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At least 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

FE K EMISSION AND ABSORPTION FEATURES IN THE XMM-EPIC SPECTRUM OF THE SEYFERT GALAXY IC 4329A

We present a re-analysis of the XMM-Newton long-look of the X-ray bright Seyfert galaxy IC 4329a. The Fe K bandpass is dominated by two peaks, consistent with emission from neutral or near-neutral Fe Ka and KP. A relativistic diskline model whereby both peaks are the result of one doubly-peaked diskline profile is found to be a poor description of the data. Models using two relativistic disklines are found to describe the emission profile well. A low-inclination, moderately-relativistic dual-diskline model is possible if the contribution from narrow components, due to distant material, is small or absent. A high-inclination, moderately relativistic profile for each peak is possible if there are roughly equal contributions from both the broad and narrow components. Upper limits on Fe XXV and Fe XXVI emission and absorption at the systemic velocity of IC 4329a are obtained. We also present the results of RXTE monitoring of this source obtained so far; the combined XMM-Newton and RXTE data sets allow us to explore the time-resolved spectral behavior of this source on time scales ranging from hours to 2 years. We find no strong evidence for variability of the Fe Ka emission line on any time scale probed, likely due to the minimal level of continuum variability. We detect a narrow absorption line, at a energy of 7.68 keV in the rest frame of the source; its significance has been confirmed using Monte Carlo simulations. This feature is most likely due to absorption from Fe XXVI blueshifted to approximately 0.1c relative to the systemic velocity, making IC 4329a the lowest-redshift AGN known with a high-velocity, highly-ionized outflow component. As is often the case with similar outflows seen in high-luminosity quasars, the estimated mass outflow rate is larger than the inflow accretion rate, signaling that the outflow represents a substantial portion of the total energy budget of the AGN. The outflow could arise from a radiatively-driven disk wind, or it may be in the form of a discrete, transient blob of ejected material.

Markowitz, A.↗
NASA NTRS2011

Compression Behavior of Fluted-Core Composite Panels

In recent years, fiber-reinforced composites have become more accepted for aerospace applications. Specifically, during NASA s recent efforts to develop new launch vehicles, composite materials were considered and baselined for a number of structures. Because of mass and stiffness requirements, sandwich composites are often selected for many applications. However, there are a number of manufacturing and in-service concerns associated with traditional honeycomb-core sandwich composites that in certain instances may be alleviated through the use of other core materials or construction methods. Fluted-core, which consists of integral angled web members with structural radius fillers spaced between laminate face sheets, is one such construction alternative and is considered herein. Two different fluted-core designs were considered: a subscale design and a full-scale design sized for a heavy-lift-launch-vehicle interstage. In particular, axial compression of fluted-core composites was evaluated with experiments and finite-element analyses (FEA); axial compression is the primary loading condition in dry launch-vehicle barrel sections. Detailed finite-element models were developed to represent all components of the fluted-core construction, and geometrically nonlinear analyses were conducted to predict both buckling and material failures. Good agreement was obtained between test data and analyses, for both local buckling and ultimate material failure. Though the local buckling events are not catastrophic, the resulting deformations contribute to material failures. Consequently, an important observation is that the material failure loads and modes would not be captured by either linear analyses or nonlinear smeared-shell analyses. Compression-after-impact (CAI) performance of fluted core composites was also investigated by experimentally testing samples impacted with 6 ft.-lb. impact energies. It was found that such impacts reduced the ultimate load carrying capability by approximately 40% on the subscale test articles and by less than 20% on the full-scale test articles. Nondestructive inspection of the damage zones indicated that the detectable damage was limited to no more than one flute on either side of any given impact. More study is needed, but this may indicate that an inherent damage-arrest capability of fluted core could provide benefits over traditional sandwich designs in certain weight-critical applications.

