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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Theoretical implications of detecting gravitational waves

This paper is the third in a series of theorems which state how cosmological observations can provide evidence for an early phase of acceleration in the universe. It was demonstrated in [1,2], that the observed power spectrum for scalar perturbations forces all possible alternative theories of inflation to theories other than General Relativity. It was shown that generically, without a phase of accelerated expansion, these alternatives have to break at least one of the following tenets of classical general relativity: the Null Energy Condition (NEC), subluminal signal propagation, or sub-Planckian energy densities. In this paper we prove how detection of primordial gravitational waves at large scales can provide independent evidence to support a phase of accelerated expansion. This proof does not rely on the spectral index for tensor modes but relies on validity of quantum field theory in curved space time and tensor modes being sourced from adiabatic vacuum fluctuations. Our approach, like in the case of scalars, is proof by contradiction: we investigate the possibility of a detectable tensor signal sourced by vacuum fluctuations in a non-accelerating, sub-Planckian universe using cosmological perturbation theory and derive contradictory limits on cosmological dynamics. The contradiction implies that one or more of our axioms for early universe must have been broken. The bound from tensor perturbations is not only independent of, but also stronger than the one obtained from scalar power spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Robust global detection of forced changes in mean and extreme precipitation despite observational disagreement on the magnitude of change

Detection and attribution (D&A) of forced precipitation change are challenging due to internal variability, limited spatial, and temporal coverage of observational records and model uncertainty. These factors result in a low signal-to-noise ratio of potential regional and even global trends. Here, we use a statistical method – ridge regression – to create physically interpretable fingerprints for the detection of forced changes in mean and extreme precipitation with a high signal-to-noise ratio. The fingerprints are constructed using Coupled Model Intercomparison Project phase 6 (CMIP6) multi-model output masked to match coverage of three gridded precipitation observational datasets – GHCNDEX, HadEX3, and GPCC – and are then applied to these observational datasets to assess the degree of forced change detectable in the real-world climate in the period 1951–2020. We show that the signature of forced change is detected in all three observational datasets for global metrics of mean and extreme precipitation. Forced changes are still detectable from changes in the spatial patterns of precipitation even if the global mean trend is removed from the data. This shows the detection of forced change in mean and extreme precipitation beyond a global mean trend is robust and increases confidence in the detection method's power as well as in climate models' ability to capture the relevant processes that contribute to large-scale patterns of change. We also find, however, that detectability depends on the observational dataset used. Not only coverage differences but also observational uncertainty contribute to dataset disagreement, exemplified by the times of emergence of forced change from internal variability ranging from 1998 to 2004 among datasets. Furthermore, different choices for the period over which the forced trend is computed result in different levels of agreement between observations and model projections. These sensitivities may explain apparent contradictions in recent studies on whether models under- or overestimate the observed forced increase in mean and extreme precipitation. Lastly, the detection fingerprints are found to rely primarily on the signal in the extratropical Northern Hemisphere, which is at least partly due to observational coverage but potentially also due to the presence of a more robust signal in the Northern Hemisphere in general.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Research in the use of electrets in measuring effluents from rocket exhaust of the space shuttle (6.4 percent scaled model) and Viking 1 launch

Electrets used to detect the chemical composition of rocket exhaust effluents were investigated. The effectiveness of electrets was assessed while comparisons were made with hydrogen chloride measuring devices from chamber and field tests, and computed results from a multilayer diffusion model. The experimental data used were obtained from 18 static test firings, chamber tests, and the Viking 1 launch to Mars. Results show that electrets have multipollutant measuring capabilities, simplicity of deployment, and speed of assessment. The electrets compared favorably with other hydrogen chloride measuring devices. The summary of the measured data from the electrets and the hydrogen chloride detectors was within the upper and lower bounds of the computed hydrogen chloride concentrations from the multilayer diffusion model.

