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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

PV-Finder: ML Based Algorithm for Primary Vertex Identification

he CMS detector at the High-Luminosity Large Hadron Collider (HL-LHC) will operate in challenging conditions with expected pile-up of up to 200 collisions per bunch crossing, necessitating the development of a more resilient primary vertex (PV) reconstruction method to ensure the integrity of data analysis and the efficiency of the CMS triggering system. This contribution describes preliminary studies on a new ML based PV-Finder method for PV identification. The method is based on a model trained using Kernel Density Estimations (KDEs) derived from the positions of reconstructed tracks at the beamline, incorporating uncertainties from track parameters. It also utilizes target histograms, modeled as Gaussian distributions centered on the actual ground truth values of specific primary vertices.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Anomaly Detection in Connected and Autonomous Vehicle Trajectories Using LSTM Autoencoder and Gaussian Mixture Model

Connected and Autonomous Vehicles (CAVs) technology has the potential to transform the transportation system. Although these new technologies have many advantages, the implementation raises significant concerns regarding safety, security, and privacy. Anomalies in sensor data caused by errors or cyberattacks can cause severe accidents. To address the issue, this study proposed an innovative anomaly detection algorithm, namely the LSTM Autoencoder with Gaussian Mixture Model (LAGMM). This model supports anomalous CAV trajectory detection in the real-time leveraging communication capabilities of CAV sensors. The LSTM Autoencoder is applied to generate low-rank representations and reconstruct errors for each input data point, while the Gaussian Mixture Model (GMM) is employed for its strength in density estimation. The proposed model was jointly optimized for the LSTM Autoencoder and GMM simultaneously. The study utilizes realistic CAV data from a platooning experiment conducted for Cooperative Automated Research Mobility Applications (CARMAs). The experiment findings indicate that the proposed LAGMM approach enhances detection accuracy by 3% and precision by 6.4% compared to the existing state-of-the-art methods, suggesting a significant improvement in the field.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Functional Data Analysis for Extracting the Intrinsic Dimensionality of Spectra: Application to Chemical Homogeneity in the Open Cluster M67

High-resolution spectroscopic surveys of the Milky Way have entered the Big Data regime and have opened avenues for solving outstanding questions in Galactic archeology. However, exploiting their full potential is limited by complex systematics, whose characterization has not received much attention in modern spectroscopic analyses. In this work, we present a novel method to disentangle the component of spectral data space intrinsic to the stars from that due to systematics. Using functional principal component analysis on a sample of 18,933 giant spectra from APOGEE, we find that the intrinsic structure above the level of observational uncertainties requires ≈10 functional principal components (FPCs). Our FPCs can reduce the dimensionality of spectra, remove systematics, and impute masked wavelengths, thereby enabling accurate studies of stellar populations. To demonstrate the applicability of our FPCs, we use them to infer stellar parameters and abundances of 28 giants in the open cluster M67. We employ Sequential Neural Likelihood, a simulation-based Bayesian inference method that learns likelihood functions using neural density estimators, to incorporate non-Gaussian effects in spectral likelihoods. By hierarchically combining the inferred abundances, we limit the spread of the following elements in M67: Fe ≲ 0.02 dex; C ≲ 0.03 dex; O, Mg, Si, Ni ≲ 0.04 dex; Ca ≲ 0.05 dex; N, Al ≲ 0.07 dex (at 68% confidence). Our constraints suggest a lack of self-pollution by core-collapse supernovae in M67, which has promising implications for the future of chemical tagging to understand the star formation history and dynamical evolution of the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-scale Structure Using Sequential Methods

Strong gravitational lenses are a singular probe of the Universe’s small-scale structure—they are sensitive to the gravitational effects of low-mass (<10 10 M ⊙ ) halos even without a luminous counterpart. Recent strong-lensing analyses of dark matter structure rely on simulation-based inference (SBI). Modern SBI methods, which leverage neural networks as density estimators, have shown promise in extracting the halo-population signal. However, it is unclear whether the constraints from these models are limited by the methodology or the data. In this study, we introduce an accelerator-optimized simulation pipeline that can generate lens images with realistic subhalo populations in milliseconds. Leveraging this simulator, we identify the main limitation of our fiducial SBI analysis: training set size. We then adopt a sequential neural posterior estimation (SNPE) approach, allowing us to refine the training distribution to align with the observed data. Using only one-fifth as many mock Hubble Space Telescope images, SNPE matches the constraints on the low-mass halo population produced by our best nonsequential model. Our experiments suggest that an over 3 order-of-magnitude increase in training set size and GPU hours would be required to achieve an equivalent result without sequential methods. While the full potential of the existing lens sample remains to be explored, the notable improvement in constraining power enabled by our sequential approach highlights that current constraints are limited primarily by methodology and not the data itself. Moreover, our results emphasize the need to treat training set generation and model optimization as interconnected stages of any cosmological analysis using SBI.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1965

Plasma pressures in the magnetosphere

Plasma energy density estimation near equatorial magnetopause considering only solar wind protons and plasma effect on geomagnetic field

PLASMA SPECTRUM↗
NASA NTRS1971

Boundary layer transition detection on the X-15 vertical fin using surface-pressure-fluctuation measurements

A flush-mounted microphone on the vertical fin of an X-15 airplane was used to investigate boundary layer transition phenomenon during flights to peak altitudes of approximately 70,000 meters. The flight results were compared with those from wind tunnel studies, skin temperature measurements, and empirical prediction data. The Reynolds numbers determined for the end of transition were consistent with those obtained from wind tunnel studies. Maximum surface-pressure-fluctuation coefficients in the transition region were about an order of magnitude greater than those for fully developed turbulent flow. This was also consistent with wind tunnel data. It was also noted that the power-spectral-density estimates of the surface-pressure fluctuations were characterized by a shift in power from high frequencies to low frequencies as the boundary layer changed from turbulent to laminar flow. Large changes in power at the lowest frequencies appeared to mark the beginning of transition.

