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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Bayesian Cross-matching of High Proper-motion Stars in Gaia DR2 and Photometric Metallicities for ∼1.7 million K and M Dwarfs

We present a Bayesian method to cross-match 5,827,988 high proper-motion Gaia sources (μ > 40 mas yr{sup −1}) to various photometric surveys: Two Micron All Sky Survey, AllWISE data release from the Wide-field Infrared Explorer (WISE) mission, Galaxy Evolution Explorer, Radial Velocity Experiment, Sloan Digital Sky Survey, and Panoramic Survey Telescope and Rapid Response System (Pan-STARRS). To efficiently associate these objects across catalogs, we develop a technique that compares the multidimensional distribution of all sources in the vicinity of each Gaia star to a reference distribution of random field stars obtained by extracting all sources in a region on the sky displaced 2′. This offset preserves the local field stellar density and magnitude distribution, allowing us to characterize the frequency of chance alignments. The resulting catalog with Bayesian probabilities >95% has a marginally higher match rate than current internal Gaia data release 2 (DR2) matches for most catalogs. However, a significant improvement is found with Pan-STARRS, where ∼99.8% of the sample within the Pan-STARRS footprint is recovered, as compared to a low ∼20.8% in Gaia DR2. Using these results, we train a Gaussian process regressor to calibrate two photometric metallicity relationships. For dwarfs of 3500 < T{sub eff} < 5280 K, we use metallicity values of 4378 stars from the Apache Point Observatory Galactic Evolution Experiment and Hejazi et al. to calibrate the relationship, producing results with a 1σ precision of 0.12 dex and few systematic errors. We then indirectly infer the metallicity of 4018 stars with 2850 < T{sub eff} < 3500 K, which are wide companions of primaries whose metallicities are estimated with our first regressor, to produce a relationship with a 1σ precision of 0.21 dex and significant systematic errors. Additional work is needed to better remove unresolved binaries from this second sample to reduce these systematic errors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Modeling strength and failure variability due to porosity in additively manufactured metals

To model and quantify the variability in plasticity and failure of additively manufactured metals due to imperfections in their microstructure, we have developed uncertainty quantification methodology based on pseudo marginal likelihood and embedded variability techniques. We account for both the porosity resolvable in computed tomography scans of the initial material and the sub-threshold distribution of voids through a physically motivated model. Calibration of the model indicates that the sub-threshold population of defects dominates the yield and failure response. Finally, the technique also allows us to quantify the distribution of material parameters connected to microstructural variability created by the manufacturing process, and, thereby, make assessments of material quality and process control.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A spatial evaluation of Arctic sea ice and regional limitations in CMIP6 historical simulations

The Arctic sea ice response to a warming climate is assessed in a subset of models participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6), using several metrics in comparison with satellite observations and results from the Pan-Arctic Ice Ocean Modeling and Assimilation System and the Regional Arctic System Model. Our study examines the historical representation of sea ice extent, volume, and thickness using spatial analysis metrics, such as the integrated ice-edge error, Brier score, and Spatial Probability Score. We find that the CMIP6 multi-model mean captures the mean annual cycle and 1979-2014 sea ice trends remarkably well. However, individual models experience a wide range of uncertainty in the spatial distribution of sea ice when compared against satellite measurements and reanalysis data. Our metrics expose common and individual regional model biases, which sea ice temporal analyses alone do not capture. We identify large ice edge and ice thickness errors in Arctic sub-regions, implying possible model specific limitations in or lack of representation of some key physical processes. We postulate that many of them could be related to the oceanic forcing, especially in the marginal and shelf seas, where seasonal sea ice changes are not adequately simulated. We therefore conclude that an individual model’s ability to represent the observed/reanalysis spatial distribution still remains a challenge. We propose the spatial analysis metrics as useful tools to diagnose model limitations, narrow down possible processes affecting them, and guide future model improvements critical to the representation and projections of Arctic climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Mobile genetic elements shape microbial diversity and functions in thawing permafrost soils

