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DOE OSTI2023

A Design and Fabrication Options Trade Study for Metallic Fuel without Internal Sodium Bonding

Nuclear fuels using alloys of uranium, or metallic fuels, have many beneficial properties. The classical metallic fuel design uses a loose fitting cylindrical “slug” of fuel placed inside stainless-steel cladding tubes where the gap is filled with sodium. This sodium bond is liquid at operating temperature and conducts heat from the slug to the cladding, especially in early life before fuel swells into contact with the cladding. Despite the benefits of sodium bonding, there is a desire to develop metallic fuel technologies without it chiefly to reduce chemical reaction hazards in spent fuel storage from sodium fast reactors operating on once-through fuel cycles. Elimination of the sodium bond may also help unlock potential benefits for fuel fabrication, reactor neutronics, and compatibility with other types of reactors. Creating a sodium-free metallic fuel revolves around the problem of manufacturing fuel slug geometries which are in close contact with the cladding at beginning of life to facilitate heat transport while alleviating fuel-cladding chemical interactions (FCCI) at this interface and providing enough free volume to accommodate fuel swelling. Accelerating development and qualification of this fuel system will require careful selection of design and manufacturing options. To this end, a design trade-off study was performed to evaluate candidate options. Several design and manufacturing options were assessed, weighted, scored, and ranked with respect to fabrication, normal reactor operation, off-normal scenarios, and back-end considerations. This effort was performed both for “baseline” needs, which represented a once-through fuel cycle at temperatures and burnups known to be viable for sodium-bonded metallic fuel, and for “enhanced” needs to represent opportunities for closed fuel cycles and/or more aggressive temperatures/burnups. The outcomes of this study prioritized a baseline technology using U-Zr alloy with additives to mitigate FCCI, produced in annular slug geometry by continuous casting, clad in austenitic stainless-steel alloy, and followed by a final step to swage the cladding down to close the gap. This study prioritized an enhanced fuel technology using U-Mo alloy, also produced by continuous casting into an annular geometry, followed by coating/plating with an FCCI barrier on the slug, again with a final step to swage the cladding diameter down using oxide dispersion strengthened steel. It was noted that development of the enhanced fuel technology would entail more risk, thus U-Zr alloy was put forth as a backup to U-Mo if challenges are encountered with FCCI barriers, and advanced ferritic/martensitic steels are put forth as a backup to oxide dispersion strengthened steels if swaging and welding are found unworkable.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Noble Gas Transport in the MSRE

This study explores the relationship between the physicochemical parameter known as Henry’s gas constant and gas transport across a two-layer film interface. The investigation utilized the Gibbs free energy, incorporating surface and volume terms to elucidate trends in enthalpy and entropy. Notably, our findings align with experimental data and offer predictive insights into the Henry’s gas constants for helium and krypton, which hold significance for future experiments and theoretical developments. Furthermore, this study enhances the Gibbs free energy theory pertaining to the liquid–gas interface. It underscores the substantial contribution of noble gases in this region to volumetric energy as temperature increases. Additionally, we employed Monte Carlo simulations to analyze the effective thermal neutron multiplication factor, denoted as k eff . Our analysis reveals a linear correlation between graphite density and uniform density as a function of temperature. For the 1D Molten Salt Reactor Experiment (MSRE) system, we employed the Mole code to conduct heat and mass transfer calculations. These computations enable us to ascertain the distribution of fuel temperature based on coefficients and thermal properties. We also studied delayed neutron precursors during fuel cycling, taking into account the drift of cycling fuel through Mole–Griffin coupling. Our model represents k eff and β eff across various volume flow rates and salinity compositions. Finally, this study leveraged xenon-135 for continuous on-line monitoring of fuel salts to investigate the impact of steady-state xenon-135 on the MSRE and to better understand its distribution. These efforts build upon previous research related to removal processes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

FY26 Progress on Demonstration of a Multiphysics Steady State Capability for Modeling Core Radial Expansion in SFRs

