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

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Safety Analysis of FeCrAl Accident-Tolerant Fuels with Increased Enrichment and Extended Burnup

The U.S. nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor nuclear power plants (NPPs), and it can be achieved more economically by using a risk-informed ecosystem, such as that being developed by the Risk-Informed Systems Analysis Pathway under the U.S. Department of Energy Light Water Reactor Sustainability Program. This program is promoting a wide range of research and development activities to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering a second license renewal. The Risk-Informed Systems Analysis Pathway has two main goals: (1) The deployment of methodologies and technologies that enable a better representation of the safety margins and factors that contribute to cost and safety, and (2) The development of advanced applications that enable cost-effective plant operation. As part of this pathway, the Enhanced Resilient Plant project refers to an NPP where safety is improved by implementing various measures, such as accident-tolerant fuels, diverse and flexible coping strategies, enhancements to plant components and systems, incorporation of augmented or new passive cooling systems, and utilization of advanced battery technologies. The objective of the Enhanced Resilient Plant project is to use novel methods and computational tools to enhance existing reactors’ safety while reducing operational costs. This report documents research and development conducted in support of deployment of accident-tolerant fuels. This project performed safety analyses for the steady-state normal operation, anticipated operational occurrences, and design-basis accidents of a representative four-loop pressurized water reactor model with Zr and FeCrAl accident-tolerant fuel clad with higher enrichment and burnup supporting plant refueling cycles of 18 and 24 months. The source terms and environmental impacts were studied for a large-break loss of coolant accident, including uncertainty analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Integration of Condition-Based, Diagnostic, Prognostic, And Anomaly Detection Data into Reliability Models to Support a Predictive Maintenance Context

Reliability data employed in plant reliability models are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating actual health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). This paper proposes a reliability modeling approach that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. We show how state-of-the art condition-based, diagnostic, prognostic, and anomaly detection models can be linked to system reliability models not in probability terms, but in terms of margin where margin is defined as the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Then, we show how the propagation of margin data from the asset to the system level is performed through classical reliability models such as fault trees or reliability block diagrams. The described method is in fact able to propagate heterogenous health data from the asset to the system level in order to analytically assess system health.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Unraveling the Threads of Environmental Justice in Critical Mineral Extraction: A Framework for Regionalized Life Cycle Data

As we transition to a more sustainable energy system, the extraction and processing of critical minerals becomes increasingly important. However, these industries often raise concerns about environmental and social impacts, particularly in disadvantaged communities. To address these concerns, our research focuses on regionalizing environmental life cycle data to connect it with communities affected by mineral extraction. A framework was developed for collecting life cycle background data that supports the Justice40 Toolset, a market-based approach to evaluating net benefits and costs of critical mineral material recovery pathways. A goal was to alleviate public skepticism around mineral extraction processes, including secondary and unconventional feedstocks, by highlighting both environmental and social impacts. To achieve this, computational analysis and geospatial data science techniques were employed, such as within-scale and across-scale methods and proxy dataset usage. By doing so, we were able to develop a framework for identifying and disaggregating data down to regions small enough to support Justice40 goals. Our approach not only provides valuable tools fo insight into the environmental implications of mineral extraction but also helps policymakers evaluate the social impacts on local communities. This research contributes to a more just and equitable transition to a sustainable energy system, ensuring that marginalized voices are heard in decision-making process.

Davis, Tyler [NETL Site Support Contractor, Nation↗
DOE OSTI2023

Assessment of Modeling and Simulation Technical Gaps in Safety Analysis of High Burnup Accident-Tolerant Fuels