Ecosystems are shaped by communities of microorganisms whose niches and impacts depend on functional profiles influenced by gene gains and losses. Culture-based experiments demonstrate that mobile genetic elements (MGEs) can mediate gene flux, but quantitative understanding of these dynamics in natural systems remains limited. Here we develop and apply a systematic, meta-omic framework to investigate MGEs in a complex natural system using an 8-year soil time series collected at Stordalen Mire, in Sweden’s thawing permafrost margin. In this climate-critical peatland, we identify ~2.1 million MGE recombinases across 89 microbial phyla and assess ecological distributions, affected functions, past mobility and current activity. This revealed an active mobilome that shapes natural genetic diversity via differential impacts on major phyla and affects a wide range of functions, including metabolic genes involved in carbon flux and nutrient cycling. These findings and this analytic framework suggest avenues towards a better understanding of MGE diversity, activity, mobility and impacts across ecosystems.

Biological and medical sciences↗
DOE OSTI2020

Voltage positioning using co-optimization of controllable grid assets in radial networks

With increasing penetration of solar PV, some distribution feeders are experiencing highly variable net-load flows and even reverse flows. To optimize distribution systems under such conditions, the scheduling of mechanical devices, such as OLTCs and capacitor banks, needs to take into account forecasted solar PV and actual grid conditions. However, these legacy switching assets are operated on a daily or hourly timescale, due to the wear and tear associated with mechanical switching, which makes them unsuitable for real-time control. Therefore, there is a natural timescale- separation between these slower mechanical assets and the responsive nature of inverter-based resources. In this paper, we present a network admissible convex formulation for holistically scheduling controllable grid assets to position voltage optimally against solar PV. An optimal hourly schedule is presented that utilizes mechanical resources to position the predicted voltages close to nominal values, while minimizing the use of inverter-based resources (i.e., DERs), making them available for control at a faster time-scale (after the uncertainty reveals itself). A convex, inner approximation of the OPF problem is adapted to a mixed-integer linear program that minimizes voltage deviations from nominal (i.e., maximizes voltage margins). Here, the resulting OPF solution respects all the network constraints and is, hence, robust against modeling simplifications. Simulation based analysis on IEEE distribution feeders validates the approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Sequential removal of cation/H + exchangers reveals their additive role in elemental distribution, calcium depletion and anoxia tolerance

Multiple Arabidopsis H + /Cation exchangers (CAXs) participate in high-capacity transport into the vacuole. Previous studies have analysed single and double mutants that marginally reduced transport; however, assessing phenotypes caused by transport loss has proven enigmatic. Here, in this study, we generated quadruple mutants (cax1-4: qKO) that exhibited growth inhibition, an 85% reduction in tonoplast-localised H + /Ca transport, and enhanced tolerance to anoxic conditions compared to CAX1 mutants. Leveraging inductively coupled plasma mass spectrometry (ICP-MS) and synchrotron X-ray fluorescence (SXRF), we demonstrate CAX transporters work together to regulate leaf elemental content: ICP-MS analysis showed that the elemental concentrations in leaves strongly correlated with the number of CAX mutations; SXRF imaging showed changes in element partitioning not present in single CAX mutants and qKO had a 40% reduction in calcium (Ca) abundance. Reduced endogenous Ca may promote anoxia tolerance; wild-type plants grown in Ca-limited conditions were anoxia tolerant. Sequential reduction of CAXs increased mRNA expression and protein abundance changes associated with reactive oxygen species and stress signalling pathways. Multiple CAXs participate in postanoxia recovery as their concerted removal heightened changes in postanoxia Ca signalling. This work showcases the integrated and diverse function of H + /Cation transporters and demonstrates the ability to improve anoxia tolerance through diminishing endogenous Ca levels.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Formation and Redshift Evolution of Dark Matter Spikes

