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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

SB10 Frit Recommendation, and Evaluations of the Glass Variability Study and Cs-137 Concentrations in Strip Effluent Based on May 2021 Projections

The Defense Waste Processing Facility (DWPF) is currently preparing to initiate processing of Sludge Batch 10 (SB10), which is comprised of material from Tanks 11H, 13H, 15H, and 26F, Alternate Feed Stock-2 (AFS-2) and Sodium Reactor Experiment (SRE) material from H-Canyon. In support of SB10 qualification, frit development using 2020 Tank 40 blend projections and experimental work for the glass variability study were previously conducted. Frit 473 and Frit 209 were identified as candidate frits and both were included in the development of the variability study test matrix; however, a final frit recommendation was postponed until more information could be determined about the composition of SB10 after washing. In May 2021, Savannah River Remediation (SRR) reprojected SB10 based on the analytical results from the Tank 51 qualification sample that was washed in the Savannah River National Laboratory (SRNL) Shielded Cells Facility.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Sludge Batch 10 Frit Development and Variability Study Matrix Design

The Defense Waste Processing Facility (DWPF) is currently preparing to initiate processing of Sludge Batch 10 (SB10), which is comprised of material from Tanks 11H, 13H, 15H, and 26H, and Alternate Feed Stock-2 (AFS-2). H-Canyon also had a need to discard Sodium Reactor Experiment (SRE) material that was stored in Tanks 16.3 and 16.4. Savannah River Remediation (SRR) added a portion of the SRE material to Sludge Batch 9 (SB9) in Tank 40 and the remainder was added to SB10 that is currently being prepared in Tank 51. In support of sludge batch preparation and qualification efforts, SRR requested that the Savannah River National Laboratory (SRNL) complete the following tasks based on the SB10 projections provided by the SRR System Planning group.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Radial velocity variability and the evolution of hot subdwarf stars

Hot subdwarf stars represent a late and peculiar stage in the evolution of low-mass stars, since they are likely formed by close binary interactions. In this work, we perform a radial velocity (RV) variability study of a sample of 646 hot subdwarfs with multi-epoch radial velocities based on spectra from Sloan Digital Sky Survey (SDSS) and Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST). The atmospheric parameters and RVs were taken from the literature. For stars with archival spectra but without literature values, we determined the parameters by fitting model atmospheres. In addition, we redetermined the atmospheric parameters and RVs for all the He-enriched sdO/Bs. This broad sample allowed us to study RV-variability as a function of the location in theT eff - log g- and T eff - log n (He)/n (H) diagrams in a statistically significant way. We used the fraction of RV-variable stars and the distribution of the maximum RV variations ΔRV max as diagnostics. Both indicators turned out to be quite inhomogeneous across the studied parameter ranges. A striking feature is the completely dissimilar behaviour of He-poor and He-rich hot subdwarfs. While the former have a high fraction of close binaries, almost no significant RV variations could be detected for the latter. This has led us to the conclusion that there is likely no evolutionary connection between these subtypes. On the other hand, intermediate He-rich- and extreme He-rich sdOB/Os are more likely to be related. Furthermore, we conclude that the vast majority of this population is formed via one or several binary merger channels. Hot subdwarfs with temperatures cooler than ~24 000 K tend to show fewer and smaller RV-variations. These objects might constitute a new subpopulation of binaries with longer periods and late-type or compact companions. The RV-variability properties of the extreme horizontal branch (EHB) and corresponding post-EHB populations of the He-poor hot subdwarfs match and confirm the predicted evolutionary connection between them. Stars found below the canonical EHB at somewhat higher surface gravities show large RV variations and a high RV variability fraction. These properties are consistent with most of them being low-mass EHB stars or progenitors of low-mass helium white dwarfs in close binaries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Measurement Acceptance Region (MAR) Assessment Results Based On Sludge Batch 10 Projections from December 2021, February 2022 and August 2022