The United States nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor (LWR) nuclear power plants (NPPs), and it can be achieved more economically by using a risk-informed ecosystem, such as that being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program is promoting a wide range of research and development activities to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering second license renewal. The RISA Pathway has two main goals: The deployment of methodologies and technologies that enable better representation of safety margins and the factors that contribute to cost and safety, and; The development of advanced applications that enable cost-effective plant operation. As part of the RISA Pathway, the Enhanced Resilient Plant (ERP) project refers to an NPP where safety is improved by implementing various measures, such as accident-tolerant fuels (ATF), diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, incorporation of augmented or new passive cooling systems, and utilization of advanced battery technologies. The objective of the ERP research is to use novel methods and computational tools to enhance existing reactors’ safety while reducing operational costs. Many U.S. utilities are targeting implementation of ATFs instead of traditional fuel in the near future since ATFs offer benefits in terms of improved performance and cost savings. The robust properties of ATF make it possible to extend the refueling cycle from 18 to 24 months in addition to the opportunity to use less of fuel. Extensive safety assessments are required to support regulatory requirements and obtain the approvals to use ATFs and the ERP project support the industry by developing novel effective methodologies for safety evaluations. In this project, the technical gaps in the modeling and simulation of the high burnup (HBU) ATF were assessed in terms of the fuel cladding behavior during the postulated accident events. The issues were identified in modeling the cladding deformation, the hydrodynamic change due to cladding deformation and the critical heat flux (CHF). The RELAP5-3D cladding deformation model was assessed by multiple verification tests and validation with the instrumented fuel assembly (IFA) experiment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Solvable theory of a strange metal at the breakdown of a heavy Fermi liquid

In this work, we introduce an effective theory for quantum critical points (QCPs) in heavy-fermion systems, involving a change in carrier density without symmetry breaking. Our theory captures a strongly coupled metallic QCP, leading to robust marginal Fermi-liquid transport phenomenology, and associated linear in temperature (T) "strange metal" resistivity, all within a controlled large-N limit. In the parameter regime of strong damping of emergent bosonic excitations, the QCP also displays a near-universal "Planckian" transport lifetime τ tr ~ℏ/(k B T). This is contrasted with the conventional so-called "slave boson" theory of the Kondo breakdown, where the large-N limit describes a weak coupling fixed point and nontrivial transport behavior may only be obtained through uncontrolled 1/N corrections. We also compute the weak-field Hall coefficient within the effective model as the system is tuned across the transition. We then find that, between the two plateaus reflecting the different carrier densities in the two Fermi-liquid phases, the Hall coefficient can develop a peak in the critical crossover regime, like in recent experimental findings, in the parameter regime of weak boson damping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

A Novel Protection Scheme for Unbalanced Faults in Inverter Dominated Networks: A Computationally Efficient Algorithm for Entry-Level Relays

Microgrids are now a common practice in distribution systems to increase resilience and reliability. However, microgrid protection remains a critical challenge, considering its requirement to operate in both grid connected and islanded, and the variability in fault characteristics under each mode of operation. This paper presents unbalanced power (S unb ) based fault detection algorithm, which considers local voltage and current unbalances to determine faults in the system. S unb is a computationally efficient fault detection algorithm that is suitable for implementation in the programmable logic of entry level protective relays. In addition, the difference in current and voltage unbalance (D n ) is used to determine the fault type. The proposed method demonstrates high sensitivity and selectivity for line-to-ground (LG), line-to-line (LL), and double line-to-ground (LLG) faults, representing the most common faults in distribution systems. It also allows relay coordination with upstream and downstream protection devices in both island and grid connected operation, while preserving grading margins. The same pickup and time multiplier settings of a particular relay for both modes of operation eliminates the need for adaptive settings, which rely on communication networks. Validation was performed with a hardware-in-the-loop (HIL) setup using Typhoon HIL real time simulator interfaced with three entry-level, SEL 751 relays. Results confirmed the algorithm’s ability to discriminate fault conditions, and determine the fault type under both operating modes, maintain fast detection times, and ensure proper protection coordination.

fault classification↗
DOE OSTI2021

Nuclear Data Assessment for Advanced Reactors

Advanced reactor concepts being developed throughout the industry are significantly different from light-water reactor (LWR) designs with respect to geometry, materials, and operating conditions, and consequently, with respect to their reactor physics behavior. Given the limited operating experience with non-LWRs, the accurate simulation of reactor physics and the quantification of associated uncertainties are important for ensuring that the nuclear design for advanced reactor concepts include appropriate margins. Nuclear data are a major source of input uncertainties in reactor physics analysis. As part of a project sponsored by the US Nuclear Regulatory Commission at Oak Ridge National Laboratory (ORNL), key nuclear data relevant to reactor safety analysis in selected advanced reactor technologies were identified, and their impacts on important key figures of merit were assessed based on (1) a review of available advanced reactor specifications, (2) analysis of previous studies performed at ORNL and other research institutions, and (3) sensitivity and uncertainty analyses performed for six selected benchmarks—three experimental and three computational—to quantify the impacts of the identified key nuclear data on several key metrics. This report summarizes the key nuclear data—nominal data and nuclear data uncertainties— considering the most important nuclear reactions in the fuel and in various materials for the moderator, coolant, and structure of the considered advanced reactors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Multiphysics simulation of TRISO fuel compacts and the effects of homogenization on silver release predictions

