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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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DOE OSTI2021

Postselection-Free Entanglement Dynamics via Spacetime Duality

The dynamics of entanglement in 'hybrid' non-unitary circuits (for example, involving both unitary gates and quantum measurements) has recently become an object of intense study. A major hurdle toward experimentally realizing this physics is the need to apply postselection on random measurement outcomes in order to repeatedly prepare a given output state, resulting in an exponential overhead. We propose a method to sidestep this issue in a wide class of non-unitary circuits by taking advantage of spacetime duality. This method maps the purification dynamics of a mixed state under non-unitary evolution onto a particular correlation function in an associated unitary circuit. This translates to an operational protocol which could be straightforwardly implemented on a digital quantum simulator. We discuss the signatures of different entanglement phases, and demonstrate examples via numerical simulations. With minor modifications, the proposed protocol allows measurement of the purity of arbitrary subsystems, which could shed light on the properties of the quantum error correcting code formed by the mixed phase in this class of hybrid dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Rational Selection of Transition-Metal Oxide Electrocatalysts from Structure Electronic Structure-Activity Relations: The Role of Defects, Strain, and Sub-Surface Layering

This BES research investigates the physicochemical properties of metal oxides and how they affect electrocatalytic functionalities. The goal is to develop a predictive framework for realizing top-performing electrocatalytic materials for energy-critical reactions. The hypothesis is that well-defined thin films allow detailed mapping of structural-activity relationships because flat surfaces are more straightforward to characterize. Furthermore, the well-defined nature of thin-film metal oxides allows precise tuning of structural and chemical variables for structure-activity-relationship mapping. The proposed research has two technical objectives. The first is to experimentally assess whether the binding energies of surface oxygen can serve as an activity descriptor for oxygen electrocatalysis on metal oxides and then how to control them by tuning the structure and chemical variables. The second is to find the rate-limiting process in oxygen electrocatalysis and other small-molecule reactions. Similar mechanistic insights have been developed on well-defined platinum surfaces but not yet on oxides. This research addresses this gap and uses electrochemistry and X-ray photoemission spectroscopy to study oxide surface chemistry. The obtained insights are collectively analyzed to reveal how the oxides’ structural and chemical variables affect kinetics and can be used to design more active electrocatalysts for energy-critical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Computational Tool Compatible with NEAMS Code Packages for Optimizing the Shape of Nuclear Reactor Components and of Whole Core Performance

We designed and implemented a shape optimization tool that functions with NEAMS codes, and that nuclear scientists and engineers can employ to optimize the shape of individual components and the whole core under the applicable single- or multi-physics model comprising the employed code(s). The shape-optimization tool enables varying the geometric shape itself as well as its dimensions to yield, potentially, new component designs that are not limited by the designer’s intuition and previous experience. In cases where the optimal-shape object is an individual component, we provide the capability for additional verification that the whole-core performance using the optimized component performs better, under the prescribed optimization criteria, than the initial design. Our shape-optimization tool couples to NEAMS codes via a flexible input- composer interface and enables the user to constrain the shape’s evolution to ensure the component’s manufacturability. Finally, we demonstrate our shape-optimization tool with single- and multi-physics NEAMS codes. This objective is motivated by the recent advances in manufacturing technology that, combined with rising interest in novel reactor concepts, are creating new opportunities for innovation in the design of individual components that affect the performance of the full reactor system. In particular, Additive Manufacturing (AM) enables mass production of highly precise, intricate and complex component shapes that are not feasible with traditional manufacturing techniques. To accomplish this goal we developed and implemented in MOOSE: (1) discrete shape optimization capability based on a state-space search that uses Artificial Intelligence strategies to find the optimal state/shape; (2) smooth shape optimization tool that employs PETSc’s toolkit for advanced optimization (TAO) to optimize node-displacement of the components’ model sidesets; (3) hierarchical core optimization workflow that recognizes the repeating patterns typical in a nuclear reactor and performs the optimization one level at a time with increasing length scale. Each of these tools is equipped with user-specified constraints to avoid optimal shapes that are not manufacturable. The developed shape optimization tool is verified and demonstrated on various nuclear reactor core components and models. The optimization process accounts for tightly coupled physics that govern the behavior of these target reactors, and exercises several NEAMS codes in a coupled multiphysics fashion. The impact of the delivered shape optimization tool will materialize in the optimal design, from the outset, of advanced reactors currently contemplated to regain the US’s leadership in nuclear energy R&D. Novel reactor concepts, e.g. Molten Salt Reactors, and sizes/capacities, e.g. micro- reactors, provide a unique opportunity to optimize performance from the early stages of development, before the investment in components’ production lines, validation experiments, and licensing regimes make future improvements in performance prohibitively expensive and force sub-optimal performance on the affected reactor concept in perpetuity. This benefit will be realized by the delivered shape optimization tool regardless of the applicable manufacturing process whether traditional or AM, thereby broadening the impact of this project on current and future reactor concepts and technologies

