model single-phase flows through liquid-metal cooled, wire-wrapped fuel pin sub-assemblies, ordered in a triangular lattice. The SCM code was modified to be able to model MARVEL?s unique geometry. SAM is a systems analysis module based on the MOOSE framework. It aims to provide fast-running, whole-plant transient analyses capability with improved-fidelity for various advanced reactor types. The coupling between the two SCM and SAM for MARVEL modeling is done implementing a domain over-lapping approach. The resulting coupled simulation can model transients such as reactor startup/shutdown and provide an intermediate fidelity picture of the temperature field and other variables, in the core. Results for the steady-state simulations are presented in the article as well as flow blockage transient.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2025

Scattering insights into shear-induced scission of rod-like micelles

Understanding the scission of rod-like micelles under mechanical forces is crucial for optimizing their stability and behavior in industrial applications. This study investigates how micelle length, flexibility, and external forces interact, offering insights into the design of micellar systems in processes influenced by mechanical stress. Although significant, direct experimental observations of flow-induced micellar scission using scattering techniques remain scarce. Small angle neutron scattering (SANS) is used to explore the shear response of aqueous cetyltrimethylammonium bromide (CTAB) solutions with sodium nitrate. Rheological tests show shear thinning with no shear banding, ensuring a uniform flow field for reliable interpretation of scattering data. As shear rate increases, the scattering spectra show angular distortion, which is analyzed using spherical harmonic decomposition to characterize flow-induced scission and micelle orientation under shear. Two analysis steps are used: a model-independent spectral eigendecomposition reveals a decrease in micellar length, while regression analysis quantifies the evolution of the length distribution and mean length with shear rate. Additionally, micelle alignment increases with shear, quantified by the orientational distribution function. In conclusion, these findings provide experimental evidence for flow-induced alignment and scission, offering a new framework for understanding shear-induced phenomena in micellar systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Thermal Performance of Triply Periodic Minimal Surface Lattice Structures in Single-Phase Dielectric Fluid Cooling of Power Electronics

Additive manufacturing has transformed thermal management by enabling the production of complex, optimized geometries that conventional manufacturing methods cannot achieve. This study investigates the single-phase convective heat transfer performance of gyroid triply periodic minimal surface (TPMS) lattice structures with functional porosity. TPMS structures provide high surface area to volume ratios and are amenable to 3D printing. A gyroid numerical model was created and validated against an existing experimental study with a similar feature size to the investigated geometries. The TPMS structure has a periodic width of 1.6 mm, a length of 10 mm, and a height of 4 mm, with a functional porosity ranging from 0.5 to 0.8, decreasing with distance from the heated surface. Three different flow configurations were examined for an inlet fluid temperature of 70 °C. The inlet velocities range from 0.01 to 1.2 m/s, corresponding to a Reynolds number range of 10–900 with a heat flux of 50 W/cm 2 applied at the base. AmpCool ® AC-110 dielectric fluid (Prandtl number 59.5) was used as the coolant. Thermal performance and friction characteristics were studied for the three flow orientations. The parallel flow configuration was identified as the most efficient for heat removal. A detailed analysis of the numerical results highlights the underlying physics behind the thermal performance differences among the flow configurations.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

An approximate inertial manifold (AIM) based closure for turbulent flows

A closure model for turbulent flows is developed based on a dynamical system theory. An appropriately discretized formulation of the governing equations is considered for this process. The key ingredient is an approximation of the system’s attractor, where all the trajectories in phase space are confined. This approximate inertial manifold based approach provides a path to track trajectories of the system in a lower-dimensional subspace. Unlike conventional coarse-graining approaches, the turbulent field is decomposed into resolved and unresolved dynamics using the properties of the governing equations. The novelty of the approach relies on the reconstruction of the unresolved field constrained by the governing equations. A posteriori tests for homogeneous isotropic turbulence and the Kuramoto–Sivashinsky equation show promising results for considerable dimension reduction with strong convergence properties. The proposed model outperforms the dynamic Smagorinsky model, and the computational overhead is competitive with similar approaches.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

SAS4A/SASSYS-1 Validation with EBR-II Tests Performed During the SHRT Testing Program (Rev. 2)