This work studies the impact of explicit and homogenized modeling approaches on the multiphysics simulation of TRistructural ISOtropic (TRISO) fuel compacts in prismatic High Temperature Gas Reactors (HTGRs) and the silver release predictions. TRISO fuel compacts exhibit complex double heterogeneity that significantly affects heat conduction, neutron transport, and fission products release. In this work, we use Cardinal, a multiphysics tool based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, to couple neutron transport and heat conduction. OpenMC is used for neutron transport and the MOOSE heat transfer module is used for the heat conduction. Then, we use BISON for the silver release predictions. Two different modeling approaches—explicit modeling of individual TRISO particles and homogenized representation using effective thermal properties—are compared at high TRISO packing fractions (20% and 40%) across varying power densities. Results demonstrate that homogenization significantly under-predicts peak temperatures, for the case of high power/TRISO, there is a difference of 83.73 K in the maximum temperature. Additionally, homogenization underestimates the silver release predictions compared to explicit modeling. Specifically, the temperature and power density differences lead to significant differences in silver release predictions. This work demonstrates the importance of accurately modeling heterogeneity of the TRISO particles to reliably predict fission product release and assess reactor safety margins.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Novel Gloeobacterales spp. from Diverse Environments across the Globe

Photosynthetic Cyanobacteria and their descendants are the only known organisms capable of oxygenic photosynthesis. Their metabolism permanently changed the Earth’s surface and the evolutionary trajectory of life, but little is known about their evolutionary history. Genomes of the Gloeobacterales, an order of deeply divergent photosynthetic Cyanobacteria, may hold clues about the evolutionary process. However, there are only three published genomes within this order, and it is difficult to make broad inferences based on such little data. Here, I describe five species within the Gloeobacterales retrieved from publicly available databases and examine their photosynthetic gene content and the environments in which Gloeobacterales genomes and 16S rRNA gene sequences are found. The Gloeobacterales contain reduced photosystems and inhabit cold, wet-rock, and low-light environments. They are likely present in low abundances due to their low growth rate. Future searches for Gloeobacterales should target these environments, and samples should be deeply sequenced to capture the low-abundance taxa. Publicly available databases contain undescribed taxa within the Gloeobacterales. However, searching through all available data with current methods is computationally expensive. Therefore, new methods must be developed to search for these and other evolutionarily important taxa. Once identified, these novel photosynthetic Cyanobacteria will help illuminate the origin and evolution of oxygenic photosynthesis. Early branching photosynthetic Cyanobacteria such as the Gloeobacterales may provide clues into the evolutionary history of oxygenic photosynthesis, but there are few genomes or cultured taxa from this order. Five new metagenome-assembled genomes suggest that members of the Gloeobacterales all contain reduced photosystems and lack genes associated with thylakoids and circadian rhythms. Their distribution suggests that they may thrive in environments that are marginal for other species, including wet-rock and cold environments. These traits may aid in the discovery and cultivation of novel species in this clade.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Mapping Stellar Surfaces. II. An Interpretable Gaussian Process Model for Light Curves

The use of Gaussian processes (GPs) as models for astronomical time series data sets has recently become almost ubiquitous, given their ease of use and flexibility. In particular, GPs excel at marginalization over the stellar signal when the variability due to starspots is treated as a nuisance, as in exoplanet transit modeling. However, these effective models are less useful in cases where the starspot signal is of primary interest, since it is not obvious how the parameters of the GP relate to physical parameters like the spot size, contrast, and latitudinal distribution. Instead, it is common practice to explicitly model the effect of individual starspots on the light curve and attempt to infer their properties via optimization or posterior inference. Unfortunately, this process is ill-posed and often computationally intractable when applied to stars with more than a few spots and/or to ensembles of many stars. Here we derive a closed-form expression for a GP that describes the light curve of a rotating, evolving stellar surface conditioned on a given distribution of starspot sizes, contrasts, and latitudes. We demonstrate that this model is correctly calibrated, allowing one to robustly infer physical parameters of interest from one or more light curves, including the typical spot radii and latitudes. Our GP has far-ranging implications for understanding the variability and magnetic activity of stars from light curves and radial velocity measurements, as well as for modeling correlated noise in exoplanet searches. Our implementation is efficient, user-friendly, and open-source, available in the package starry-process.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Molecular Recognition with Resolution Below 0.2 Angstroms Through Thermoregulatory Oscillations in Covalent Organic Frameworks

