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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Numerical relativity estimates of the remnant recoil velocity in binary neutron star mergers

We present, for the first time, recoil velocity estimates for binary neutron star mergers using data from numerical relativity simulations. We find that binary neutron star merger remnants can have recoil velocity of the order of a few tens of kilometers per second and as high as 150 kilometers per second in our dataset. These recoils are attained due to equivalent contributions from the anisotropic gravitational wave emission as well as the asymmetric ejection of dynamical matter during the merger. Here, we provide fits for net recoil velocity as well as its ejecta component as a function of the amount of ejected matter, which may be useful when constraints on the ejected matter are obtained through electromagnetic observations. We also estimate the mass and spin of the remnants and find them to be in the range [2.34,3.38]M ⊙ and [0.63, 0.82], respectively, for our dataset.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Bayesian inference of nuclear incompressibility from collective flow in mid-central Au+Au collisions at 400–1500 MeV/nucleon

The incompressibility K of symmetric nuclear matter (SNM) is determined through a Bayesian analysis of collective flow data from Au + Au collisions at beam energies $E = 400 -1500$ MeV/nucleon. This analysis utilizes a Gaussian process (GP) emulator applied to the isospin-dependent quantum molecular dynamics (IQMD) model for heavy-ion collisions, both with and without incorporating the momentum dependence of the single-nucleon potentials. Specifically, at the 68% confidence level, using rapidity and transverse velocity dependence of proton elliptic flow data with and without consideration of the momentum dependence, the inferred incompressibility values are $K=188.9^{+2.9}_{-4.5}$ MeV and $256.1^{+8.2}_{-8.7}$ MeV at $E = 400$ MeV/nucleon, respectively. When the transverse momentum dependence of proton-like directed flow data is included, the inferred incompressibility values become $K=222.3^{+9.0}_{-9.9}$ MeV and $K=285.5^{+6.7}_{-7.3}$ MeV, respectively. Furthermore, we found that the value of K derived from observables of proton elliptic flow increases with beam energy. Finally, this indicates that the equation of state (EoS) of nuclear matter hardens at higher densities and temperatures in reactions with higher beam energies.

Bayesian inference↗
DOE OSTI2025

Detection of multi-modal Doppler spectra – Part 1: Establishing characteristic signals in radar moment data

Vertically pointing millimeter-wavelength radars provide a wealth of information about cloud and precipitation particle properties. Doppler spectral data can inform on how particles of varying vertical velocities contribute to the total backscattered power observed. It is more computationally cost effective to process moment data instead of spectra data, but doing so leaves valuable information on the cutting room floor. To confidently identify a multi-modal spectra event, in which two or more modes are present within a layer, Doppler spectral data are essential. This means long-term identification of layers featuring multi-modal spectra can be cost prohibitive. To address this, we explore three multi-modal spectra cases from winter precipitation events to determine characteristic signatures of these layers in the moment data averaged over short time periods (∼ 145 s) and explore how these layers differ from the rest of the vertical profiles. We find that the mean spectrum width and the standard deviation of mean Doppler velocity can be used to determine whether or not a layer is multi-modal. In particular, multi-modal layers in mixed-phase and ice clouds feature larger mean spectrum width (exceeding 0.17 m s −1 ) and smaller standard deviation of the mean Doppler velocity (below 0.1 m s −1 ). In Part 1 of this study, the identification criteria and methods are described. In Part 2 (Wugofski and Kumjian, 2025), we perform a verification of the method for three years of vertically pointing radar data, and explore the meteorological conditions associated with identified multi-modal spectral events.