The Defense Waste Processing Facility (DWPF) is currently preparing to initiate processing of Sludge Batch 10 (SB10), which is comprised of material from Tanks 11H, 13H, 15H, and 26F, Alternate Feed Stock-2 and Sodium Reactor Experiment material from H-Canyon. Frit 473 (8B 2 O 3 -8Li 2 O-5Na 2 O-79SiO 2 , in weight percent) was recommended for sludge-only (SO) and coupled processing with the Salt Waste Processing Facility (SWPF) based on previous assessments of SB10 projections with the DWPF Product Composition Control System (PCCS) glass property models and their associated Measurement Acceptance Region (MAR) constraints. Due to the lower processing rate of Sludge Batch 9 (SB9), the heel in Tank 40 is anticipated to be greater than 40 inches at the projected start of SB10 processing to meet the upcoming Accelerated Basin Deinventory addition dates in Tank 51 for Sludge Batch 11. In December 2021 and February 2022, Savannah River Remediation System Planning provided updated SB10 Tank 40 blend projections based on heels of 74 inches, 84 inches, 94 inches and 103.4 inches. Savannah River Mission Completion (SRMC) subsequently pursued Wash Cycle Y to further reduce the total sulfur in the sludge batch and increase processing flexibility at DWPF. In August 2022, SRMC System Planning provided an updated SB10 Tank 40 blend projection with a 76 inch-heel representing Decant Y2 and 60 kilogallons of bearing water inleakage that is anticipated during the Tank 51 to Tank 40 transfer. The objectives of this task were to: • Determine the impact on the operating windows for SO and coupled processing • Determine whether any composition gaps exist between the already completed SB10 variability study and the reprojected SB10 glass composition region • Compare the SB10 reprojected glass composition region to the DWPF PCCS model development and validation ranges to ensure that compositional gaps do not exist between the data sets. This report documents the results of these evaluations. Calculation-based frit assessments were performed using the DWPF PCCS glass property models and their associated MAR constraints. Evaluated parameters for coupled processing included the following transfer volumes per Sludge Receipt and Adjustment Tank batch: 5700 gallons of Tank 40 sludge, 2400-4500 gallons of the SWPF monosodium titanate (MST) and sludge solids stream, and 15,000 gallons of strip effluent. Based on these MAR assessment results, Frit 473 remains viable for SB10 processing. A target waste loading (WL) of 36% is possible for SO operation and single strike (0.4 g/L MST) coupled processing up to 600 mg/L of SB9 insoluble sludge solids at a nominal transfer volume of ~2800 gallons. Increasing the single strike transfer volume to 4500 gallons may reduce the maximum WL below 40%. Operating windows are 12 percentage points for SO processing and 14-16 percentage points for coupled processing. Frit 625 allows for a target WL of 36% and is acceptable for use during the SB9 to SB10 transition to deplete remaining inventory as needed. Operating windows are 8 percentage points for SO processing and 12-14 percentage points for coupled processing. Predictive PCCS evaluations performed at DWPF will provide insight into batch-specific acceptability at desired WLs for compositions having expected oxide ratios during processing versus the extreme vertices (corner points) evaluated in this study. The reprojected SB10 glass composition region generally overlaps the previously evaluated SB10 variability study composition region. Thus, the minor composition shift of these updated SB10 projections indicates that no additional glasses are necessary to demonstrate acceptability relative to the chemical durability of the Environmental Assessment benchmark glass and predictability using the current PCCS models for durability. Based on a comparison of the PCCS model development and validation data to the reprojected SB10 glass composition region, the viscosity and liquidus temperature models will reliably predict SB10 compositions. No additional glasses are necessary to demonstrate predictability of these models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Computational Study of Variable Fuel-Air Ratio and Hydrogen Doping in a Rotating Detonation Engine

Rotating detonation engines (RDEs) hold great promise as a technology for powering aviation engines. The pressure gain that results from continuously traversing detonation waves enables high theoretical performance compared to deflagration-based combustion. However, the harsh operating conditions inside an RDE restrict the availability of suitable experimental diagnostics to study these systems in detail and the range of spatial and temporal scales render numerical simulations of these systems difficult. In this study, we have combined adaptive mesh refinement and a robust shock-capturing approach to study RDE systems computationally using the compressible, reactive solver PeleC. Multi-species transport along with compressible Navier-Stokes equations are solved in the model along with finite-rate chemistry. Complex geometries are represented using an embedded boundary method with second-order spatial accuracy and the system is evolved in time using a second-order Runge-Kutta method. We present studies of a methane-air RDE system that is doped with varying levels of hydrogen. Our analysis focusses on how fuel mixture and doping levels effect the detonation flame structure and the generation of multiple wave modes.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