Under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, an integrated multiphysics approach is being developed to model the core bowing phenomena important to liquid metal-cooled fast reactors. Core bowing is an important passive safety mechanism in liquid metal-cooled fast reactors and involves multiphysics effects including radiation transport, fluid flow, heat transfer, and mechanical response to temperature and flux gradients. This report summarizes recent progress on developing a multiphysics, MOOSE-based workflow to predict core bowing and associated reactivity feedback. Significant new capabilities in the reactor physics code Griffin - sodium backfill and pin power reconstruction for deformed geometries - were applied in this effort. This year’s work included verification, code comparisons, sensitivity studies, and coupled demonstrations that advance the state of MOOSE-based core bowing workflow. Griffin’s sodium backfill capability was verified by demonstrating that its automated treatment of geometry expansion and material-density updates reproduces manual calculations exactly, confirming solid mass conservation and proper coolant backfilling in expanded geometries. Reconstructed pin powers were compared for Griffin’s ductheterogeneous and ring-heterogeneous treatments in single-, seven-, and nineteen-assembly cases, with best agreement observed in lower-leakage configurations and the duct-heterogeneous approach offering substantially lower computational cost. Thermal-hydraulic sensitivity sensitivities showed that MOOSE SCM, SAM, and CFD are expected to produce similar deformation predictions despite variances in their temperature predictions, and that explicit treatment of inter-assembly flow becomes increasingly important as gap flow rate increases. Finally, coupled demonstrations on small multi-assembly configurations using Griffin, MOOSE Solid Mechanics, MOOSE SCM, and Heat Conduction produced physically consistent reactivity feedback from thermal expansion and bowing. The coupled demonstrations simulated grid plate expansion as well as resultant core bowing at full power conditions. Simplifications were made in current workflow, namely the assumption of instantaneous full power conditions following hot zero power, and pre-expanding the Griffin geometry axially due to lack of an axial fuel pin expansion model and temperature feedback to Griffin.

Wozniak, Nicholas↗

DOE OSTI2023

Numerical Investigation of Wall-Cooling Effect on Aero-Optical Distortions for Hypersonic Boundary Layer

Compressible wall-modeled large-eddy simulations of Mach 8 turbulent boundary-layer flows over a flat plate were carried out for the conditions of the hypersonic wind tunnel at Sandia National Laboratories. The simulations provide new insight into the effect of wall cooling on the aero-optical path distortions for hypersonic turbulent boundary-layer flows. Four different wall-to-recovery temperature ratios, 0.3, 0.48, 0.71, and 0.89, are considered. Despite the much lower grid resolution, the mean velocity, temperature, and resolved Reynolds stress profiles from the simulation for a temperature ratio of 0.48 are in good agreement with those from a reference direct numerical simulation. The normalized root-mean-square optical path difference obtained from the present simulations is compared with that from reference direct numerical simulations, Sandia experiments, as well as predictions obtained with a semi-analytical model by Notre Dame University. Here the present analysis focuses on the effect of wall cooling on the wall-normal density correlations, on key underlying assumptions of the aforementioned model such as the strong Reynolds analogy, and on the elevation angle effect on the optical path difference. Wall cooling is found to increase the velocity fluctuations and decrease the density fluctuations, resulting in an overall reduction of the normalized optical path distortion. Compared to the simulations, the basic strong Reynolds analogy overpredicts the temperature fluctuations for cooled walls. Also different from the strong Reynolds analogy, the velocity and temperature fluctuations are not perfectly anticorrelated. Finally, as the wall temperature is raised, the density correlation length, away from the wall but inside the boundary layer, increases significantly for beam paths tilted in the downstream direction.

42 ENGINEERING↗

DOE OSTI2023

Demonstration of Pronghorn’s Subchannel Code Modeling of Liquid-Metal Reactors and Validation in Normal Operation Conditions and Blockage Scenarios

Pronghorn-SC is a subchannel code within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Initially designed to simulate flows in water-cooled, square lattice, subchannel assemblies, Pronghorn-SC has been expanded to simulate liquid-metal-cooled flows in triangular lattices, hexagonal subchannel assemblies. For this purpose, the algorithm of Pronghorn-SC was adapted to solve the subchannel equations as they are applicable to a hexagonal wire-wrapped sodium-cooled fast reactor. Cheng–Todreas models for pressure drop and cross-flow models were adopted and a coolant heat conduction term was added. To solve these equations, an improved implicit algorithm was developed robust enough to deal with the numerical issues, associated with low flow and recirculation phenomena. To confirm the prediction capability of Pronghorn-SC, calculations and comparisons with available experimental data of 19- and 37-pin assemblies were performed, as well as other subchannel codes. Finally, a flow blockage modeling feature was added. This capability was validated for both water-cooled square sub-assemblies and sodium-cooled hexagonal sub-assemblies, using experimental data of partially and fully blocked cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Creep Behavior of Compact γ′-γ″ Coprecipitation Strengthened IN718-Variant Superalloy