Wugofski, Sarah [Pennsylvania State Univ., Univers↗
DOE OSTI2021

Unveiling the star formation history of the Upper Scorpius association through its kinematics

ABSTRACT Stellar associations can be discerned as overdensities of sources not only in the physical space but also in the velocity space. The common motion of their members, gradually eroded by the galactic tidal field, is partially reminiscent of the initial kinematic structure. Using recent data from Gaia EDR3, combined with radial velocities from GALAH and APOGEE, we traced back the present positions of stars belonging to Upper Scorpius (USCO), a subgroup of Scorpius–Centaurus, the nearest OB association. About one half of the subgroup (the ‘clustered’ population) appears composed of many smaller entities, which were in a more compact configuration in the past. The presence of a kinematic duality is reflected into an age spread between this younger clustered population and an older diffuse population, in turn confirmed by a different fraction fD of disc-bearing stars (fD = 0.24 ± 0.02 versus fD = 0.10 ± 0.01). Star formation in USCO appears to have lasted more than 10 Myr and proceeded in small groups that, after a few Myr, dissolve in the field of the older population but retain for some time memory of their initial structure. The difference of ages inferred through isochrones and kinematics, in this regard, could provide a powerful tool to quantify the time-scale of gas removal.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

BASS. XXVI. DR2 Host Galaxy Stellar Velocity Dispersions

We present new central stellar velocity dispersions for 484 Sy 1.9 and Sy 2 from the second data release of the Swift/BAT AGN Spectroscopic Survey (BASS DR2). This constitutes the largest study of velocity dispersion measurements in X-ray-selected obscured active galactic nuclei (AGN) with 956 independent measurements of the Ca II H and K λ3969, 3934 and Mg I λ5175 region (3880–5550 Å) and the calcium triplet region (8350–8730 Å) from 642 spectra mainly from VLT/X-Shooter or Palomar/DoubleSpec. Our sample spans velocity dispersions of 40–360 km s 1 , corresponding to 4–5 orders of magnitude in black hole mass (M BH = 10 5.5-9.6 M ⊙ ), bolometric luminosity (L bol ~ 10 42–46 erg s -1 ), and Eddington ratio (L/L Edd ~ 10 -5 to 2). For 281 AGN, our data and analysis provide the first published central velocity dispersions, including six AGN with low-mass black holes (M BH = 10 5.5-6.5 M ⊙ ), discovered thanks to high spectral resolution observations (σ inst ~ 25 km s -1 ). The survey represents a significant advance with a nearly complete census of velocity dispersions of hard X-ray–selected obscured AGN with measurements for 99% of nearby AGN (z < 0.1) outside the Galactic plane (|b| > 10°). The BASS AGN have much higher velocity dispersions than the more numerous optically selected narrow-line AGN (i.e., ~150 versus ~100 km s -1 ) but are not biased toward the highest velocity dispersions of massive ellipticals (i.e., >250 km s -1 ). Despite sufficient spectral resolution to resolve the velocity dispersions associated with the bulges of small black holes (~10 4–5 M ⊙ ), we do not find a significant population of super-Eddington AGN. Using estimates of the black hole sphere of influence from velocity dispersion, direct stellar and gas black hole mass measurements could be obtained with existing facilities for more than ~100 BASS AGN.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Relating flow resistance to equivalent roughness

