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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Pions in hot dense matter and their astrophysical implications

Here we study the role of pions in hot dense matter encountered in astrophysics. We find that strong interactions enhance the number density of negatively charged pions and that this enhancement can be calculated reliably for a relevant range of density and temperature by using the virial expansion. We assess the influence of pions and muons on the equation of state (EOS) and weak-interaction rates in hot dense matter. We find that thermal pions increase the proton fraction and soften the EOS. We also find that charged current weak reactions involving pions and muons $\bar{ν}_ μ + μ^– → π$ and $ν_μ + π^– → μ^–$ make an important contribution to the opacity of muon neutrinos. This could influence the dynamics of core-collapse supernovae and neutron-star mergers. Finally, we note that pion-nucleon reactions can alter the evolution of the proton fraction when weak interactions are not in equilibrium.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Detectability of standing accretion shock instabilities activity in supernova neutrino signals

We introduce a novel methodology for establishing the presence of standing accretion shock instabilities (SASI) in the dynamics of a core collapse supernova from the observed neutrino event rate at water- or ice- based neutrino detectors. The methodology uses a likelihood ratio in the frequency domain as a test- statistics; it is also employed to assess the potential to estimate the frequency and the amplitude of the SASI modulations of the neutrino signal. The parameter estimation errors are consistent with the minimum possible errors as evaluated from the inverse of the Fisher information matrix, and close to the theoretical minimum for the SASI amplitude. Using results from a core-collapse simulation of a 15 solar-mass star by Kuroda et al. [Astrophys. J. 851, 62 (2017).] as a test bed for the method, we find that SASI can be identified with high confidence for a distance to the supernova of up to ~6 kpc for IceCube and up to ~3 kpc for a 0.4 Mt mass water Cherenkov detector. This methodology will aid the investigation of a future galactic supernova.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Data for "Soil carbon dynamics during drying vs. rewetting: Importance of antecedent moisture conditions"

This dataset contains data used for the paper "Soil carbon dynamics during drying vs. rewetting: importance of antecedent moisture conditions". The Related References field will be updated with a full citation when available.Soil moisture influences soil carbon dynamics, including microbial growth and respiration. The response of such ‘soil respiration’ to moisture changes is generally assumed to be linear and reversible, i.e. to depend only on the current moisture state. Current models thus do not account for antecedent soil moisture conditions when determining soil respiration or the available substrate pool. We conducted a laboratory incubation to determine how the antecedent conditions of drought and flood influenced soil organic matter (SOM) chemistry, bioavailability, and respiration. We sampled soils from an upland coastal forest, Beaver Creek, WA USA, and subjected them to drying and rewetting treatments. For the drying treatment, field moist soils were saturated and then dried to 75, 50, 35, and 5 % saturation. In the rewetting treatment, field moist soils were air-dried and then rewet to 35, 50, 75, and 100 % saturation. We measured respiration and water extractable organic carbon (WEOC) concentrations and used 1H-NMR and FT-ICR-MS to characterize the WEOC pool across the treatments. The drying vs. wetting treatment strongly influenced SOM bioavailability, as rewet soils (with antecedent drought) had greater WEOC concentrations and respiration fluxes compared to the drying soils (with antecedent flood). In addition, air-dry soils had the highest WEOC concentrations, and the NMR-resolved peaks showed a strong contribution of protein groups in these soils. Both NMR and FT-ICR-MS analyses indicated increased contribution of complex aromatic groups/molecules in the rewet soils, compared to the drying soils. We suggest that drying introduced organic matter into the WEOC pool via desorption of aromatic molecules and/or by microbial cell lysis, and this stimulated microbial mineralization rates. Our work indicates that even short-term shifts in antecedent moisture conditions can strongly influence soil C dynamics at the core scale. The predictive uncertainties in current soil models may be reduced by a more accurate representation of soil water and C persistence that includes a mechanistic and quantitative understanding of the impact of antecedent moisture conditions.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv and .txt format, which can be accessed and processed using MS Excel or R. NMR data are provided as raw output data (accessed in Bruker TopSpin or MestreNova) as well as the MestreNova-processed files. This archive can also be accessed on GitHub at https://github.com/kaizadp/hysteresis_and_soil_carbon (DOI: 10.5281/zenodo.4432885).