The development of high-temperature heavy-duty turbine disk materials is critical for improving the overall efficiency of combined cycle power plants. An alloy development strategy to this end involves superalloys strengthened by ‘compact’ γ′-γ″ coprecipitates. Compact morphology of coprecipitates consists of a cuboidal γ′ precipitate such that γ″ discs coat its six {001} faces. The present work is an attempt to investigate the microstructure and creep behavior of a fully aged alloy exhibiting compact coprecipitates. We conducted heat treatments, detailed microstructural characterization, and creep testing at 1200 °F (649 °C) on an IN718-variant alloy. Our results indicate that aged IN718-27 samples exhibit a relatively uniform distribution of compact coprecipitates, irrespective of the cooling rate. However, the alloy ruptured at low strains during creep tests at 1200 °F (649 °C). At 100 ksi (689 MPa) load, the alloy fails around 0.1% strain, and 75 ksi (517 MPa) loading causes rupture at 0.3% strain. We also report extensive intergranular failure in all the tested samples, which is attributed to cracking along grain boundary precipitates. The results suggest that while the compact coprecipitates are indeed thermally stable during thermomechanical processing, the microstructure of the alloy needs to be optimized for better creep strength and rupture life.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Effects of Plasma on Physical Properties of Water: Nanocrystalline-to-Amorphous Phase Transition and Improving Produce Washing

Washing fresh produce using Plasma-activated water recently became a promising eco-friendly alternative to using chemical additives such as Chlorine. We discuss the produce-washing experiments that illustrate that addition of plasma to washing water is a multi-faced phenomena. Not only it increases the sterilization ability of water by killing pathogens, but it also has improved washibility: the ability to remove pathogens from the cleaning surface. We propose an explanation of these features based on the recently discoveries that many physical and chemical properties of water change their temperature dependence between about 35 and 60 degrees Celsius. In particular, heat conductance, light absorption, and surface tension all change their temperature dependence. These drastic changes were associated with water gradually changing its mesoscopic structure: while at the higher temperatures water is a uniform media (amorphous state), at the temperatures below transition it consists of many nano-to-micro-scale clusters (crystalline state). This transition is similar to the second order phase transition. In the present paper we propose that treating water with non-thermal plasma (adding plasma-created active compounds) can lower the temperature of the transition and thus cause a significant change in such physical quantities as surface tension, viscosity, freezing rate, and wettability and washability.

He, Jinjie↗

DOE OSTI2024

A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling

Numerical solvers of partial differential equations (PDEs) have been widely employed for simulating physical systems. However, the computational cost remains a major bottleneck in various scientific and engineering applications, which has motivated the development of reduced-order models (ROMs). Recently, machine-learning-based ROMs have gained significant popularity and are promising for addressing some limitations of traditional ROM methods, especially for advection dominated systems. In this chapter, we focus on a particular framework known as Latent Space Dynamics Identification (LaSDI), which transforms the high-fidelity data, governed by a PDE, to simpler and low-dimensional latent-space data, governed by ordinary differential equations (ODEs). These ODEs can be learned and subsequently interpolated to make ROM predictions. Each building block of LaSDI can be easily modulated depending on the application, which makes the LaSDI framework highly flexible. In particular, we present strategies to enforce the laws of thermodynamics into LaSDI models (tLaSDI), enhance robustness in the presence of noise through the weak form (WLaSDI), select high-fidelity training data efficiently through active learning (gLaSDI, GPLaSDI), and quantify the ROM prediction uncertainty through Gaussian processes (GPLaSDI). We demonstrate the performance of different LaSDI approaches on Burgers equation, a non-linear heat conduction problem, and a plasma physics problem, showing that LaSDI algorithms can achieve relative errors of less than a few percent and up to thousands of times speed-ups.

Computational Engineering, Finance, and Science (c↗

DOE OSTI2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data

This dataset consists of soil temperature time series that were used to estimate soil thermal diffusivity and its uncertainty trough the probabilistic modelling approach developed and presented in the article named "Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series" and published in Earth Surface Dynamics. There are two compressed (.zip) files that contains synthetic (Synthetic_soiltemp_Teller.zip) and field (Field_soiltemp_Teller.zip) data. There is one MATLAB file that requires MATLAB to execute but any text editor can open it. The Synthetic_soiltemp_Teller.zip file includes 5 comma-delimited data files (.csv) each of which contains soil temperature time series generated through forward modeling (i.e., heat-conduction process in a heterogeneous medium using an explicit finite difference method) to mimic various types of temperature gradients, trend and fluctuations. These synthetic soil temperatures were used to investigate the impact of different environmental conditions on the uncertainty of thermal diffusivity estimates. The Field_soiltemp_Teller.zip file contains 28 comma-delimited data files (.csv) out of which (a) 27 files includes soil temperature time series recorded from 27 temperature probes located in a site along Teller Road about 40 km northwest of Nome, Alaska (64.72°N, 165.94°W), (b) one includes the name and coordinates of the 27 probes. These field soil temperatures were used to infer soil thermal diffusivity at numerous locations and depths in a discontinuous permafrost environment, and to evaluate the links between the estimated soil thermal diffusivity values and soil physical properties. The comma-delimited data files (.csv) of the synthetic and field soil temperature time series includes date and time (UTC) in the first column and soil temperature from 5 cm below the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors) in the other columns. The measurements were acquired every 15 minutes. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Comparison between PARFUME and Bison Using the AGR-2 Irradiation Experiment