Schultz, Marc R.↗
NASA NTRS2005

Satellite-Derived Management Zones

The term "satellite-derived management zones" (SAMZ) denotes agricultural management zones that are subdivisions of large fields and that are derived from images of the fields acquired by instruments aboard Earth-orbiting satellites during approximately the past 15 years. "SAMZ" also denotes the methodology and the software that implements the methodology for creating such zones. The SAMZ approach is one of several products of continuing efforts to realize a concept of precision agriculture, which involves optimal variations in seeding, in application of chemicals, and in irrigation, plus decisions to farm or not to farm certain portions of fields, all in an effort to maximize profitability in view of spatial and temporal variations in the growth and health of crops, and in the chemical and physical conditions of soils. As used here, "management zone" signifies, more precisely, a subdivision of a field within which the crop-production behavior is regarded as homogeneous. From the perspective of precision agriculture, management zones are the smallest subdivisions between which the seeding, application of chemicals, and other management parameters are to be varied. In the SAMZ approach, the main sources of data are the archives of satellite imagery that have been collected over the years for diverse purposes. One of the main advantages afforded by the SAMZ approach is that the data in these archives can be reused for purposes of precision agriculture at low cost. De facto, these archives contain information on all sources of variability within a field, including weather, crop types, crop management, soil types, and water drainage patterns. The SAMZ methodology involves the establishment of a Web-based interface based on an algorithm that generates management zones automatically and quickly from archival satellite image data in response to requests from farmers. A farmer can make a request by either uploading data describing a field boundary to the Web site or else drawing the boundary on a reference image. Hence, a farmer can start to engage in precision farming shortly after gaining access to the Web site, without the need for incurring the high costs of conventional precision-agriculture data-collection practices that include collecting soil samples, mapping electrical conductivity of soil, and compiling multiyear crop-yield data. Given the boundary of a field, a SAMZ server computes the zones within the field in a three-stage process. In the first stage, a vector-valued image of the field is constructed by assembling, from the archives, the equivalent of a stack of the available images of the field (see figure). In the second stage, the vector-valued image is analyzed by use of a wavelet transform that detects spatial variations considered significant for precision farming while suppressing small-scale heterogeneities that are regarded as insignificant. In the third stage, a segmentation algorithm assembles the zones from smaller regions that have been identified in the wavelet analysis.

Lepoutre, Damien↗
NASA NTRS2011

Solar Cycle Fine Structure and Surface Rotation from Ca II K-Line Time Series Data

Analysis of three and a half decades of data from the NSO/AFRL/Sac Peak K-line monitoring program yields evidence for four components to the variation: (a) the solar cycle, with considerable fine structure and a quasi-periodicity of 122.4 days; (b) a stochastic process, faster than (a) and largely independent of it, (c) a quasi-periodic signal due to rotational modulation, and of course (d) observational errors (shown to be quite small). Correlation and power spectrum analyses elucidate periodic and aperiodic variation of these chromospheric parameters. Time-frequency analysis is especially useful for extracting information about differential rotation, and in particular elucidates the connection between its behavior and fine structure of the solar cycle on approximately one-year time scales. These results further suggest that similar analyses will be useful at detecting and characterizing differential rotation in stars from stellar light-curves such as those being produced at NASA's Kepler observatory.

Scargle, Jeff↗
NASA NTRS2012

Anisotropies in the Diffuse Gamma-Ray Background Measured by the Fermi LAT

The contribution of unresolved sources to the diffuse gamma-ray background could induce anisotropies in this emission on small angular scales. We analyze the angular power spectrum of the diffuse emission measured by the Fermi LAT at Galactic latitudes absolute value of b > 30 deg in four energy bins spanning 1 to 50 GeV. At multipoles l >= 155, corresponding to angular scales approx < 2 deg, angular power above the photon noise level is detected at > 99.99% CL in the 1-2 GeV, 2- 5 GeV, and 5- 10 GeV energy bins, and at > 99% CL at 10-50 GeV. Within each energy bin the measured angular power takes approximately the same value at all multipoles l >= 155, suggesting that it originates from the contribution of one or more unclustered source populations. The amplitude of the angular power normalized to the mean intensity in each energy bin is consistent with a constant value at all energies, C(sub p) / (I)(exp 2) = 9.05 +/- 0.84 x 10(exp -6) sr, while the energy dependence of C(sub p) is consistent with the anisotropy arising from one or more source populations with power-law photon spectra with spectral index Gamma (sub s) = 2.40 +/- 0.07. We discuss the implications of the measured angular power for gamma-ray source populations that may provide a contribution to the diffuse gamma-ray background.