1H-NMR↗
DOE OSTI2022

Hydrogen solubility in FeSi alloy phases at high pressures and temperatures

Abstract Light elements alloying with metallic Fe can change the properties and therefore play a key role in the structure and dynamics of planetary cores. Hydrogen and silicon are possible light elements in the rocky planets’ cores. However, hydrogen storage in Fe-Si alloy systems remains unclear at high pressures and high temperatures because of experimental difficulties. Taking advantage of pulsed laser heating combined with high-energy synchrotron X-ray diffraction, we studied reactions between FeSi and H in laser-heated diamond-anvil cells (LHDACs) up to 61.9 GPa and 3500 K. We found that under H-saturated conditions the amount of H alloying with FeSi (0.3 and <0.1 wt% for the B20 and B2 structures, respectively) is much smaller than that in pure Fe metal (>1.8 wt%). Our experiments also suggest that H remains in the crystal structure of FeSi alloy when recovered to 1 bar. Further density functional theory (DFT) calculations indicate that the low-H solubility likely results from the highly distorted interstitial sites in the B20 and B2 structures, which are not favorable for H incorporation. The recovery of H in the B20 FeSi crystal structure at ambient conditions could open up possibilities to understand geochemical behaviors of H during core formation in future experiments. The low-H content in FeSi alloys suggests that if a planetary core is Si-rich, Si can limit the ingassing of H into the Fe-rich core.

Geochemistry & Geophysics↗
DOE OSTI2025

Hybrid learning techniques for scientific data reduction with performance guarantees

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Final report- UFL - RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

FPGA Acceleration of GCN in Light of the Symmetry of Graph Adjacency Matrix

Graph Convolutional Neural Networks (GCNs) are widely used to process large-scale graph data. Different from deep neural networks (DNNs), GCNs are sparse, irregular, and unstructured, posing unique challenges to hardware acceleration with regular processing elements (PEs). In particular, the adjacency matrix of a GCN is extremely sparse, leading to frequent but irregular memory access, low spatial/temporal data locality and poor data reuse. Furthermore, a realistic graph usually consists of unstructured data (e.g., unbalanced distributions), creating significantly different processing times and imbalanced workload for each node in GCN acceleration. To overcome these challenges, we propose an end-to-end hardware-software co-design to accelerate GCNs on resource-constrained FPGAs with the features including: (1) A custom dataflow that leverages symmetry along the diagonal of the adjacency matrix to accelerate feature aggregation for undirected graphs. We utilize either the upper or the lower triangular matrix of the adjacency matrix to perform aggregation in GCN to improve data reuse. (2) Unified compute cores for both aggregation and transform phases, with full support to the symmetry-based dataflow. These cores can be dynamically reconfigured to the systolic mode for transformation or as individual accumulators for aggregation in GCN processing. (3) Preprocessing of the graph in software to rearrange the edges and features to match the custom dataflow. This step improves the regularity in memory access and data reuse in the aggregation phase. Moreover, we quantize the GCN precision from FP32 to INT8 to reduce the memory footprint without losing the inference accuracy. We implement our accelerator design in Intel Stratix10 MX FPGA board with HBM2, and demonstrate 1.3x-110.5x improvement in end-to-end GCN latency as compared to the state-of the-art FPGA implementations, on the graph datasets of Cora, Pubmed, Citeseer and Reddit.

Nair, Gopikrishnan R.↗
NASA NTRS1984

Determination of the mass of globular cluster X-ray sources

The precise positions of the luminous X-ray sources in eight globular clusters have been measured with the Einstein X-Ray Observatory. When combined with similarly precise measurements of the dynamical centers and core radii of the globular clusters, the distribution of the X-ray source mass is determined to be in the range 0.9-1.9 solar mass. The X-ray source positions and the detailed optical studies indicate that (1) the sources are probably all of similar mass, (2) the gravitational potentials in these high-central density clusters are relatively smooth and isothermal, and (3) the X-ray sources are compact binaries and are probably formed by tidal capture.

Grindlay, J. E.↗
NASA NTRS1986

Thunderstorm cloud top dynamics as inferred from satellite observations and a cloud top parcel model

Thunderstorm top temperature-height structure and temperature-height conversion relations in the convective overshooting top region are examined using data from GOES IR, AVHRR, and aircraft overflights, and GOES stereoscopic observations. Using a Lagrangian one-dimensional cloud parcel model applied in the overshooting region, three classes of storm tops are described and the causes of their unique temperature-height structures are explored. Although the parcel model used does not fully reproduce the three-dimensional structure and dynamics of an evolving thunderstorm top, it is shown to crudely reproduce the parcel dynamics of updraft core parcels. The locations of cold points, high points, warm points, and the magnitude of cold-high offsets compare favorably between the model and the satellite observations.