Dark matter density spikes forming around adiabatically growing black holes can dramatically enhance indirect and direct detection signals. Canonical predictions, however, assume a zero-mass seed in a purely dark matter environment and do not track the long-term dynamical impact of surrounding stars. We present a semi-analytic framework that first generalizes adiabatic spike formation to include finite seed masses, stellar cusps, and non-circular orbits, and then studies the subsequent cosmic evolution by solving coupled Fokker-Planck equations for the dark matter and stellar phase-space distributions, with a heating rate modulated by the cosmic star formation rate. Starting conservatively from canonical Gondolo-Silk spikes and marginalizing over astrophysical uncertainties, we find that stellar gravitational heating drives the inner slope towards $γ_χ\simeq 1.5$ within a few Gyrs (e.g by $z \lesssim 2$ for spikes formed at $z\simeq 10$), yielding overdensities two to four orders of magnitude below canonical expectations but still well above an NFW-like cusp. We provide redshift-dependent benchmarks for the column density and $J$-factor relevant to scattering, decay and annihilation signatures. Any robust interpretation of indirect dark matter signals from galactic nuclei must account for this evolution.

Herrera, Gonzalo [MIT, LNS; MIT, MKI; Harvard U.]↗
DOE OSTI2022

Data-model files associated with the manuscript "The Effects of Spatial and Temporal Resolution of Gridded Meteorological Forcing on Watershed Hydrological Responses" (Shuai et al., 2022 HESS)

This data package contains the model inputs and outputs used in "The Effects of Spatial and Temporal Resolution of Gridded Meteorological Forcing on Watershed Hydrological Responses" (Shuai et al., 2022 HESS). The data.zip file contains the data used to drive the model simulations. The model.zip file contains the XML input file for ATS. The notebook.zip file contains the Jupyter notebooks for pre- and post- processing model results. The figures.zip file contains the raw figures associated with the manuscript.Meteorological forcing plays a critical role in accurately simulating the watershed hydrological cycle. With the advancement of high-performance computing and the development of integrated watershed models, simulating the watershed hydrological cycle at high temporal (hourly to daily) and spatial resolution (10s of meters) has become efficient and computationally affordable. These hyperresolution watershed models require high resolution of meteorological forcing as model input to ensure the fidelity and accuracy of simulated responses. In this study, we utilized the Advanced Terrestrial Simulator (ATS), an integrated watershed model, to simulate surface and subsurface flow and land surface processes using unstructured meshes at the Coal Creek Watershed near Crested Butte (Colorado). We compared simulated watershed hydrologic responses including streamflow, and distributed variables such as evapotranspiration, snow water equivalent (SWE), and groundwater table driven by three publicly available, gridded meteorological forcings (GMFs) -- Daily Surface Weather and Climatological Summaries (Daymet), Parameter-elevation Regressions on Independent Slopes Model (PRISM), and North American Land Data Assimilation System (NLDAS). By comparing various spatial resolutions (ranging from 400 m to 4 km) of PRISM, the simulated streamflow only becomes marginally worse when spatial resolution of meteorological forcing is coarsened to 4 km (or 30% of the watershed area). However, the 4 km resolution has much worse performance than finer resolution in spatially distributed variables such as SWE. Using temporally disaggregated PRISM, we compared models forced by different temporal resolutions (hourly to daily), sub-daily resolution preserves the dynamic watershed responses (e.g., diurnal fluctuation of streamflow) that are absent in results forced by daily resolution. Conversely, the simulated streamflow shows better performance using daily resolution compared to that using sub-daily resolution. Our findings suggest that the choice of GMF and its spatiotemporal resolution depends on the quantity of interest and its spatial and temporal scale, which may have important implications on model calibration and watershed management decisions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluating generative networks using Gaussian mixtures of image features

We develop a measure for evaluating the performance of generative networks given two sets of images. A popular performance measure currently used to do this is the Fréchet Inception Distance (FID). However, FID assumes that images featurized using the penultimate layer of Inception follow a Gaussian distribution. This assumption allows FID to be easily computed, since FID uses the 2-Wasserstein distance of two Gaussian distributions fitted to the featurized images. However, we show that Inception features of the ImageNet dataset are not Gaussian; in particular, each marginal is not Gaussian. To remedy this problem, we model the featurized images using Gaussian mixture models (GMMs) and compute the 2-Wasserstein distance restricted to GMMs. We define a performance measure, which we call WaM, on two sets of images by using inception (or another classifier) to featurize the images, estimate two GMMs, and use the restricted 2-Wasserstein distance to compare the GMMs. We experimentally show the advantages of WaM over FID, including how FID is more sensitive than WaM to image perturbations. By modelling the non-Gaussian features obtained from inception as GMMs and using a GMM metric, we can more accurately evaluate generative network performance.