A multi-dimensional parametric study of variability in multi-phase flow dynamics during geologic CO 2 sequestration accelerated with machine learning

Successful geologic CO 2 storage projects depend on numerical simulations to predict reservoir performance during site selection, injection verification, and post-injection monitoring phases of the project. These numerical simulations solve non-linear sets of coupled partial differential equations, while accounting for multi-phase fluid dynamics on the basis of constitutive equations that are embedded into the solution scheme. As a consequence, individual simulations often require tens to hundreds of hours to complete on high-performance computing clusters. Moreover, laboratory experiments reveal that parametric functions for capillary pressure and relative permeability exhibit substantial variability, even within the same rock type. This combination of computational expense and wide-ranging parametric variability means that there remains substantial uncertainty in the behavior of multi-phase CO 2 -water systems, particularly in the context of feedbacks between relative permeability and capillary pressure. To bridge this knowledge gap, here we develop a novel workflow that utilizes physics-based numerical simulation to train an artificial neural network (ANN) emulator for interrogating the multivariate parameter space that governs both capillary pressure and relative permeability. With this approach, the ANN is trained to emulate both fluid pressure distribution and CO 2 saturation, which are then interrogated quantitatively to generate parametric response surface mappings with high-fidelity resolution. Results from this study initially show that capillary entry pressure is the dominant control on both CO 2 plume geometry and fluid pressure propagation when considering the combined effects of capillary pressure and relative permeability, particularly when phase interference is low and residual CO 2 saturation is high. Moreover, the ANN emulator provides tremendous computational speed-up by computing 2691 individual simulations in several minutes; whereas, the same simulation ensemble would have required ~3 years of simulation time using only physics-based simulation methods (25,000 times speed up).

58 GEOSCIENCES↗
DOE OSTI2022

How long can luminous blue variables sleep? A long-term photometric variability and spectral study of the Galactic candidate luminous blue variable MN 112

ABSTRACT Luminous blue variables (LBVs) are massive stars that show strong spectral and photometric variability. The questions of what evolutionary stages they represent and what exactly drives their instability are still open, and thus it is important to understand whether LBVs without significant ongoing activity exist, and for how long such dormant LBVs may ‘sleep’. In this paper we investigate the long-term variability properties of the LBV candidate MN 112, by combining its optical and infrared spectral data covering 12 years with photometric data covering nearly a century, as acquired from both modern time-domain sky surveys and historical photographic plates. We analyse the spectra, derive the physical properties of the star by modelling its atmosphere, and use a new distance estimate from Gaia data release 3 (DR3) to determine the position of MN 112 both inside the Galaxy and in the Hertzsprung–Russell diagram. The distance estimation has almost doubled in comparison with Gaia DR2. Because of this, MN 112 moved to upper part of the diagram, and according to our modelling it lies on an evolutionary track for a star with initial mass $M_*=70~\rm M_\odot$ near the Humphreys–Davidson limit. Given the absence of any significant variability, we conclude that the star is a dormant LBV that has now been inactive for at least a century.