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Data-driven Identification of Occupant Thermostat-Behavior Dynamics

Building occupant behavior drives significant differences in building energy use, even in automated buildings. Users’ distrust in the automation causes them to override settings. This results in responses that fail to satisfy both the occupants’ and/or the building automation’s objectives. The transition toward grid-interactive efficient buildings will make this evermore important as complex building control systems optimize not only for comfort, but also changing electricity costs. This paper presents a data-driven approach to study thermal comfort behavior dynamics which are not captured by standard steady-state comfort models such as predicted mean vote. The proposed model captures the time it takes for a user to override a thermostat setpoint change as a function of the manual setpoint change magnitude. The model was trained with the ecobee Donate Your Data dataset of 5 min. resolution data from 27,764 smart thermostats and occupancy sensors. The resulting population-level model shows that, on average, a 2°F override will occur after ~30 mins. and an 8°F override will occur in only ~15 mins., indicating the magnitude of discomfort as a key driver to the swiftness of an override. Such models could improve demand response programs through personalized controls.

Kane, Michael↗
DOE OSTI2020

Evaluating the Effectiveness of an Ultrasonic Acoustic Deterrent in Reducing Bat Fatalities at Wind Energy Facilities

This project was designed to use thermal video cameras and fatality monitoring to evaluate the effectiveness of an ultrasonic acoustic deterrent (UAD) on bat activity and mortality, respectively. Our goals were to redesign the UAD device and installation infrastructure, determine the placement on wind turbines to optimize safety, compatibility and functionality, and to compare the mortality among the following conditions: Control (deterrents off and turbines feathered up to the manufacturer’s cut-in speed of 3.5 m/s), Deterrent (deterrents on and turbines feathered up to the manufacturer’s cut-in speed of 3.5 m/s), Curtailment (deterrents off and turbines feathered up to 5/ m/s), and combination (deterrents on and turbines feathered up to 5 m/s). The project was divided into a Feasibility Study and Comparative Study. The objectives for the Feasibility Study were to develop an installation strategy, redesign a previous iteration of a UAD to improve performance and weatherization, and test the effectiveness of the deterrents on bat activity. The Feasibility Study was intended to work out potential issues using a relatively small number of devices prior to manufacturing and installing numerous devices for a larger-scale comparative study. The division of the project into these separate studies was based on previous experience and the challenges of assessing the capabilities of an untested UAD. During the initial development and manufacturing of the UAD, NRG Systems decided to use a piezoelectric transducer rather than an electrostatic transducer, which was used by a previous device (i.e. Deaton UAD). NRG Systems conducted lab testing (i.e., IP67 or Ingress Protection) to ensure no water or dust ingress. In addition, shock/drop trials and variations in temperature exposure were conducted as part of the reliability testing. NRG Systems also developed a communications system to allow for continuous performance monitoring of the UADs. For the Feasibility Study, we installed 6 UADs on each of 2 Gamesa G90 2-MW wind turbines (Turbine 14 and 8) at the South Chestnut Wind Energy Facility, Pennsylvania and monitored activity under control and treatment (i.e. Deterrent) conditions using thermal video monitoring. There are two major sources of variation in bat activity (beyond the anticipated treatment effect): 1) environment around the turbines might inherently favor more activity at one than the other; 2) weather conditions on any given night or within season difference (e.g., migration later during the study period) might favor more activity on some nights than on other nights. Because we could only monitor two turbines on any night, we sought to control the potential influences of these two sources by alternating the turbine on which deterrents were activated each night. If there were no loss of data due to technical failures, this design would result in an equal number of deterrent and control nights at each turbine through the monitoring period, balancing the effects of both sources of variation. We compared the time bats spent and the number of events that occurred in overlapping cameras FOV as an indicator of risk, since 80% of the overlapping FOV of the cameras was in the RSA. Equipment failures, majority due to lightning, resulted in only 17 nights with useable data, with unbalanced treatment assignment within turbines and uneven distribution of treatment assignment throughout the observational period. This resulted in a confounding of treatment assignment and seasonal change. Deterrent treatment was measured at Turbine 14 on only 2 of the first 8 usable nights (spanning the period from 8/18-9/17), whereas 6 times on Turbine 8. From 9/18-927, deterrent was on at Turbine 14 on 6 of the remaining 10 nights, and 4 on Turbine 8. We recorded a total of 1,057 bats and observed a reduction in number of events and duration of events at the UAD-activated turbine when it was Turbine 14. When Turbine 8 had the UAD activated, we observed no difference in number or duration of events. Variation between turbines is not unusual and can cause issues when study designs have no true replication, i.e., multiple turbines per treatment. Within-turbine differences suggested a trend for reduced activity when UADs were activated, particularly for Turbine 14. These results may be caused by the overall higher bat activity at Turbine 8 and confounding of treatment assignment and seasonal trends. We mapped 58 bat events in 3-dimensional space (3D), 30 and 28 events during control and treatment conditions, respectively. We