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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Properties of young clusters near reflection nebulae

Near infrared observations in the reflection nebulae NGC 7023, 2023, and 2068 are used to study clusters of young stars found associated with these nebulae. At least 30% to 60% of these stars are pre-main sequence objects, as indicated by their infrared excesses, hydrogen line emission, or irregular variability. The spatial distributions and observed luminosity functions of these young open clusters are derived, and the inferred mass function and star formation efficiencies are discussed.

Sellgren, K.↗
NASA NTRS1983

Properties of young clusters near reflection nebulae

Near infrared observations in the reflection nebulae NGC 703, 2023, and 2068 are used to study clusters of young stars found associated with these nebulae. At least 30 percent to 60 percent of these stars are pre-main sequence objects, as indicated by their infrared excesses, hydrogen line emission, or irregular variability. The spatial distributions and observed luminosity functions of these young open clusters are derived, and the inferred mass function and star formation efficiencies are discussed. Previously announced in STAR as N83-25628

Sellgren, K.↗
NASA NTRS1988

Where do the Apollo objects come from?

The orbital evolutions of 1-45 km-diameter Apollo and Amor bodies generated by asteroid belt collisions interior to 2.6 AU are presently traced by Monte Carlo calculations. About 3 percent of the asteroidal fragments of this type and size that are ejected with velocities of 100 m/sec are perturbed into earth-crossing orbits by the 3:1 Jovian commensurability resonance at 2.5 AU, as well as a secular resonance in the innermost asteroid belt. While the initial earth-crossing orbits of these bodies are concentrated near 1 AU, their steady-state orbital distribution is widely dispersed. Additional objects that may be characterized as inactive comets are inferred from strongly suggestive data.

Wetherill, G. W.↗
NASA NTRS1990

Measurements of CH4, N2O, CO, H2O, and O3 in the middle atmosphere by the Atmospheric Trace Molecule Spectroscopy Experiment on Spacelab 3

The volume mixing ratios of five minor gases (CH4, N2O, CO, H2O, and O3) have been retrieved through the middle atmosphere from the analysis of 0.01/cm resolution infrared solar occultation spectra recorded near 28 deg N and 48 deg S latitudes with the Atmospheric Trace Molecule Spectroscopy instrument, flow on board Spacelab 3 (April 30 through May 6, 1985). The results are in general agreement with reported measurements from ground-, balloon-, and satellite-based instruments for the same seasons. In detail, the vertical profiles of these gases show the effects of the upper and middle atmospheric transport patterns dominant during the season of these observations. The profiles inferred at different longitudes around 28 deg N suggest a near-uniform zonal distribution of these gases, for conditions corresponding to late spring. The sunrise occultation measurements point to a larger longitudinal variability in the vertical distribution of these gases at 48 deg S.

Gunson, M. R.↗
NASA NTRS1991

Measurements in polar stratospheric clouds over Antarctica in September 1989

The results of six balloon flights at McMurdo Station, Antarctica, under varying temperature conditions, are used in a study of polar stratospheric clouds during Sept. 1989. A particle counter, with size resolution in the 0.5 micron radius region, indicates that cloud size distributions are always bimodal. Mode radii ranging from 0.05 to 0.10 microns were observed for the small particle mode, representing the sulfate layer or condensational growth enhancements of it. The data are not inconsistent with the expected increase in size with decreasing temperature of the small particle mode in the sulfate layer owing to deliquescence although this phenomenon is often masked by nitric acid trihydrate (NAT) condensation when temperatures are sufficiently low. Mode radii generally ranged from 1.5 to 3.5 micron for the large particle mode at concentrations 3 to 4 orders of magnitude lower than the small particle mode. The large particle mode, which normally comprises most of the mass, is presumably caused by NAT condensation on larger particles of the sulfate layer and indicates HNO3 mixing ratios of 1 to 5 ppbv for most of the cloud layers observed, suggesting substantial denitrification. On several occasions, distributions were observed with mode radii as high as 7 microns, and correspondingly large inferred mass, indicating water ice clouds in the 12 to 15 km region. On other occasions, absence of such clouds at very low temperatures indicated water vapor mixing ratios of less than 3 ppmv suggesting dehydration. Generally, the inferred HNO3 mixing ratios were higher in the lower stratosphere, suggesting redistribution through particle sedimentation.

