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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Landsat/4/Global Positioning System navigation results

An experimental GPSPAC flown on the Landsat-4 spacecraft was the first spaceborne navigation system to use the NAVSTAR Global Position System (GPS). In order to validate the accuracy and reliability of GPSPAC orbit solutions, definitive Landsat-4 ephemerides, derived from ground based tracking data, were generated and compared with GPSPAC estimates. In addition, Landsat-4 orbital solutions were reconstructed from raw GPS measurement data with a GPSPAC navigation simulator program using different Kalman filter constants. Ephemeris comparisons and simulator results are presented, as well as recommendations for the navigation filter.

Heuberger, H.↗
DOE OSTI2020

Model-based Reconstruction for Single Particle Cryo-Electron Microscopy

Single particle cryo-electron microscopy is a vital tool for 3D characterization of protein structures. A typical workflow involves acquiring projection images of a collection of randomly oriented particles, picking and classifying individual particle projections by orientation, and finally using the individual particle projections to reconstruct a 3D map of the electron density profile. The reconstruction is challenging because of the low signal-to-noise ratio of the data, the unknown orientation of the particles, and the sparsity of data especially when dealing with flexible proteins where there may not be sufficient data corresponding to each class to obtain an accurate reconstruction using standard algorithms. In this paper we present a model-based image reconstruction technique that uses a regularized cost function to reconstruct the 3D density map by assuming known orientations for the particles. Our method casts the reconstruction as minimizing a cost function involving a novel forward model term that accounts for the contrast transfer function of the microscope, the orientation of the particles and the center of rotation offsets. We combine the forward model term with a regularizer that enforces desirable properties in the volume to be reconstructed. Using simulated data, we demonstrate how our method can significantly improve upon the typically used approach.

Venkatakrishnan, Singanallur↗
NASA NTRS1987

DSS 43 antenna gain analysis for Voyager Uranus encounter: 8.45-GHz radio science data correction

A malfunction of the Deep Space Network (DSN) 64-meter antenna in Australia forced the antenna to operate with a mispositioned subreflector during the Voyager Uranus encounter period (January 24, 1986). Because of changing main reflector shape and quadripod position as a function of elevation angle, the antenna gain and pointing were not as expected, and the 8.45 GHz received signal level changed during the pass. The study described here used the Geometrical Theory of Diffraction (GTD) analysis to determine actual antenna gain and pointing during that period in an attempt to reconstruct the radio science data. It is found that the 1.4 dB of signal variation can be accounted for by antenna geometry changes and pointing error. Suggested modifications to the values measured during the pass are presented. Additionally, an extremely useful tool for the analysis of gravity deformed reflectors was developed for use in future antenna design and analysis projects.

Slobin, S. D.↗
NASA NTRS2023

Global and Zonal-Mean Hydrological Response to Early Eocene Warmth

Earth's hydrological cycle is expected to intensify in response to global warming, with a “wet-gets-wetter, dry-gets-drier” response anticipated over the ocean. Subtropical regions (∼15°–30°N/S) are predicted to become drier, yet proxy evidence from past warm climates suggests these regions may be characterized by wetter conditions. Here we use an integrated data-modeling approach to reconstruct global and zonal-mean rainfall patterns during the early Eocene (∼56–48 million years ago). The Deep-Time Model Intercomparison Project (DeepMIP) model ensemble indicates that the mid- (30°–60°N/S) and high-latitudes (>60°N/S) are characterized by a thermodynamically dominated hydrological response to warming and overall wetter conditions. The tropical band (0°–15°N/S) is also characterized by wetter conditions, with several DeepMIP models simulating narrowing of the Inter-Tropical Convergence Zone. However, the latter is not evident from the proxy data. The subtropics are characterized by negative precipitation-evaporation anomalies (i.e., drier conditions) in the DeepMIP models, but there is surprisingly large inter-model variability in mean annual precipitation (MAP). Intriguingly, we find that models with weaker meridional temperature gradients (e.g., CESM, GFDL) are characterized by a reduction in subtropical moisture divergence, leading to an increase in MAP. These model simulations agree more closely with our new proxy-derived precipitation reconstructions and other key climate metrics and imply that the early Eocene was characterized by reduced subtropical moisture divergence. If the meridional temperature gradient was even weaker than suggested by those DeepMIP models, circulation-induced changes may have outcompeted thermodynamic changes, leading to wetter subtropics. This highlights the importance of accurately reconstructing zonal temperature gradients when reconstructing past rainfall patterns.