Lewis, T. L.↗
NASA NTRS1971

The minimum distance approach to classification

The work to advance the state-of-the-art of miminum distance classification is reportd. This is accomplished through a combination of theoretical and comprehensive experimental investigations based on multispectral scanner data. A survey of the literature for suitable distance measures was conducted and the results of this survey are presented. It is shown that minimum distance classification, using density estimators and Kullback-Leibler numbers as the distance measure, is equivalent to a form of maximum likelihood sample classification. It is also shown that for the parametric case, minimum distance classification is equivalent to nearest neighbor classification in the parameter space.

Wacker, A. G.↗
NASA NTRS1973

Phase 1 of the earth resources data analysis program

Research completed in the Earth Resources Data Analysis Program is discussed along with recommendations for future study. Projects discussed include use of the Cholesky decomposition in feature selection and classification algorithms; optimal feature selection and extraction, probability density estimation and nonparametric classifiers; use of spatial information in classification; and model for crop row reflectance. The installation of LARSYS on the ICSA's IBM 370/155 is discussed, and a list of technical reports is included.

Source record↗
NASA NTRS1974

Earth resources data analysis program, phase 2

The efforts and findings of the Earth Resources Data Analysis Program are summarized. Results of a detailed study of the needs of EOD with respect to an applications development system (ADS) for the analysis of remotely sensed data, including an evaluation of four existing systems with respect to these needs are described. Recommendations as to possible courses for EOD to follow to obtain a viable ADS are presented. Algorithmic development comprised of several subtasks is discussed. These subtasks include the following: (1) two algorithms for multivariate density estimation; (2) a data smoothing algorithm; (3) a method for optimally estimating prior probabilities of unclassified data; and (4) further applications of the modified Cholesky decomposition in various calculations. Little effort was expended on task 3, however, two reports were reviewed.

Source record↗
NASA NTRS1976

Statistical model of meteor streams. IV - A study of radio streams from the synoptic year

The paper gives a detailed description of a search procedure for radio meteor streams and reports the detection of 275 streams in a synoptic-year sample of 19,698 radio meteors observed by the radar system of the Radio Meteor Project at Havana, Illinois. The orbital elements and related parameters of the detected streams are presented, the two parameters of the D-distribution of the streams are determined, and their mean radiants are plotted. Possible associations between the streams and possible parent objects are identified; it is found that streams may be associated with seven periodic comets, five other comets, at least nine asteroids (especially Adonis), and several fireballs. The mean space density in the streams is found to be much lower than the sporadic density, although the central density may be considerably greater than the sporadic density. It is shown that the derived absolute stream-density values are in agreement with the order of magnitude of the space densities estimated from cometary production rates for solid material of comparable particle size.

Sekanina, Z.↗
NASA NTRS1980

A hill-sliding strategy for initialization of Gaussian clusters in the multidimensional space

A hill sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimate of sample data for the first step of iterative unsupervised classification. Each cluster was assumed to posses a unimodal normal distribution. A clustering function proposed distinguished elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with LANDSAT multispectral scanner data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill sliding clustering technique developed herein has the potential applicability to decomposition any multivariate mixture distribution into a number of unimodal distributions when an appropriate distribution function to the data set is employed.

Park, J. K.↗
NASA NTRS1979

Chemical stratification of the mantle

A possible scenario for the chemical stratification of the earth's mantle is presented. Differentiation of the mantle by either the production of basaltic magmas or partial melting by the upper mantle is proposed to lead to a thick basalt layer, the lower part of which is converted to eclogite as the earth cools. Density estimates indicate that the eclogite formed would not be able to sink to below 670 km. The eclogite layer is thus demonstrated to be trapped as a result of whole-mantle convection and possible irreversible differentiation of the mantle into eclogite and overlying residual peridotite layers.

Anderson, D. L.↗
NASA NTRS1980

Observations of SO in dark and molecular clouds

The 1(0)-0(1) transition of SO at 30 GHz has been observed in several sources, including the first detection of sulfur monoxide in cold dark clouds without apparent internal energy sources. The SO transition appears to be an excellent tracer of structure in dark clouds, and the data support suggestions that self-absorption is important in determining emission profiles in such regions for large line-strength transitions. Column densities estimated from a comparison of the results for the two isotopic species indicate a high fractional abundance of SO in dark clouds.

Rydbeck, O. E. H.↗
NASA NTRS1982

The Crab Nebula. I - Spectrophotometry of the filaments

Relative line intensities in the 3700-7400 A region are obtained from new spectrophotometric measurements of ten positions in the Crab Nebula. O III forbidden line intensities imply electron temperatures of 11,000-18,300 K, while generally lower temperatures are indicated by the O II, N II and S II forbidden lines. The 6717 and 6731 A forbidden S II line ratio yields electron density estimates of 550-3500/cu cm, with a typical filament value of 1300 cu cm. While Balmer decrements are generally consistent with pure recombination, some filaments show steeper decrements. He line intensities are found to have significant variation. The presence of a moderately strong line at 7378 A, which may be due to the Ni II forbidden line is confirmed. Some filaments are found to exhibit a wide range of ionization states.

Fesen, R. A.↗
NASA NTRS1982

Cross-validation for densities and regressions

Virtually all nonparametric (infinite dimensional) problems require the choice of a smoothing parameter. It is natural to attempt to use the data to guide the choice of this parameter. The most widely applicable data driven technique is cross validation. The method of cross validation is introduced and results are presented which establish consistency for certain cross validated density estimators and consistency as well as asymptotic normality for rigid regression.

Geman, S.↗