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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Time Series Analysis in the Search for Other Worlds Through Transit Photometry

The Kepler Mission launched in June 2009 to commence NASA's first mission to search for potentially habitable, Earth-size planets orbiting Sun-like stars. Kepler discovered explanets via the transit method: searching for minute (100 ppm) drops in brightness lasting 1 - 13 hours corresponding to occasions where the planet crosses the face of its host star from Kepler's point of view. The exquisite precision required to carry out the Kepler mission (20 ppm in 6.5 hours) pushed astronomical time series analysis to the limits, and motivated the development of novel algorithmic approaches. Transit signatures of rocky planets are often dwarfed by the intrinsic stellar variability, which is not white noise, and often is non-stationary, and by instrumental systematic effects, which can include transients and electronic artifacts. Surmounting this challenging regime of weak, temporally compact, periodic signals in observation noise with strong systematics and other sources of variability motivated the development of 1) an overcomplete, non-decimated, wavelet-based matched filter to jointly estimate the properties of the non-stationary, non-white observation noise process, and 2) a multi-scale, maximum a posteriori (msMAP) approach to identifying and removing instrumental systematic effects. After over nine years of observations, the Kepler spacecraft finally ran out of fuel in November 2018, ending its data collection activities. Over 2300 planets were discovered by Kepler in its primary mission, and over 355 have been discovered by K2, the repurposed mission that followed Kepler's primary mission after the loss of a second reaction wheel in May 2013. We have ported the Kepler science pipeline for the Transiting Exoplanet Survey Satellite (TESS) Mission, which began science observations in July 2019, and report initial results and performance of the modified science pipeline.The Kepler and TESS Missions are supported by NASA's Science Mission Directorate.

transit surveys↗
DOE OSTI2024

Physics and chemistry from parsimonious representations: image analysis via invariant variational autoencoders

Electron, optical, and scanning probe microscopy methods are generating ever increasing volume of image data containing information on atomic and mesoscale structures and functionalities. This necessitates the development of the machine learning methods for discovery of physical and chemical phenomena from the data, such as manifestations of symmetry breaking phenomena in electron and scanning tunneling microscopy images, or variability of the nanoparticles. Variational autoencoders (VAEs) are emerging as a powerful paradigm for the unsupervised data analysis, allowing to disentangle the factors of variability and discover optimal parsimonious representation. Here, we summarize recent developments in VAEs, covering the basic principles and intuition behind the VAEs. The invariant VAEs are introduced as an approach to accommodate scale and translation invariances present in imaging data and separate known factors of variations from the ones to be discovered. We further describe the opportunities enabled by the control over VAE architecture, including conditional, semi-supervised, and joint VAEs. Several case studies of VAE applications for toy models and experimental datasets in Scanning Transmission Electron Microscopy are discussed, emphasizing the deep connection between VAE and basic physical principles. Python codes and datasets discussed in this article are available at https://github.com/saimani5/VAE-tutorials and can be used by researchers as an application guide when applying these to their own datasets.

36 MATERIALS SCIENCE↗
NASA NTRS2013

Semi-Supervised Eigenbasis Novelty Detection

Recent discoveries in high-time-resolution radio astronomy data have focused attention on a new class of events. Fast transients are rare pulses of radio frequency energy lasting from microseconds to seconds that might be produced by a variety of exotic astrophysical phenomena. For example, X-ray bursts, neutron stars, and active galactic nuclei are all possible sources of short-duration, transient radio signals. It is difficult to anticipate where such signals might appear, and they are most commonly discovered through analysis of high-time- resolution data that had been collected for other purposes. Transients are often faint and difficult to detect, so improved detection algorithms can directly benefit the science yield of all such commensal monitoring. A new detection algorithm learns a low-dimensional linear manifold for describing the normal data. High reconstruction error indicates a novel signal that does not match the patterns of normal data. One unsupervised portion of the manifold model adapts its representation in response to recent data. A second supervised portion of the model is made of a basis trained in advance using labeled examples of RFI; this prevents false positives due to these events. For a linear model, an orthonormalization operation is used to combine these bases prior to the anomaly detection decision. Another novel aspect of the approach lies in combining basis vectors learned in an unsupervised, online fashion from the data stream with supervised basis vectors learned in advance from known examples of false alarms. Adaptive, data-driven detection is achieved that is also informed by existing domain knowledge about signals that may be statistically anomalous, but are not interesting and should therefore be ignored. The method was evaluated using data from the Parkes Multibeam Survey. This data set was originally collected to search for pulsars, which are astronomical sources that emit radio pulses at regular periods. However, several non-pulsar anomalies have recently been discovered in this dataset, making it a compelling test case. By explicitly filtering known false alarm patterns, the approach yields significantly better performance than current transient detection methods.