observed bats crossing the rotor plane under both control and treatment conditions and observed a total of 40 confirmed or near-collisions (i.e., target close to blade but no visual confirmation of a strike) out of a total of 1,491 medium and high confidence bat observations (880 control, 611 at treatment). Twice as many collisions/possible collisions were observed during control conditions. Given the challenges with the equipment and potential confounding of the data (i.e., different activity levels at the two wind turbines), we were unable to determine whether this initial turbine placement and orientation was optimal. Given no new information on how best to install the devices, we elected to use the same placement and orientation for the comparative study. For the Comparative Study, the objectives were to investigate the relative mortality rates among 4 treatments. We searched the area within 90 m of each turbine daily to recover the highest number of fresh fatalities possible. We were unable to detect a clear reduction in mortality from deterrents alone for any individual species. Surprisingly, mortality rate of the eastern red bat (Lasiurus borealis) was estimated to be 1.3–4.2 times as much when turbines were operating normally and UADs were on than when UADs were off. Reduction in mortality of all bat species combined due to curtailment of turbines was estimated to be between 0%–38%. This effect was nullified when, in addition to curtailment, UADs were on, with 95% confidence interval ranging from a 45% reduction to a 36% increase in mortality. This was likely due to the large proportion of eastern red bats in the total carcass population. Mortality of all low-frequency echolocating bats combined (i.e. hoary bat [L. cinereus], big brown bat [Eptesicus fuscus], silver-haired bat [Lasionycteris noctivagans]) relative to control was lower when curtailed (95% CI: 0%–74%), but the addition of UADs had no detectable effect (95%CI: 13%–79%). The combined treatment reduced mortality in silver-haired bats relative to control by 11%–99%, compared to curtailment (81% reduction–67% increase) or deterrent (82% reduction–67% increase) alone. Because silver-haired bats comprised a large proportion of low-frequency calling bats found during this study, a similar effect was seen for that group. The higher mortality observed for eastern red bats at UAD compared to control could have been caused by several factors, such as the effective range of the UAD, particularly at higher frequencies, behavior, positioning of the devices on the nacelle, or a combination of these. We used 3D thermal videography to compare control and UAD bat behavior from two turbines using a total of 203 3D bat-tracks across 34 nights. We recorded a similar number of bat-tracks between treatment groups, with 51% and 49% for control and UAD, respectively. Due to potential differences in bat behavior around spinning vs stationary turbine blades, we examined UAD effectiveness separately for non-operating turbines (feathered below cut-in speed of 3.5 m/s) and operating (normal operation above wind speed of 3.5 m/s). We found a higher proportion of bat-tracks at operating turbines (82%) compared to non-operating turbines (18%), although this does not account for overall time turbines were operating versus not. At non-operating turbines the UAD appears to be effective at reducing the amount of time, flight length, and number of passes through the rotor plane, compared to control. In addition, we found bats approached turbines similarly between control and treatment turbines, with 61% of control and 63% of UAD bat-tracks originating leeward of the hub. In contrast, at operating turbines, we saw little change in bat behavior in response to UADs. For example, we found an increase in the average duration of bat-tracks between non-operating and operating turbines for UAD but at control turbines we found average duration decreased once turbines became operational. Both control and UAD had a high proportion of bat-tracks that crossed the rotor plane (i.e., collision risk) originate from the windward side when turbines were operational 65% to 92%, respectively. Given that the UAD devices closest to the blades were orientated parallel to the blades, its possible bats were not exposed to the signal until they were close to the turbine blades, as suggested by the slightly higher mean duration within 5 meters of the blades for UAD turbines. Future research should consider concentrating UAD intensity on the areas of risk (i.e. blades) with enough buffer to allow bats to react to the sound before entering the rotor-swept area (RSA). In addition, investigating the potential of installing UAD units windward of the turbine blades (e.g. a hub-mounted UAD), particularly since even under control conditions, a relatively high proportion (65%) of crosses through the blade plane originated windward. 3D thermal videography provided valuable information on future testing strategies (e.g. device placement, UAD orientation) to improve UAD effectiveness when bats are at risk (i.e., operating wind turbines). Across the entire project we experienced issues with the operation and communication with the UADs. Most of the issues occurred during the Feasibility Study and were resolved prior to the Comparability Study. Additional challenges surfaced during the Comparability Study but were remedied immediately and are thought to have little impact on the results. We had logistical constraints at the project that limited our ability use traditional methods in our camera calibration. Several calibrations showed inaccurate scales, which may have been related to inadequate spatial coverage of “points” in the camera calibration volume. Because we were using actual video recordings of bats at a wind turbine, the behavior of bats could have concentrated “points” in specific areas of the turbine (i.e. leeward of nacelle), and limited “points” in other areas, resulting in camera calibration issues. We have plans to address these inconsistencies and improving the software and related methodologies by early 2020.