Ferrara, E. C.↗
NASA NTRS2017

Characterizing GEO Titan IIIC Transtage Fragmentations using Ground-Based and Telescopic Measurements

In a continued effort to better characterize the geosynchronous orbit (GEO) environment, NASA's Orbital Debris Program Office (ODPO) utilizes various ground-based optical assets to acquire photometric and spectral data of known debris associated with fragmentations in or near GEO. The Titan IIIC Transtage upper stage is known to have fragmented four times. Two of the four fragmentations were in GEO while the Transtage fragmented a third time in GEO transfer orbit. The forth fragmentation occurred in low Earth orbit. To better assess and characterize these fragmentations, the NASA ODPO acquired a Titan Transtage test and display article previously in the custody of the 309th Aerospace Maintenance and Regeneration Group (AMARG) in Tucson, Arizona. After initial inspections at AMARG demonstrated that it was of sufficient fidelity to be of interest, the test article was brought to NASA Johnson Space Center (JSC) to continue material analysis and historical documentation. The Transtage has undergone two separate spectral measurement campaigns to characterize the reflectance spectroscopy of historical aerospace materials. These data have been incorporated into the NASA Spectral Database, with the goal of using telescopic data comparisons for potential material identification. A Light Detection and Ranging (LIDAR) system scan also has been completed and a scale model has been created for use in the Optical Measurement Center (OMC) for photometric analysis of an intact Transtage, including bidirectional reflectance distribution function (BRDF) measurements. An historical overview of the Titan IIIC Transtage, the current analysis that has been done to date, and the future work to be completed in support of characterizing the GEO and near GEO orbital debris environment will be discussed in the subsequent presentation.

Cowardin, Heather↗
NASA NTRS2019

Deep Mapping of Small Solar System Bodies with Galactic Cosmic Ray Secondary Particle Showers

We will investigate the use of galactic cosmic ray (GCR) secondary particles to probe the deep interiors of small solar system bodies (SSBs), including comets, asteroids, and geologic structures on the surfaces of airless bodies. Applications include solar system science, planetary defense, and resource utilization. Our Phase I study demonstrated that muons, the long-range charged component of GCR showers, can penetrate SSBs up to a km in diameter, providing information on their interior structure. Muons produced in Earth’s atmosphere have been applied to image the interior of large objects for science and engineering. In Phase I, we found that the production of muons in the solid surfaces of airless bodies is much smaller than in Earth’s atmosphere. Nevertheless, the flux of transmitted muons is sufficient to detect inclusions within an asteroid or comet in a reasonable amount of time, ranging from hours to weeks, depending on the size of the SSB and the density contrast, position and size of the inclusion. For asteroids and comets, large density variations (e.g., porous soil or ice versus solid rock) are relatively easy to detect. The intrinsic spatial resolution of muon radiography (“muography”) is on the scale of a few meters. The spatial resolution that can be achieved in practice depends on signal intensity and integration time (counting statistics), the angular resolution of the muon tracker (hodoscope) and details of data reduction and analysis methodology. Our Phase II project will assess remaining unknowns for the application of muography to determining the interior structure of SSBs, assess risks for implementation, and provide a roadmap for development of SSB muography beyond the NIAC program. To achieve our objectives, we will focus on four interrelated tasks: Task1) Signal and background characterization: Characterize the production and transmission of muons and secondary particle backgrounds made by cosmic ray showers in SSBs; and near-surface features from radiographic and tomographic data; Task2) Imaging studies: Develop methods to determine the density structure of SSB interiors and near-surface features from radiographic and tomographic data; Task3) Instrument design: Using simulations and bench-top laboratory experiments, investigate specific concepts for the design of compact hodoscopes and components; Task4) Synthesis: Combine the results of the first three tasks to determine the range of applicability of the method, identify the steps needed for maturation of the concept, and explore concepts for a pilot muography mission.