Deshler, Terry↗
NASA NTRS1991

Cyclic AMP-receptor proteins in heart muscle of rats flown on Cosmos 1887

The cellular compartmentalization of the cyclic AMP-receptor proteins in heart ventricular tissue obtained from rats flown on the Cosmos 1887 is determined. Photoaffinity labeling of soluble and particular cell fractions with a (32P)-8-azido analog of cyclic AMP is followed by electrophoretic separation of the proteins and by autoradiographic identification of the labeled isoforms of cAPK R subunits. It is shown that RII in the particulate subcellular fraction was significantly decreased in heart cells from rats in the flight group when compared to controls. Protein banding patterns in both the cytoplasmic fraction and in a fraction enriched in chromatin-bound proteins exhibited some variability in tissues of individual animals, but showed no changes that could be directly attributed to flight conditions. No significant change was apparent in the distribution of RI or RII cyclic AMP binding in the soluble fractions. It is inferred that the cardiac cell integrity or its protein content is not compromised under flight conditions.

Mednieks, Maija I.↗
NASA NTRS1995

Understanding COMPTEL Al-26 1.8 MeV map features

The COMPTEL sky map of the 1.8 MeV line emission from Al-26 shows an extended diffuse distribution along the Galactic plane with a peculiar large scale asymmetry about the Galactic center (GC) and a clumpy structure with several noticeable hot spots. The most prominent hot spot at the GC appears shifted to positive longitude by about 2 deg. Nearby supernova remnants or Wolf-Rayet stars are plausible explanations for individual hot spots such as in the Vela region. We show that the global asymmetry and most hot spots can be understood by a more general model: the Al-26 sources are confined in the spiral arms of our Galaxy, and coagent star formation is responsible for additional clumpiness. The off-centered GC hot spot is probably due to the observed asymmetrically distributed circumnuclear molecular gas interacting with a central stellar bar, whose existence has been inferred from IR observations.

Chen, Wan↗
NASA NTRS2006

Analysis of ISS Plasma Interaction

To date, the International Space Station (ISS) has been one of the largest objects flown in lower earth orbit (LEO). The ISS utilizes high voltage solar arrays (160V) that are negatively grounded leading to pressurized elements that can float negatively with respect to the plasma. Because laboratory measurements indicate a dielectric breakdown potential difference of 80V, arcing could occur on the ISS structure. To overcome the possibility of arcing and clamp the potential of the structure, two Plasma Contactor Units (PCUs) were designed, built, and flown. Also a limited amount of measurements of the floating potential for the present ISS configuration were made by a Floating Potential Probe (FPP), indicating a minimum potential of 24 Volts at the measurement location. A predictive tool, the ISS Plasma Interaction Model (PIM) has been developed accounting for the solar array electron collection, solar array mast wire and effective conductive area on the structure. The model has been used for predictions of the present ISS configuration. The conductive area has been inferred based on available floating potential measurements. Analysis of FPP and PCU data indicated distribution of the conductive area along the Russian segment of the ISS structure. A significant input to PIM is the plasma environment. The International Reference Ionosphere (IRI 2001) was initially used to obtain plasma temperature and density values. However, IRI provides mean parameters, leading to difficulties in interpretation of on-orbit data, especially at eclipse exit where maximum charging can occur. This limits our predicative capability. Satellite and Incoherent Scatter Radar (ISR) data of plasma parameters have also been collected. Approximately 130,000 electron temperature (Te) and density (Ne) pairs for typical ISS eclipse exit conditions have been extracted from the reduced Langmuir probe data flown aboard the NASA DE-2 satellite. Additionally, another 18,000 Te and Ne pairs of ISR data from several radar locations around the globe were used to assure consistency of the satellite data. PIM predictions for ISS charging made with this data correlated very well with FPP data, indicating that the general physics of spacecraft charging with high voltage solar arrays have been captured. The predictions also provided the probabilities of occurrences for ISS charging. These probabilities give a numerical measure of the number of times when the ISS will approach or exceed the vehicle plasma hazard conditions for each configuration. In this paper we shall present the interaction mechanisms between the ISS and the surrounding plasma and give an overview of the PIM components. PIM predictions are compared with available data followed by a discussion of the variability of plasma parameters and the conductive area on the ISS. The ISS PIM will be further tested and verified as data from the Floating Potential Measurement Unit become available, and construction of the ISS continues.