17 WIND ENERGY↗
DOE OSTI2022

Volumetric Rendering on Wavelet-Based Adaptive Grid

Numerical modeling of physical phenomena frequently involves processes across a wide range of spatial and temporal scales. In the last two decades, the advancements in wavelet-based numerical methodologies to solve partial differential equations, combined with the unique properties of wavelet analysis to resolve localized structures of the solution on dynamically adaptive computational meshes, make it feasible to perform large-scale numerical simulations of a variety of physical systems on a dynamically adaptive computational mesh that changes both in space and time. Volumetric visualization of the solution is an essential part of scientific computing, yet the existing volumetric visualization techniques do not take full advantage of multi-resolution wavelet analysis and are not fully tailored for visualization of a compressed solution on the wavelet-based adaptive computational mesh. Our objective is to explore the alternatives for the visualization of time-dependent data on space-time varying adaptive mesh using volume rendering while capitalizing on the available sparse data representation. Two alternative formulations are explored. The first one is based on volumetric ray casting of multi-scale datasets in wavelet space. Rather than working with the wavelets at the finest possible resolution, a partial inverse wavelet transform is performed as a preprocessing step to obtain scaling functions on a uniform grid at a user-prescribed resolution. As a result, a solution in physical space is represented by a superposition of scaling functions on a coarse regular grid and wavelets on an adaptive mesh. An efficient and accurate ray casting algorithm is based just on these coarse scaling functions. Additional details are added during the ray tracing by taking an appropriate number of wavelets into account based on support overlap with the interpolation point, wavelet coefficient magnitude, and other characteristics, such as opacity accumulation (front to back ordering) and deviation from frontal viewing direction. The second approach is based on complementing of wavelet-based adaptive mesh to the traditional Adaptive Mesh Refinement (AMR) mesh. Both algorithms are illustrated and compared to the existing volume visualization software for Rayleigh-Benard thermal convection and electron density data sets in terms of rendering time and visual quality for different data compression of both wavelet-based and AMR adaptive meshes.

