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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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All sources NASA NTRS DOE OSTI

NASA NTRS1994

Modeling and simulation of the data communication network at the ASRM Facility

This paper describes the modeling and simulation of the communication network for the NASA Advanced Solid Rocket Motor (ASRM) facility under construction at Yellow Creek near Luka, Mississippi. Manufacturing, testing, and operations at the ASRM site will be performed in different buildings scattered over an 1800 acre site. These buildings are interconnected through a local area network (LAN), which will contain one logical Fiber Distributed Data Interface (FDDI) ring acting as a backbone for the whole complex. The network contains approximately 700 multi-vendor workstations, 22 multi-vendor workcells, and 3 VAX clusters interconnected via Ethernet and FDDI. The different devices produce appreciably different traffic patterns, each pattern will be highly variable, and some patterns will be very bursty. Most traffic is between the VAX clusters and the other devices. Comdisco's Block Oriented Network Simulator (BONeS) has been used for network simulation. The two primary evaluation parameters used to judge the expected network performance are throughput and delay.

Nirgudkar, R. P.↗

DOE OSTI2021

APOGEE detection of N-rich stars in the tidal tails of Palomar 5

Recent results from chemical tagging studies using Apache Point Observatory Galactic Evolution Experiment data suggest a strong link between the chemical abundance patterns of stars found within globular clusters (GC), and chemically peculiar populations in the Galactic halo field. In this paper, we analyse the chemical compositions of stars within the cluster body and tidal streams of Palomar 5, a GC that is being tidally disrupted by interaction with the Galactic gravitational potential. Here we report the identification of nitrogen-rich (N-rich) stars both within and beyond the tidal radius of Palomar 5, with the latter being clearly aligned with the cluster tidal streams; this acts as confirmation that N-rich stars are lost to the Galactic halo from GCs, and provides support to the hypothesis that field N-rich stars identified by various groups have a GC origin.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1985

Anatomic evidence for peripheral neural processing in mammalian graviceptors

Ultrastructural study of utricular and saccular maculas demonstrates that their innervation patterns are complex. There is a clustering of type I and type II hair cells based upon a sharing of afferents, a system of efferent-type beaded fibers that is of intramacular (mostly calyceal) origin, and a plexus-like arrangement of afferents and efferents at many sites in the neuroepithelium. Results suggest that information concerning linear acceleration is processed peripherally, beginning at the hair cell level, before being sent to the central nervous system. The findings may supply a structural basis for peripheral adaptation to a constant stimulus, and for lateral inhibition to improve signal relative to noise.

Ross, M. D.↗

NASA NTRS1989

Personality based clusters as predictors of aviator attitudes and performance

The feasibility of identification of personality-based population clusters was investigated along with the relationships of these subpopulations to relevant attitude and performance measures. The results of instrumental and expressive personality tests, using the Personal Characteristics Inventory (PCI) test battery and the Cockpit Management Attitudes Questionnaire, suggest that theoretically meaningful subpopulations exist among aviators, and that these groupings are useful in understanding of personality factors acting as moderator variables in the determination of aviator attitudes and performance. Out of the three clusters most easily described in terms of their relative elevations on the PCI subscales ('the right stuff', the 'wrong stuff', and the 'no stuff'), the members of the right stuff cluster tended to have more desirable patterns of responses along relevant attitudinal dimensions.

Gregorich, Steve↗

NASA NTRS1990

Predicting thunderstorm evolution using ground-based lightning detection networks

Lightning measurements acquired principally by a ground-based network of magnetic direction finders are used to diagnose and predict the existence, temporal evolution, and decay of thunderstorms over a wide range of space and time scales extending over four orders of magnitude. The non-linear growth and decay of thunderstorms and their accompanying cloud-to-ground lightning activity is described by the three parameter logistic growth model. The growth rate is shown to be a function of the storm size and duration, and the limiting value of the total lightning activity is related to the available energy in the environment. A new technique is described for removing systematic bearing errors from direction finder data where radar echoes are used to constrain site error correction and optimization (best point estimate) algorithms. A nearest neighbor pattern recognition algorithm is employed to cluster the discrete lightning discharges into storm cells and the advantages and limitations of different clustering strategies for storm identification and tracking are examined.

