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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Hierarchical Testing of a Hybrid Machine Learning‐Physics Global Atmosphere Model

Machine learning (ML)-based models have demonstrated high skill and computational efficiency, often outperforming conventional physics-based models in weather and subseasonal predictions. While prior studies have assessed their fidelity in capturing synoptic-scale atmospheric dynamics, their performance across timescales and under out-of-distribution forcing, such as +3K or +4K uniform-warming forcings, and the sources of biases remain elusive, to establish the model's reliability for Earth science. Here, we design three sets of experiments targeting synoptic-scale phenomena, interannual variability, and out-of-distribution uniform-warming forcings. We evaluate the Neural General Circulation Model (NeuralGCM), a hybrid model integrating a dynamical core with ML-based component, against observations and physics-based Earth system models (ESMs). At the synoptic scale, NeuralGCM captures the evolution and propagation of extratropical cyclones with performance comparable to ESMs. At the interannual scale, when forced by El Niño-Southern Oscillation sea surface temperature (SST) anomalies, NeuralGCM successfully reproduces associated teleconnection patterns but exhibits deficiencies in capturing nonlinear response. Under out-of-distribution uniform-warming forcings, NeuralGCM simulates similar responses in global-average temperature and precipitation and reproduces large-scale tropospheric circulation features similar to those in ESMs. Notable weaknesses include overestimating the tracks and spatial extent of extratropical cyclones, biases in the teleconnected wave train triggered by tropical SST anomalies, and differences in upper-level warming and stratospheric circulation responses to SST warming compared to physics-based ESMs. The causes of these weaknesses were explored. Despite the noted weaknesses, NeuralGCM reproduces responses across experiments reasonably and performs comparably to ESMs. By integrating a dynamical core with ML, NeuralGCM shows potential for developing ML-based ESMs.

global warming↗
DOE OSTI2022

Cosmic ray muon clustering for the MicroBooNE liquid argon time projection chamber using sMask-RCNN

In this article, we describe a modified implementation of Mask Region-based Convolutional Neural Networks (Mask-RCNN) for cosmic ray muon clustering in a liquid argon TPC and applied to MicroBooNE neutrino data. Our implementation of this network, called sMask-RCNN, uses sparse submanifold convolutions to increase processing speed on sparse datasets, and is compared to the original dense version in several metrics. The networks are trained to use wire readout images from the MicroBooNE liquid argon time projection chamber as input and produce individually labeled particle interactions within the image. These outputs are identified as either cosmic ray muon or electron neutrino interactions. We find that sMask-RCNN has an average pixel clustering efficiency of 85.9% compared to the dense network's average pixel clustering efficiency of 89.1%. We demonstrate the ability of sMask-RCNN used in conjunction with MicroBooNE's state-of-the-art Wire-Cell cosmic tagger to veto events containing only cosmic ray muons. The addition of sMask-RCNN to the Wire-Cell cosmic tagger removes 70% of the remaining cosmic ray muon background events at the same electron neutrino event signal efficiency. Furthermore, this event veto can provide 99.7% rejection of cosmic ray-only background events while maintaining an electron neutrino event-level signal efficiency of 80.1%. In addition to cosmic ray muon identification, sMask-RCNN could be used to extract features and identify different particle interaction types in other 3D-tracking detectors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Metabolomics analysis reveals differences in evolution between maize and rice

SUMMARY Metabolites are the intermediate and final products of metabolism, which play essential roles in plant growth, evolution and adaptation to changing climates. However, it is unclear how evolution contributes to metabolic variation in plants. Here, we investigated the metabolomics data from leaf and seed tissues in maize and rice. Using principal components analysis based on leaf metabolites but not seed metabolites, metabolomics data could be clearly separated for rice Indica and Japonica accessions, while two maize subgroups, temperate and tropical, showed more visible admixture. Rice and maize seed exhibited significant interspecific differences in metabolic variation, while within rice, leaf and seed displayed similar metabolic variations. Among 10 metabolic categories, flavonoids had higher variation in maize than rice, indicating flavonoids are a key constituent of interspecific metabolic divergence. Interestingly, metabolic regulation was also found to be reshaped dramatically from positive to negative correlations, indicative of the differential evolutionary processes in maize and rice. Moreover, perhaps due to this divergence significantly more metabolic interactions were identified in rice than maize. Furthermore, in rice, the leaf was found to harbor much more intense metabolic interactions than the seed. Our result suggests that metabolomes are valuable for tracking evolutionary history, thereby complementing and extending genomic insights concerning which features are responsible for interspecific differentiation in maize and rice.