Vezolainen, Alexei V.↗
DOE OSTI2021

Jet tagging in the Lund plane with graph networks

The identification of boosted heavy particles such as top quarks or vector bosons is one of the key problems arising in experimental studies at the Large Hadron Collider. In this article, we introduce LundNet, a novel jet tagging method which relies on graph neural networks and an efficient description of the radiation patterns within a jet to optimally disentangle signatures of boosted objects from background events. We apply this framework to a number of different benchmarks, showing significantly improved performance for top tagging compared to existing state-of-the-art algorithms. We study the robustness of the LundNet taggers to non-perturbative and detector effects, and show how kinematic cuts in the Lund plane can mitigate overfitting of the neural network to model-dependent contributions. Finally, we consider the computational complexity of this method and its scaling as a function of kinematic Lund plane cuts, showing an order of magnitude improvement in speed over previous graph-based taggers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Shape- and Orientation-Dependent Scattering of Isolated Gold Nanostructures Using Polarized Dark-Field Microscopy

In this work, we demonstrate a simple and robust method for measuring the shape- and orientation-dependent optical scattering of various plasmonic nanostructures adsorbed onto a solid surface using polarized dark-field microscopy. By analyzing the dark-field scattering images of gold nanostructures using grazing incidence polarized light with a bench-top microscope, we are able to correlate optical scattering from the individual nanostructures with their shape and orientation. Depending on the size, shape, and orientation of the plasmonic nanostructures, they exhibit characteristic angle- and polarization-dependent scattering signals. Extracting the red, green, and blue channels of the scattering signals from a color-imaging detector as a function of azimuthal angle provides a polar plot of color intensity values that is characteristic of the underlying nanostructure. Examples are presented for various nanostructures, including spherical nanoparticles, nanotriangles, and nanorods. Experimental results are complemented by numerical calculations of the scattering spectra of representative model nanostructures. We demonstrate that the polarization- and orientation-dependent scattering behavior is a consequence of various localized surface plasmon modes existing in the nanostructures and can be used to verify the shape of individual objects as well as quickly identify the orientation of numerous objects on a densely populated substrate. We anticipate that this method will provide a rapid and efficient complement to the typical structural analysis of nanoparticles that is achieved by electron microscopy as well as providing a simple method for generating detailed information of the optical scattering of various types of individual plasmonic nanostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Understanding Transient Combustion Phenomena in Low-NO x Gas Turbines

The goal of this work was to understand, quantify, and eventually predict combustion instability during operational transients in low-NO x gas turbine combustors. Transient operation is defined as a mode where one or more key operating parameters, including equivalence ratio, fuel composition, or fuel splitting between nozzles in a combustor, are varying in time. The timescale over which this variation occurs will be referred to as the transient timescale, the magnitude of the change in the transient parameter will be referred to as the transient amplitude, and the direction of the variation will be referred to as the transient direction. Transients occur regularly in power generation gas turbine operation. For example, load-following gas turbines vary load to meet power demands while accounting for variation in unsteady grid contributors like wind and solar power. Operators achieve this by varying equivalence ratio and fuel splitting inside the combustors to produce more or less power. Another example of transient operation is during fuel-switching operations, a particular issue for turbines operating with syngas fuels in a co-generation facility. In this case, the composition of the fuel stream may vary in time either as a result of fluctuations in the pipeline, or in the case of a co-generation plant, variations in feedstock or gasification processes. This fluctuation in fuel composition can have significant implications for combustion processes, particularly with high-hydrogen fuels. A small number of studies have investigated transient behavior in gas turbine combustors, particularly in the context of flame blow-off; here, investigators have typically focused on issues of transient amplitude, though without the depth and physics-based experimental design that is proposed in this program. To our knowledge, there have been no studies that have quantified the impact of the transient timescale on combustion. The work helped us understand the impact of several types of transients on combustion stability. Both static and dynamic combustion stability will be considered. The transients will be quantified using their amplitude, direction, and timescale, and we will consider transients in equivalence ratio, fuel composition, and fuel splitting. There were two main objectives of this work: 1. Provide a fundamental understanding of combustion stability during transient operation using data obtained from a number of high-speed diagnostic techniques on experimental configurations that capture important gas turbine combustor features and operating conditions. This goal was met in conjunction with our industrial partner, GE Global Research, with whom we worked closely throughout the program. 2. Develop a stability prediction framework that will allow for the prediction, and possible control, of instabilities as a function of the transient amplitude, direction, and timescale. This input/output model should be physics-based and allow for screening of operating conditions and prediction of unstable behavior at the end of a transient by monitoring combustor health and precursor signals during operation.