Goodman, Steven J.↗

NASA NTRS2021

Identifying Meteorological Influences on Marine Low Cloud Mesoscale Morphology Using Satellite Classifications

Marine low cloud mesoscale morphology in the southeastern Pacific Ocean is analyzed using a large dataset of machine-learning generated classifications spanning three years. Meteorological variables and cloud properties are composited 10by mesoscale cloud type, showing distinct meteorological regimes of marine low cloud organization from the tropics to the midlatitudes. The presentation of mesoscale cellular convection, with respect to geographic distribution, boundary layer structure, and large-scale environmental conditions, agrees with prior knowledge. Two tropical and subtropical cumuliform boundary layer regimes, suppressed cumulus and clustered cumulus, are studied in detail. The patterns in precipitation, circulation, column water vapor, and cloudiness are consistent with the representation of marine shallow mesoscale convective 15 self-aggregation by large eddy simulations of the boundary layer. Although they occur under similar large-scale conditions, the suppressed and clustered low cloud types are found to be well-separated by variables associated with low-level mesoscale circulation, with surface wind divergence being the clearest discriminator between them, whether reanalysis or satellite observations are used. Clustered regimes are associated with surface convergence and suppressed regimes are associated with surface divergence.

Johannes Mohrmann↗

DOE OSTI2025

Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning

Seismic data recorded at industrial sites contain valuable information on anthropogenic activities. With advances in machine learning and computing power, new opportunities have emerged to explore the seismic wavefield in these complex environments. We applied two unsupervised machine learning algorithms to analyze continuous seismic data collected from an industrial facility in Texas, United States. The Uniform Manifold Approximation and Projection for Dimension Reduction algorithm was used to reduce the dimensionality of the data and generate 2D embeddings. Then, the Hierarchical Density-Based Spatial Clustering of Applications with Noise method was employed to automatically group these embeddings into distinct signal clusters. Our analysis of over 1400 hr (around 59 days) of continuous seismic data revealed five and seven signal clusters at two separate stations. At both stations, we identified clusters associated with background noise and vehicle traffic, with the latter’s temporal patterns aligning closely with the facility’s work schedule. Furthermore, the algorithms detected signal clusters from unknown sources and underline the ability of unsupervised machine learning for uncovering previously unrecognized patterns. Our analysis demonstrates the effectiveness of unsupervised approaches in examining continuous seismic data without requiring prior knowledge or pre-existing labels.

58 GEOSCIENCES↗

DOE OSTI2021

Modified microstructures in proton irradiated dual phase 308L weldment filler material

In this study, the effect of proton irradiation on the microstructure of δ ferrite—γ austenite mixed phase 308L filler material in a 508–304 dissimilar metal weldment was investigated over a depth of 0 to 10 µm. Ni–Si–Mn G-phase precipitates were observed with SEM and TEM in δ ferrite but not in γ austenite. Our density functional theory based calculations show that the G/Fe interface energy in δ-Fe is significantly lower than that in γ-Fe (0.35 versus 1.25 J/m 2 ), which provides a thermodynamics-based explanation for our experimental observations of preferential formation of G-phase in δ ferrite. STEM-EDS, TEM dark field imaging, and diffraction patterns confirmed the Ni–Si–Mn enriched precipitates were G-phase precipitates with a stoichiometry of Mn 6 Ni 16 Si 7 . Intragranular voids and Ni–Si enriched clusters were observed in irradiated γ austenite. Additionally, Ni and Si segregation was observed along the void interfaces. In both cases, Ni–Si clusters and segregation to voids, selected area diffraction patterns did not reveal the existence of a second phase. Proton irradiation induced Cr depletion and Si and Ni enrichment at γ-γ austenite grain boundaries that was characterized with STEM/EDS.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1980

Probabilistic cluster labeling of imagery data

The problem of obtaining the probabilities of class labels for the clusters using spectral and spatial information from a given set of labeled patterns and their neighbors is considered. A relationship is developed between class and clusters conditional densities in terms of probabilities of class labels for the clusters. Expressions are presented for updating the a posteriori probabilities of the classes of a pixel using information from its local neighborhood. Fixed-point iteration schemes are developed for obtaining the optimal probabilities of class labels for the clusters. These schemes utilize spatial information and also the probabilities of label imperfections. Experimental results from the processing of remotely sensed multispectral scanner imagery data are presented.