Deng, Min↗
DOE OSTI2020

Processing MCNP Elemental Edit Outputs

The Los Alamos National Laboratory's (LANL) Monte Carlo N-Particle® (MCNP®) transport code version 6 has the capability for tracking particles on unstructured mesh (UM) geometry models. The MCNP UM feature was originally designed for the UM models created by the Abaqus/CAE software product. The MCNP version 6.2.0 and later recognizes the UM models read from Abaqus INP files or MCNPUM files converted from Abaqus INP files. Other finite element analysis software packages may generate UM models and then convert these models into Abaqus INP formats.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A data-driven method to estimate the antiproton background in Mu2e

The Mu2e experiment at Fermilab will search for the Charged Lepton Flavour Violating (CLFV) process of neutrinoless conversion of muon to electron in the field of an Al nucleus. The experimental signature is a monochromatic 104.97 MeV conversion electron. One of the expected backgrounds to the conversion electron search is antiprotons produced by the proton beam at the Production Target and annihilating in the Stopping Target (ST). The background expected from antiprotons is low but highly uncertain due to the uncertainty in the antiproton production cross section for the Mu2e beam energy in the relevant angular region. Antiprotons are significantly slower than the other beam particles, so they cannot be efficiently suppressed by the time window cut used to reduce the prompt background. At Mu2e energies, antiproton annihilation at rest in the ST is the only source of events with multiple, simultaneous particle trajectories. We utilized this unique feature and developed a novel way to reconstruct the multi-track events and estimate the antiproton background in situ.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1983

Fundamental research data base

A fundamental research data base was created on a single 9-track 1600 BPI tape containing ground truth, image, and Badhwar profile feature data for 17 North Dakota, South Dakota, and Minnesota agricultural sites. Each site is 5x6 nm in area. Image data has been provided for a minimum of four acquisition dates for each site. All four images have been registered to one another. A list of the order of the files on tape and the dates of acquisition is provided.

Source record↗
NASA NTRS1989

Observation and analysis for the bidirectional reflectance of stratus clouds at near-infrared wavelengths

Results are presented from observations of the spectral reflectance of marine stratocumulus clouds acquired during the First ISCCP Regional Experiment in June and July, 1987. The data were obtained with aircraft-mounted cross track scanning radiometers. The radiance data show persistent and significant scattering features. The characteristics of the observed NIR reflectance patterns are examined and compared with model calculations based on in situ particle measurements.

Spinhirne, J. D.↗
NASA NTRS1993

A Novel Optical/digital Processing System for Pattern Recognition

This paper describes two processing algorithms that can be implemented optically: the Radon transform and angular correlation. These two algorithms can be combined in one optical processor to extract all the basic geometric and amplitude features from objects embedded in video imagery. We show that the internal amplitude structure of objects is recovered by the Radon transform, which is a well-known result, but, in addition, we show simulation results that calculate angular correlation, a simple but unique algorithm that extracts object boundaries from suitably threshold images from which length, width, area, aspect ratio, and orientation can be derived. In addition to circumventing scale and rotation distortions, these simulations indicate that the features derived from the angular correlation algorithm are relatively insensitive to tracking shifts and image noise. Some optical architecture concepts, including one based on micro-optical lenslet arrays, have been developed to implement these algorithms. Simulation test and evaluation using simple synthetic object data will be described, including results of a study that uses object boundaries (derivable from angular correlation) to classify simple objects using a neural network.

Boone, Bradley G.↗
NASA NTRS2005

Expedition Memory: Towards Agent-based Web Services for Creating and Using Mars Exploration Data.

Explorers ranging over kilometers of rugged, sometimes "feature-less" terrain for over a year could be overwhelmed by tracking and sharing what they have done and learned. An automated system based on the existing Mobile Agents design [ I ] and Mars Exploration Rover experience [2], could serve as an "expedition memory" that would be indexed by voice as wel1 as a web interface, linking people, places, activities, records (voice notes, photographs, samples). and a descriptive scientific ontology. This database would be accessible during EVAs by astronauts, annotated by the remote science team, linked to EVA plans, and allow cross indexing between sites and expeditions. We consider the basic problem, our philosophical approach, technical methods, and uses of the expedition memory for facilitating long-term collaboration between Mars crews and Earth support teams. We emphasize that a "memory" does not mean a database per se, but an interactive service that combines different resources, and ultimately could be like a helpful librarian.