Describing flow resistance using the physical properties of an underlying surface is a recalcitrant problem in overland flow models. If discharge measurements are available, an equivalent roughness (e.g., Manning’s n) can be calibrated to represent the effects of surface properties within the domain with a single numerical value. Alternatively, the flow resistance can be estimated from discharge and velocity measured at a point, typically a runoff plot outlet. However, such experimental estimates are often inconsistent with the equivalent roughness determined from calibration to discharge, even if both derive from the same dataset. For example, if Manning’s equation is used to parameterize flow resistance, the Manning’s n obtained by calibrating a model to discharge differs from the value of n calculated from measured flow and velocity at the hillslope outlet. Here, this discrepancy is resolved by deriving a correction factor relating experimentally-determined flow resistance to the equivalent roughness. The derived correction factor is tested for four commonly-used resistance formulations using 129 rainfall simulator experiments. The correction factor is necessary to reproduce measured velocities, and yields minor improvements in discharge prediction. Plain Language Summary: Accurate runoff prediction is needed for land and water management in dryland regions, where sporadic and limited rainfall necessitate efficient water use and drought mitigation strategies. The skill of runoff models is known to be hindered by out ability to estimate flow resistance, which is the quantity that describes how energy is lost from flowing water to the underlying surface. Typically, models represent flow resistance with an equivalent roughness, e.g., Manning’s n, that is adjusted until the model can reproduce available discharge observations at watershed scale. However, the flow resistance measured in plot-scale experiments (1–10 m) often exceeds equivalent roughness coefficients by a factor of 10. This means that the direct use of plot-scale experimental data to parameterize runoff models could cause errors in discharge and runoff velocity predictions. Here, we resolve these differences by deriving an analytic correction factor that relates flow resistance to the equivalent roughness required for models to reproduce experimental velocity and discharge data. This correction factor is tested using rainfall simulator data from 129 experiments performed in the US Southwest covering a wide range of precipitation intensities, soil textures and vegetation types. Use of the correction factor substantially improves model prediction of flow velocity, which is needed for reproducing the timing of flood events and the estimation of erosion.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DESI Early Data Release Milky Way Survey value-added catalogue

We present the stellar value-added catalogue based on the Dark Energy Spectroscopic Instrument (DESI) Early Data Release. The catalogue contains radial velocity and stellar parameter measurements for $\simeq$ 400 000 unique stars observed during commissioning and survey validation by DESI. These observations were made under conditions similar to the Milky Way Survey (MWS) currently carried out by DESI but also include multiple specially targeted fields, such as those containing well-studied dwarf galaxies and stellar streams. The majority of observed stars have $16\lt r\lt 20$ with a median signal-to-noise ratio in the spectra of $\sim$ 20. In the paper, we describe the structure of the catalogue, give an overview of different target classes observed, as well as provide recipes for selecting clean stellar samples. We validate the catalogue using external high-resolution measurements and show that radial velocities, surface gravities, and iron abundances determined by DESI are accurate to 1 km s −1 , 0.3 dex, and $\sim$ 0.15 dex respectively. We also demonstrate possible uses of the catalogue for chemo-dynamical studies of the Milky Way stellar halo and Draco dwarf spheroidal. The value-added catalogue described in this paper is the very first DESI MWS catalogue. The next DESI data release, expected in less than a year, will add the data from the first year of DESI survey operations and will contain approximately 4 million stars, along with significant processing improvements.

Galaxy: general↗
DOE OSTI2020

Determination of acoustic nonlinearity parameters using thermal modulation of ultrasonic waves

This study presents a test method and its theoretical framework to determine the acoustic nonlinearity parameters (α, β, δ) of material using thermal modulation of ultrasonic waves. Temperature change-induced thermal strain excites the nonlinear response of the material and modulates the ultrasonic wave propagating in it. Experimental results showed a strong correlation between the relative wave velocity change and the temperature change. With a quadratic polynomial model, the acoustic nonlinearity parameters were obtained from the polynomial coefficients by curve fitting the experimental data. Their effects on thermal-induced velocity change were discussed. The parameters α, β, and δ govern the hysteretic gap, average slope, and curvature of the correlation curve, respectively. The proposed theory was validated on aluminum, steel, intact and damaged concrete samples. The obtained nonlinear parameters show reasonable agreement with values reported in the literature. Compared to other nonlinear acoustic methods using vibration or acoustic excitation, the thermal modulation method generates more uniform, slow changing, and larger strain field in the test sample. Employing the thermal effect as the driving force for nonlinearity instead of an undesired influencing factor, this method can measure the absolute values of α, β, and δ with good accuracy using a simple ultrasonic test setup.