Prettyman, Thomas H.↗
DOE OSTI2018

Big Data Mining for Applied Energy Savings in Buildings

Residential and commercial buildings in China, India, the United States (US), United Kingdom (UK), and Italy consume 39-45% of each nation's primary energy (approximately 73% of electricity). Building energy models can be used to automatically optimize the return-on-investment for retrofits to improve a building’s energy efficiency. However, with an average of 3,000 building descriptors necessary to accurately simulate a single building, there is a market need to reduce the transaction cost for creating a simulatable model for every building in a city and calibrate the models to utility data prior to capital expenditures. Oak Ridge National Laboratory has utilized two of the world’s fastest supercomputers, assembled unique datasets, and developed innovative algorithms for big data mining to produce the Automatic detection and creation of Building Energy Models (AutoBEM) technology for urban-scale energy modeling. The project developed the world’s most accurate method for determining building footprints from satellite imagery and the world’s fastest building energy model generator. The team has also leveraged a total of eight supercomputers to analyze the best methods, metrics, and algorithms for calibrating building models to measured data within 4% of hourly electricity use; well beyond current industry standards necessary for private-sector financing. The project developed the world’s fastest buildings simulator, over 8 million simulations totaling over 200TB, and mined this data with over 130,000 parallel artificial intelligence algorithmic instances to develop the world’s best calibration algorithm in terms of accuracy, runtime, and robustness.

New, Joshua↗
DOE OSTI2025

Harnessing the Power of AI: Status and Expansion of Current Domestic Transport Security Through Flexible Embedded Hardware

As applications of Artificial Intelligence (AI) continue to expand, there are increasing opportunities to leverage applied AI methodologies with mobile transportation focused embedded systems. Current applications of AI in transportation focus on a variety of areas, including fuel efficiency, safety, security, and other broad fields of optimization or detection. To leverage these AI workflows and methodologies in the field, teams must utilize complex embedded systems capable of implementing these AI-enabled algorithms in real-time. In this paper, we will investigate how these algorithms can be integrated into existing technologies leveraging vehicle data - such as the Controller Area Network Transport Security Tracking and Reporting Unit (C-STAR). The C-STAR technology is an embedded platform with onboard computation capable of running next generation algorithms in vehicle systems AI, such as preventative maintenance, driver authentication, and transport security. As deployed in the field, the C-STAR has a limited AI functionality –this paper will directly discuss how a device like C-STAR can be utilized and the advantages of integrating these new technologies. We will open with relevant background information and transportation projects that leverage AI, focusing specifically on those around transport security such as vehicle identification, anomaly detection, and deterrence. We will then extend this into potential opportunities and scaling for AI methodologies using platforms like the C-STAR. Finally, we will speak directly to the challenges of deploying AI-powered workflows, such as computing power needs, bandwidth, hallucinations, and other regulatory considerations.

Cook, Adian [ORNL] (ORCID:0000000160825395)↗
DOE OSTI2024

Crescendo beyond the horizon: More gravitational waves from domain walls bounded by inflated cosmic strings

Gravitational-wave (GW) signals offer a unique window into the dynamics of the early universe. GWs may be generated by the topological defects produced in the early universe, which contain information on the symmetry of UV physics. We consider the case in which a two-step phase transition produces a network of domain walls bounded by cosmic strings. Specifically, we focus on the case in which there is a hierarchy in the symmetry-breaking scales, and a period of inflation pushes the cosmic string generated in the first phase transition outside the horizon before the second phase transition. We show that the GW signal from the evolution and collapse of this string-wall network has a unique spectrum, and the resulting signal strength can be sizeable. In particular, depending on the model parameters, the resulting signal can show up in a broad range of frequencies and can be discovered by a multitude of future probes, including the pulsar timing arrays and space- and ground-based GW observatories. As an example that naturally gives rise to this scenario, we present a model with the first phase transition followed by a brief period of thermal inflation driven by the field responsible for the second stage of symmetry breaking. Here, the model can be embedded into a supersymmetric setup, which provides a natural realization of this scenario. In this case, the successful detection of the peak of the GW spectrum probes the soft supersymmetry breaking scale and the wall tension.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Gamma-ray probes of dark matter substructure