Reddell, Brandon↗
NASA NTRS2004

Objective Lightning Forecasting at Kennedy Space Center/Cape Canaveral Air Force Station using Cloud-to-Ground Lightning Surveillance System Data

The 45th Weather Squadron (45 WS) forecasters at Cape Canaveral Air Force Station (CCAFS) in Florida include a probability of thunderstorm occurrence in their daily morning briefings. This information is used by personnel involved in determining the possibility of violating Launch Commit Criteria, evaluating Flight Rules for the Space Shuttle, and daily planning for ground operation activities on Kennedy Space Center (KSC)/CCAFS. Much of the current lightning probability forecast is based on a subjective analysis of model and observational data. The forecasters requested that a lightning probability forecast tool based on statistical analysis of historical warm-season (May - September) data be developed in order to increase the objectivity of the daily thunderstorm probability forecast. The tool is a set of statistical lightning forecast equations that provide a lightning occurrence probability for the day by 1100 UTC (0700 EDT) during the warm season. This study used 15 years (1989-2003) of warm season data to develop the objective forecast equations. The local CCAFS 1000 UTC sounding was used to calculate stability parameters for equation predictors. The Cloud-to-Ground Lightning Surveillance System (CGLSS) data were used to determine lightning occurrence for each day. The CGLSS data have been found to be more reliable indicators of lightning in the area than surface observations through local informal analyses. This work was based on the results from two earlier research projects. Everitt (1999) used surface observations and rawinsonde data to develop logistic regression equations that forecast the daily thunderstorm probability at CCAFS. The Everitt (1999) equations showed an improvement in skill over the Neumann-Pfeffer thunderstorm index (Neumann 1971), which uses multiple linear regression, and also persistence and climatology forecasts. Lericos et al. (2002) developed lightning distributions over the Florida peninsula based on specific flow regimes. The flow regimes were inferred from the average wind direction in the 1000-700 mb layer at Miami (MIA), Tampa (TBW), and Jacksonville (JAX), Florida, and the lightning data were from the National Lightning Detection Network. The results suggested that the daily flow regime may be an important predictor of lightning occurrence on KSC/CCAFS.

Lambert, Winifred↗
DOE OSTI2021

On the Stochastic Stability of Deep Markov Models

Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. DMMs using deep neural networks to parametrize the transition of Markov probability distributions have recently been shown to provide more expressiveness in modeling sequential data and dynamical system responses. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we present a rigorous analytical method to prove the necessary and sufficient conditions of DMM's stochastic stability. This task is achieved by spectral analysis of the efficiently computed Jacobians of probabilistic maps modeled by deep neural networks. We make theoretical connections between the eigenvalues of neural network's weights and the different activation function types used on the stability and overall dynamic behavior of DMMs with Gaussian distributions. We empirically substantiate our theoretical results on stochastic stability and eigenvalue spectra via several numerical experiments. Formal stability guarantees of DMMs can substantially improve their robustness and trustworthiness, necessary for reliable use in safety-critical real-world applications.