Margot J. Cramwinckel↗
DOE OSTI2025

Experimental study of multiple-orientation muon tomography with image optimization in sparse data environments

Due to the high penetrating power of cosmic-ray muons, they can be used to probe very thick and dense objects. As muons are charged particles, they can be tracked by ionization detectors, determining the position and direction of the muons. With detectors on either side of an object to measure particle direction change, scattering information within the object can be found. This can be used to produce a scattering-intensity image within the object related to density and atomic number. Such imaging is typically performed with a single detector-object orientation, taking advantage of the more intense downward flux of muons, producing planar imaging with some depth-of-field information in the third dimension. Several simulation studies were published with multiorientation tomography, which can form a three-dimensional representation faster than a single-orientation view. In this study, experimental muon-scatter-based tomography was performed using a concrete filled steel drum with several different metal wedges inside, with the drum between detector planes. Data were collected from different detector-object orientations by rotating the steel drum. The data collected from each orientation were combined using two different tomographic methods. A traditional inverse Radon transform approach used for computed tomography and a combination of multiple depth-of-field reconstructions were applied to the data. As cosmic-ray muon flux imaging is rate limited, the imaging techniques were compared for sparse data. Using the combined depth-of-field reconstruction technique, fewer detector-object orientations were needed to reconstruct images that could be used to differentiate the metal wedges.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

TRINIDI: Time-of-Flight Resonance Imaging With Neutrons for Isotopic Density Inference

Accurate reconstruction of 2D and 3D isotope densities is a desired capability with great potential impact in applications such as evaluation and development of next-generation nuclear fuels. Neutron time-of-flight (TOF) resonance imaging offers a potential approach by exploiting the characteristic neutron absorption spectra of each isotope. However, it is a major challenge to compute quantitatively accurate images due to a variety of confounding effects such as severe Poisson noise, background scatter, beam non-uniformity, absorption non-linearity, and extended source pulse duration. We present the TRINIDI algorithm which is based on a two-step process in which we first estimate the neutron flux and background counts, and then reconstruct the areal densities of each isotope and pixel. Both components are based on the inversion of a forward model that accounts for the highly non-linear absorption, energy-dependent emission profile, and Poisson noise, while also modeling the substantial spatio-temporal variation of the background and flux. Further, to do this, we formulate the non-linear inverse problem as two optimization problems that are solved in sequence. We demonstrate on both synthetic and measured data that TRINIDI can reconstruct quantitatively accurate 2D views of isotopic areal density that can then be reconstructed into quantitatively accurate 3D volumes of isotopic volumetric density.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A machine learning decision criterion for reducing scan time for hyperspectral neutron computed tomography systems

We present the first machine learning-based autonomous hyperspectral neutron computed tomography experiment performed at the Spallation Neutron Source. Hyperspectral neutron computed tomography allows the characterization of samples by enabling the reconstruction of crystallographic information and elemental/isotopic composition of objects relevant to materials science. High quality reconstructions using traditional algorithms such as the filtered back projection require a high signal-to-noise ratio across a wide wavelength range combined with a large number of projections. This results in scan times of several days to acquire hundreds of hyperspectral projections, during which end users have minimal feedback. To address these challenges, a golden ratio scanning protocol combined with model-based image reconstruction algorithms have been proposed. This novel approach enables high quality real-time reconstructions from streaming experimental data, thus providing feedback to users, while requiring fewer yet a fixed number of projections compared to the filtered back projection method. In this paper, we propose a novel machine learning criterion that can terminate a streaming neutron tomography scan once sufficient information is obtained based on the current set of measurements. Our decision criterion uses a quality score which combines a reference-free image quality metric computed using a pre-trained deep neural network with a metric that measures differences between consecutive reconstructions. The results show that our method can reduce the measurement time by approximately a factor of five compared to a baseline method based on filtered back projection for the samples we studied while automatically terminating the scans.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Streaming Compression of Scientific Data via Weak-SINDy