The EBR-II sodium-cooled fast reactor supported a wide range of fast reactor research activities. The final fifteen years of operations at EBR-II were used for experiments and tests to demonstrate the importance of passive safety in liquid metal reactors and the capability of such systems to provide strong passive responses during off-normal conditions. The Shutdown Heat Removal Test program at EBR-II provided test data supporting the validation of computer codes for design, licensing, and operation of LMRs, among other objectives. The program included nearly sixty tests, most of which were protected and unprotected loss of flow and loss of heat sink tests run at various initial powers and flow rates. This report documents the results of modeling and simulation of tests from the Shutdown Heat Removal Test program to support validation of Argonne’s SAS4A/SASSYS-1 fast reactor safety analysis code. SHRT-17 and SHRT-6 were protected loss of flow tests where a loss of electrical power to all sodium coolant pumps was simulated to demonstrate the effectiveness of natural circulation cooling characteristics. SHRT-45R, SHRT-39, and SHRT-43R were unprotected loss of flow tests where the control rod scram function of the plant protection system was disabled to demonstrate the effectiveness of EBR-II’s passive reactivity feedbacks. BOP-301 and BOP-302R were unprotected loss of heat sink tests that demonstrated how reactivity feedback effects driven by changes to the core inlet temperature can shut down the fission process. PICT-5/6 demonstrated how core power could be increased and decreased via changes in the intermediate sodium and feedwater flow rates. This validation activity leverages modeling and simulation efforts that originated under an International Atomic Energy Agency Coordinated Research Project for benchmark analysis of the EBR-II Shutdown Heat Removal Tests. The SAS4A/SASSYS-1 models originally developed for the CRP have been modernized to utilize new code features and modeling practices. Differences between the predicted and measured test data were explored and the causes of these differences were identified as being due to modeling approximations, uncertainty in transient component behavior, and instrumentation uncertainties. Overall, it was concluded that for all tests simulated there was good agreement between the flow, power, and temperature predictions and the measured data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Particle image velocimetry analysis with simultaneous uncertainty quantification using Bayesian neural networks

Particle image velocimetry (PIV) is an effective tool in experimental fluid mechanics for extracting flow fields from images. Recently, convolutional neural networks (CNNs) have been used to perform PIV analysis with accuracy on par with classical methods. Here we extend the use of CNNs to analyze PIV data while providing simultaneous uncertainty quantification on the inferred flow field. The method we apply in this paper is a Bayesian convolutional neural network (BCNN) which learns distributions of the CNN weights through variational Bayes. In order to demonstrate the utility of BCNNs for the PIV task, we compare the performance of three distinct BCNN models with simple architectures. The first network estimates flow velocity from image interrogation regions only. Our second model learns to infer velocity from both the image interrogation regions and interrogation region cross-correlation maps. Finally, our best performing network infers velocities from interrogation region cross-correlation maps only. We find that BCNNs using interrogation region cross-correlation maps as inputs perform better than those using interrogation windows only as inputs and discuss reasons why this may be the case. Additionally, we test the best performing BCNN on a full synthetic test image pair and a real image pair from the 1st International PIV Challenge. We show that ~98% of true particle displacements from the full synthetic image pair can be captured within the BCNN's 95% confidence intervals, and that the BCNN's performance on the real image pair is quantitatively similar to that of algorithms tested in the 1st International PIV Challenge. Finally, we show that BCNNs can be generalized to be used with multi-pass PIV algorithms with a moderate loss in accuracy, which may be overcome by future work on finetuning and training schemes. So to our knowledge, this is the first use of Bayesian neural networks to perform PIV.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Reduced Order Models Generation for HTGRs Pebble Shuffling Procedure Optimization Studies

This report provides an initial study for producing reduced-order models (ROMs) of pebble-bed high temperature gas reactor (HTGR) models for the purposes of design optimization. As an initial study, this work is meant to be exploratory---identifying useful workflows and methods for ROM generation---and not meant to be a catch-all analysis of HTGR ROM generation and usage for optimization. This report summarizes three tasks performed in Fiscal Year 2022: 1) the creation of HTGR model, 2) the sensitivity analysis of model design parameters, and 3) an introduction to ROM generation techniques. The representative HTGR model created in this work is a multiphysics equilibrium-core using the BlueCRAB (comprehensive reactor analysis bundle) reactor analysis application, coupling four physical phenomena: neutronics, streamline depletion, porous flow thermal hydraulics, and pebble heat conduction. Part of the model creation was identifying some design parameters and quantities of interest that are relevant in an optimization analysis and adjustable in the model. The sensitivity analysis utilized a polynomial chaos expansion methodology to compute global sensitivity metrics. This analysis showed that thermal hydraulics parameters and quantities of interest had a relatively small impact on simulation results. Finally, the ROM generation work involved exploring three different ROM methodologies: polynomial regression, a Gaussian process, and artificial neural networks. Using a cross-validation technique to characterize ROM performance, the Gaussian process and single-layer artificial neural networks showed the most promising results. Overall, this study was insightful and the lessons learned will be invaluable for the eventual development of an HTGR design optimization workflow.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Can classical DEM simultaneously capture compressibility and flowability of milled biomass?