The substructure content of dark matter halos is interesting because it can be affected by complex galaxy physics and dark matter particle physics. However, observing the small scale structure of dark matter is a challenge. The subhalo abundance (mass function, minimum mass) and morphology (density profile, subhalo shape, subsubstructure) contain information about complex astrophysics (halo formation processes) and new exotic fundamental physics (dark matter interactions). Indirect detection of dark matter annihilation radiation (DMAR) in gamma rays may be the most direct method for observing small scale structure. I outline the ways in which gamma rays may probe halo substructure. If substructure is bountiful, it may be responsible for the eventual discovery of DMAR, for instance in galaxy clusters or the diffuse gamma-ray background. Otherwise, the observation of DMAR in places without much substructure, such as the Galactic center, would lead to strict limits on the properties of small scale structure. Properties of the gamma-ray angular power spectrum will also provide information or constraints on Milky Way halo substructure.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Probing the Properties of Superheavy Dark Matter Annihilating or Decaying into Neutrinos With Ultra-High Energy Neutrino Experiments

The evidence for dark matter particles,x, is compelling based on Galactic to cosmological scale observations. Thus far, the promising weakly interacting massive particle scenario have eluded detection, motivating alternative models of dark matter. We consider scenarios involving super-heavy dark matter (SHDM) that potentially can decay or annihilate to neutrinos and antineutrinos. In the mass range m(sub x) =10(exp 7) −10(exp 15) GeV, we evaluate the sensitivities of future observatories PO-EMMA and GRAND for indirect dark matter detection via the measurement of neutrino-induced extensive air showers (EAS), compute the Auger and ANITA limits using their last up-to-date sensitivities, and compare them with IceCube limits. We also show that the uncertainties related to the dark matter distribution in the Galactic halo have a large impact on the neutrino flux. We show that a ground-based radio detector such as GRAND can achieve high sensitivities due to its large effective area and high duty cycle. Space-based Cherenkov detectors such as POEMMA that measure the EAS optical Cherenkov signal have the advantage of full-sky coverage and rapid slewing, enabling an optimized SHDM observation strategy focusing on the Galactic Center. We show that increasing the field of view of the Cherenkov detectors can significantly enhance the sensitivity. Moreover, POEMMA’s fluorescence observation mode that measures EAS above20EeV will achieve state-of-the-art sensitivity to SHDM properties at the highest mass scales.

Claire Guepin↗
DOE OSTI2023

Large Deviations Anomaly Detection (LAD) for collection of multivariate time series data: Applications to COVID-19 data

Time series anomaly detection is frequently used to identify extreme behaviors within a single time series. Identifying extreme trends in relation to a collection of other time series, on the other hand, is frequently of significant interest, such as in public health policy, social justice, and pandemic propagation. Using concepts from large deviations theory , we propose an algorithm that can scale to large collections of time series data. This paper expands on the LAD algorithm presented in Guggilam et al. (2022). The proposed algorithm is an online anomaly detection method for identifying anomalies in a collection of multivariate time series that takes advantage of the algorithm’s ability to scale to high-dimensional data. We show how the proposed Large Deviations Anomaly Detection (LAD) algorithm can be used to identify regions with anomalous trends in COVID-19 cases, deaths, biweekly growth rates, vaccinations, and fatality rates. Several of the observed anomalous trends are associated with regions that have demonstrated poor response to the COVID pandemic.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2021

Satellite Remote Sensing to Assess Cyanobacterial Bloom Frequency Across the United States at Multiple Spatial Scales

Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria. Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency’s Ocean and Land Colour Imager for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.