Susko, M.↗
NASA NTRS1985

G27.4+0.0 - A galactic supernova remnant with a central compact source

High-resolution X-ray and radio images of the galactic supernova remnant G27.4+0.0 are presented. The X-ray image reveals a centrally located compact source of emission which accounts for 25 percent + or - 2 percent of the emission. The rest of the emission is found in diffuse patches defining a circle of diameter 4 arc min. The radio image is an incomplete shell of comparable diameter with no apparent counterpart to the compact X-ray source. The X-ray luminosity of the supernova remmant implied by the distance of 26 kpc inferred from the Sigma-D relationship exceeds that of any known remnant. This fact, plus the relatively low X-ray absorption, suggests that the remnant is substantially closer than 26 kpc. No X-ray variability of the central source has been detected to a level of 50 percent on time scales of about 1 year, and no periodicity in the range 0.0001-100 Hz to a limit of 16 percent was detected. If G27.4 +0.0 is within a few kiloparsecs, the central source is most likely to be an accretion-powered X-ray binary.

Kriss, G. A.↗
NASA NTRS1996

The HST Key Project on the Extragalactic Distance Scale VI. The Cepheids in NGC925

We report the detection of Cepheid Variable stars in the barred spiral galaxy NGC925, using the Hubble Space Telescope (HST) Wide Field and Planetary Camera 2 (WFPC2). Twelve V (F555W), four I (F814W) and three B (F439W) epochs of cosmic ray split observations were obtained. Eighty Cepheids were discovered, with periods from 6 to +-80 days. Light curves of the Cepheids are presented, and their corresponding period-luminosity diagrams are discussed.

Cepheids Cepheid Cepheid Variable stars barred spi↗
DOE OSTI2021

High-energy micrometre-scale pixel direct conversion X-ray detector

The objective of this work was to fabricate and characterize a new X-ray imaging detector with micrometre-scale pixel dimensions (7.8 µm) and high detection efficiency for hard X-ray energies above 20 keV. A key technology component consists of a monolithic hybrid detector built by direct deposition of an amorphous selenium film on a custom designed CMOS readout integrated circuit. Characterization was carried out at the synchrotron beamline 1-BM-B at the Advanced Photon Source of Argonne National Laboratory. The direct conversion detector demonstrated micrometre-scale spatial resolution with a 63 keV modulation transfer function of 10% at Nyquist frequency. In addition, spatial resolving power down to 8 µm was determined by imaging a transmission bar target at 21 keV. X-ray signal linearity, responsivity and lag were also characterized in the same energy range. Finally, phase contrast edge enhancement was observed in a phase object placed in the beam path. This amorphous selenium/CMOS detector technology can address gaps in commercially available X-ray detectors which limit their usefulness for existing synchrotron applications at energies greater than 50 keV; for example, phase contrast tomography and high-resolution imaging of nanoscale lattice distortions in bulk crystalline materials using Bragg coherent diffraction imaging. Here, the technology will also facilitate the creation of novel synchrotron imaging applications for X-ray energies at or above 20 keV.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Utility of Infrasound in Global Monitoring of Extraterrestrial Impacts: A Case Study of the 2008 July 23 Tajikistan Bolide

Abstract Among the various observational techniques used for the detection of large bolides on a global scale is a low-frequency sound known as infrasound. Infrasound, which is also one of the four sensing modalities used by the International Monitoring System, offers continuous global monitoring and can be leveraged for planetary defense. Infrasonic records can provide an additional dimension for event characterization and a distinct perspective that might not be available through any other observational method. This paper describes the infrasonic detection and characterization of the bolide that disintegrated over Tajikistan on 2008 July 23. This event was detected by two infrasound stations at distances of 1530 and 2130 km. Propagation paths to one of the stations were not predicted by the model, despite being clearly detected. The presence of the signal is attributed to the acoustic energy being trapped in a weak but leaky stratospheric AtmoSOFAR channel. The infrasound signal analysis indicates that the shock originated at the point of the main breakup at an altitude of 35 km. The primary mode of the shock production of the signal detected at the two stations was a spherical blast resulting from the main gross fragmentation episode. The energy estimate, based on the signal period, is 0.17–0.51 kt of TNT equivalent, suggesting a mass of 6.6–23.5 tons. The corresponding object radius, assuming the chondritic origin, was 0.78–1.18 m.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Detecting magnetic ordering with atomic size electron probes