Wagstaff, Kiri L.↗
NASA NTRS1996

Parallelization and Visual Analysis of Multidimensional Fields: Application to Ozone Production, Destruction, and Transport in Three Dimensions

The three-dimensional, spectral transport model used in the current project was first successfully integrated over climatological time scales by Dr. Guang Ping Lou for the simulation of atmospheric N2O using the United Kingdom Meteorological Office (UKMO) 4-dimensional, assimilated wind and temperature data set. A non-parallel, FORTRAN version of this integration using a fairly simple N2O chemistry package containing only photo-chemical reactions was used to verify our initial parallel model results. The integrations reproduced the gross features of the observed stratospheric climatological N2O distributions but also simulated the structure of the stratospheric Antarctic vortex and its evolution. Subsequently, Dr. Thomas Kindler, who produced much of the parallel version of our model, enlarged the N2O model chemistry package to include N2O reactions involving O(D-1) and also introduced assimilated wind data from NASA as well as UKMO. Initially, transport calculations without chemistry were run using Carbon-14 as a non-reactive tracer gas with the result that large differences in the transport properties of the two assimilated wind data sets were apparent from the resultant Carbon-14 distributions. Subsequent calculations for N2O, including its chemistry, with the two input winds data sets with verification from UARS satellite observations have refined the transport differences between the two such that the model's steering capabilities could be used to infer the correct climatological vertical velocity fields required to support the N2O observations. During this process, it was also discovered that both the NASA and the UKMO data contained spurious values in some of the higher frequency wave components, leading to incorrect local transport calculations and ultimately affecting the large scale properties of the model's N2O distributions, particularly at tropical latitudes. Subsequent model runs with wind data that had been filtered to remove some of the high frequency components produced much more realistic N2O distributions. During the past few months, the UKMO wind data base for a complete two-year period was processed into spectral form for model use. This new version of the input transport data base now includes complete temperature fields as well as the necessary wind data. This was done to facilitate advanced chemical calculations in the parallel model which often depend upon temperature. Additional UKMO data is being added as it becomes available.

Schwan, Karsten↗
DOE OSTI2024

Model-Based Approaches to Generate Knowledge from Data in a Plant Reliability Context

One challenge that nuclear power plant system engineers are facing is that the amount of equipment reliability (ER) data being continuously generated are extremely large. These data elements come in different forms: textual (e.g., condition reports) and numeric (e.g., generated by monitoring systems) and they provide system engineers with valuable insights and information regarding the discovery of anomalous behaviors or degradation trends, the identification of the possible causes behind such behaviors and trends, and the prediction of their direct consequences. This paper directly targets the generation of knowledge from ER data by putting “data into context”. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional (i.e., cause-effect) relations. ER data elements are processed by identifying first which elements of the developed MBSE elements they are referring to. This task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process “knowledge extraction” where our methods to extract knowledge from textual data. Lastly, once numeric and textual ER data elements have been processed and “understood”, we discover possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if there is a temporal relation among them. The logic and temporal are the two main ingredients to perform “machine reasoning” from ER data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Managing the Digital Thread for Structural Applications With Fit for Purpose Materials