Accurate prediction of the rheological behavior of biomass is essential for the design and operation of hoppers, feeders, and storage systems in biorefineries. This study examines whether the classical, coarse-grained discrete element method (DEM) formulation can simultaneously reproduce the compressibility and flowability of milled herbaceous biomass, using Miscanthus × giganteus as a representative material. The model represents particles as rigid spheres interacting through Hertz-Mindlin elastic-frictional contacts augmented with an area-dependent cohesion term. Laboratory cyclic compression and wedge-shaped hopper discharge experiments were used as calibration benchmarks. Although the model can independently reproduce each behavior by appropriately tuning particle Young's modulus E and cohesion energy density k, an extensive parametric investigation comprising more than 600 simulations reveals that the optimal parameter regions for compression and hopper flow are distinct and non-overlapping in (E, k) space. Surrogate surface analysis further shows that the corresponding objective-function valleys exhibit similar trends but are approximately parallel and spatially offset, precluding a unified calibration within the explored domain. Sensitivity analysis indicates that compressibility is governed predominantly by stiffness and cohesion, whereas the slope of the mass flow rate-opening relation in hopper discharge is primarily controlled by tangential friction. Extensions incorporating particle size distribution and clumped-sphere representations do not eliminate the incompatibility. These results systematically reveal, for the first time, the structural limitation of simplified DEM formulations in representing biomass rheological behavior, underscoring the necessity for models incorporating additional physical mechanisms, such as particle deformability or enhanced interlocking, to achieve unified predictive capability for biomass handling behavior.

09 BIOMASS FUELS↗

DOE OSTI2022

Experimental measurements of fluid flow in an 84-pin hexagonal rod bundle with spacer grid for a gas-cooled fast modular reactor

A 50 MW e helium-cooled fast modular reactor (FMR) is under development, and as part of the Department of Energy Integrated Research Project (IRP), Texas A&M University is conducting the thermal-hydraulic characterization of its baseline core configuration. Here, we experimentally investigated the axial and cross flow fields characteristics in the hexagonal fuel rod bundle composed of 84 rods, a central rod, and spacer grids at a Reynolds number of 12,000. A fully transparent experimental facility resembling of one unit of the fuel assembly was constructed. Time-resolved particle image velocimetry (TR-PIV) measurements were performed to characterize hydraulic behavior downstream the spacer grid. Velocity measurements were conducted in the axial and radial direction of the rod bundle. From the PIV velocity vector fields, the full-field flow statistics were computed for the mean velocity, vorticity, and Reynolds stresses. An analysis of the energy decay downstream of the spacer grid was conducted with calculations of secondary-flow intensities, turbulent kinetic energy, power spectrum, and spatial-temporal velocity cross correlations. The vorticity field was obtained and pairs of counter-rotating vortexes were identified using a 3D reconstruction of several measurement planes. The data from this experimental campaign will be used to validate numerical models based on Computational Fluid Dynamics and other codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

A methodology for domain overlapping coupling of thermal-hydraulic systems

Multi-scale coupling has increasingly drawn attention as a promising approach for modeling thermal systems. Traditional system codes provide fast and robust predictions at the plant scale, while high-fidelity computational fluid dynamics (CFD)-based tools resolve localized flow and heat transfer phenomena with greater accuracy. By combining these complementary strengths, co-simulations enable multi-scale analysis that would otherwise be computationally prohibitive for a standalone CFD code. Here, this work introduces a robust and problem-agnostic domain overlapping (DO) coupling between the system thermal-hydraulic (STH) code System Analysis Module (SAM) and the coarse-mesh CFD code Pronghorn. Both applications belong to the Comprehensive Reactor Analysis Bundle (BlueCRAB) code suite, a code suite in active development at the Idaho National Laboratory (INL), tailored for multi-physics analysis of advanced reactors. Unlike previous approaches, BlueCRAB supports an agnostic interface between codes based on different fidelity, while its coupling formulation can address arbitrary flow geometries with multiple inlets and outlets in coupled components. The implemented method leads to consistent pressure drops, enthalpies, and scalar concentrations between coupled SAM and Pronghorn simulations. The methodology is demonstrated through two verification tests, which ensure the numerical consistency and conservation across the codes, and through one validation test against experimental data. The proposed problems explore different physical aspects inherent to thermal systems, with particular attention given to nuclear reactor analysis. These include buoyancy-driven flows, complex flow patterns, and setups with multiple inlets and outlets, representing challenges in advanced reactor applications.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Aerosol Particle Deposition on a Spent Nuclear Fuel Assembly Spacer Grid