This report documents comparisons between Fuel Model (PARFUME) model predictions versus Bison for selected compacts from the second irradiation test of the Advanced Gas Reactor (AGR) program that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). PARFUME is a fuel performance analysis and modeling code, used for evaluating gas-reactor tristructural isotropic (TRISO) coated particle fuel for prismatic, pebble bed, plate, and cylindrical type fuel geometries. PARFUME is an integrated mechanistic computer code that evaluates the thermal, mechanical, and physico-chemical behavior of TRISO coated-fuel particles and the probability for fuel failure given the particle-to-particle statistical variations in physical dimensions and material properties that arise during the fuel fabrication process. Bison is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library (Permann 2020). Bison is capable of modeling multiple fuel forms in a wide variety of dimensions and geometries. It solves coupled nonlinear partial differential equations, including heat conduction, mechanics, fission product species transport etc., in a fully implicit manner. Comparisons between PARFUME and Bison were performed using four compacts from the AGR-2 experiment. Selected outputs were chosen based on their impact on the probability of the SiC layer failing. In general there was good agreement between PARFUME and Bison with the exception of predicting the gap formed between the buffer and IPyC. Further comparisons between PARFUME and Bison are planned to further develop Bison’s capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials

Topology optimization (TO) is a popular and powerful computational approach for designing novel structures, materials, and devices. Two computational challenges have limited the applicability of TO to a variety of industrial applications. First, a TO problem often involves a large number of design variables to guarantee sufficient expressive power. Second, many TO problems require a large number of expensive physical model simulations, and those simulations cannot be parallelized. To address these issues, we propose a general scalable deep-learning (DL) based TO framework, referred to as SDL-TO, which utilizes parallel schemes in high performance computing (HPC) to accelerate the TO process for designing additively manufactured (AM) materials. Unlike the existing studies of DL for TO, our framework accelerates TO by learning the iterative history data and simultaneously training on the mapping between the given design and its gradient. The surrogate gradient is learned by utilizing parallel computing on multiple CPUs incorporated with a distributed DL training on multiple GPUs. The learned TO gradient enables a fast online update scheme instead of an expensive update based on the physical simulator or solver. Using a local sampling strategy, we achieve to reduce the intrinsic high dimensionality of the design space and improve the training accuracy and the scalability of the SDL-TO framework. The method is demonstrated by benchmark examples and AM materials design for heat conduction. The proposed SDL-TO framework shows competitive performance compared to the baseline methods but significantly reduces the computational cost by a speed up of around 8.6x over the standard TO implementation.

Bi, Sirui↗

DOE OSTI2021

Solid-state optical refrigerator for cryogenic cooling of payloads

A solid-state optical refrigerator for cryogenic cooling of a payload, the solid-state optical refrigerator including a laser cooling crystal including a first material and a dopant material; a thermal link including a second material, the thermal link being bonded to the laser cooling crystal and the thermal link being configured to be thermally linked to the payload to transfer heat conductively from the payload to the laser cooling crystal via the thermal link; and a vacuum chamber housing the laser cooling crystal and the thermal link, the vacuum chamber and thermal link having a combination of shape and coating such that laser and fluorescence light reflected off a wall of the vacuum chamber and laser and fluorescence light propagating within the thermal link are not incident on the payload.