03 NATURAL GAS↗
DOE OSTI2025

SAM Linear Fresnel Model, Project B (CRADA Final Report)

Objective performance and economic modeling of solar thermal plants is of keen interest to many EPRI funders. One solar thermal technology that is not currently available to model in any non-vendor, non-proprietary tool is linear Fresnel. This technology has garnered enough interest from EPRI funders to merit investing in a tool to objectively model its performance. Early in 2010, EPRI performed a comparison of modeling solar thermal power plants using the IPSEPRO, CNRS and Solar Advisor (SAM) tools. After completing this effort, EPRI decided to adopt NREL’s Solar Advisor Model as its default modeling tool based in part on user friendliness, flexibility, number of technologies covered, integrated financial model and ease of running sensitivities. Furthermore, it was recognized that NREL continues to invest considerable time and resources into improving capabilities and functionality of the model.

14 SOLAR ENERGY↗
DOE OSTI2021

Predictions for axion couplings from ALP cogenesis

Adding an axion-like particle (ALP) to the Standard Model, with a field velocity in the early universe, simultaneously explains the observed baryon and dark matter densities. This requires one or more couplings between the ALP and photons, nucleons, and/or electrons that are predicted as functions of the ALP mass. These predictions arise because the ratio of dark matter to baryon densities is independent of the ALP field velocity, allowing a correlation between the ALP mass, ma, and decay constant, f a . The predicted couplings are orders of magnitude larger than those for the QCD axion and for dark matter from the conventional ALP misalignment mechanism. As a result, this scheme, ALP cogenesis, is within reach of future experimental ALP searches from the lab and stellar objects, and for dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Multilabel proportion prediction and out-of-distribution detection on gamma spectra of short-lived fission products

In the machine learning problem of multilabel classification, the objective is to determine for each test instance which classes the instance belongs to. In this work, we consider an extension of multilabel classification, called multilabel proportion prediction, in the context of radioisotope identification (RIID) using gamma spectra data. We aim to not only predict radioisotope proportions, but also identify out-of-distribution (OOD) spectra. We achieve this goal by viewing gamma spectra as discrete probability distributions, and based on this perspective, we develop a custom semi-supervised loss function that combines a traditional supervised loss with an unsupervised reconstruction error function. Our approach was motivated by its application to the analysis of short-lived fission products from spent nuclear fuel. In particular, we demonstrate that a neural network model trained with our loss function can successfully predict the relative proportions of 37 radioisotopes simultaneously. The model trained with synthetic data was then applied to measurements taken by Pacific Northwest National Laboratory (PNNL) to conduct analysis typically done by subject-matter experts. Here, we also extend our approach to successfully identify when measurements are OOD, and thus should not be trusted, whether due to the presence of a novel source or novel proportions.

Anomaly detection↗
DOE OSTI2023

Impact of Open Communication Networks on Load Frequency Control with Plug-In Electric Vehicles by Cyber-Physical Dynamic Co-Simulation

With the increasing electrification of the transportation sector to achieve the carbon neutrality objective, despite the challenges of charging electric vehicles (EV), there are also opportunities through smart charging EVs to improve system frequency stability; however, EV control technologies might require nontraditional communication support. This paper investigates the impacts of communication variations of EV on power system load frequency control through a cyber-physical dynamic system (CPDS) co-simulation. Here, the CPDS is built upon our previously developed transmission-and-distribution dynamic co-simulation model with the added communication variation functions (i.e., delay and packet loss). The case studies consider multiple communication variation scenarios when the system experiences an N-1 generation trip contingency. The scenarios include communication delays and packet loss using both homogeneous and heterogeneous assumptions. The outcomes of this work can help improve EV frequency regulation services and provide robust and effective tests for different load frequency control algorithms of the future power systems.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2024