While magnetism originates at the atomic scale, the existing spectroscopic techniques sensitive to magnetic signals only produce spectra with spatial resolution on a larger scale. However, recently, it has been theoretically argued that atomic size electron probes with customized phase distributions can detect magnetic circular dichroism. Here, we report a direct experimental real-space detection of magnetic circular dichroism in aberration-corrected scanning transmission electron microscopy (STEM). Using an atomic size-aberrated electron probe with a customized phase distribution, we reveal the checkerboard antiferromagnetic ordering of Mn moments in LaMnAsO by observing a dichroic signal in the Mn L-edge. The novel experimental setup presented here, which can easily be implemented in aberration-corrected STEM, opens new paths for probing dichroic signals in materials with unprecedented spatial resolution.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Implementation of the Waveform Correlation Event Detection System (WCEDS) Method for Regional Seismic Event Detection in Utah

Backprojection techniques are a class of methods for detecting and locating events that have been successfully implemented at local scales for dense networks. This paper develops the framework for applying a backprojection method to detect and locate a range of event sizes across a heteorogeneous regional network. This article extends previous work on the development of a backprojection method for local and regional seismic event detection, the Waveform Correlation Event Detection System (WCEDS). The improvements outlined here make the technique much more flexible for regional earthquake or explosion monitoring. We first explore how the backprojection operator can be formulated using either a travel-time model or a stack of full waveforms, showing that the former approach is much more flexible and can lead to the detection of smaller events, and to significant improvements in the resolution of event parameters. Second, we discuss the factors that influence the grid of event hypotheses used for backprojection, and develop an algorithm for generating suitable grids for networks with variable density. Third, we explore the effect of including different phases in the backprojection operator, showing that the best results for the study region can be obtained using only the Pg phase, and by including terms for penalizing early arrivals when evaluating the fit for a given event hypothesis. Fourth, we incorporate two parallel backprojection computations with different distance thresholds to enable the robust detection of both network-wide and small (sub-network-only) events. Finally, the set of improvements are outlined by applying WCEDS to four example events on the University of Utah Seismograph Stations (UUSS) network.

58 GEOSCIENCES↗
DOE OSTI2016

SGR A* and its environment: low-mass star formation, the origin of X-ray gas and collimated outflow

We present high-resolution multiwavelength radio continuum images of the region within 150″ of Sgr A*, revealing a number of new extended features and stellar sources in this region. First, we detect a continuous 2″ east–west ridge of radio emission, linking Sgr A* and a cluster of stars associated with IRS 13 N and IRS 13E. The ridge suggests that an outflow of east–west blob-like structures is emerging from Sgr A*. In particular, we find arc-like radio structures within the ridge with morphologies suggestive of photoevaporative protoplanetary disks. We use infrared K{sub s} and L′ fluxes to show that the emission has similar characteristics to those of a protoplanetary disk irradiated by the intense radiation field at the Galactic center. This suggests that star formation has taken place within the S-cluster 2″ from Sgr A*. We suggest that the diffuse X-ray emission associated with Sgr A* is due to an expanding hot wind produced by the mass loss from B-type main sequence stars, and/or the disks of photoevaporation of low mass young stellar objects (YSOs) at a rate of ∼10{sup −6} M{sub ⊙} yr{sup −1}. The proposed model naturally reduces the inferred accretion rate and is an alternative to the inflow–outflow style models to explain the underluminous nature of Sgr A*. Second, on a scale of 5″ from Sgr A*, we detect new cometary radio and infrared sources at a position angle PA ∼ 50° which is similar to that of two other cometary sources X3 and X7, all of which face Sgr A*. In addition, we detect a striking tower of radio emission at a PA ∼ 50°–60° along the major axis of the Sgr A East supernova remnant shell on a scale of 150″ from Sgr A*. We suggest that the cometary sources and the tower feature are tracing interaction sites of a mildly relativistic jet from Sgr A* with the atmosphere of stars and the nonthermal Sgr A East shell at a PA ∼ 50°–60° with M-dot ∼1×10{sup −7} M{sub ⊙} yr{sup −1}, and opening angle 10°. Lastly, we suggest that the east–west ridge of radio emission traces an outflow that is potentially associated with past flaring activity from Sgr A*. The position angle of the outflow driven by flaring activity is close to −90°.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2021