With the increased emphasis on reducing the cost and time to market of new materials, the need for analytical tools that enable the virtual design and optimization of materials throughout their processing - internal structure - property - performance envelope, along with the capturing and storing of the associated material and model information across its lifecycle, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Consequently, at NASA Glenn Research Center a robust information management system that manages the digital thread across the full material life (i.e., capture, analysis, maintenance, and dissemination of data) cycle directed at the design of ‘fit-for-purpose materials’ is under development. To this end the Application Table has been incorporated within NASA Glenn Research Center’s ICME Information Management framework within the ANSYS Granta MI tool. The Application Table provides a place where material and structural application information/requirements can be linked to marry the “design-the-material” (structural engineering) and the “design-with-material” (material science) paradigms and thereby enable application-driven design and optimization of materials and structures. In additional several associated toolsets, specifically: AIMAOS (Automated Information Management Across Organizations and Scales), Py MILab, and JARIMIS (Just A Rather Intelligent Material Interrogation System) are also under development to assist in the judicious automation of this process. AIMOAS offers users an interactive graphical user interface for connecting material information management systems with both commercial and in-house simulation tools at various length scales to enable such automation in the handoff across scales and maintenance of material digital twins and the digital thread. Py MILab, is an automatic framework for the capture, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. Finally, JARIMIS is an expert system that integrates various materials informatics tools (e.g., MicroNet, Surrogate ML models, ANSYS Granta MI, etc.) to enable inverse design of materials and facilitate the application of machine learning (ML) and data science with human in the loop decision making to rapidly discover and optimize new materials.

Digital Transformation↗
NASA NTRS2001

Thermal Performance of the Hubble Space Telescope (HST) Solar Array-3 During the Disturbance Verification Test (DVT)

The Hubble Space Telescope (HST) is one of NASA's most productive astronomical observatories. Launched in 1990, the HST continues to gather scientific data to help scientists around the world discover amazing wonders of the universe. To maintain HST in the fore front of scientific discoveries, NASA has routinely conducted servicing missions to refurbish older equipment as well as to replace existing scientific instruments with better, more powerful instruments. In early 2002, NASA will conduct its fourth servicing mission to the HST. This servicing mission is named Servicing Mission 3B (SM3B). During SM3B, one of the major refurbishment efforts will be to install new rigid-panel solar arrays as a replacement for the existing flexible-foil solar arrays. This is necessary in order to increase electrical power availability for the new scientific instruments. Prior to installing the new solar arrays on HST, the HST project must be certain that the new solar arrays will not cause any performance degradations to the observatory. One of the major concerns is any disturbance that can cause pointing Loss of Lock (LOL) for the telescope. While in orbit, the solar-array temperature transitions quickly from sun to shadow. The resulting thermal expansion and contraction can cause a "mechanical disturbance" which may result in LOL. To better characterize this behavior, a test was conducted at the European Space Research and Technology Centre (ESTEC) in the Large Space Simulator (LSS) thermal-vacuum chamber. In this test, the Sun simulator was used to simulate on-orbit effects on the solar arrays. This paper summarizes the thermal performance of the Solar Array-3 (SA3) during the Disturbance Verification Test (DVT). The test was conducted between 26 October 2000 and 30 October 2000. Included in this paper are: (1) brief description of the SA3's components and its thermal design; (2) a summary of the on-orbit temperature predictions; (3) pretest thermal preparations; (4) a description of the chamber and thermal monitoring sensors; and (6) presentation of test thermal data results versus flight predictions.

Nguyen, Daniel H.↗
NASA NTRS2017

The Kepler Data Processing Handbook: A Field Guide to Prospecting for Habitable Worlds