Clancey, William J.↗
NASA NTRS2017

Application of Machine Learning to Rotorcraft Health Monitoring

Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

machine learning↗
NASA NTRS2018

Compact Telescoping Surface Array for Mars Solar Power

This paper describes a lightweight, large-area solar array concept for Mars surface power called the Compact Telescoping Surface Array (CTSA). The design is derived from the Compact Telescoping Array (CTA) proposed in 2015 for high-power spacecraft. The CTSA deploys horizontally from Mars landers, provides 1000 sq.m of solar cell area, and generates about 50-80 kW daytime and 10 kW nighttime power (from energy storage) near the equator with clear skies. The total mass is about 1500 kg, and the stowed volume is about 10 cu.m, equivalent to 200 W/kg and 30 kW/cu.m at 1 astronomical unit (AU) from the sun. These challenging mass and volume goals require compact, lightweight structures to deploy and tension thin solar cell blankets in the Mars 0.38 g gravity field. Other features include single-axis rotation for daily or seasonal sun tracking, dust shedding, and feathering in high winds and sufficient strength for sustained 40 m/s winds in dust storms and brief 100 m/s winds in dust devils (dynamic pressure of 120 Pa). Based on preliminary design and analysis reported in the paper, CTSA appears to be a feasible approach for 1000 sq.m-class Mars solar arrays that autonomously deploy from landers prior to human arrival.

Pappa, Richard↗
NASA NTRS2015

A Heuristic Approach to Correlating ERAM Flight Data from Twenty Centers

Among its many other functions, the Federal Aviation Administration’s En Route Automation Modernization (ERAM) provides external systems with real-time air traffic data for flights in enroute airspace in the National Airspace System. It replaced the En Route Host computer and backup system used at 20 FAA Air Route Traffic Control Centers (Centers) nationwide. Among the new features of ERAM, its output data stream of flight plan and track data includes a unique identifier for a flight originating in any one of the 20 ERAM Centers. The unique identifier, called the Global Unique Flight Identifier (GUFI), is persistent across all the Centers that track the flight. However, certain factors make it difficult to correlate data using the GUFI. First, the value of the GUFI is only unique within a time window of seven days. Second, the GUFI is attached only to flight-plan related data messages. Finally, track positions reported by ERAM do not reference the GUFI. In order to correlate historical as well as real time flight-plan and position related ERAM data, an efficient, heuristic approach was developed, and a prototype was developed. The approach showed that the processing speed, through parallel processing, is sufficient to correlate ERAM data in real-time. As described in this paper, when there are multiple track positions reported from multiple Centers within a few seconds, each position is assigned with a weighted score to indicate the quality of the position relative to its last know position. The weighted score can be used to eliminate potentially duplicate track positions. The approach is database-agnostic, and can be implemented in a Big Data system such as an Apache Hadoop system, as well as in traditional database systems.

Correlating ERAM Flight Data↗
DOE OSTI2022

Cosmic ray muon clustering for the MicroBooNE liquid argon time projection chamber using sMask-RCNN

In this article, we describe a modified implementation of Mask Region-based Convolutional Neural Networks (Mask-RCNN) for cosmic ray muon clustering in a liquid argon TPC and applied to MicroBooNE neutrino data. Our implementation of this network, called sMask-RCNN, uses sparse submanifold convolutions to increase processing speed on sparse datasets, and is compared to the original dense version in several metrics. The networks are trained to use wire readout images from the MicroBooNE liquid argon time projection chamber as input and produce individually labeled particle interactions within the image. These outputs are identified as either cosmic ray muon or electron neutrino interactions. We find that sMask-RCNN has an average pixel clustering efficiency of 85.9% compared to the dense network's average pixel clustering efficiency of 89.1%. We demonstrate the ability of sMask-RCNN used in conjunction with MicroBooNE's state-of-the-art Wire-Cell cosmic tagger to veto events containing only cosmic ray muons. The addition of sMask-RCNN to the Wire-Cell cosmic tagger removes 70% of the remaining cosmic ray muon background events at the same electron neutrino event signal efficiency. This event veto can provide 99.7% rejection of cosmic ray-only background events while maintaining an electron neutrino event-level signal efficiency of 80.1%. In addition to cosmic ray muon identification, sMask-RCNN could be used to extract features and identify different particle interaction types in other 3D-tracking detectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2006