machine learning, genrative adversarial networks↗
DOE OSTI2022

Emerging wild virus of native grass bioenergy feedstock is well–established in the Midwestern USA and associated with premature stand senescence

The North American native prairie grass Panicum virgatum (switchgrass) is a primary bioenergy feedstock candidate. Its widespread distribution and genetic diversity enable the possibility of developing this perennial grass for high production in a variety of conditions, including on marginal lands. A critical concern in feedstock development and deployment is the risk of novel pathogen emergence. Here we investigate the landscape-scale prevalence and epidemiology of a little-studied North American virus first detected in switchgrass and other grasses in bioenergy trials in the US Midwest. Switchgrass mosaic virus (SwMV, Genus Marafivirus, Family Tymoviridae) is transmitted by leafhoppers and phylogenetically sister to Maize rayado fino virus, a significant pathogen of maize in parts of the Americas. Our goal was to determine whether SwMV is uniquely limited to specific bioenergy trials or well-established and circulating more broadly. We used molecular diagnostics to quantify naturally occurring SwMV infection in leafhoppers and switchgrass in naturalistic stands throughout a large Midwestern landscape, and quantified leafhopper abundances and stand performance. Our analysis revealed that this apparently wild virus is well-established and widespread. Infection was present at nearly all sites, across diverse landscape contexts, with prevalences ranging as high as 33%–60%. Infection appeared to accumulate and persist in stands over time. It was associated with increases in premature stand senescence but not with reductions in stand height. Although wild viruses are believed to evolve benign relationships with their natural hosts, these data suggest that SwMV has potential to impact yield components. Viruses are frequently overlooked in crop development efforts, but represent the majority of emerging plant pathogens. For SwMV, it is imperative to quantify its impact on host performance, to identify the extent of any host resistance, and to assess any risks of virus spillover to agricultural plantings of other Poaceae species, including maize and sorghum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Cambium Documentation: Version 2021

Cambium is a tool that assembles structured data sets of simulated hourly emission, cost, and operational data for modeled futures of the U.S. electric sector with metrics designed to be useful for long-term decision-making. It was built to expand the metrics reported in the National Renewable Energy Laboratory's (NREL's) Standard Scenarios - an annually released set of projections of how the U.S. electric sector could evolve across a suite of different potential futures, looking forward through 2050 (Cole et al. 2021) Information about Cambium and related publications can be found at https://nrel.gov/analysis/cambium.html, and the Cambium data sets for the Standard Scenarios can be viewed and downloaded at https://cambium.nrel.gov/. In this documentation, we define the metrics reported in Cambium databases (Section 4) and document the Cambium-specific methods for calculating those metrics (Section 5). As this document is intended to cover multiple Cambium data releases, we do not document specific scenarios here - for individual data releases, readers should look for an accompanying report that describes the assumptions and data that underlie that specific release. For Cambium databases that are built on NREL's Standard Scenarios, for example, reports describing the scenarios can be found on the Standard Scenarios web site (https://www.nrel.gov/analysis/standard-scenarios.html).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

The effects of spatial and temporal resolution of gridded meteorological forcing on watershed hydrological responses