Drgona, Jan↗
DOE OSTI2026

MULTI-FIDELITY MODELING AND UNCERTAINTY QUANTIFICATION OF INVERTER BASED RESOURCES IN INTEGRATED T&D SYSTEMS

Uncertainty quantification plays a pivotal role in improving the accuracy and reliability of inverter operation within modern power systems that are increasingly dominated by inverter-based resources (IBRs). IBRs, especially those operating under grid forming (GFM) control, rely heavily on a complex set of control parameters and system measurements to maintain voltage, frequency, and power balance. Traditional deterministic modeling approaches often fail to capture these parameter deviations, potentially resulting in suboptimal control actions, reduced system stability, or even instability under high penetration of IBRs. In this paper, we demonstrate the application of model calibration and uncertainty quantification (UQ) principles to an integrated transmission and distribution (T&D) model involving a GFM converter and provide a framework for prioritizing control improvements, guiding robust design, and informing adaptive strategies that can accommodate real-time variability in system conditions. The proposed approach could be valuable in enhancing the robustness of current and future power systems under increased IBR penetrations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2009

Understanding the Scalability of Bayesian Network Inference using Clique Tree Growth Curves

Bayesian networks (BNs) are used to represent and efficiently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to perform computation in BNs is clique tree clustering and propagation. In this approach, BN computation consists of propagation in a clique tree compiled from a Bayesian network. There is a lack of understanding of how clique tree computation time, and BN computation time in more general, depends on variations in BN size and structure. On the one hand, complexity results tell us that many interesting BN queries are NP-hard or worse to answer, and it is not hard to find application BNs where the clique tree approach in practice cannot be used. On the other hand, it is well-known that tree-structured BNs can be used to answer probabilistic queries in polynomial time. In this article, we develop an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of a BN's non-root nodes to the number of root nodes, or (ii) the expected number of moral edges in their moral graphs. Our approach is based on combining analytical and experimental results. Analytically, we partition the set of cliques in a clique tree into different sets, and introduce a growth curve for each set. For the special case of bipartite BNs, we consequently have two growth curves, a mixed clique growth curve and a root clique growth curve. In experiments, we systematically increase the degree of the root nodes in bipartite Bayesian networks, and find that root clique growth is well-approximated by Gompertz growth curves. It is believed that this research improves the understanding of the scaling behavior of clique tree clustering, provides a foundation for benchmarking and developing improved BN inference and machine learning algorithms, and presents an aid for analytical trade-off studies of clique tree clustering using growth curves.

Mengshoel, Ole Jakob↗
NASA NTRS1989

Gravity wave structure between 60 and 90 km inferred from Space Shuttle reentry data

Density fluctuations obtained along seven Space Shuttle reentry tracks are used to examine the horizontal structure and the vertical distribution of density variance in the mesosphere and lower thermosphere. The tracks lie primarily over open ocean at middle and low latitudes and represent the only measurements of horizontal atmospheric structure at these heights available to date. The density fluctuations are interpreted in terms of gravity-wave motions and reveal significant density (and velocity) variance at horizontal scales ranging from about 10 to 1000 km. Fluctuation amplitudes are used to infer corresponding velocity perturbations and characteristic vertical scales and frequencies of the wave spectrum. Results suggest that the mean velocity variance is smaller over the Pacific ocean than over major land masses, and that the variance increases with height in a manner consistent with that expected in the present of wave saturation processes.