Advanced Ka-Band Transceiver With Monopulse Tracking

A proposed Ka-band transmitting/ receiving system would embody a unique combination of established and semi-proven design features. The proposed system (see figure) would include a monopulse receiving feedback loop and a mirror that could be moved by piezoelectric actuators in the feedback loop to adjust the aim of the transmitted and received radio beams. Unlike in a phased-array tracking system, phase shifters (which can be complex and expensive) would not be needed in this monopulse tracking system. Moreover, the monopulse-tracking loop could be combined with other subsystems used in established subreflector and antenna designs. The final transmitter power amplifier in the proposed system would be a quasi-optical power amplifier (QOPA) -- a combination of a planar array of 25 amplifiers and corresponding planar arrays of antenna elements, such that free-space power combining would take place at the output.

Khan, Abdur↗
NASA NTRS1980

An initial assessment of the performance achieved by the Seasat-1 radar altimeter

This paper describes the results of an initial on-orbit engineering assessment of the performance achieved by the radar altimeter system flown on Seasat-1. Additionally, the general design characteristics of this system are discussed and illustrations of altimeter data products are provided. The instrument consists of a 13.5-GHz monostatic radar system that tracks in range only using a 1-m parabolic antenna pointed at the satellite nadir. Two of its unique features are a linear FM transmitter with 320-MHz bandwidth, which yields a 3.125-ns time-delay resolution, and microprocessor-implemented closed-loop range tracking, automatic gain control (AGC), and real-time estimation of significant wave height (SWH). Results presented herein show that the altimeter generally performed in accordance with its original performance requirements of measuring altitude to a precision of less than 10-cm rms, SWH to an accuracy of plus or minus 0.5 m or 10 percent whichever is greater, and ocean backscatter coefficient to an accuracy of plus or minus 1 dB, all over an SWH range of 1 to 20 m.

Townsend, W. F.↗
NASA NTRSDate not supplied

SURFACE EXOSURE TIMESCALES OF APOLLO CORE SAMPLE 73002 SPACE WEATHERED GRAINS

Introduction: Space weathering causes the surface regolith on airless bodies like the Moon to be morphologically, microstructurally, and chemically altered due to micrometeoroid bombardment and solar wind irradiation[1]. These processes produce a multitude of microstructural and chemical changes in individual soil grains that accumulate as grains are exposed on the surface over time. One microstructural feature produced by exposure to the solar wind is the development of ion-damaged rims on regolith grains via H+ and He+ ion irradiation. Also present are solar energetic particle (SEP) tracks, which are nanoscale lineations of ionization damage within grain interiors formed by high energy solar flare ions(primarily Fe group nuclei) which penetrate millimeters below the surface [2]. Recent work has confirmed that the thickness of solar wind-damaged amorphous rims on anorthite grains, nanocrystalline rims on olivine grains, and their respective SEP track densities are correlated with their surface exposure ages [3].Core sample 73002, recently released under the Apollo Next Generation Sample Analysis (ANGSA) Program, has provided an opportunity to study material collected from the light mantle formation during Apollo 17. The light mantle is thought to have been deposited via a landslide originating from the neighboring South Massif [4]. Spectral profiles and ferromagnetic resonance measurements of bulk soils sampled at cm-intervals from 73002 indicate the existence of mature regolith extending ~8 cm below the surface, suggesting the presence of an in-situ reworking zone in the core[5,6].Here we present the distribution of SEP track densities, solar wind damaged rim widths, and the corresponding surface exposure ages of grains residing in the proposed in-situ reworking zone of core 73002. Methods: Bulk samples of regolith from the first eight intervals and every following fourth interval down the core (dissection Pass 2) were delivered to Purdue University as <45 μm size fractions. The first eight0.5 cm intervals, representing the top 4cmof regolith, were individually dry sieved to a<20 μm size fraction, and grains were prepared by ultramicrotomy for analysis in the scanning transmission electron microscope (STEM). Bright field (BF) and dark field (DF) STEM images of solar flare tracks and solar wind damaged rims were acquired on a JEOL 2500SE TEM, equipped with a 60 mm2ultra-thin window silicon drift energy dispersive X-ray (EDX) spectrometer at NASA John-son Space Center. Grain compositions were determined by EDX compositional spectrum imaging. SEP track densities and amorphous rim thicknesses were measured on BF and DF images. Results: The fraction of grains with discernable space weathering features decreased with depth, with 100% in the first interval exhibiting space weathering features as opposed to ~60% in Interval 8.BF and DF STEM images show splash-melt and vapor deposited rims on outermost grain margins with embedded Fe-bearing nanoparticles ranging in size up to ~10 nm in diameter. Images also show solar-wind damaged rims below the vapor deposits, and SEP tracks present in grain interiors. The rim thicknesses and SEP track densities were determined using the methods of [3] for 54grains spanning the top 4 cm. ~80% of the grains analyzed were anorthite and ~20% were olivine. The track production rate from[3] was used to estimate the surface exposure times of the grains in this study. The majority of exposure times are in the 1 -5 MY range for all intervals. The lowest value was 3.8x 10¬5years in Interval 8and the highest value was1.1x 107years in Interval 6. Grains with the highest solar wind damage rim thicknesses and SEP track densities are found in Interval 6.The highest rim thickness and track density observed for anorthiteis126.5 nm and4.7 x 1011tracks/cm2, while for olivine they are 98.6 nm and 1.83 x 1011tracks/cm2, respectively. Discussion: Intervals from the top 4 cm of 73002 show similar SEP track density and solar wind damaged rim thickness distributions. Spectral and ferromagnetic resonance measurements of 73002 indicate an in-situ reworking zone up to~8 cm below the surface[5,6].The depth analyzed in this work is within the core’s uppermost in-situ reworking zone and may serve as an explanation to the homogenous distribution of exposure ages. The decreasing abundance of space weathered features with depth is consistent with regolith mixing models showing an exponential decay in regolith maturity with depth over time[7].A maximum surface exposure age determined via SEP track density is approximately 10million years. This timescale is consistent with the lower estimate of surface exposure ages of the light mantle determined in previous studies, which can range from 10s to over 100 Ma [4].It also falls within the core regolith reworking development timescale of ~17 Ma [5,6]. Additional analysis will be performed for a further seven intervals in 73002.