Here, in this paper, a streaming weak-SINDy algorithm is developed specifically for compressing streaming scientific data. The production of scientific data, either via simulation or experiments, is undergoing a stage of exponential growth, which makes data compression important and often necessary for storing and utilizing large scientific data sets. As opposed to classical “offline” compression algorithms that perform compression on a readily available data set, streaming compression algorithms compress data “online” while the data generated from simulation or experiments is still flowing through the system. This feature makes streaming compression algorithms well suited for scientific data compression, where storing the full data set offline is often infeasible. This work proposes a new streaming compression algorithm, streaming weak-SINDy, which takes advantage of the underlying data characteristics during compression. The streaming weak-SINDy algorithm constructs feature matrices and target vectors in the online stage via a streaming integration method in a memory efficient manner. The feature matrices and target vectors are then used in the offline stage to build a model through a regression process that aims to recover equations that govern the evolution of the data. For compressing high-dimensional streaming data, we adopt a streaming proper orthogonal decomposition (POD) process to reduce the data dimension and then use the streaming weak-SINDy algorithm to compress the temporal data of the POD expansion. We propose modifications to the streaming weak-SINDy algorithm to accommodate the dynamically updated POD basis. By combining the built model from the streaming weak-SINDy algorithm and a small amount of data samples, the full data flow could be reconstructed accurately at a low memory cost, as shown in the numerical tests.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Proton deflectometry analysis in magnetized plasmas: Magnetic field reconstruction in one dimension

Proton deflectometry is used in magnetized high-energy-density plasmas to observe electromagnetic fields. Here we describe a reconstruction algorithm to recover the electromagnetic fields from proton fluence data in 1-D. The algorithm is verified against analytic solutions and applied to example data. Next, we study the role of source fluence uncertainty for 1-D reconstructions. We show that reconstruction boundary conditions can be used to constrain the source fluence profile and use this to develop a reconstruction using a specified pair of boundary conditions on the magnetic field. From these considerations, we experimentally demonstrate a hybrid mesh-fluence reconstruction technique where fields are reconstructed from fluence data in an interior region with boundary conditions supplied by direct mesh measurements at the boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Precision Kinematic Sunyaev--Zel'dovich Measurements Across Halo Mass and Redshift with DESI DR2 and ACT DR6: Part II. Bright Galaxy Survey and Emission-Line Galaxies

We present the first high-significance spectroscopic stacked kinetic Sunyaev-Zel'dovich (kSZ) measurements of circumgalactic gas profiles for both Bright Galaxy Survey (BGS) and Emission Line Galaxy (ELG) tracers, combining DESI Data Release 2 with ACT Data Release 6. Using reconstructed line-of-sight velocities from the DESI galaxies and high-resolution ACT temperature maps, we detect the kSZ signal at high significance, reaching signal-to-noise ratios of up to $\sim$9 for BGS and $\sim$7.5 for ELGs in optimal stellar-mass selections. Together with the LRG measurements presented in Paper I, these constitute the most significant kSZ detections from any spectroscopic survey to date. We perform the analysis in both real and harmonic space, obtaining consistent results. By splitting both tracers into stellar-mass bins, we study the scaling of the kSZ amplitude with galaxy properties. Combining the kSZ measurements with ACT Data Release 6 (DR6) CMB lensing maps enables a joint calibration of the galaxy-halo connection and the gas fractions of host halos. For the BGS galaxies, we observe low gas fractions around the virial radius relative to standard expectations, likely attributable to active galactic nuclei (AGN) activity. We find some evidence for higher-mass halos retaining a larger fraction of their baryons, consistent with more efficient feedback in lower-mass systems. For the ELG sample, dominated by blue, star-forming galaxies, we provide the first detection of the gas distribution in ELG host halos. The ELGs appear to exhibit relatively high gas fractions, which points to the possibility of weaker feedback (due to e.g. low AGN and supernova feedback activity) at their mass scale. Finally, we present generalized Navarro-Frenk-White (GNFW) fits to the harmonic-space measurements, providing a compact parametrization of gas profiles for forward modeling in large-scale structure analyses.