Maryeva, O. V. (ORCID:0000000314424755)↗
DOE OSTI2020

COVID-19 biomarkers based on respiratory microbiome content

COVID-19 patient care management would greatly benefit from new tools that enable accurate assessment of disease severity and stage, potentially enabling a personalized medicine approach. Detection of the SARS-CoV-2 virus itself, or even quantitation of viral loads, is not sufficient for accurate assessment of disease state beyond diagnosis of infection [eg, doi:10.1093/cid/ciaa344]. Levels of usual suspect protein biomarkers associated with host response to infection [eg, C-reactive protein (CRP); cytokines like IL-6, TNF-alpha, and IL-10; complement proteins like C3a and C5a], and of individual blood cell types (eg, leukocytes, lymphocytes, and subsets thereof), show limited correlation with disease severity and stage, with high patient-to-patient and study-to-study variability [eg, doi:10.1093/cid/ciaa248]. High-dimensional panels of biomarkers should have greater predictive power and resilience to unavoidable sources of variability; however, their assembly from proteins and cell types is extremely difficult, due to technical limitations in analyte measurement, especially with regard to starting material requirements and detection sensitivity. Host response profiling through Next Generation Sequencing (NGS) of gene expression patterns (ie, RNA-Seq) is a promising approach, but at the time of this project there were only two publicly available datasets of relevance [doi:10.1093/cid/ciaa203, doi:10.1080/22221751.2020.1747363], and close inspection of them revealed that each had at least one major flaw that severely undermined its value in supporting robust analysis of host response to SARS-CoV- 2 infection. However, the first of these studies [doi:10.1093/cid/ciaa203] fortuitously collected NGS data not only from host cells, but also from bacteria present in bronchoalveolar lavage fluid (BALF) recovered from COVID-19 patients; and because the respiratory microbiome (in terms of bacterial species content) is far less complex than the human transcriptome, the NGS data collected were sufficient to provide coverage depth supporting robust analysis. Surprisingly, the authors of the study did not carry out a detailed analysis of these data and their potential for revealing important new information about COVID-19. Therefore, we carried out a meta-analysis of the dataset as a first step in evaluating the potential for profiling of respiratory microbiome dynamics as a means of accurately assessing COVID-19 disease state.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Separation of volatile organic contaminants from water using a direct-contact dehumidifier: An experimental study and modeling

A packed-bed, direct-contact dehumidifier (PB-DCD) has been developed to selectively condense water from a gaseous mixture of organic contaminants. In this process, hot air is humidified by mixing with wastewater vapor in a static mixer and is dehumidified by subcooled fresh water passing through the PB-DCD in a counter-current configuration. The goal of this study is to understand the relationship between various operating parameters and how they affect separation of isopropyl alcohol (IPA) from the gaseous mixture with the purpose of expanding the investigation to other contaminants in the future. The process has been successfully used to separate IPA from wastewater. Different parameters including the concentration of IPA in water, feed temperature, air-to-vapor ratio, and cooling-water-to-vapor mass ratio, as well as residence time were examined to determine their influence on contaminant separation and clean water recovery rate. The Buckingham Pi theorem was applied to reduce the number of studying variables by generating non-dimensional groups. Experiments were performed to determine the relationship between the non-dimensional parameters and model mass transfer in the system. Mass transfer coefficients for multicomponent gaseous mixture condensation in a packed-bed direct contact condenser column are calculated and a modified correlation of mass transfer is developed. The parameters of the mass transfer model are obtained from operating conditions of the PB-DCD, stream conditions and thermodynamic properties. A modified Sherwood correlation is developed to predict IPA separation from a gaseous mixture consisting of air, water, and IPA. The modified Sherwood correlation is applied to successfully predict the Sherwood number with a mean absolute error equal to 6.6 %. According to the experimental results, the maximum IPA separation achieved was 76.3 %, which corresponds to a water recovery rate of 58.7 %.

42 ENGINEERING↗
DOE OSTI2022

A Universal Power-law Prescription for Variability from Synthetic Images of Black Hole Accretion Flows

We present a framework for characterizing the spatiotemporal power spectrum of the variability expected from the horizon-scale emission structure around supermassive black holes, and we apply this framework to a library of general relativistic magnetohydrodynamic (GRMHD) simulations and associated general relativistic ray-traced images relevant for Event Horizon Telescope (EHT) observations of Sgr A*. We find that the variability power spectrum is generically a red-noise process in both the temporal and spatial dimensions, with the peak in power occurring on the longest timescales and largest spatial scales. When both the time-averaged source structure and the spatially integrated light-curve variability are removed, the residual power spectrum exhibits a universal broken power-law behavior. On small spatial frequencies, the residual power spectrum rises as the square of the spatial frequency and is proportional to the variance in the centroid of emission. Beyond some peak in variability power, the residual power spectrum falls as that of the time-averaged source structure, which is similar across simulations; this behavior can be naturally explained if the variability arises from a multiplicative random field that has a steeper high-frequency power-law index than that of the time-averaged source structure. We briefly explore the ability of power spectral variability studies to constrain physical parameters relevant for the GRMHD simulations, which can be scaled to provide predictions for black holes in a range of systems in the optically thin regime. We present specific expectations for the behavior of the M87* and Sgr A* accretion flows as observed by the EHT.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Progressing Analysis of Variable Electric Rates (PAVER) Study