J A McFadden↗
NASA NTRS2007

Characteristics of Cometary Dust Tracks in Stardust Aerogel and Laboratory Calibrations

The cometary tray of the NASA Stardust spacecraft s aerogel collector has been examined to study the dust that was captured during the 2004 fly by of comet 81P/Wild-2. An optical scan of the entire collector surface revealed 256 impact features in the aerogel (width > 100 microns). 20 aerogel blocks (out of a total of 132) were removed from the collector tray for a higher resolution optical scan and 186 tracks were observed (track length > 50 microns and width > 8 microns). The impact features were classified into three types based on their morphology. Laboratory calibrations were conducted which reproduce all three types. This work suggests that the cometary dust consisted of some cohesive, relatively strong particles as well as particles with a more friable or low cohesion matrix containing smaller strong grains. The calibrations also permitted a particle size distribution to be estimated for the cometary dust. We estimate that approximately 1200 particles bigger than 1 micron struck the aerogel. The cumulative size distribution of the captured particles was obtained and compared with observations made by active dust detectors during the encounter. At large sizes (>20 microns) all measures of the dust are compatible, but at micrometer scales and smaller discrepancies exist between the various measurement systems which may reflect structure in the dust flux (streams, clusters etc.) along with some possible instrument effects.

Burchell, M. J.↗
NASA NTRS1980

Simulator study of conventional general aviation instrument displays in path-following tasks with emphasis on pilot-induced oscillations

A study of the use of conventional general aviation instruments by general aviation pilots in a six degree of freedom, fixed base simulator was conducted. The tasks performed were tracking a VOR radial and making an ILS approach to landing. A special feature of the tests was that the sensitivity of the displacement indicating instruments (the RMI, CDI, and HSI) was kept constant at values corresponding to 5 n. mi. and 1.25 n. mi. from the station. Both statistical and pilot model analyses of the data were made. The results show that performance in path following improved with increases in display sensitivity up to the highest sensitivity tested. At this maximum test sensitivity, which corresponds to the sensitivity existing at 1.25 n. mi. for the ILS glide slope transmitter, tracking accuracy was no better than it was at 5 n. mi. from the station and the pilot aircraft system exhibited a marked reduction in damping. In some cases, a pilot induced, long period unstable oscillation occurred.

Adams, J. J.↗