Hehlen, Markus Peter↗

DOE OSTI2023

Converging towards atomic and nuclear pressures (Final Report)

his report details the development of transformational tools and techniques, allowing the accurate characterization of matter at the most extreme conditions yet studied in the high energy density (HED) domain. Before this work, most experiments quantitatively mapping the nature of matter in the HED realm were performed using planar geometry, which allows for the isolation and measurement of variables in a single thermodynamic state. Such measurements include equation of state variables, optical conductivity, heat transport and more. However, due to a variety of plasma processes, such experiments are limited to below ~10 TPa (100 Mbar) pressures. To achieve higher pressures, convergent experiments are needed. Historically, convergent experiments have not been used for benchmark data because they are integral measurements. That is each part of a convergent target undergoes a time dependent wide range of states, making it difficult to accurately isolate any particular quantity for a given thermodynamic state. This effort developed innovative convergent HED platforms and techniques enabling the exploration of matter from atomic to nuclear scale pressures. This effort also performed pioneering experiments that yielded the first rigorous benchmark data at these extreme conditions. This funding award began with the overarching goal to understand the behavior of matter at extreme (atomic-to-nuclear scale) pressures. The motivation for these goals lie in the fact that every time scientists explore matter beyond the threshold of an atomic unit, there is a fundamental shift in science. The atomic unit for energy, mass, charge, length, and time have each been explored, and each time such a threshold was crossed, a new sequence of discoveries was made resulting in significant awards such as the Nobel Prize. The only unexplored atomic unit is pressure, and this effort set the course for exploring matter at and beyond such pressures. That most of the recently discovered extrasolar planets and stars, as well as matter in the late implosion stages of inertial fusion targets, have deep internal pressures at and beyond atomic pressures amplifies the importance of this effort. Much of the initial work in developing techniques to create these atomic-to-nuclear pressures already existed within the HED community, predominantly at large scale laser facilities such as the National Ignition Facility (NIF) and the Omega60 laser the University of Rochester and although these experiments were routinely performed the ability to extract information about the underlying physical states and processes remained elusive due to the complexity of the experiments, extreme scales in both time and space, and the integrated nature of all the measurements. This work built a rigorous framework so such measurements can routinely be made. This was done in part through the introduction of Bayesian inference techniques into the field of HED science. These techniques allow for the self-consistent extraction of the relevant variables and their explicit and implicit correlations, so as to make use of integrated experimental data to constrain physical models and provide accurate uncertainty bounds for the data. The techniques developed here are fully transparent and proved immediately useful providing quantitative rigorous benchmarks for physical states and processes at some of the most extreme conditions yet explored on Earth. This funding is directly or partly responsible for 7 publications in major peer-reviewed scientific journals, a doctoral thesis, 3 invited talks at major conferences, and the training of a post-doc, 2 graduate students, and 1 undergraduate student. Beyond the effort supported by this award launched the introduction of Bayesian inference into the HED physics community and helped push the usage if modern data-science techniques within the physics community at large.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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 OSTI2022

Quasiparticle spectroscopy, transport, and magnetic properties of Nb films used in superconducting transmon qubits

Niobium thin films on silicon substrate used in the fabrication of superconducting qubits have been characterized using scanning and transmission electron microscopy, electrical transport, magnetization, quasiparticle spectroscopy, and real-space real-time magneto-optical imaging. We study niobium films to provide an example of a comprehensive analytical set that may benefit superconducting circuits such as those used in quantum computers. The films show outstanding superconducting transition temperature of $T_{c}=9.35$ K and a fairly clean superconducting gap, along with superfluid density enhanced at intermediate temperatures. These observations are consistent with the recent theory of anisotropic strong-coupling superconductivity in Nb. However, the response to the magnetic field is complicated, exhibiting significantly irreversible behavior and insufficient heat conductance leading to thermo-magnetic instabilities. These may present an issue for further improvement of transmon quantum coherence. Possible mitigation strategies are discussed.

Joshi, Kamal R.↗

DOE OSTI2022

3D printing of additive structures for nuclear fuels

A method for manufacturing a nuclear fuel compact is provided. The method includes forming an additive structure, consolidating a fuel matrix around the additive structure, and thermally processing the fuel matrix to form a fuel compact in which the additive structure is encapsulated therein. The additive structure optionally includes a vertical segment and a plurality of arm segments that extend generally radially from the vertical segment for conducting heat outwardly toward an exterior of the fuel compact. In addition to improving heat transfer, the additive structure may function as burnable absorbers, and may provide fission product trapping.

Terrani, Kurt A.↗

DOE OSTI2023

Differential emissivity based evaporable particle measurement

A differential emissivity imaging device for measuring evaporable particle properties can include a heated plate, a thermal camera, a memory device, and an output interface. The heated plate can have an upper surface oriented to receive falling evaporable particles. The evaporable particles have a particle emissivity and the upper surface has a plate surface emissivity. The thermal camera can be oriented to produce a thermal image of the upper surface. A memory device can include instructions that cause the imaging device to calculate a mass of the individual evaporable particle via heat conduction using a calculated surface area and an evaporation time.

Garrett, Tim↗

DOE OSTI2023

3D printing of additive structures for nuclear fuels

Terrani, Kurt A.↗