The flow and particle deposition patterns on surfaces in an idealized spacer grid for a 17x17 pressurized water reactor (PWR) assembly in a spent fuel canister are modeled using computational fluid dynamics (CFD) with laminar flow. The effects of gravitational settling, non-Stokesian flow, and particle slip are first rigorously analyzed. From the analysis, non-Stokesian effects and slip may be neglected for the particle sizes and conditions expected in a canister. For particles that do not settle out, a swirling flow pattern at the corners of a spacer grid channel directs particles to the leeward side of the flow vanes where much of the deposition occurs. Particle deposition increases with increasing particle diameter. Deposition also increases with decreasing flow velocity as this provides more time for particles to settle and deposit on the leeward side of the flow vanes. The fraction of particles that are transmitted through a spacer grid is determined as a function of inlet gas velocity and particle diameter by running the CFD calculation for each set of conditions and for each particle diameter. Curve fits of the transmission curve as a function of particle diameter for a specified spacer grid and flow velocity are applied to a lognormal particle mass density function for the inlet particles. The resulting mass density function and aerosol mass fraction that passes through the spacer grid can be determined analytically without resorting to numerical iteration. A sample calculation of the analytical solution is demonstrated for a lognormal particle mass density function.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Tritium Transport Phenomena in Molten-Salt Reactors: Molten Salt Tritium Transport Experiment Design

Tritium is produced from neutron interactions with both lithium and beryllium. Large quantities of tritium are generated in Molten Salt Reactors (MSRs) which use LiF/BeF2 (FLiBe) as the fuel salt. Tritium is unique among the radionuclide hazards as it readily permeates through metal structural materials at high temperatures. All metal surfaces are potential release paths for tritium. For adequate safety analysis and eventual licensing of new reactors, predictive models for tritium transport and release from MSRs must be developed. These models must account for the multiple transport phenomena involved with tritium: fuel salt phase mass transport, dissociation/recombination reactions on metal surfaces, interstitial diffusion through the metal structure, and salt or gas phase mass transport in the downstream fluid. These models also must also be validated with representative experiments. Our previous report outlined tritium transport phenomena involved in MSRs, made suggestions on gaps in the transport dataset, and proposed an experimental test stand to test combined transport effects – tritium transport through pipe walls in a convective salt flow. In this report, we summarize an updated analysis framework for tritium transport in MSRs, report our results on hydrogen and deuterium permeation through Hastelloy N, and describe the final design of the Molten Salt Tritium Transport Experiment (MSTTE, pronounced “misty”). The MSRE provides the only wholistic experimental data set for tritium transport in MSRs and understanding the transport phenomena involved in the MSRE is crucial for future model development. One set of parameters in our analysis framework was unknown for the MSRE—surface reaction rates for tritium on Hastelloy N. This warranted our hydrogen and deuterium permeation campaign to assess the permeability, diffusivity, and solubility of hydrogen isotopes in clean Hastelloy N. Surface reaction rate constants were probed by low pressure measurements, however, no surface effects were observed in the limits of our permeation apparatus. Permeation experiments on oxidized Hastelloy N were not performed for this report but are planned in future work. The experimental test stand, MSTTE, measures combined transport properties of the salt-metal system. MSTTE is a forced convection FLiBe loop with custom designed test section to measure tritium transport through candidate structural materials. We use MSRE relevant dimensionless numbers to design and scale the test section. Hastelloy N is a candidate loop and test section material due to the relevance for the MSRE and related designs, however, other metals are being considered (e.g. 316H SS) which may better align with current vendor concepts.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Experimental Investigation of Uranium and Iron Condensation from High-Temperature Plasma Conditions

We used a plasma flow reactor (PFR) to generate synthetic fallout nanoparticles from vapor-phase condensation of two different input concentrations of uranium and iron analytes (U/Fe = 1:1 and 1:2). Synthetic fallout from complex chemical matrices (e.g., mixtures of U and Fe) has not been generated in this setup before and allows for the observation of relative condensation and fractionation of nuclear debris. Experiments were conducted under two different temperature histories with variations in particle flow patterns along the PFR. Transmission electron microscopy (TEM) observation and analysis of the nanoparticles revealed variations in speciation of uranium oxides (UO 2 and α-UO 3 ) depending on the competition between flow mixing and oxygen sequestration by iron. A ternary metal oxide, UFeO 4 , was observed in addition to iron oxides (e.g., FeO and Fe 3 O 4 ), which suggests that fallout models should account for chemical speciation of ternary metal oxides (i.e., UFeO 4 ) and their relative condensation behaviors in addition to those of singular metal oxides (e.g., FeO and UO 2 ). X-ray Energy Dispersive Spectroscopy (EDS) elemental maps showed that some particles had Fe-rich cores surrounded by U-rich regions. This suggests that either condensed U oxides coagulate onto molten Fe oxides or that the increase in iron analyte concentration might drive the system toward a higher degree of supersaturation, leading to earlier formation of iron oxide particles and providing an energetically favored pathway for nucleation of uranium oxides around iron oxide particles.

and nuclear chemistry↗