KOMPASS-II: Compaction of Crushed salt for Safe Containment – Phase 2

Long-term stable sealing elements are a basic component in the safety concept for a possible repository for heat-emitting radioactive waste in rock salt. The sealing elements will be part of the closure concept for drifts and shafts. They will be made from a welldefinied crushed salt in employ a specific manufacturing process. The use of crushed salt as geotechnical barrier as required by the German Site Selection Act from 2017 /STA 17/ represents a paradigm change in the safety function of crushed salt, since this material was formerly only considered as stabilizing backfill for the host rock. The demonstration of the long-term stability and impermeability of crushed salt is crucial for its use as a geotechnical barrier. The KOMPASS-II project, is a follow-up of the KOMPASS-I project and continues the work with focus on improving the understanding of the thermal-hydraulic-mechanical (THM) coupled processes in crushed salt compaction with the objective to enhance the scientific competence for using crushed salt for the long-term isolation of high-level nuclear waste within rock salt repositories. The project strives for an adequate characterization of the compaction process and the essential influencing parameters, as well as a robust and reliable long-term prognosis using validated constitutive models. For this purpose, experimental studies on long-term compaction tests are combined with microstructural investigations and numerical modeling. The long-term compaction tests in this project focused on the effect of mean stress, deviatoric stress and temperature on the compaction behavior of crushed salt. A laboratory benchmark was performed identifying a variability in compaction behavior. Microstructural investigations were executed with the objective to characterize the influence of pre-compaction procedure, humidity content and grain size/grain size distribution on the overall compaction process of crushed salt with respect to the deformation mechanisms. The created database was used for benchmark calculations aiming for improvement and optimization of a large number of constitutive models available for crushed salt. The models were calibrated, and the improvement process was made visible applying the virtual demonstrator.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Development of spectroscopy apparatus for molten salt reactor safeguards and material characterization

A molten salt reactor (MSR) produces nuclear fission energy using mixture of fissile and non-fissile salts. Salt in the reactor functions as the nuclear material and the coolant allowing for a safer design. International nuclear safeguards is the monitoring of nuclear reactors, nuclear fuel, and irradiated material to prevent the proliferation of nuclear weapon grade material in hostile foreign nations. The mixture of salt creates a proliferation risk as it generates a conglomeration of fuel, daughter nuclei, and corrosive material. A method to monitor and measure the materials present in the reactor is essential to the scalable deployment of MSRs. The objective of this project was to design a spectroscopy apparatus for aqueous salt so it can be measured and collected consistently in the aerosol phase.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Modeling and Simulation of Fuel Dispersal During the Loss-of-Coolant Accident

This document is the compilation of the milestone portion to a larger end of project NEUP report. The executive summary of the modeling portion is provided below: In the event of cladding rupture during a postulated LOCA in a pressurized water reactor, fuel particles, along with fission gases, can be expelled into the reactor core from the fractured fuel rod, a phenomenon referred to as fuel dispersal. The initial stage of fuel dispersal is strongly influenced by the high-pressure ejection of fuel fragments, the size and geometry of the ruptured cladding, and the depressurization history of the fuel rod during the postulated LOCA transient. Depending on the location of the burst orifice relative to the quench front, the dispersal event represents an intricate three-phase flow and heat transfer phenomenon, where high-temperature fuel particles carried by the fission gases interact with the coolant within the narrow subchannels of the fuel assemblies, inducing localized phase change. Given the unique multiphysics nature of this phenomena, the current study develops a dedicated computational framework to predict the mass distribution and cooling of dispersing fuel particles, facilitating post-accident assessment and management of the fuel assemblies. Considering the scale of nuclear reactor applications, a continuum three-fluid model is proposed for simulating the transport of solids within the reactor core. With high-temperature fuel fragments within the liquid media, nucleation sites inducing phase changes are dispersed within the flow domain. Coupled with the fact that the transient dispersal event occurs on different time scales than other three-phase flow applications, this study derives a time-averaged three-fluid flow model without losing generality. The assumptions regarding the continuum treatment of the solid phase and the modeling of fuel dispersal behavior are incorporated to simplify the governing equations and derive applicable closure relations. The computational validation of the model was conducted using adiabatic experimental results obtained from ongoing research at Oregon State University, focusing on characterizing fuel dispersal behavior during simulated LOCA conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched the probability density functions reported in experimental studies. The transport of fuel particles within a scaled 5 × 5 lattice of a pressurized-water reactor rod bundle geometry was modeled through a two-fluid Eulerian framework. The required boundary conditions were evaluated from the fuel performance code BISON in a postulated large-break LOCA scenario. The modeling framework considered solid fuel particles as granular matter, interacting with the gaseous dry steam phase and fission gases through the governing interfacial momentum exchange between the participating fluids. The simulation results provided the volume fraction of the solids obtained at the bottom surface of the enclosing tank geometry. Postulated LOCA leading to fuel dispersal phenomena involves the strong coupling between fuel thermomechanics, cladding deformation, thermal-hydraulics, and fuel particle transport. Incorporation of such a strong coupling in numerical simulation is performed by coupling the multiphysics solvers. In the case of fuel dispersal, a strong coupled simulation can be performed by coupling the BISON code for fuel performance, the TRACE code for system-level thermal hydraulics, and fuel particle transport in Multiphysics Object-Oriented Simulation Environment (MOOSE). For such intricate infrastructure, the MOOSE Framework eases the data transfer between codes. The recent version of MOOSE has incorporated the Navier-Stokes module for the fluid flow. An exploratory exercise was done to gain familiarity with finite volume capabilities in the MOOSE framework to incorporate the Spalart-Allmaras (SA) turbulence model. New finite-volume and auxiliary kernels were introduced to assemble the SA transport equation, compute turbulent viscosity, and evaluate wall distance and diagnostic turbulence terms, fully integrated with existing Navier-Stokes modules. A turbulent lid-driven cavity at a Reynolds number of approximately 10,000 is used for verification. MOOSE shows the robust solver convergence and produces the turbulent features. But it underpredicts the velocity profile and turbulent quantities, emphasizing the need to develop improved SA near-wall treatments (e.g., low-Re corrections or wall functions) as a key direction for future work.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Mechanisms of Biomolecular Self-Assembly Investigated Through In Situ Observations of Structures and Dynamics