Hadzhiyska, B. [Cambridge U.; Cambridge U., Inst. ↗
NASA NTRS1994

Tomographic separation of composite spectra. 2: The components of 29 UW Canis Majoris

We have analyzed the UV photospheric lines of 29 CMa, a 4.39 day period, double-lined O-type spectroscopic binary. Archival data from International Ultraviolet Explorer (IUE)(28 spectra well distributed in oribital phase) were analyzed with several techniques. We find that the mass ratio is q = 1.20 +/- 0.16 (secondary more massive) based on three independent arguments. A tomography algorithm was used to produce the separate spectra of the two stars in six UV spectral regions. The MK spectral classifications of the primary and secondary, O7.5-8 Iab and O9.7 Ib, respectively, were estimated through a comparison of UV line ratios with those in spectral standard stars. The flux ratio of the stars in the UV is 0.36 +/- 0.07 (primary brighter). The primary has a strong P Cygni NIV wavelength 1718 feature, indicating a strong stellar wind. We also present tomographic reconstructions of visual spectral data in the range 4300-4950 A, based on seven observations of differing orbital phases, which confirm the UV classifications, and show that the primary is an Of star. From the spectral classifications, we estimate the temperatures of the stars to be 33,750 K and 29,000 K for primary and secondary, respectively. We then fit visual and UV light curves and show that reasonably good fits can be obtained with these temperatures, a semicontact configuration, an inclination of 74 deg. +/- 2 deg., and an intensity ratio r is less than 0.5.

Bagnuolo, William G., Jr.↗
DOE OSTI2026

Leaf Wax Hydrogen Isotopes Reflect Storm Track Position Over Western North America

Proxy records of past climates have yielded powerful insights into regional hydroclimate dynamics. Novel insights may be gained by reconstructing spatiotemporal changes in precipitation isotopologues in past climate states that cannot be gleaned from individual site‐level studies. In this paper, we ask whether latitudinal gradients in the stable hydrogen isotopic composition of precipitation, as inferred from sedimentary leaf wax biomarkers, reflect aspects of large‐scale climate conditions in western North America (WNA). Modern coretop samples from offshore WNA show that leaf wax hydrogen isotopes broadly track the hydrogen isotopic composition of rainfall between 20 and 40N, but with an offset corresponding to a relatively constant “apparent fractionation” value. Poleward of 40N, the leaf wax signal may be complicated by fluvial transport of leaf waxes from the continental interior. Leaf wax‐inferred precipitation hydrogen isotopes show a shift to more negative values between 30 and 40N. We use modern observational data to show that this latitudinal range marks a major transition between the subtropical arid zone and the location of the midlatitude storm tracks over the northeast Pacific. Nudged water isotope‐enabled models capture the location of the arid to mesic climate transition with fidelity. This modern data set suggests that reconstructions of the latitudinal gradient of precipitation hydrogen isotopes can constrain the sensitivity of the storm tracks to shifts in climatic boundary conditions in past climate states. This approach can yield novel insights into past, present, and future hydroclimate variability in this arid region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Terabase-Scale Coassembly of a Tropical Soil Microbiome

Petabases of reads are being produced by environmental metagenome sequencing. An essential step in analyzing these data is metagenome assembly, the computational reconstruction of genome sequences from microbial communities. “Coassembly” of metagenomic sequence data, in which multiple samples are assembled together, enables more complete detection of microbial genomes in an environment than “multiassembly,” in which samples are assembled individually.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Comparing Proxy and Model Estimates of Hydroclimate Variability and Change over the Common Era

Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy-model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform interpretations of both proxy data and model simulations.We subsequently explore means of using proxy-model comparisons to better constrain and characterize future hydroclimate risks. This is explored specifically in the context of several examples that demonstrate how proxy-model comparisons can be used to quantitatively constrain future hydroclimatic risks as estimated from climate model projections.

Common Era↗
NASA NTRS2020

Advanced Supersonic Parachute Inflation Research Experiment Preflight Trajectory Modeling and Postflight Reconstruction

