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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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582 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The chemical nature of the young 120-Myr-old nearby Pisces–Eridanus stellar stream flowing through the Galactic disc

Recently, a new cylindrical-shaped stream of stars up to 700 pc long was discovered hiding in the Galactic disc using kinematic data enabled by the Gaia mission. This stream of stars, dubbed Pisces–Eridanus (Psc–Eri), was initially thought to be as old as 1 Gyr, yet its stars shared a rotation period distribution consistent with a population that was 120 Myr old. Here, we explore the detailed chemical nature of this stellar stream. We carried out high-resolution spectroscopic follow-up of 42 Psc–Eri stars using McDonald Observatory and combined these data with information for 40 members observed with the low-resolution LAMOST spectroscopic survey. Together, these data enabled us to measure the abundance distribution of light/odd-Z (Li, Na, Al, Sc, V), α (Mg, Si, Ca, Ti), Fe-peak (Cr, Mn, Fe, Co, Ni, Zn), and neutron capture (Sr, Y, Zr, Ba, La, Nd, Eu) elements along the Psc–Eri stream. We find that the stream is (1) near-solar metallicity with [Fe/H] = –0.03 dex and (2) has a metallicity spread of 0.07 dex (or 0.04 dex when outliers are excluded). We also find that (3) the abundance of Li indicates that Psc–Eri is ~120 Myr old, consistent with its gyrochronology age. Additionally, Psc–Eri has (4) [X/Fe] abundance spreads that are just larger than the typical uncertainty in most elements, (5) it is a cylindrical-like system whose outer edges rotate about the centre, and (6) no significant abundance gradients along its major axis except a potentially weak gradient in [Si/Fe]. These results show that Psc–Eri is a uniquely close young chemically interesting laboratory for testing our understanding of star and planet formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

QA/QC-ed Groundwater Level Time Series in PLM-1 and PLM-6 Monitoring Wells, East River, Colorado (2016-2022)

This data set contains QA/QC-ed (Quality Assurance and Quality Control) water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location at the East River Watershed, Colorado, USA. These wells are used to monitor subsurface water and carbon inventories and fluxes, and to determine the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry (see related references) can be used to estimate rates of solute export from the hillslope to the floodplain and river. QA/QC analysis of measured groundwater levels in monitoring wells PLM-1 and PLM-6 included identification and flagging of duplicated values of timestamps, gap filling of missing timestamps and water levels, removal of abnormal/bad and outliers of measured water levels. The QA/QC analysis also tested the application of different QA/QC methods and the development of regular (5-minute, 1-hour, and 1-day) time series datasets, which can serve as a benchmark for testing other QA/QC techniques, and will be applicable for ecohydrological modeling. The package includes a Readme file, one R code file used to perform QA/QC, a series of 8 data csv files (six QA/QC-ed regular time series datasets of varying intervals (5-min, 1-hr, 1-day) and two files with QA/QC flagging of original data), and three files for the reporting format adoption of this dataset (InstallationMethods, file level metadata (flmd), and data dictionary (dd) files).QA/QC-ed data herein were derived from the original/raw data publication available at Williams et al., 2020 (DOI: 10.15485/1818367). For more information about running R code file (10.15485_1866836_QAQC_PLM1_PLM6.R) to reproduce QA/QC output files, see README (QAQC_PLM_readme.docx). This dataset replaces the previously published raw data time series, and is the final groundwater data product for the PLM wells in the East River. Complete metadata information on the PLM1 and PLM6 wells are available in a related dataset on ESS-DIVE: Varadharajan C, et al (2022). https://doi.org/10.15485/1660962. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales. 2022/09/09 Update: Converted data files using ESS-DIVE’s Hydrological Monitoring Reporting Format. With the adoption of this reporting format, the addition of three new files (v1_20220909_flmd.csv, V1_20220909_dd.csv, and InstallationMethods.csv) were added. The file-level metadata file (v1_20220909_flmd.csv) contains information specific to the files contained within the dataset. The data dictionary file (v1_20220909_dd.csv) contains definitions of column headers and other terms across the dataset. The installation methods file (InstallationMethods.csv) contains a description of methods associated with installation and deployment at PLM1 and PLM6 wells. Additionally, eight data files were re-formatted to follow the reporting format guidance (er_plm1_waterlevel_2016-2020.csv, er_plm1_waterlevel_1-hour_2016-2020.csv, er_plm1_waterlevel_daily_2016-2020.csv, QA_PLM1_Flagging.csv, er_plm6_waterlevel_2016-2020.csv, er_plm6_waterlevel_1-hour_2016-2020.csv, er_plm6_waterlevel_daily_2016-2020.csv, QA_PLM6_Flagging.csv). The major changes to the data files include the addition of header_rows above the data containing metadata about the particular well, units, and sensor description. 2023/01/18 Update: Dataset updated to include additional QA/QC-ed water level data up until 2022-10-12 for ER-PLM1 and 2022-10-13 for ER-PLM6. Reporting format specific files (v2_20230118_flmd.csv, v2_20230118_dd.csv, v2_20230118_InstallationMethods.csv) were updated to reflect the additional data. R code file (QAQC_PLM1_PLM6.R) was added to replace the previously uploaded HTML files to enable execution of the associated code. R code file (QAQC_PLM1_PLM6.R) and ReadMe file (QAQC_PLM_readme.docx) were revised to clarify where original data was retrieved from and to remove local file paths.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Observation of weakly damped modes using high resolution measurement of turbulence in a dipole confined plasma