Physics↗
DOE OSTI2020

Pass-efficient methods for compression of high-dimensional turbulent flow data

The future of high-performance computing, specifically on future Exascale computers, will presumably see memory capacity and bandwidth fail to keep pace with data generated, for instance, from massively parallel partial differential equation (PDE) systems. Current strategies proposed to address this bottleneck entail the omission of large fractions of data, as well as the incorporation of in situ compression algorithms to avoid overuse of memory. To ensure that post-processing operations are successful, this must be done in a way that a sufficiently accurate representation of the solution is stored. Moreover, in situations where the input/output system becomes a bottleneck in analysis, visualization, etc., or the execution of the PDE solver is expensive, the number of passes made over the data must be minimized. In the interest of addressing this problem, this work focuses on the utility of pass-efficient, parallelizable, low-rank, matrix decomposition methods in compressing high-dimensional simulation data from turbulent flows. Additionally, a particular emphasis is placed on using coarse representation of the data – compatible with the PDE discretization grid – to accelerate the construction of the low-rank factorization. This includes the presentation of a novel single-pass matrix decomposition algorithm for computing the so-called interpolative decomposition. The methods are described extensively and numerical experiments on two turbulent channel flow data are performed. In the first (unladen) channel flow case, compression factors exceeding 400 are achieved while maintaining accuracy with respect to first- and second-order flow statistics. In the particle-laden case, compression factors of 100 are achieved and the compressed data is used to recover particle velocities. These results show that these compression methods can enable efficient computation of various quantities of interest in both the carrier and disperse phases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Seismic Monitoring at the Farnsworth CO2-EOR Field Using Time-Lapse Elastic-Waveform Inversion of 3D-3C VSP Data

During the Development Phase of the U.S. Southwest Regional Partnership on Carbon Sequestration, supercritical CO2 was continuously injected into the deep oil-bearing Morrow B formation of the Farnsworth Unit in Texas for Enhanced Oil Recovery (EOR). The project injected approximately 94 kilotons of CO2 to study geologic carbon storage during CO2-EOR. A three-dimensional (3D) surface seismic dataset was acquired in 2013 to characterize the subsurface structures of the Farnsworth site. Following this data acquisition, the baseline and three time-lapse three-dimensional three-component (3D-3C) vertical seismic profiling (VSP) data were acquired at a narrower surface area surrounding the CO2 injection and oil/gas production wells between 2014 and 2017 for monitoring CO2 injection and migration. With these VSP datasets, we inverted for subsurface velocity models to quantitatively monitor the CO2 plume within the Morrow B formation. We first built 1D initial P-wave (Vp) and S-wave (Vs) velocity models by upscaling the sonic logs. We improved the deep region of the Vp and Vs models by incorporating the deep part of a migration velocity model derived from the 3D surface seismic data. We improved the shallow region of 3D Vp and Vs models using 3D traveltime tomography of first arrivals of VSP downgoing waves. We further improved the 3D baseline velocity models using elastic-waveform inversion (EWI) of the 3D baseline VSP upgoing data. Our advanced EWI method employs alternative tomographic and conventional gradients and total-variation-based regularization to ensure the high-fidelity updates of the 3D baseline Vp and Vs models. We then sequentially applied our 3D EWI method to the three time-lapse datasets to invert for spatiotemporal changes of Vp and Vs in the reservoir. Our inversion results reveal the volumetric changes of the time-lapse Vp and Vs models and show the evolution of the CO2 plume from the CO2 injection well to the oil/gas production wells.

42 ENGINEERING↗
DOE OSTI2021

Assimilation of X-band Phased-Array Radar Data with EnKF for the Analysis and Warning Forecast of a Tornadic storm