The Kepler telescope hurtled into orbit in March 2009, initiating NASA's first mission to discover Earth-size planets orbiting Sun-like stars. Kepler simultaneously collected data for approximately 165,000 target stars at a time over its four-year mission, identifying over 4700 planet candidates, over 2300 confirmed or validated planets, and over 2100 eclipsing binaries. While Kepler was designed to discover exoplanets, the long-term, ultrahigh photometric precision measurements it achieved made it a premier observational facility for stellar astrophysics, especially in the field of asteroseismology, and for variable stars, such as RR Lyrae. The Kepler Science Operations Center (SOC) was developed at NASA Ames Research Center to process the data acquired by Kepler from pixel-level calibrations all the way to identifying transiting planet signatures and subjecting them to a suite of diagnostic tests to establish or break confidence in their planetary nature. Detecting small, rocky planets transiting Sun-like stars presents a variety of daunting challenges, including achieving an unprecedented photometric precision of ~20 ppm on 6.5-hour timescales, and supporting the science operations, management, processing, and repeated reprocessing of the accumulating data stream. A newly revised and expanded version of the Kepler Data Processing Handbook (KDPH) has been released to support the legacy archival products. The KDPH details the theory, design and performance of the algorithms supporting each data processing step. This paper presents an overview of the KDPH and features illustrations of several key algorithms in the Kepler Science Data Processing Pipeline. Kepler was selected as the 10th mission of the Discovery Program. Funding for this mission is provided by NASA, Science Mission Directorate.

high performance computing↗
NASA NTRS2019

Optical Communications Feasibility Study for Science Mission Located at Sun-Earth Lagrange Point L2

NASA's Exploration and Space Communications projects division recently completed an investigative study, researching the feasibility of integrating optical communications capabilities onto a science-based mission orbiting at Lagrange Point 2 (L2). Optical communications has been demonstrated and integrated into many low-Earth-orbiting missions, however, using the technology as far as L2 needed to be thoroughly researched and proven similarly as efficient as the mission's planned radio frequency (RF) system, but preferably more efficient that the equivalent RF systems. The investigation team was charged with assessing the feasibility of including optical communications on the mission without interfering with its primary science objectives. This came to be known as the "Do No Harm" approach to accommodation. As science and detection technologies become more advanced, data rates and communications requirements continue to evolve. Missions with complex science instruments have a need for more optimized communications capabilities. Optical communications technologies provide NASA and industry missions with increased data rates and quicker response times, allowing scientists to access more data than ever before. Missions utilizing optical communications will have a lighter and more efficient method of transmitting data to users on Earth. The team investigating this opportunity discovered that including an optical communications payload on board the mission to provide a bi-directional link between the spacecraft and Earth-based ground stations is feasible and reaches data rates that are comparable to, and even exceed, the mission's RF system. In the course of their investigation, the team also discovered significant navigation and ranging benefits provided by the optical communications payload (OCP).

LCRD↗
DOE OSTI2026

Spatio-temporal dynamics of Hendra virus in Australia reveal stable maintenance of diverse viral clades among Pteropus bats

Hendra virus (HeV) was discovered in 1994 in Australia. Limited genomic data have hindered comprehensive understanding of HeV’s evolutionary dynamics. Here, in this work, we recovered 48 HeV genomes from bats and 9 from horses from Australia between 2016 and 2020, revealing four distinct clades. Each clade was distributed over a large spatial area with multiple clades co-circulating within a single bat roost on the same day and over consecutive years. The diversity and temporal stability of co-circulating clades suggest that viral dynamics are driven by episodic shedding of existing lineages maintained at the population level, rather than immune-driven strain-replacement dynamics. HeV isolates of different clades displayed variation in phenotypic properties but minimal antigenic differences. We provide an overview of evolutionary dynamics, phenotypic properties and assessment of countermeasures for HeV, and provide insights into the processes that maintain virus diversity in bats and influence the potential for viral emergence.

genetic variation↗
DOE OSTI2025

Relationship between microporous structure and light gas transport through glassy polymeric membranes revealed by molecular simulations