When plasma is confined by a levitated superconducting current ring, the turbulent radial particle flux changes the direction depending upon the gradient of the particle number within tubes of equal magnetic flux [Garnier et al., Phys. Plasmas 24, 012506 (2017)]. When the density profile is highly peaked, the particle flux is outward. When the density profile is less peaked, turbulence drives an inward “particle pinch.” This change in the direction of particle flux coincides with a reversal of the mean toroidal propagation direction of turbulent fluctuations. Previously, only the mean wavenumber of the fluctuations was reported. The mean wavenumber was computed from the ensemble correlation between two probes. Here, the full frequency-wavenumber power spectrum of the saturated turbulence is calculated by applying Capon’s “maximum likelihood method” to floating potential measurements from an array of probes. The power spectrum shows that the highest intensity modes are due to unstable entropy modes, and the less intense modes coincide with weakly damped convective cells, which rotate toroidally in the direction opposite to the unstable modes. Because the weakly damped modes make up a significant fraction of the fluctuating power, these measurements imply that saturated turbulence in a dipole-confined plasma involves the excitation of weakly damped rotating convective cells.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Tuning Solvation Dynamics of Electrolytes at Their Eutectic Point Through Halide Identity

Deep eutectic solvents (DESs) are regarded as highly promising solvent systems for redox flow batteries. DESs, composed of choline halides (ChX, X = F − , Cl − , Br − , I − ) and ethylene glycol (EG), exhibit distinct physicochemical properties at their eutectic points, including halide-dependent phase behavior, viscosity, polarity, conductivity, and solvation dynamics. In this study, we investigate the effects of the halide identity on the solvation properties of ChX:EG mixtures at varying mol % of ChX salt content. The solvatochromic polarity based on ET(30) measurements indicates higher polarity for larger halides (I − > Br − ) than for smaller halides (Cl − > F − ), which exhibit larger compensating solvation shells. The ionic conductivity follows the trend of the solvent fluidity (the inverse of the viscosity), namely ChCl > ChBr > ChI > ChF, influenced by the ion mobility and solvodynamic radii. Measurements of the liquidus temperatures (T L ) reveal that the system with ChCl exhibits the deepest eutectic point (at ~20 mol % ChCl), while ChBr and ChI have shallower minima at ~10 mol % ChBr and ~3 mol % ChI, respectively. ChF does not display a eutectic transition but instead appears to readily supercool at salt concentrations above 30 mol % ChF. Consistent with the phase transition measurements, femtosecond transient absorption spectroscopy shows that in the ChCl system, the solvation dynamics become faster with an increasing salt concentration up to ~16.67 mol %, after which the dynamics slow down with further increases in the salt content. The ChF-based system exhibits similar behavior, though with slower dynamics. In contrast, the solvation dynamics of the systems containing ChBr and ChI monotonously slow down with an increasing salt concentration, in agreement with the phase transition measurements, which show that the eutectic points occur at low salt concentrations. These measurements suggest that the solvent composition and, in particular, the identity of the halide anion play a significant role in the solvation behavior of these ethylene-glycol-based DESs, offering a foundation for tuning the DES properties for specific applications.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 1. Evaluating Above- and Below-ground Controls of Flow Persistence in a Forested Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in a forested catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, ground penetrating radar (GPR), continuous self-potential (SP) monitoring, electromagnetic (EM) imaging, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Contains two subfolders: Synthetic and Field_Application subfolder. Synthetic subfolder contains the ATS XML input script (can be opened using any code editor) for the four synthetic hydrological cases tested (Connected and gaining, Connected and losing, Disconnected and losing, and dry stream). It also includes other experimental cases to test the influence of precipitation and concentration gradient. For each synthetic case, the flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.mph can be opened with the commercial software COMSOL and requires a license) is executed using the ATS output data to simulate the potential field. It also includes the Synthetic_model_plot.ipynb (can be opened using any code editor) to visualize the SP result and generate manuscript figures. The data subfolder contains mesh files to run both the ATS (.exo and .stl files can be viewed using Paraview; .h5 files can be opened using HDFView software and h5py Python package) and COMSOL models. Field_Application subfolder contains two subfolders: ES_MDA_inversion and Final_Model. ES_MDA_inversion contains the Python script (.py can be opened using any code editor) and SP observation data used to run the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) inversion sequence to get the optimal model parameters. The Final_model subfolder contains the ATS XML input scripts, data files, output data for the two SP sites. The same workflow steps outlined for the Synthetic subfolder apply here. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) EM Contains the CSV file of the EM data from the DUALEM-42, including spatial coordinates (x, y, z), apparent conductivity, and in-phase measurements at 2 m coil separations for horizontal coplanar (HCP) and perpendicular (PRP) geometries. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion (.resipy can be opened with the open-source ResIPy software). 6) GPR Includes GPR field datasets collected at 100 MHz and 250 MHz antenna frequencies, along with the processing/interpretation project file (GPR_process.gpz can be viewed using EKKO_Project 6, a commercial software by Sensors & Software that requires a license). 7) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 8) SP Contains the SP data collected in field at the two SP sites (one in the perennial reach and the other in the intermittent reach), provided as DAT files. 9) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). It also includes DTW.ipynb, a Jupyter notebook containing the code for the dynamic time warping (DTW) with sliding window to evaluate SP signal synchronicity.