Chittineni, C. B.↗

DOE OSTI2022

Chemolithoautotroph distributions across the subsurface of a convergent margin

Subducting oceanic crusts release fluids rich in biologically relevant compounds into the overriding plate, fueling subsurface chemolithoautotrophic ecosystems. To understand the impact of subsurface geochemistry on microbial communities, we collected fluid and sediments from 14 natural springs across a ~200 km transect across the Costa Rican convergent margin and performed shotgun metagenomics. The resulting 404 metagenome-assembled genomes (MAGs) cluster into geologically distinct regions based on MAG abundance patterns: outer forearc-only (25% of total relative abundance), forearc/arc-only (38% of total relative abundance), and delocalized (37% of total relative abundance) clusters. In the outer forearc, Thermodesulfovibrionia, Candidatus Bipolaricaulia, and Firmicutes have hydrogenotrophic sulfate reduction and Wood-Ljungdahl (WL) carbon fixation pathways. In the forearc/arc, Anaerolineae, Ca. Bipolaricaulia, and Thermodesulfovibrionia have sulfur oxidation, nitrogen cycling, microaerophilic respiration, and WL, while Aquificae have aerobic sulfur oxidation and reverse tricarboxylic acid carbon fixation pathway. Transformation-based canonical correspondence analysis shows that MAG distribution corresponds to concentrations of aluminum, iron, nickel, dissolved inorganic carbon, and phosphate. While delocalized MAGs appear surface-derived, the subsurface chemolithoautotrophic, metabolic, and taxonomic landscape varies by the availability of minerals/metals and volcanically derived inorganic carbon. Furthermore, the WL pathway persists across all samples, suggesting that this versatile, energy-efficient carbon fixation pathway helps shape convergent margin subsurface ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Large‐Scale Statistically Meaningful Patterns (LSMPs) Associated With Precipitation Extremes Over Northern California

Abstract We analyze large‐scale statistically meaningful patterns (LSMPs) that precede extreme precipitation (PEx) events over Northern California (NorCal). We find LSMPs by applying k‐means clustering to the two leading principal components of daily 500 hPa geopotential height anomalies two days before the onset, from October to March during 1948–2015. Statistical significance testing based on Monte Carlo simulations suggests a minimum of four statistically distinguished LSMP clusters. The four LSMP clusters are characterized as Northwest continental negative height anomaly, Eastward positive “Pacific‐North American Pattern (PNA),” Westward negative “PNA,” and Prominent Alaskan ridge. These four clusters, shown in multiple variables, evolve very differently and have differing links to the Arctic and tropical Pacific regions. Using binary forecast skill measures and a new copula‐based framework for predicting PEx events, we find LSMP indices that are useful predictors of NorCal PEx events, with moisture‐based variables being the best predictors of PEx events at least 6 days before the onset, and the lower atmospheric variables being better than their upper atmospheric counterparts any day in advance tested. To ensure statistical rigor, the LSMPs analyzed here (with the modified acronym) include local tests of both significance and consistency, which are not always featured in the literature on large‐scale meteorological patterns.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Machine-learning-assisted analysis of transition metal dichalcogenide thin-film growth

In situ reflective high-energy electron diffraction (RHEED) is widely used to monitor the surface crystalline state during thin-film growth by molecular beam epitaxy (MBE) and pulsed laser deposition. With the recent development of machine learning (ML), ML-assisted analysis of RHEED videos aids in interpreting the complete RHEED data of oxide thin films. The quantitative analysis of RHEED data allows us to characterize and categorize the growth modes step by step, and extract hidden knowledge of the epitaxial film growth process. In this study, we employed the ML-assisted RHEED analysis method to investigate the growth of 2D thin films of transition metal dichalcogenides (ReSe2) on graphene substrates by MBE. Principal component analysis (PCA) and K-means clustering were used to separate statistically important patterns and visualize the trend of pattern evolution without any notable loss of information. Using the modified PCA, we could monitor the diffraction intensity of solely the ReSe2 layers by filtering out the substrate contribution. These findings demonstrate that ML analysis can be successfully employed to examine and understand the film-growth dynamics of 2D materials. Further, the ML-based method can pave the way for the development of advanced real-time monitoring and autonomous material synthesis techniques.

36 MATERIALS SCIENCE↗

NASA NTRS2003

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/~ge/gedihome.html Supplementary information: http://www.chip.org/~ge/gedihome.html.

Database Management Systems↗

NASA NTRS2003

CIZA: The First Systematic X-Ray Search for Clusters of Galaxies Behind the Milky Way

The aim of the CIZA project (Clusters In the Zone of Avoidance) was to take the first step toward a complete X-ray census of clusters of galaxies behind the plane of the Galaxy (the absolute value of b less than or equal to 20 degrees), the historical Zone of Avoidance of optical extragalactic surveys. Finding these heavily obscured clusters in ROSAT All-Sky Survey data would allow us to: 1. Construct the first truly all-sky, statistically complete, X-ray flux limited sample of galaxy clusters; 2. Use this sample to obtain an improved measurement of the cluster dipole (both amplitude and direction); 3. Chart large-scale structure across the plane of the Milky Way as traced by galaxy clusters; 4. Identify potential massive galaxy clusters contributing to the observed large-scale flow pattern in the local universe, specifically in the region around the Great Attractor; and 5. Use least-action modelling to deduce the gravitational fields created by galaxy clusters and compare this reconstruction with the one obtained from local galaxy surveys. Our project was highly successful in demonstrating the feasibility of this undertaking and allowed substantial progress toward achieving the stated science goals.