Adler, Robert F.↗
NASA NTRS1990

Interannual and decade fluctuations in the earth's rotation

The main findings of a study of earth rotation changes on the longer interannual and decade range of time scales are summarized. The earth rotation data provide important constraints on models of the internal structure and dynamics of the core and lower mantle. Torques at the core-mantle interface are due to time varying fluid motions in the core. A torque of about 0.2 Hadley units is found in the axial component during the 1980 period.

Dickey, Jean O.↗
NASA NTRS2004

The Structure of Young Stellar Systems: Establishing the Initial Conditions for Planet Formation

FYO1-FY03 Origins support to the PI had been as part of an effort involving Profs. Blake, van Dishoeck and L.G. Mundy of the University of Maryland. As outlined below, the merging of BIMA+OVRO into the Combined Array for Research in Millimeter Astronomy (CARMA) and our mutual involvement in the Spitzer Legacy Science program now provides a more natural means of continuing the Caltech/Maryland collaboration. In addition, the spectroscopy/radiative transfer programs led by Profs. Blake, Hogerheijde, and van Dishoeck form a more cohesive basis for a single proposal. Students supported by our previous Origins grant have been involved in making some of the first sub-arcsecond resolution images of the morphology and chemistry of individual YSOs at OVRO and BIMA, in the analysis of IR spectra taken by ISO, and in continuing exploratory IR diffraction-limited imaging and spectroscopy at the Keck and VLT observatories. Notable scientific accomplishments in the past grant period include: 1) detecting high density and temperature hot cores in the dynamically accreting envelopes of low mass protostars that contain significant quantities of complex, prebioitc molecules, 2) imaging chemical and isotopic zonation in the outer regions of T Tauri star accretion disks, particularly fractional ionization and D/H studies, 3) acquiring and modeling the first extensive CO v = 1 approaches 0 spectroscopy survey of the terrestrial planet-forming region of circumstellar accretion disks, and 4) optimizing detailed radiative transfer modeling of the molecular and dust emission from YSO envelopes and from comets, including a new parallelized implementation.

Blake, Geoffrey A.↗
DOE OSTI2020

Simultaneous Observation of Carrier-Specific Redistribution and Coherent Lattice Dynamics in 2H-MoTe 2 with Femtosecond Core-Level Spectroscopy

In this study, we employ few-femtosecond extreme ultraviolet (XUV) transient absorption spectroscopy to reveal simultaneously the intra- and interband carrier relaxation and the light-induced structural dynamics in nanoscale thin films of layered 2H-MoTe 2 semiconductor. By interrogating the valence electronic structure via localized Te 4 d (39-46 eV) and Mo 4 p (35-38 eV) core levels, the relaxation of the photoexcited hole distribution is directly observed in real time. We obtain hole thermalization and cooling times of 15 ± 5 fs and 380 ± 90 fs, respectively, and an electron-hole recombination time of 1.5 ± 0.1 ps. Furthermore, excitations of coherent out-of-plane A 1g (5.1 THz) and in-plane E 1g (3.7 THz) lattice vibrations are visualized through oscillations in the XUV absorption spectra. By comparison to Bethe-Salpeter equation simulations, the spectral changes are mapped to real-space excited-state displacements of the lattice along the dominant A 1g coordinate. By directly and simultaneously probing the excited carrier distribution dynamics and accompanying femtosecond lattice displacement in 2H-MoTe 2 within a single experiment, our work provides a benchmark for understanding the interplay between electronic and structural dynamics in photoexcited nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The 3D Kinematics of the Orion Nebula Cluster: NIRSPEC-AO Radial Velocities of the Core Population