ATS↗
NASA NTRSDate not supplied

Effect of Vacuum on Force Response of an Ultrasonic Penetrator

Introduction: The Apollo astronauts encountered higher than expected resistances when interacting with the lunar soil via the Apollo Lunar Surface Drill (ALSD) and the trenching tool. Reducing the force required to move tools or other mechanical components through regolith will impact many steps of the resource extraction process. Force reduction has been achieved in soil materials by imparting vibration to tooling interfaces such as a vibratory farming cultivator, a percussive scoop, and ultrasonically resonant penetrators. Vibration-assisted tools in granular media reduce interaction forces by fluidizing a volume around the tool, allowing the tool to progress through a dynamic (fluid) medium instead of a static (solid) medium. This work seeks to quantify ultrasonic vibration’s effect on the force response of a penetrator in lunar soil simulant in vacuum sufficient to be within the molecular flow regime of any disturbed gases. Methods: A custom vacuum chamber setup, CUBEvac, was designed and built to facilitate penetration testing in a high vacuum environment, for comparison to penetration behavior in ambient terrestrial environment. A two-stage pumping system (Agilent Triscroll 600 roughing pump, Agilent VHS-6 oil diffusion pump) reached chamber pressures of about 5x10-6 Torr with regolith simulant in place. Figure 1 is a schematic of the heart of the assembly (note the penetration drive mechanisms above the chamber feedthrough and the regolith simulant sample in the bottom are not shown). The penetration actuation stack was comprised of a stepper motor driving a lead screw to move the ultra-sonic probe vertically inside the chamber. Motion was coordinated with an Arduino Uno. GRC-3 lunar simulant was used for this set of experiments. Samples were prepared in a four-liter stain-less steel, cylindrical pot with an internal diameter of approximately 15.56 cm (6.125 in) and a depth of 19.37 cm (7 5/8 in) for testing. The soil was baked out prior to compaction preparation as a measure to reduce soil moisture which interfered with pump down capacity. The soil was not baked again if it was removed from the vacuum chamber, prepped, and immediately returned to the vacuum chamber for pump down. The soil was compacted using a 60 Hz vibration table with a surcharge of 34 kg place on top of the soil in the container. Prepared soil samples weighed approximately 6.5 kg (bulk density 1.895-1.934 g/cm3). Two probe end effectors were tested: A cone penetrometer (static only) with a nominal diameter of 12.7 mm (0.5 in) and a nominal height of 28.6 mm (1.125 in); and a vibrating cylindrical probe measuring 12.7 mm in diameter and 50.8 mm in effective length from the tip (Figure 2). The cylindrical probe vibrated resonantly at 20 kHz with an amplitude 23 μm. The cone penetration tests were conducted to assess potential soil behavior differences in vacuum. The cylinder probe tests were conducted as the primary subject of this investigation to assess force response in vacuum. For each test, a regolith simulant sample was load-ed and compacted in the chamber, which was then evacuated for roughly 18 hours to reach the lowest possible pressure (approximately 5x10-6 Torr for most tests). The probe was then moved to about 10 mm above the soil surface before being pushed to a depth of 50 mm for the cylinder probe tests and to a depth of 100 mm for the cone penetrometer tests, both at a speed of 2 mm/s. The simulant samples were prepared the same for all tests. Ideally, they would respond consistently to probe penetration under ambient and vacuum conditions. This was evaluated by measuring the resistance of representative prepared simulant beds with a standard cone penetrometer in both environments. Results and Discussion: The resistance of the simulant samples in the vacuum tests was consistently lower than in the ambient tests as determined by the cone penetration tests. Thus, the ambient and vacuum results cannot be compared directly; work is underway to de-confound and better correlate the data. Still, figures 3-6 show that probe penetration forces are lower overall in the vacuum environment. In both environments, resonant vibration of the probe provides two useful effects: It reduces the probe penetration force and smooths the force-depth curve, significantly reducing local maxima. These effects have implications for various potential applications, such as astronaut hand-tools, where benefits (reducing astronaut effort) outweigh the cost of the additional energy re-quired to generate vibration. These results demonstrate that resonantly vibrating tools can meaningfully reduce the penetration force required for excavation, probing, and drilling tools in simulated lunar regolith deposits under vacuum levels approaching those that will be experience on the Moon’s surface. Lunar-gravity, ambient environment tests are scheduled soon. The effects of realistic temperatures and temperature gradients and deeper vacuum remain to be tested.

E Rezich↗