Mapping Boreal Forest Spruce Beetle Health Status at the Individual Crown Scale Using Fused Spectral and Structural Data

The frequency and severity of spruce bark beetle outbreaks are increasing in boreal forests leading to widespread tree mortality and fuel conditions promoting extreme wildfire. Detection of beetle infestation is a forest health monitoring (FHM) priority but is hampered by the challenges of detecting early stage (“green”) attack from the air. There is indication that green stage might be detected from vertical gradients of spectral data or from shortwave infrared information distributed within a single crown. To evaluate the efficacy of discriminating “non-infested”, “green”, and “dead” health statuses at the landscape scale in Alaska, USA, this study conducted spectral and structural fusion of data from: (1) Unoccupied aerial vehicle (UAV) multispectral (6 cm) + structure from motion point clouds (~700 pts per sq. m); and (2) Goddard Lidar Hyperspectral Thermal (G-LiHT) hyperspectral (400 to 1000 nm, 0.5 m) + SWIR-band lidar (~32 pts per sq.m). We achieved 78% accuracy for all three health statuses using spectral + structural fusion from either UAV or G-LiHT and 97% accuracy for non-infested/dead using G-LiHT. We confirm that UAV 3D spectral (e.g., greenness above versus below median height in crown) and lidar apparent reflectance metrics (e.g., mean reflectance at 99th percentile height in crown), are of high value, perhaps capturing the vertical gradient of needle degradation. In most classification exercises, UAV accuracy was lower than G-LiHT indicating that collecting ultra-high spatial resolution data might be less important than high spectral resolution information. While the value of passive optical spectral information was largely confined to the discrimination of non-infested versus dead crowns, G-LiHT hyperspectral band selection (~400, 675, 755, and 940 nm) could inform future FHM mission planning regarding optimal wavelengths for this task. Interestingly, the selected regions mostly did not align with the band designations for our UAV multispectral data but do correspond to, e.g., Sentinel-2 red edge bands, suggesting a path forward for moderate scale bark beetle detection when paired with suitable structural data.

Janice Cessna↗
NASA NTRS1988

Mass killings and detection of impacts

Highly energetic bolide impacts occur and their flux is known. For larger bodies the energy release is greater than for any other short-term global phenomenon. Such impacts produce or release a large variety of shock induced changes including major atmospheric, sedimentologic, seismic and volcanic events. These events must necessarily leave a variety of records in the stratigraphic column, including mass killings resulting in major changes in population density and reduction or extinction of many taxonomic groups, followed by characteristic patterns of faunal and flora replacement. Of these effects, mass killings, marked by large-scale loss of biomass, are the most easily detected evidence in the field but must be manifest on a near-global scale. Such mass killings that appear to be approximately synchronous and involve disappearance of biomass at a bedding plane in many sedimentologically independent sections globally suggest a common cause and probable synchroneity. Mass killings identify an horizon which may be examined for evidence of cause. Geochemical markers may be ephemeral and absence may not be significant. There appears to be no reason why ongoing phenomena such as climate and sea-level changes are primary causes of anomolous episodic events.

Mclaren, Digby J.↗
DOE OSTI2017

Toward General Software Level Silent Data Corruption Detection for Parallel Applications

Silent data corruption (SDC) poses a great challenge for high-performance computing (HPC) applications as we move to extreme-scale systems. Mechanisms have been proposed that are able to detect SDC in HPC applications by using the peculiarities of the data (more specifically, its “smoothness” in time and space) to make predictions. However, these data-analytic solutions are still far from fully protecting applications to a level comparable with more expensive solutions such as full replication. In this work, we propose partial replication to overcome this limitation. More specifically, we have observed that not all processes of an MPI application experience the same level of data variability at exactly the same time. Thus, we can smartly choose and replicate only those processes for which the lightweight data-analytic detectors would perform poorly. In addition, we propose a new evaluation method based on the probability that a corruption will pass unnoticed by a particular detector (instead of just reporting overall single-bit precision and recall). Here in our experiments, we use four applications dealing with different explosions. Finally, our results indicate that our new approach can protect the MPI applications analyzed with 7–70% less overhead (depending on the application) than that of full duplication with similar detection recall.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Coil Detection System for Dynamic Wireless Charging of Electric Vehicle