The impact of assimilating China's operational X-band Phased-Array radar's (X-PAR) data on the analysis and warning forecast of the vortex structure and intensity of the June 8, 2018 Foshan, Guangdong province, tornadic storm was investigated for the first time using an Ensemble Kalman Filter (EnKF) data assimilation system. Both radar radial velocity (Vr) and reflectivity (Z) from two S-band operational radars and one X-PAR were assimilated. Deterministic forecasts were launched every 6 min from 05:42 UTC (20 min before the tornado touched down) to 06:00 UTC from the EnKF mean analysis field. Five experiments were conducted to examine the added capability of Z assimilation of the EnKF system, and to investigate the impact of assimilating X-PAR data on the analysis and prediction of the tornadic storm. Compared to the experiment without Z assimilation, the assimilation of Z reduced the analysis error and greatly reduced the forecast error of Z. Furthermore, the assimilation of X-PAR data greatly improved the vortex structure of the tornadic storm at low levels, and improved the intensity of the rear inflow of the tornadic storm, especially with a higher assimilation frequency. Compared to the experiments without X-PAR data assimilation, assimilating X-PAR data improved the predictability of tornadic storm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Machine-learning identification of the variability of mean velocity and turbulence intensity for wakes generated by onshore wind turbines: Cluster analysis of wind LiDAR measurements

Light detection and ranging (LiDAR) measurements of isolated wakes generated by wind turbines installed at an onshore wind farm are leveraged to characterize the variability of the wake mean velocity and turbulence intensity during typical operations, which encompass a breadth of atmospheric stability regimes and rotor thrust coefficients. The LiDAR measurements are clustered through the k-means algorithm, which enables identifying the most representative realizations of wind turbine wakes while avoiding the imposition of thresholds for the various wind and turbine parameters. Considering the large number of LiDAR samples collected to probe the wake velocity field, the dimensionality of the experimental dataset is reduced by projecting the LiDAR data on an intelligently truncated basis obtained with the proper orthogonal decomposition (POD). The coefficients of only five physics-informed POD modes are then injected in the k-means algorithm for clustering the LiDAR dataset. The analysis of the clustered LiDAR data and the associated supervisory control and data acquisition and meteorological data enables the study of the variability of the wake velocity deficit, wake extent, and wake-added turbulence intensity for different thrust coefficients of the turbine rotor and regimes of atmospheric stability. Furthermore, the cluster analysis of the LiDAR data allows for the identification of systematic off-design operations with a certain yaw misalignment of the turbine rotor with the mean wind direction.

17 WIND ENERGY↗
DOE OSTI2022

ORPC RivGen 2.0 at Igiugig, AK Operational Data 2019 and 2020

Information enclosed includes operational data from the ORPC RivGen 2.0 deployed at Igiugig, AK in 2019 and 2020. Flow velocities and device performance metrics are recorded along with a report detailing flow speed characterization where Igiugig river flow data is aggregated into a single flow velocity.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Investigating biological nitrogen fixation via single-cell transcriptomics

The extensive use of nitrogen fertilizers has detrimental environmental consequences, and it is essential for society to explore sustainable alternatives. One promising avenue is engineering root nodule symbiosis, a naturally occurring process in certain plant species within the nitrogen-fixing clade, into non-leguminous crops. Advancements in single-cell transcriptomics provide unprecedented opportunities to dissect the molecular mechanisms underlying root nodule symbiosis at the cellular level. This review summarizes key findings from single-cell studies in Medicago truncatula, Lotus japonicus, and Glycine max. We highlight how these studies address fundamental questions about the development of root nodule symbiosis, including the following findings: (i) single-cell transcriptomics has revealed a conserved transcriptional program in root hair and cortical cells during rhizobial infection, suggesting a common infection pathway across legume species; (ii) characterization of determinate and indeterminate nodules using single-cell technologies supports the compartmentalization of nitrogen fixation, assimilation, and transport into distinct cell populations; (iii) single-cell transcriptomics data have enabled the identification of novel root nodule symbiosis genes and provided new approaches for prioritizing candidate genes for functional characterization; and (iv) trajectory inference and RNA velocity analyses of single-cell transcriptomics data have allowed the reconstruction of cellular lineages and dynamic transcriptional states during root nodule symbiosis.