Fritts, David C.↗
DOE OSTI2023

Zero-truncated Poisson regression for sparse multiway count data corrupted by false zeros

Abstract We propose a novel statistical inference methodology for multiway count data that is corrupted by false zeros that are indistinguishable from true zero counts. Our approach consists of zero-truncating the Poisson distribution to neglect all zero values. This simple truncated approach dispenses with the need to distinguish between true and false zero counts and reduces the amount of data to be processed. Inference is accomplished via tensor completion that imposes low-rank tensor structure on the Poisson parameter space. Our main result shows that an $N$-way rank-$R$ parametric tensor $\boldsymbol{\mathscr{M}}\in (0,\infty )^{I\times \cdots \times I}$ generating Poisson observations can be accurately estimated by zero-truncated Poisson regression from approximately $IR^2\log _2^2(I)$ non-zero counts under the nonnegative canonical polyadic decomposition. Our result also quantifies the error made by zero-truncating the Poisson distribution when the parameter is uniformly bounded from below. Therefore, under a low-rank multiparameter model, we propose an implementable approach guaranteed to achieve accurate regression in under-determined scenarios with substantial corruption by false zeros. Several numerical experiments are presented to explore the theoretical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Progress on the National Solar Radiation Data Base (NSRDB): A New DNI Computation

This study introduces a new technique to compute direct normal irradiance (DNI) for improving the National Solar Radiation Data Base (NSRDB). A finite-surface integration algorithm is developed to compute solar radiation in differential solid angles and efficiently infer its contribution to a surface perpendicular to the solar direction. A lookup table of cloud bi-directional transmittance distribution function (BTDF) is developed by use of the discrete ordinates radiative transfer (DISORT) model for possible solar and observing directions and various cloud optical and microphysical properties. In each solar incident direction, DNI is given by the cloud BTDFs from approximately 200 differential solid angles. The simulated DNI is calibrated and evaluated using surface observations at the National Renewable Energy Laboratory's (NREL's) Solar Energy Research Laboratory (SRRL) and the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) facility.

41 EE - Solar Energy Technologies Office (EE-4S)↗
NASA NTRS1991

Strong plasma turbulence in the earth's electron foreshock

A quantitative model is developed to account for the distribution in magnitude and location of the intense plasma waves observed in the earth's electron foreshock given the observed rms levels of waves. In this model, nonlinear strong-turbulence effects cause solitonlike coherent wave packets to form and decouple from incoherent background beam-excited weak turbulence, after which they convect downstream with the solar wind while collapsing to scales as short as 100 m and fields as high as 2 V/m. The existence of waves with energy densities above the strong-turbulence wave-collapse threshold is inferred from observations from IMP 6 and ISEE 1 and quantitative agreement is found between the predicted distribution of fields in an ensemble of such wave packets and the actual field distribution observed in situ by IMP 6. Predictions for the polarization of plasma waves and the bandwidth of ion-sound waves are also consistent with the observations. It is shown that strong-turbulence effects must be incorporated in any comprehensive theory of the propagation and evolution of electron beams in the foreshock. Previous arguments against the existence of strong turbulence in the foreshock are refuted.

Robinson, P. A.↗
DOE OSTI2026

Real-Time Inference For MI/RR Deblending

The Fermilab Main Injector (MI) and Recycler Ring (RR) share a common beam loss monitor (BLM) system, making loss events difficult to attribute to their source machine when beam is present in both simultaneously. The Real-time Edge AI for Distributed Systems (READS) project addresses this by deblending BLM readings in real time using machine learning (ML). The current FPGA based implementation meets the sub-3 ms latency requirement but carries a resource intensive hls4ml development cycle, motivating exploration of GPU based deployment. This paper characterizes inference latency on an NVIDIA Jetson Orin Nano and introduces a packet organization scheme for assembling synchronized event frames from seven distributed BLM DAQ streams. Using a Python based DAQ simulation with injected timing jitter in place of unavailable live beam data, the pipeline achieved an average end to end latency of 0.456 ms (σ = 0.122 ms) across 167,000 test frames, comfortably meeting the timing constraint. Early outliers were attributed to TensorRT warm-up rather than steady state limitations, suggesting GPU based inference is a viable alternative to the existing FPGA implementation.

Yu, Kellen [Cornell U.]↗
DOE OSTI2025

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

adaptation models↗