The Advanced Supersonic Parachute Inflation Research and Experiments (ASPIRE) was a series of sounding rocket flights aimed at understanding the dynamics of supersonic parachutes that are used for Mars robotic applications. The 2012 Mars Science Laboratory (MSL) had a successful deployment of a supersonic parachute, but based on post-flight analysis of parachute margins, the ASPIRE project was created as a risk-reduction program to improve quantification of these margins and qualify a supersonic parachute for Mars 2020, the follow-on mission to MSL. The first sounding rocket (SR01) flight of ASPIRE occurred near Wallops Island, Virginia on Oct. 4, 2017 and demonstrated the successful deployment and inflation of a MSL build-to-print parachute in flight conditions similar to the 2012 MSL mission. The ASPIRE SR02 and SR03 were successful follow-on flights on Mar. 31, 2018 and Sep. 7, 2018 that demonstrated the new, strengthened supersonic parachute designed for the Mars 2020 project. The SR02 and SR03 parachuteswere targeted to 100% and 140% of the expected flight limit load for Mars 2020 to confirm new margins expected from the strengthened parachute. Prior to all flights, a multi-body flight dynamics simulation was developed to predict the parachute dynamics and was used, in conjunction with other tools, to target Mars-relevant flight conditions. After each flight, the on-board data were used to reconstruct the flight trajectory and to validate the pre-flight dynamics simulation. Post-flight analysis showed that all three tests achieved their targeted conditions and pre-flight modeling bounded the key performance metrics for the parachute. This paper describes the flight mechanics simulation, post-flight reconstruction, and the reconciliation process used to validate the flight models.

Soumyo Dutta↗
DOE OSTI2020

SuperCDMS Event Reconstruction Using Convolutional Neural Networks [Thesis]

The SuperCDMS experiment uses cryogenic silicon and germanium detectors to search for dark matter candidates such as WIMPs (Weakly Interacting Massive Particles) streaming through the Earth. Collisions in the silicon and germanium crystals are expected to produce phonons whose thermal signatures can be measured. This thesis first describes the integration of a new Signal Distribution Unit (SDU) to the SuperCDMS data acquisition system, which allows for synchronization of multiple detectors and electronic/mechanical noise characterization via accelerometer, antenna, and AC phase measurements. From SuperCDMS detector data it is necessary to reconstruct the energies of the particle events. This thesis explores the use of Convolutional Neural Networks (CNNs) to perform this reconstruction and finds that, although they perform well, changing the noise model breaks the model and requires the neural network to be retrained. In order to mitigate this issue, a new CNN model is proposed which includes the noise Power Spectral Density (PSD) of the data as an additional input to the CNN. While it proves to be effective as a denoising algorithm, it still fails for data with a different noise model. However, including data from multiple PSDs in the neural network training sample allows it to handle data with different types of noise while still maintaining the quality of the reconstruction. Nevertheless, neural networks trained even on multiple PSDs do not robustly handle data taken with PSDs dissimilar to those in the training sample, suggesting that CNNs may need to be retrained whenever the noise environment changes in a significant way.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Reconstruction and identification of boosted di-τ systems in a search for Higgs boson pairs using 13 TeV proton-proton collision data in ATLAS

In this paper, a new technique for reconstructing and identifying hadronically decaying τ+τ- pairs with a large Lorentz boost, referred to as the di-τ tagger, is developed and used for the first time in the ATLAS experiment at the Large Hadron Collider. A benchmark di-τ tagging selection is employed in the search for resonant Higgs boson pair production, where one Higgs boson decays into a boosted $b\overline b$ pair and the other into a boosted τ+τ- pair, with two hadronically decaying τ-leptons in the final state. Using 139 fb -1 of proton-proton collision data recorded at a centre-of-mass energy of 13 TeV, the efficiency of the di-τ tagger is determined and the background with quark- or gluon-initiated jets misidentified as di-τ objects is estimated. The search for a heavy, narrow, scalar resonance produced via gluon-gluon fusion and decaying into two Higgs bosons is carried out in the mass range 1–3 TeV using the same dataset. No deviations from the Standard Model predictions are observed, and 95% confidence-level exclusion limits are set on this model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

AFRL Additive Manufacturing Modeling Series: Challenge 4, In Situ Mechanical Test of an IN625 Sample with Concurrent High-Energy Diffraction Microscopy Characterization

In this work, we describe 3D characterization of an additively manufactured Inconel 625 nickel-base superalloy specimen conducted during a uniaxial tension test using a suite of nondestructive x-ray techniques. High-energy diffraction microscopy in both near- and far-field modalities are employed in situ to track evolution of the material orientation and stress–strain fields at six points during the mechanical test, and these data streams are registered with micro-computed tomography reconstructions which probe the material density. This data volume was matched to a multi-modal serial sectioning characterization of the specimen taken after loading, described in this article’s companion. Twenty-eight grains which were monitored throughout the experiment were selected to form the basis for AFRL AM Modeling Series Challenge 4, Microscale Structure-to-Properties.

36 MATERIALS SCIENCE↗