Microporous glassy polymers are attractive materials for gas separation membranes, due to their high permeability and tailorable selectivity, provided physical aging can be delayed. The archetypal microporous glassy polymer, PTMSP, can be blended with a hyper-crosslinked isatin–triptycene porous polymer network (PPN) to delay physical aging. However, while PPN is effective at reducing physical aging, it also affects the permeability of light gases through PTMSP. Molecular dynamics simulations were used here to shed fundamental light on the mechanisms responsible for these effects. Atomistic models are developed that satisfactorily reproduce experimental observations such as matrix density and cavity size distributions for neat PTMSP as well as for PTMSP–PPN blends. Analysis of the simulation results suggests that physical aging is delayed because the PPN inclusions slow down PTMSP relaxation while reducing the connectivity between free volume pockets. To understand how PPN inclusions affect light gas permeability, the atomistic models developed are used to probe CO 2 and CH 4 diffusion and sorption. These simulations are conducted for PTMSP matrices exhibiting varying density, towards reproducing experimental permeability data. Interrogating the simulation trajectories, it is discovered that while CH 4 travels preferentially through the free volume cavities, CO 2 preferentially interacts with the available surfaces, especially in the presence of PPN. These differences help interpret experimental observations. The transport of C 2 H 6 and H 2 S through PTMSP matrices was also investigated. These gases, and in particular H 2 S, were found to absorb within PTMSP, yielding very low diffusion coefficients. The ability to predict differences in diffusion pathways for various natural gas components unveils the possibility of engineering membranes to control permeability and selectivity towards large-scale applications.

Bao Le, Tran Thi [Univ. of Oklahoma, Norman, OK (U↗
DOE OSTI2024

Data Science Enabled Enabled Discovery of Superconductors (Final Progress Report)

This Final Technical Report describes efforts by 4 PIs at the University of Florida (Peter Hirschfeld, Richard Hennig, Greg Stewart and James Hamlin), over the period September 2019-August 2023, to use data science and machine learning techniques to discover new conventional superconductors. The PIs constructed a discovery loop with two theorists and two experimentalists to: develop algorithms to machine learn descriptors correlating strongly with the critical temperature Tc (PI's Peter Hirschfeld, UF Physics and Richard Hennig, UF Materials Science and En), synthesize and measure properties of promising materials, and feed back the knowledge gained into the prediction algorithm. This work was motivated by the theoretical prediction and experimental discovery of high-pressure, high-pressure hydride superconductors, and to find ways to recreate the high critical temperatures in these systems at ambient pressure. Highlights from the grant include: 1) a new equation for Tc in terms of moments of the electron-phonon spectral function, improving on the so-called Allen-Dynes equation (1975); 2) study of the metastable A15 superconductor Nb3Si, formed under explosive compression at ~1000GPa to determine the kinetic barrier to the ground state structure; 3) the development of ultra-fast machine-learned atomic potentials for molecular dynamics, and 4) the discovery of superconductivity at 19K in WB2 arising from metastable defect structures in the crystal.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1975

The spectral energy distribution of NGC 1275

An analysis of absolute spectral energy distributions for NGC 1275 (Per A) covering the wavelength interval from 3300 A to 10,800 A is presented. The data are consistent with the heavy reddening discovered by Wampler (1971). The H-alpha intensity varied by less than 10% between the times of Wampler's earlier measurements and the two occasions of the present observations. The line-emitting region has a characteristic density of about 10 to the 4.5 power per cu cm, a mass of about 10 to the 5.5 power solar masses, and a volume filling factor of about 10 to the -6th power. The gas may be ionized by shock waves or by nonthermal or stellar radiation. It is suggested, in the vein of Minkowski's (1957) original proposal, that the high-velocity emission-line knots described by Minkowski are H II regions in a Perseus-cluster galaxy or intergalactic gas cloud seen in projection against NGC 1275.

Shields, G. A.↗
NASA NTRS1976

Observations of two X-ray flares and the nearby source MX 1716-31

Observations of the X-ray source MX 1716-31 by detectors aboard OSO-7 are described. During the study of the MX 1716-31 data, an X-ray flare was discovered which was probably associated with the source. The flare had a total duration of about 10 minutes and reached a peak intensity twice that of the Crab Nebula in the 3-10-keV range. A search for similar events elsewhere turned up one other flare with a position inconsistent with MX 1716-31. Those features of both flare events which are relevant for comparison with other short-lived X-ray phenomena are discussed.