Lotus japonicus↗
DOE OSTI2021

The Youngest Planet to Have a Spin-Orbit Alignment Measurement AU Mic b

We report measurements of the sky-projected spin–orbit angle for AU Mic b, a Neptune-size planet orbiting a very young (∼20 Myr) nearby pre-main-sequence M-dwarf star, which also hosts a bright, edge-on, debris disk. The planet was recently discovered from preliminary analysis of radial-velocity observations and confirmed to be transiting its host star from photometric data from the NASA’s TESS mission. We obtained radial-velocity measurements of AU Mic over the course of two partially observable transits and one full transit of planet b from high-resolution spectroscopic observations made with the Minerva-Australis telescope array. Only a marginal detection of the Rossiter–McLaughlin effect signal was obtained from the radial velocities, in part due to AU Mic being an extremely active star and the lack of full transit coverage plus sufficient out-of-transit baseline. As such, a precise determination of the obliquity for AU Mic b is not possible in this study and we find a sky-projected spin–orbit angle of λ=47{sub −54}{sup +26°}. This result is consistent with both the planet’s orbit being aligned or highly misaligned with the spin axis of its host star. Our measurement independently agrees with, but is far less precise than observations carried out on other instruments around the same time that measure a low-obliquity orbit for the planet. AU Mic is the youngest exoplanetary system for which the projected spin–orbit angle has been measured, making it a key data point in the study of the formation and migration of exoplanets—particularly given that the system is also host to a bright debris disk.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Extending the Dynamic Range of Galaxy Outflow Scaling Relations: Massive Compact Galaxies with Extreme Outflows

We investigate galactic winds in the HizEA galaxies, a collection of 46 late-stage galaxy mergers at z = 0.4–0.8, with stellar masses of $\mathrm{log}({M}_{* }/{M}_{\odot })=10.4\mbox{--}11.5$ , star formation rates (SFRs) of 20–500 M ⊙ yr -1 , and ultra-compact (a few 100 pc) central star-forming regions. We measure their gas kinematics using the Mg II λλ 2796,2803 absorption lines in optical spectra from MMT, Magellan, and Keck. We find evidence of outflows in 90% of targets, with maximum outflow velocities of 550–3200 km s -1 . We combine these data with ten samples from the literature to construct scaling relations for outflow velocity versus SFR, star formation surface density (Σ SFR ), M * , and SFR/M * . The HizEA galaxies extend the dynamic range of the scaling relations by a factor of ~2–4 in outflow velocity and an order of magnitude in SFR and Σ SFR . The ensemble scaling relations exhibit strong correlations between outflow velocity, SFR, SFR/R, and Σ SFR , and weaker correlations with M * and SFR/M * . The HizEA galaxies are mild outliers on the SFR and M* scaling relations, but they connect smoothly with more typical star-forming galaxies on plots of outflow velocity versus SFR/R and Σ SFR . These results provide further evidence that the HizEA galaxies' exceptional outflow velocities are a consequence of their extreme star formation conditions rather than hidden black hole activity, and they strengthen previous claims that Σ SFR is one of the most important properties governing the velocities of galactic winds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

On detrending stream velocity time series for robust tidal flow turbulence characterization

We investigated the impact of detrending techniques on turbulence quantities from tidal stream flow data, focusing on the autocorrelation function, $ρ_{uu}$, and velocity spectrum, $Φ(f)$. Standard detrending methods, including high-pass frequency-based and polynomial-based techniques, are examined, alongside a proposed alternative method, the empirical mode decomposition (EMD). Our results highlight that intervals of flow acceleration and deceleration, typical in tidal and riverine flows, significantly affect the estimation of turbulence quantities using high-pass frequency filtering and polynomial detrending of varying orders. These methods can strongly influence $ρ_{uu}$ and $Φ(f)$, thereby affecting the accurate estimation of derived quantities. We examine two variations of detrending data using EMD; the first removes only the EMD residue, and the second removes both the residue and the largest scale intrinsic mode function (IMF). By comparing the detrended spectra with the modeled von Kármán spectra, we demonstrate that the second variation (i.e., removing the residue and the largest scale IMF) successfully removed the large-scale trend of the data while retaining the energy of other scales.

Detrend↗