Application of wireless power transfer while EV is in motion can significantly reduce the battery storage capacity. A major challenge in implementation of dynamic wireless power transfer (DWPT) is automatic detection of EV to avoid loss in efficiency and alleviate any safety concerns. This paper proposes a novel coil detection method for segmented DWPT. Detection of the EV ahead of its arrival will initiate energizing of the transmitter buried inside the road to enable just-in-time transfer of power. At low speeds, communication can be a reliable method to power up the transmitter coil. However, at high speeds on highways, communication latency time for the detection of an EV is long and hence impractical. This paper proposes a low cost and low power EV detection system based on a novel orthogonal coil arrangement to detect EVs traveling at high speeds. Here, the proposed detection system was tested on a laboratory scale prototype for verification purpose. For high speed verification, simulation in PLECS was conducted to test the functionality of the proposed system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1979

Gravitational field models for study of Earth mantle dynamics

The tectonic forces or stresses due to the small scale mantle flow under the South American plate are detected and determined by utilizing the harmonics of the geopotential field model. The high degree harmonics are assumed to describe the small scale mantle convection patterns. The input data used in the derivation of this model is made up of 840,000 optical, electronic, and laser observations and 1,656 5 deg x 5 deg mean free air anomalies. Although there remain some statistically questionable aspects of the high degree harmonics, it seems appropriate now to explore their implications for the tectonic forces or stress field under the crust.

Source record↗
DOE OSTI2025

Hyper Spectral Anomaly Detection

Anomaly detection is a common machine learning (ML) task with growing importance in the fields of imaging, quality assurance, and multiple security related disciplines. Anomaly detection is more difficult than traditional machine learning methods due to the inherent unlabeled nature of the datasets. Existing anomaly detection architectures commonly face challenges with explainability, retaining information related to the relational structure of the data, and false positive rates. Hyperspectral Imaging Anomaly Detection (HSI) is a statistical model that employs vertex and edge weighted graphs to preserve the data’s relationships on different topographical scales. The model is able to generalize from anomaly detection in 2D images to novel datasets related to cyber-security. Furthermore, the use of multi-spectral and other filtering methods results in fewer false positives and increases the explainability of model predictions. When applying HSI to cyber-security datasets, we are able to successfully detect malicious activity with a relatively high degree of accuracy.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Scalable Parallel Methods for Analyzing Metagenomics Data at Extreme Scale

The field of bioinformatics and computational biology is currently experiencing a data revolution. The exciting prospect of making fundamental biological discoveries is fueling the rapid development and deployment of numerous cost-effective, high-throughput next-generation sequencing technologies. The result is that the DNA and protein sequence repositories are being bombarded with new sequence information. Databases are continuing to report a Moore’s law-like growth trajectory in their database sizes, roughly doubling every 18 months. In what seems to be a paradigm-shift, individual projects are now capable of generating billions of raw sequence data that need to be analyzed in the presence of already annotated sequence information. While it is clear that data-driven methods, such as sequencing homology detection, are becoming the mainstay in the field of computational life sciences, the algorithmic advancements essential for implementing complex data analytics at scale have mostly lagged behind. Sequence homology detection is central to a number of bioinformatics applications including genome sequencing and protein family characterization. Given millions of sequences, the goal is to identify all pairs of sequences that are highly similar (or “homologous”) on the basis of alignment criteria. While there are optimal alignment algorithms to compute pairwise homology, their deployment for large-scale is currently not feasible; instead, heuristic methods are used at the expense of quality. In this dissertation, we present the design and evaluation of a parallel implementation for conducting optimal homology detection on distributed memory supercomputers. Our approach uses a combination of techniques from asynchronous load balancing (viz. work stealing, dynamic task counters), data replication, and exact-matching filters to achieve homology detection at scale. Results for a collection of 2.56M sequences show parallel efficiencies of ~75-100% on up to 8K cores, representing a time-to-solution of 33 seconds. We extend this work with a detailed analysis of single-node sequence alignment performance using the latest CPU vector instruction set extensions. Preliminary results reveal that current sequence alignment algorithms are unable to fully utilize widening vector registers.

59 BASIC BIOLOGICAL SCIENCES↗