The Progressing Analysis of Variable Electric Rates (PAVER) study analyzed the impact of a range of time-varying electric rates on the performance of a regional electric grid and the resulting costs for participating and non-participating customers. This analysis leveraged and extended the work of PNNL’s Distribution System Operator with Transactive (DSO+T) study. Five different rate designs were included: a flat volumetric energy charge, a typical Time of Use (TOU) rate, a dynamic energy (DE) rate (based on wholesale locational marginal prices), a dynamic energy and capacity (DE+C) rate, and, finally, a Block and Swing (B&S) rate that billed customers based on their average load profile at constant pricing, but used the DE+C dynamic price for load deviations from their average profile. These rates were analyzed in a large-scale co-simulation of an entire regional grid with a customer population representative of the current state. A large fraction (80%) of residential and commercial customers were assumed to participate in these time-varying rates with automatically controlled HVAC, water heaters, electric vehicles, and batteries. This study assumed no industrial sector participation. The DE and DE+C rates saw system peak loads reduced by 6-7%, while the large participation in the TOU rate case saw a significant rebound effect and a resulting peak load increase of >5%. The impacts to the annual and peak system demand impacted system wholesale prices and the overall grid operating costs. This cost structure determined the revenue needed to be collected from customers by each rate design. Participating customers on the DE and DE+C rates (located in one of the modeled DSOs) saw reductions in average annual electricity bills of 11-17% with average increases in monthly bill variation of no more than 13%. At such high participation levels, TOU customers saw 10% higher average annual bills (due to system-wide rebound effects) and average increased monthly bill variation of 16%. Residential owners of large flexible loads (such as electric vehicles) saw larger bill savings (17-20%) when on a fully dynamic rate. The presence of on-site generation (such as rooftop solar) did not appear to appreciably change customer outcomes. Customers on the Block and Swing rate did see 6% lower monthly bill variation (as intended) than the flat rate case, but at the expense of appreciable bill savings, which were only 3%, comparable to the savings seen by non-participants. Given this finding we recommend that additional research be conducted into how best various bill protection mechanisms can balance minimizing customer bill variation with providing financial incentives commensurate with the flexibility customers provide. We also recommend that customer outcomes be explored across a range of regions using current actual customer and system cost data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Identifying Periodic Variable Stars and Eclipsing Binary Systems with Long-term Las Cumbres Observatory Photometric Monitoring of ZTF J0139+5245

We present the results of our search for variable stars using the long-term Las Cumbres Observatory (LCO) monitoring of white dwarf ZTF J0139+5245 with the two 1.0 m telescope nodes located at McDonald Observatory using the Sinistro imaging instrument. In this search, we find 38 variable sources, of which 27 are newly discovered or newly classified (71%) based on comparisons with previously published catalogs, thereby increasing the number of detections in the field of view under consideration by a factor of ≈2.5. We find that the improved photometric precision per exposure due to longer exposure time for LCO images combined with the greater time sampling of LCO photometry enables us to increase the total number of detections in this field of view. Each LCO image covers a field of view of 26' × 26' and observes a region close to the Galactic plane (b = -9.°4) abundant in stars with an average stellar density of ≈8 arcmin{sup -2}. We perform aperture photometry and Fourier analysis on over 2000 stars across 1560 LCO images spanning 537 days to find 28 candidate BY Draconis variables, three candidate eclipsing binaries of type EA, and seven candidate eclipsing binaries of type EW. In assigning preliminary classifications to our detections, we demonstrate the applicability of the Gaia color–magnitude diagram as a powerful classification tool for variable-star studies.

47 OTHER INSTRUMENTATION↗