Abstract. Meteorological forcing plays a critical role in accurately simulating the watershed hydrological cycle. With the advancement of high-performance computing and the development of integrated watershed models, simulating the watershed hydrological cycle at high temporal (hourly to daily) and spatial resolution (tens of meters) has become efficient and computationally affordable. These hyperresolution watershed models require high resolution of meteorological forcing as model input to ensure the fidelity and accuracy of simulated responses. In this study, we utilized the Advanced Terrestrial Simulator (ATS), an integrated watershed model, to simulate surface and subsurface flow and land surface processes using unstructured meshes at the Coal Creek Watershed near Crested Butte (Colorado). We compared simulated watershed hydrologic responses including streamflow and distributed variables such as evapotranspiration, snow water equivalent (SWE), and groundwater table driven by three publicly available, gridded meteorological forcings (GMFs) – Daily Surface Weather and Climatological Summaries (Daymet), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the North American Land Data Assimilation System (NLDAS). By comparing various spatial resolutions (ranging from 400 m to 4 km) of PRISM, the simulated streamflow only becomes marginally worse when spatial resolution of meteorological forcing is coarsened to 4 km (or 30 % of the watershed area). However, the 4 km-resolution has much worse performance than finer resolution in spatially distributed variables such as SWE. Using the temporally disaggregated PRISM, we compared models forced by different temporal resolutions (hourly to daily), and sub-daily resolution preserves the dynamic watershed responses (e.g., diurnal fluctuation of streamflow) that are absent in results forced by daily resolution. Conversely, the simulated streamflow shows better performance using daily resolution compared to that using sub-daily resolution. Our findings suggest that the choice of GMF and its spatiotemporal resolution depends on the quantity of interest and its spatial and temporal scale, which may have important implications for model calibration and watershed management decisions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Large balancing areas and dispersed renewable investment enhance grid flexibility in a renewable-dominant power system in China

Renewable energy is poised to play a major role in achieving China's carbon neutrality goal by 2060; however, reliability and flexibility is a big concern of a renewable-dominant power system. Various strategies of enhancing flexibility are under discussion to ensure the reliability of such a system, but no detailed quantitative analysis has been reported yet in China. We combine the advantages of a capacity expansion model, SWITCH-China, with a production simulation model, PLEXOS, and analyze flexibility options under different scenarios of a renewable-dominant power system in China. We find that a larger balancing area offers direct flexibility benefits. Regional balancing could reduce the renewable curtailment rate by 5-7%, compared with a provincial balancing strategy. National balancing could further reduce the power cost by about 16%. However, retrofitting coal power plants for flexible operation would only improve the system flexibility marginally.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Data-Consistent Inversion for Stochastic Input-to-Output Maps

Data-consistent inversion is a recently developed measure-theoretic framework for solving a stochastic inverse problem involving models of physical systems. The goal is to construct a probability measure on model inputs (i.e., parameters of interest) whose associated push-forward measure matches (i.e., is consistent with) a probability measure on the observable outputs of the model (i.e., quantities of interest). Previous implementations required the map from parameters of interest to quantities of interest to be deterministic. This work generalizes this framework for maps that are stochastic, i.e., contain uncertainties and variation not explainable by variations in uncertain parameters of interest. Generalizations of previous theorems of existence, uniqueness, and stability of the data-consistent solution are provided while new theoretical results address the stability of marginals on parameters of interest. A notable aspect of the algorithmic generalization is the ability to query the solution to generate independent identically distributed samples of the parameters of interest without requiring knowledge of the so-called stochastic parameters. This work therefore extends the applicability of the data-consistent inversion framework to a much wider class of problems. This includes those based on purely experimental and field data where only a subset of conditions are either controllable or can be documented between experiments while the underlying physics, measurement errors, and any additional covariates are either uncertain or not accounted for by the researcher. Finally, numerical examples demonstrate application of this approach to systems with stochastic sources of uncertainties embedded within the modeling of a system and a numerical diagnostic is summarized that is useful for determining if a key assumption is verified among competing choices of stochastic maps.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2022

Assessment of Core Physics Characteristics of Extended Enrichment and Higher Burnup LWR Fuels using the Polaris/PARCS Two-Step Approach. Vol. I: PWR Fuel