Crystalline materials with uniform molecular-sized pores are desirable for a broad range of applications, such as sensors, catalysis, and separations. However, it is challenging to tune the pore size of a single material continuously and to reversibly distinguish small molecules (below 4 angstroms). We synthesized a series of ionic covalent organic frameworks using a tetraphenoxyborate linkage that maintains meticulous synergy between structural rigidity and local flexibility to achieve continuous and reversible (100 thermal cycles) tunability of “dynamic pores” between 2.9 and 4.0 angstroms, with resolution below 0.2 angstroms. This results from temperature-regulated, gradual amplitude change of high-frequency linker oscillations. These thermoelastic apertures selectively block larger molecules over marginally smaller ones, demonstrating size-based molecular recognition and the potential for separating challenging gas mixtures such as oxygen/nitrogen and nitrogen/methane.

crystalline materials↗
DOE OSTI2023

Retrieval of temperature and humidity profiles from ground-based high-resolution infrared observations using an adaptive fast iterative algorithm

Various retrieval algorithms have been developed for retrieving temperature and water vapor profiles from Atmospheric Emitted Radiance Interferometer (AERI) observations. The physical retrieval algorithm, named AERI Optimal Estimation (AERIoe), outperforms other retrieval algorithms in many aspects except the retrieval time, which is significantly increased due to the complex radiative transfer process. The calculation of the Jacobian matrix is the most computationally intensive step of the physical retrieval algorithm. Interestingly, an analysis of the change in AERI observations' information content with respect to Jacobians revealed that the AERIoe algorithm's performance presents negligible dependence on these metrics. Thus, the Jacobian matrix could remain unchanged when the variation in the atmospheric state is small in the retrieval process to reduce the most time-consuming computation. On the basis of the above findings, a fast physical–iterative retrieval algorithm was proposed by adaptively recalculating Jacobians in keeping with the changes in the atmospheric state. Experiments with synthetic observations demonstrate that the proposed method experiences an average reduction in retrieval time by an impressive 59 % compared to the original AERIoe algorithm while achieving maximum root-mean-square errors of less than 0.95 K and 0.22 log(ppmv) for heights below 3 km for the temperature and water vapor profile, respectively. Further analyses revealed that the fast-retrieval algorithm reached an acceptable convergence rate of 98.7 %, marginally lower than AERIoe's 99.9 % convergence rate for the 826 cases used in this study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Uncertainty Quantification for Component Modeling Using the Discrete-Direct Approach

Threaded fastener behavior can be an important aspect of complex component and system behavior, but there is no one-size-fits-all finite element analysis technique. Proper modeling of threaded fastener joints requires careful consideration of many details, from test setup and data acquisition to constitutive modeling and uncertainty quantification approaches. This report details analysis of a “mini-radax” bolted-joint exemplar where a Discrete-Direct uncertainty quantification approach is employed to evaluate margin of the component. The mini-radax geometry is tested to failure on a drop table, and single-coupon tests of individual fasteners serve as foundational data for the analysis. Analysis predictions complement the test data well and provide additional context for engineering decision-making.

42 ENGINEERING↗
DOE OSTI2020

Assessment of Critical Experiment Benchmark Applicability to a Large-Capacity HALEU Transportation Package Concept