Biomolecular self-assembly of hierarchical materials is a precise and adaptable bottom-up approach to synthesizing across scales with considerable energy, health, environment, sustainability, and information technology applications. To achieve desired functions in biomaterials, it is essential to directly observe assembly dynamics and structural evolutions that reflect the underlying energy landscape and the assembly mechanism. This report will summarize the current understanding of biomolecular assembly mechanisms based on in situ characterization and discuss the broader significance and achievements of newly gained insights. In addition, we will also introduce how emerging deep learning/machine learning-based approaches, multiparametric characterization, and high-throughput methods can boost the development of biomolecular self-assembly. The objective of this review is to accelerate the development of in situ characterization approaches for biomolecular self-assembly and to inspire the next generation of biomimetic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Comparative analysis of atmospheric parameters from high-resolution spectroscopic sky surveys: APOGEE, GALAH, Gaia -ESO

SDSS-IV APOGEE-2, GALAH, and Gaia-ESO are high-resolution, ground-based, multi-object spectroscopic surveys providing fundamental stellar atmospheric parameters and multiple elemental abundance ratios for hundreds of thousands of stars of the Milky Way. Data from these and other surveys contribute to investigations of the history and evolution of the Galaxy. We undertake a comparison between the most recent data releases of these surveys to investigate the accuracy and precision of derived parameters by placing the abundances on an absolute scale. We also discuss the correlations in parameter and abundance differences as a function of main parameters. Uncovering the variants provides a basis to continue the efforts of future sky surveys. Quality samples from the APOGEE-GALAH (15 537 stars), APOGEE-GES (804 stars), and GALAH-GES (441 stars) overlapping catalogs were collected. We investigated the mean variants between the surveys, and linear trends were also investigated. We compared the slope of correlations and mean differences with the reported uncertainties. The average and scatter of v rad , T eff , log g, [M/H], and v micro , along with numerous species of elemental abundances in the combined catalogs, show that in general there is a good agreement between the surveys. We find large radial velocity scatters ranging from 1.3 km s -1 to 4.4 km s -1 when comparing the three surveys. We observe some weak trends (e.g., in ΔT eff vs. Δlog g for the APOGEE-GES stars) and a clear correlation in the v micro - Δv micro planes in the APOGEE-GALAH common sample. For [α/H], [Ti/H] (APOGEE-GALAH giants), and [Al/H] (APOGEE-GALAH dwarfs) potential strong correlations are discovered as a function of the differences in the main atmospheric parameters, and we also find weak trends for other elements. In general we find good agreement between the three surveys within their respective uncertainties. However, there are certain regimes in which strong variants exist, which we discuss. There are still offsets larger than 0.1 dex in the absolute abundance scales.

79 ASTRONOMY AND ASTROPHYSICS↗