Nuclear fuel with extended enrichment (235U enrichment within 5-8 wt%) is one of the evolutionary changes that have been pursued in recent years by commercial light water reactor operators and fuel vendors to improve the fuel cycle economy and operation performance of a nuclear plant. This work assesses the performance of the Polaris/PARCS two-step approach in core physics modeling of the pressurized water reactor cores with extended enrichment fuel, referred to as “LEU+” in this report. A representative LEU+ core with a 24-month fuel cycle developed by Southern Nuclear Company (SNC) was modeled using this two-step approach. A representative LEU core with an 18-month fuel cycle was also modeled to provide a reference for the LEU+ core. As expected, significantly more burnable poison absorbers were used in the LEU+ core to accomodate its higher fuel enrichment. Nine different fuel assembly types were modeled using Polaris for each core to generate the assembly cross sections, which were then processed by GenPMAX to prepare the cross-section data for PARCS. The average specific powers of each fuel batch in each core were derived from VERA results and higher specific powers in fresh assemblies were found in the LEU core due to its less total uranium loading included in the VERA LEU model, given that the total core power was assumed to be the same for both cores. PARCS models were developed to simulate the steady-state operations of both cores. PARCS results on the LEU+ core were first compared with the VERA results for verification purpose; good agreements were seen in soluble boron and burnup distribution results, indicating that the Polaris/PARCS modeling and simulation were correctly implemented. Core physics parameters calculated by PARCS, at zero power physics tests, beginning of cycle (BOC), and end of cycle conditions (EOC), were compared between the LEU+ core and the LEU core, including soluble boron concentration, burnup distributions, assembly and pin power peaking factors, fuel temperature reactivity coefficients, moderator temperature and density reactivity coefficients, control rod worth, and shut down margin. The main differences in PARCS results between the LEU+ and the LEU cores are summarized below: 1)The critical boron concentrations were found to be much higher in the LEU+ core than in the LEU core (1582 vs. 1335 ppm for peak values). 2)Higher assembly radial power peaking factors (1.4 vs. 1.3 for peak values), 2D pin peaking factors (1.53 vs. 1.42 for peak values), and 3D pin peaking factors (1.89 vs. 1.81 for peak values) were found in the LEU+ core than in the LEU core. 3)Significantly higher reactivity coefficients of moderator temperature (and density) were found in LEU+ than in LEU.4)Significantly lower control rod worth at EOC were found in LEU+ than LEU for all but one control banks.5)Significantly lower shut down margins were found in the LEU+ core than in the LEU core. The Polaris/GenPMAX/PARCS code suite was found to be capable of modeling the LEU+ PWR core for steady-state operations and no unexpected results in core physics parameters were observed, in spite of that a) several bugs in PARCS were identified and workarounds were used; b) several features were found lacking in the current version of PARCS that would be useful for core modeling. A list of requests for bug fixes and feature upgrades for PARCS originated from this work were transmitted to the code developers. The assessments on the performance of the Polaris/PARCS two-step approach in core modeling for boiling water reactor with LEU+ fuel is ongoing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Ring Asymmetry and Spin in M87*

Event Horizon Telescope (EHT) images of the supermassive black hole M87* depict an asymmetric ring of emission. General relativistic magnetohydrodynamic (GRMHD) models of M87* and its accretion disk predict that the amplitude and location of the ring’s peak brightness asymmetry should fluctuate due to turbulence in the source plasma. We compare the observed distribution of brightness asymmetry amplitudes to the simulated distribution in GRMHD models, across varying black hole spin a * . We show that, for strongly magnetized (MAD) models, three epochs of EHT data marginally disfavor ∣a * ∣ ≲ 0.2. This is consistent with the Blandford–Znajek model for M87’s jet, which predicts that M87* should have nonzero spin. We show quantitatively how future observations could improve spin constraints and discuss how improved spin constraints could distinguish between differing jet-launching mechanisms and black hole growth scenarios.

Bernshteyn, Vadim [Univ. of Illinois at Urbana-Cha↗
DOE OSTI2021

MRP and NEAMS Meeting - Current Modeling to Support Experiments

Heat-pipe cooled micro-reactor is currently being actively investigated in the NS&T department at INL. Given the high operation temperature and large temperature gradients in the system, the induced thermal stresses need to be well analyzed and kept within the safety margin. Two commercial FEM software (ABAQUS and STAR-CCM+) have been proposed to simulate and compare for both the temperature and stress distributions for the single heat pipe experiments, with the middle single heat pipe and 6 heaters surrounded. This presentation file is aimed to provide the latest updates for the researchers who is under NEAMS program and involved with the DOE micro-reactor program

22 GENERAL STUDIES OF NUCLEAR REACTORS↗