This work presents an assessment of the applicability of existing benchmark critical experiments to the criticality safety code validation for a large-capacity high-assay low-enriched uranium (HALEU) transportation package concept. Numerous next-generation nuclear reactor designs require HALEU fuel, which is characterized by an enrichment between 5 and 20 wt% 235 U. The U.S. Department of Energy (DOE) has proposed to recover and downblend highly enriched uranium from DOE-owned used nuclear fuel to accelerate the demonstration of commercially viable microreactor technologies. One element of the infrastructure needed to demonstrate HALEU-fueled reactors is the ability to safely transport enriched product to be used for fuel fabrication. There is uncertainty as to whether existing critical benchmark experiment data are sufficient to support criticality safety code validation for HALEU transportation applications. The anticipated chemical form of the HALEU in the proposed transportation concept is UO 2 with 20 wt% 235 U/U. The concept uses a combination of an existing transportation packaging design and a novel basket design, including borated aluminum flux traps. The basket provides space for 18 reusable, stainless steel canisters that contain the HALEU. In 10 CFR 71, normal conditions of transport (NCTs) and hypothetical accident conditions (HACs) are defined for fissile material transportation packages. NCT and HAC KENO-VI models of the transportation package were developed using the Standardized Computer Analyses for Licensing Evaluation (SCALE) 6.2.3 computer code package, and optimum moderation conditions were determined using the SCALE SAMPLER sequence. The SCALE Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI) sequences were then used to compare the neutronic characteristics of 1584 International Criticality Safety Benchmark Evaluation Project benchmark critical experiments with the NCT and HAC HALEU transportation models. The TSUNAMI integral correlation coefficient c k was the criterion used to rank neutronic similarity. Thirty-four experiments were identified as similar (c k ≥ 0.9) to the NCT model, and 55 experiments were identified as similar to the HAC model. Hundreds of experiments were also identified as at least marginally similar (c k ≥ 0.8) to both models. The results indicate that additional critical experiments are unlikely to be needed to support HALEU transportation criticality safety analyses for package concepts similar to the concept package analyzed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Joint Development of SAS4A Code in Application to Oxide-fueled LFR Severe Accident Analysis

The scope of this project was to pursue specific SAS4A liquid-metal cooled reactor (LMR) safety analysis software extensions to simulate postulated accidents with fuel failures for oxide-fueled Lead-cooled Fast Reactors (LFRs). Since most U.S. LMR experience is on sodium-cooled fast reactor options based on past testing and operation experience with EBR-II and FFTF, the DOE’s legacy fast reactor safety analysis capabilities were focused on metal-fueled pool-type concepts with sodium coolant. In recent years, Westinghouse Electric Company (WEC) has decided to pursue an LFR design as one of their next generation nuclear technology options because of its favorable safety and economics attributes. Oxide fuel is considered among other fuel options due to previous WEC experience with this fuel form. Development of this new technology requires the availability of adequately accurate computational tools, some of which can be adapted from versions of similar software used for analysis of other LMRs. Although Argonne National Laboratory’s (ANL) SAS4A/SASSYS-1 safety analysis software suite (shortened as SAS4A code hereafter for brevity) has the basic capabilities to model LFR system designs, the SAS4A code modules used in the analysis of accidents with fuel/cladding failures lack appropriate models for the unique phenomena that govern as-irradiated oxide-fuel damage mechanisms in lead coolant. Therefore, the objective of this project was to extend the capabilities of SAS4A with mechanistic oxide-fuel failure models in lead coolant for margin to failure assessments, analysis of failure modes, location and timing of failures under different accident scenarios consistent with the whole-plant dynamic response including the reactivity feedback, and assessment of the potential for fuel damage propagation due to potential fission gas jet and fuel-fragment/molten fuel impingement to neighboring fuel pins in an assembly. This report provides mainly a summary of Argonne’s technical contributions in the joint project, but the reports and publications by the Participant team are included as references at the end of the report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Challenges in Markov Chain Monte Carlo for Bayesian Neural Networks

Markov chain Monte Carlo (MCMC) methods have not been broadly adopted in Bayesian neural networks (BNNs). This paper initially reviews the main challenges in sampling from the parameter posterior of a neural network via MCMC. Such challenges culminate to lack of convergence to the parameter posterior. Nevertheless, this paper shows that a nonconverged Markov chain, generated via MCMC sampling from the parameter space of a neural network, can yield via Bayesian marginalization a valuable posterior predictive distribution of the output of the neural network. Further, classification examples based on multilayer perceptrons showcase highly accurate posterior predictive distributions. The postulate of limited scope for MCMC developments in BNNs is partially valid; an asymptotically exact parameter posterior seems less plausible, yet an accurate posterior predictive distribution is a tenable research avenue.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Status Update on the High Precision Isotopic Measurements on High Burnup LWR Fuel in 2020