remote sensing↗
NASA NTRS2001

Application of Computer Tomography for Life Detection

Perhaps one of the most fundamentally difficult challenges facing those who would search for life is that of scale determination. Spatial scales of life on Earth range over more than 15 orders of magnitude in mass and volume, and more than 8 orders of magnitude in 2 dimensional space. If the distribution of life is sparse in comparison to the background on which it is found, then the choice of the right scale is critical to finding that life. But how does one identify the proper scale? To put this in other words, how does one recognize the "haystacks" in which the needles (biosignatures and evidence of life) might be most profitably searched for? The problem is further exacerbated when conditions get extreme because much of the life moves from the clement surface environment into the pores and more clement environments inside of rocks, minerals and soils. Once encased in their lithic homes, these microbes become nearly impossible to study by standard techniques because of the opacity of the rocks. It is this problem that we propose to address in the work proposed here. Computer Tomography (CT) has been a very valuable tool in medicine, where the best resolution available has typically been of the order of about 0.5 mm. However, to adapt the approach for life detection of microbial endoliths, the resolution needs to be moved to the micrometer and even submicrometer levels. Thus for the studies proposed here, we begin with a commercially available instrument that can yield resolution of approximately 10 micrometers. The rational for this is twofold: first, this is the "state of the art" in laboratory instruments; and second, that while the usual size of a microbial cell is about 1 micron, microorganisms tend to live in communities that usually exceed the 10 micrometer size range. The resolution also depends on the sample size itself, so having a small lab instrument into which small samples can be placed will be beneficial to the resolution. We have now used several different CT systems, beginning with the medical scanners (Arcadia CT group) for the detection of layered communities in sandstone rocks from Antarctica. Even this crude instrument was able to point to the areas of the rock that were dominated by microbial populations - this provides the critical first information that says, "Go back and look at these sites with other methods." We showed that without sample preparation or destruction it was possible to gain knowledge as to the presence of density differences suggestive of life.

Tsapin, A.↗
NASA NTRS1986

The ABC of Population III

The author discusses the circumstances in which Population III stars are expected to form and examines their cosmological consequences. Consideration of their production of light, metals, and remnants places a strong constraint on their formation epoch and mass spectrum. However, these constraints would still allow Population III stars to provide the dark matter in galactic halos, a helium abundance of around 25 percent, a detectable background of gravitational waves, a possible infrared background, and the generation of large-scale cosmological structure through explosions. All of these features could be achieved by VMOs in the range 100 to 100,000 solar masses. On the other hand, the Population III scenario would be most compatible with the standard Big Bang picture if the stars were SMOs with mass around a million solar masses. Such stars could still provide the dark matter and detectable gravitational waves.

Carr, B. J.↗
NASA NTRS2002

A Sensitive VLA Search for Small-Scale Glycine Emission Toward OMC-1

We have conducted a deep Q-band (lambda-7 mm) search with the Very Large Array (VLA) toward OMC-1 for the lowest energy conformation (conformer I) of glycine (NH2CH2COOH) in four rotational transitions: the 6(sub 15)- 5(sub 14), 6(sub 24)-5(sub 23), 7(sub 17- 6(sub 16), and 7(sub 07)-6(sub 06). Our VLA observations sample the smallest-scale structures to date in the search for glycine toward OMC-1. No glycine emission features were detected. Thus if glycine exists in OMC-1, either it is below our detection limit, or it is more spatially extended than other large molecules in this source, or it is primarily in its high energy form (conformer II). Our VLA glycine fractional abundance limits in OMC-1 are comparable to those determined from previous IRAM 30m measurements -- somewhat better or worse depending on the specific source model -- and the entire approximately 1 foot primary beam of the VLA was searched while sensitive to an areal spatial scale approximately 150 times smaller than the 24 inch beam of the IRAM single-element telescope. In the course of this work, we detected and imaged the 4(sub 14)-3(sub 13) A and E transitions of methyl formate (HCOOCH3) and also the 2(sub 02) - 1(sub 01) transition of formic acid (HCOOH). Since formic acid is a possible precursor to glycine, our glycine limits and formic acid results provide a constraint on this potential formation chemistry route for glycine in OMC-1.

Hollis, J. M.↗
DOE OSTI2022

Online Power System Event Detection via Bidirectional Generative Adversarial Networks

Accurate and speedy detection of power system events is critical to enhancing the reliability and resiliency of power systems. Although supervised deep learning algorithms show great promise in identifying power system events, they require a large volume of high-quality event labels for training. This paper develops a bidirectional anomaly generative adversarial network (GAN)-based algorithm to detect power system events using streaming PMU data, which does not rely on a huge amount of event labels. By introducing conditional entropy constraint in the objective function of GAN and graph signal processing-based PMU sorting technique, our proposed algorithm significantly outperforms state-of-the-art event detection algorithms in terms of accuracy. To facilitate the adoption of the proposed algorithm, a prototype online platform is also developed using Apache Hadoop, Kafka, and Spark to enable real-time event detection. Here, the accuracy and computational efficiency of the proposed algorithm are validated using a large-scale real-world PMU dataset from the Eastern Interconnection of the United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