Markert, T. H.↗
NASA NTRS1980

Observations of the magnetic field and plasma flow in Jupiter's magnetosheath

Large scale (many minutes to 10 hours) magnetic field structures consisting predominantly of nearly north-south field direction were discovered in Jupiter's magnetosheath from the data of Voyagers 1 and 2 and Pioneer 10 during their outbound encounter trajectories. The Voyager 2 data, and that of Voyager 1 to a lesser extent, show evidence of a quasi-period of 10 hours (and occasionally 5 hours) for these structures. The north-south components of the field and plasma velocity were strongly correlated in the outbound magnetosheath as observed by Voyagers 1 and 2, and the components orthogonal to the north-south direction showed weak correlations. For both Voyager encounters the sense (positive and negative) of the north-south correlations were directly related to the direction of the ecliptic plane component of the interplanetary magnetic field using the field and plasma measurements of the non-encountering spacecraft.

Lepping, R. P.↗
NASA NTRS2002

The Extreme Universe Space Observatory

This talk will describe the Extreme Universe Space Observatory (EUSO) mission. EUSO is an ESA mission to explore the most powerful energy sources in the universe. The mission objectives of EUSO are to investigate EECRs, those with energies above 3x10(exp 19) eV, and very high-energy cosmic neutrinos. These objectives are directly related to extreme conditions in the physical world and possibly involve the early history of the big bang and the framework of GUTs. EUSO tackles the basic problem posed by the existence of these extreme-energy events. The solution could have a unique impact on fundamental physics, cosmology, and/or astrophysics. At these energies, magnetic deflection is thought to be so small that the EECR component would serve as the particle channel for astronomy. EUSO will make the first measurements of EAS from space by observing atmospheric fluorescence in the Earth's night sky. With measurements of the airshower track, EUSO will determine the energy and arrival direction of these extreme-energy events. EUSO will make high statistics observations of CRs beyond the predicted GZK cutoff energy and widen the channel for high-energy neutrino astronomy. The energy spectra, arrival directions, and shower profiles will be analyzed to distinguish the nature of these events and search for their sources. With EUSO data, we will have the possibility to discover a local EECR source, test Z-burst scenarios and other theories, and look for evidence of the breakdown of the relativity principle at extreme Lorentz factors.

Adams, Jim↗
NASA NTRS2002

Discovery of a Second Millesecond Accreting Pulsar: XTE J1751-305

We report the discovery by the RXTE PCA of a second transient accreting millisecond pulsar, XTE J1751-305, during regular monitoring observations of the galactic bulge region. The pulsar has a spin frequency of 435 Hz, making it one of the fastest pulsars. The pulsations contain the signature of orbital Doppler modulation, which implies an orbital period of 42 minutes, the shortest orbital period of any known radio or X-ray millisecond pulsar. The mass function, f(sub x) = (1.278 +/- 0.003) x 10 (exp -6) solar mass, yields a minimum mass for the companion of between 0.013 and 0.0017 solar mass depending on the mass of the neutron star. No eclipses were detected. A previous X-ray outburst in June, 1998, was discovered in archival All-Sky Monitor data. Assuming mass transfer in this binary system is driven by gravitational radiation, we constrain the orbital inclination to be in the range 30 deg-85 deg and the companion mass to be 0.013-0.035 solar mass. The companion is most likely a heated helium dwarf. We also present results from the Chandra HRC-S observations which provide the best known position of XTE J1751-305.

Markwardt, C. B.↗
NASA NTRS1998

Visit to an Ocean Planet

"Visit to an Ocean Planet" is an interactive, educational CD-ROM that reveals the importance of our oceans to global climate and life. It is designed to complement middle and high school science curricula, as well as to be enjoyed by the general public. The CD-ROM allows users to explore the Gulf of Mexico with satellite data, investigate the 1997-1998 El Nino, discover "what's up" with Earth-orbiting satellites, and learn about the real life oceanographers. The curriculum background material are arranged in the context of widely accepted teaching themes. The CD-ROM also highlights results from the TOPEX/Poseidon satellite launched by NASA and the Centre National Etudes Spatiales (CNES). It has been measuring our oceans since 1992. This product is a result of NASA's commitment to involve the educational community in endeavors to inspire America's students, create learning opportunities, and enlighten inquisitive minds.

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