Ebeling, Harald↗

NASA NTRS2012

An In-Depth Study of the Abundance Pattern in the Hot Interstellar Medium in NGC 4649

We present our X-ray imaging spectroscopic analysis of data from deep Suzuku and XMM-Newton Observatory exposures of the Virgo Cluster elliptical galaxy NGC 4649 (M60), focusing on the abundance pattern in the hot interstellar medium (ISM). All measured elements show a radial decline in abundance, with the possible exception of O. We construct steady state solutions to the chemical evolution equations that include infall in addition to stellar mass return and SNIa enrichment, and consider recently published SNIa yields. By adjusting a single model parameter to obtain a match to the global abundance pattern in NGC 4649 we infer that accretion of subsolar metallicity external gas has reduced the overall ISM metallicity and diluted the effectiveness of SNIa to skew the pattern towards low alpha/Fe ratios, and estimate the combination of SNIa rate and level of dilution. Evidently, newly-introduced gas is heated as it is integrated into. and interacts with, the hot gas that is already present. These results indicate a complex flow and enrichment history for NGC 4649, reflecting the continual evolution of elliptical galaxies beyond the formation epoch. The heating and circulation of accreted gas may help reconcile this dynamic history with the mostly passive evolution of elliptical stellar populations. In an appendix we examine the effects of the recent updated atomic database AtomDB in spectral fitting of thermal plasmas with hot ISM temperatures in the elliptical galaxy range.

Lowenstein, Michael↗

NASA NTRS2012

An In-Depth Study of the Abundance Pattern in the Hot Interstellar Medium in NGC 4649

We present our X-ray imaging spectroscopic analysis of data from deep Suzaku and XMM-Newton Observatory exposures of the Virgo Cluster elliptical galaxy NGC 4649 (M60), focusing on the abundance pattern in the hot interstellar medium (ISM). All measured elements show a radial decline in abundance, with the possible exception of Oxygen. We construct steady state solutions to the chemical evolution equations that include infall in addition to stellar mass return and Type Ia supernovae (SNIa) enrichment, and consider recently published SNIa yields. By adjusting a single model parameter to obtain a match to the global abundance pattern in NGC 4649 we infer that introduction of subsolar metallicity external gas has reduced the overall ISM metallicity and diluted the effectiveness of SNIa to skew the pattern towards low alpha/Fe ratios, and estimate the combination of SNIa rate and level of dilution. Evidently, newly-introduced gas is heated as it is integrated into, and interacts with, the hot gas that is already present. These results indicate a complex flow and enrichment history for NGC 4649, reflecting the continual evolution of elliptical galaxies beyond the formation epoch. The heating and circulation of accreted gas may help reconcile this dynamic history with the mostly passive evolution of elliptical stellar populations. In an appendix we examine the effects of the recent updated atomic database AtomDB in spectral fitting of thermal plasmas with hot ISM temperatures in the elliptical galaxy range.

Loewenstein, Michael↗

DOE OSTI2020

In search of molecular ions for optical cycling: a difficult road

Optical cycling, a continuous photon scattering off atoms or molecules, plays a central role in the quantum information science. While optical cycling has been experimentally achieved for many neutral species, few molecular ions have been investigated. We present a systematic theoretical search for diatomic molecular ions suitable for optical cycling using equation-of-motion coupled-cluster methods. Inspired by the electronic structure patterns of laser-cooled neutral molecules, we establish the design principles for molecular ions and explore various possible cationic molecular frameworks. The results show that finding a perfect molecular ion for optical cycling is challenging, yet possible. Among various possible diatomic molecules we suggest several candidates, which require further attention from both theory and experiment: YF + , SiO + , PN + , SiBr + , and BO + .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1970

The application of automatic recognition techniques in the Apollo 9 SO-65 experiment

A synoptic feature analysis is reported on Apollo 9 remote earth surface photographs that uses the methods of statistical pattern recognition to classify density points and clusterings in digital conversion of optical data. A computer derived geological map of a geological test site indicates that geological features of the range are separable, but that specific rock types are not identifiable.

Macdonald, R. B.↗