The US Department of Energy (DOE) Office of Nuclear Energy (NE) is currently investigating the feasibility of directly disposing dual-purpose (storage and transportation) canisters (DPCs) in a spent nuclear fuel (SNF) repository. Criticality during the repository performance period (10,000 years or more) is one of the major concerns related to direct disposal of DPCs, specifically as the system undergoes degradation in the repository environment and timeframe. Oak Ridge National Laboratory (ORNL) is developing an as-loaded criticality analysis methodology using full (actinides + fission products) burnup credit that exploits the inherent criticality margin associated with actual canister-specific loading configuration. Burnup credit criticality analysis requires validation of the depletion/decay codes used to generate the burned isotopic inventory of an assembly by comparing the code-predicted inventory with experimentally determined isotopic data. Currently, isotopic measurement data for boiling water reactors (BWR) SNF are limited, and additional measurements will be highly beneficial for BWR burnup credit analysis, which is essential to demonstrate disposability of BWR DPCs. Moreover, new pressurized water reactor (PWR) samples of isotopic measurements will expand the PWR sample population and consequently will greatly improve sample statistics. In turn, this will reduce uncertainty in the computational determination of the isotopic composition of commercial SNF and eliminate additional penalties currently used for lack of data. As part of the isotopic analysis task, eight diverse, high burnup (HBU) samples from several PWR rods are being dissolved and isotopically analyzed to provide high-quality measurement data for PWR SNF to reducing the uncertainties associated with PWR isotopic depletion validation. The isotopics of interest focus on nuclides important to burnup credit, shielding, and decay heat in PWR SNF. Additionally, eight high burnup BWR fuel samples from the Limerick nuclear power plant have been identified for measurement to support reducing uncertainties associated with BWR isotopic depletion validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Evaluation of Thermal Neutron Scattering Cross Section of Uranium Silicide with Ab Initio Lattice Dynamics

Uranium silicide (U 3 Si 2 ) is a candidate material for the high-density nuclear fuel in commercial light water reactors [1], [2]. Its higher uranium density, 11.3 g-U/cm3, compared to that of uranium dioxide (UO 2 ), 9.7 g-U/cm3, can improve the performance of a nuclear reactor while using low enriched uranium (LEU) and diversify the choice of cladding materials [1]–[3]. It also has a higher thermal conductivity than UO 2 , which can reduce the thermal stress on the material caused by a temperature gradient across the fuel pellet and provide a larger margin for some postulated accidents [1], [2], [4]. Furthermore, compared to U3Si, another high-density fuel candidate, it has better resistance to in-pile swelling due to less irradiation-induced rapid amorphization [1], [3]. Corresponding to its importance in nuclear engineering, many previous studies have reported the properties of U3Si2. Experiments showed that U 3 Si 2 is a paramagnetic (PM) metal, where a slight linear increase in magnetic susceptibility was measured with increasing temperature [5], [6]. In addition, thermodynamic quantities such as thermal expansion coefficient, heat capacity, and thermal conductivity were experimentally determined over a wide temperature range [1], [7], [8]. In several computational studies, ab initio atomistic simulations based on density functional theory (DFT) were performed to calculate various properties including elastic constants, electronic density of states (DOS), and phonon dispersion curves [9]–[12]. Nevertheless, thermal neutron scattering cross sections, which are critical to the prediction of the parameters in reactor physics that are ultimately related to reactor criticality, have not yet been evaluated for U3Si2. The scattering cross section can be calculated from the phonon DOS, or the energy spectrum of lattice vibrations, of the crystalline system [13], [14]. However, there is also no experimental data available for the phonon DOS of U 3 Si 2 . While some computational studies reported the phonon DOS and/or dispersion curves from ab initio simulations [9]–[12], the accuracy cannot be guaranteed because it is unclear whether the spin-polarization behavior of PM U 3 Si 2 was properly described. In the present study, the thermal neutron scattering cross section for U 3 Si 2 is evaluated for the first time by calculating the phonon DOS for U3Si2 from ab initio lattice dynamics (AILD) simulations based on DFT. First, U 3 Si 2 is modeled based on the experimental structure, and AILD simulations are performed on the modeled U3Si2 to optimize the structure. Next, AILD simulations are performed for supercells with atomic displacement to calculate Hellmann-Feynman forces. Based on the calculated forces, partial phonon DOSs for U and Si are obtained, and the thermal neutron scattering law (TSL) for U 3 Si 2 is finally evaluated. To verify the accuracy of the calculations in the present study, the calculation results are compared with experimental data on the structure and heat capacity of U3Si2 [1], [7], [8], [15].

Geometry Optimization↗