The kinematics and dynamics of stellar and substellar populations within young, still-forming clusters provide valuable information for constraining theories of formation mechanisms. Using Keck II NIRSPEC+AO data, we have measured radial velocities for 56 low-mass sources within 4' of the core of the Orion Nebula Cluster (ONC). We also remeasure radial velocities for 172 sources observed with SDSS/APOGEE. These data are combined with proper motions measured using HST ACS/WFPC2/WFC3IR and Keck II NIRC2, creating a sample of 135 sources with all three velocity components. The velocities measured are consistent with a normal distribution in all three components. We measure intrinsic velocity dispersions of (${\sigma }_{{v}_{\alpha }}$, ${\sigma }_{{v}_{\delta }}$, ${\sigma }_{{v}_{r}}$) = (1.64 ± 0.12, 2.03 ± 0.13, ${2.56}_{-0.17}^{+0.16}$) km s –1 . Our computed intrinsic velocity dispersion profiles are consistent with the dynamical equilibrium models from Da Rio et al. (2014) in the tangential direction but not in the line-of-sight direction, possibly indicating that the core of the ONC is not yet virialized, and may require a nonspherical potential to explain the observed velocity dispersion profiles. We also observe a slight elongation along the north–south direction following the filament, which has been well studied in previous literature, and an elongation in the line-of-sight to tangential velocity direction. These 3D kinematics will help in the development of realistic models of the formation and early evolution of massive clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

Contributions from geomagnetic inverse theory to the study of hydromagnetic conditions near the core-mantle boundary

The Final Report on contributions from geomagnetic inverse theory to the study of hydromagnetic conditions near the core-mantle boundary (CMB) is presented. The original proposal was to study five questions concerning what the surface and satellite magnetic data imply about hydromagnetic and electromagnetic conditions near the CMB. The five questions are: (1) what do the surface and satellite data imply about the geomagnetic field B near the surface of the earth; (2) how does one extrapolate B down through the conducting mantle to the CMB; (3) if B on the CMB is visible, how accurately does it satisfy the frozen-flux approximation; (4) if frozen flux is a good approximation on the CMB, what can be inferred about the fluid velocity v in the upper core; and (5) if v at the CMB is visible, does it suggest any dynamical properties of the core, such as vertical advection, Alfven-inertial waves, link instabilities, or mantle effects. A summary of the research is provided.

Backus, George E.↗
NASA NTRS1985

On the coupling of fluid dynamics and electromagnetism at the top of the earth's core

A kinematic approach to short-term geomagnetism has recently been based upon pre-Maxwell frozen-flux electromagnetism. A complete dynamic theory requires coupling fluid dynamics to electromagnetism. A geophysically plausible simplifying assumption for the vertical vorticity balance, namely that the vertical Lorentz torque is negligible, is introduced and its consequences are developed. The simplified coupled magnetohydrodynamic system is shown to conserve a variety of magnetic and vorticity flux integrals. These provide constraints on eligible models for the geomagnetic main field, its secular variation, and the horizontal fluid motions at the top of the core, and so permit a number of tests of the underlying assumptions.

Benton, E. R.↗
DOE OSTI2024

CFD simulations of Molten Salt Fast Reactor core cavity flows

Computational Fluid Dynamics (CFD) has become increasingly important in the research and development of advanced nuclear reactors. Here, in the current study, extensive CFD simulations were conducted for the coolant flow in Molten Salt Fast Reactor (MSFR) core models using the state-of-the-art spectral element flow solver Nek5000 and multiscale coarse-mesh thermal-hydraulic software Pronghorn. The underlying motivation is to seek an in-depth understanding of how the internal velocity distribution can be influenced by the MSFR core cavity shape, the Reynolds number, turbulence modeling options and the inlet boundary conditions. The CFD techniques involved in this investigation range from coarse-mesh CFD, RANS modeling, to the high-fidelity LES calculations. Specifically, a series of RANS simulations were performed for the 2-D axisymmetric core model and 3-D wedge domains to study the flow distribution inside the MSFR core. It is observed that a proper representation of the MSFR inlet channel duct is important for the prediction of internal flow distribution. It is also showcased here how researchers can leverage the Nek5000 CFD results to calibrate more efficient coarse-mesh CFD tools, like Pronghorn, for the actual MSFR design needs. Moreover, this paper highlights a 3-D LES model for an entire MSFR core using the spectral element method and demonstrates the feasibility of this modeling approach. The readiness and potential limitations of the RANS approach are examined with respect to the high-fidelity LES simulations. The present investigation lays a solid foundation as we are leveraging the high-fidelity CFD capabilities to inform MSFR design efforts.

97 MATHEMATICS AND COMPUTING↗