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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Measure the Propagation of a Halo CME and Its Driven Shock with the Observations from a Single Perspective at Earth

We present a detailed study of an Earth-directed coronal mass ejection (full-halo CME) event that happened on 2011 February 15, making use of white-light observations by three coronagraphs and radio observations by Wind /WAVES. We applied three different methods to reconstruct the propagation direction and traveling distance of the CME and its driven shock. We measured the kinematics of the CME leading edge from white-light images observed by Solar Terrestrial Relations Observatory ( STEREO ) A and B , tracked the CME-driven shock using the frequency drift observed by Wind /WAVES together with an interplanetary density model, and obtained the equivalent scattering centers of the CME by the polarization ratio (PR) method. For the first time, we applied the PR method to different features distinguished from LASCO/C2 polarimetric observations and calculated their projections onto white-light images observed by STEREO-A and STEREO-B . By combining the graduated cylindrical shell (GCS) forward modeling with the PR method, we proposed a new GCS-PR method to derive 3D parameters of a CME observed from a single perspective at Earth. Comparisons between different methods show a good degree of consistence in the derived 3D results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Framework for Analysis and Visualization of Simulation Data (VizAly)

As supercomputing resources increase, cosmological scientists are able to run more detailed and larger simulations generating massive amounts of data. Analyzing these simulations with an available open-source toolkit is important for collaborative Department of Energy scientific discovery across labs, universities, and other partners. Developed software as a part of this collection include: comparing data with other existing simulations, verifying and validating results with observation databases, new halo finder algorithms, and using analytical tools to get insights into the physics of the cosmological universe. The goal of this software project is to provide a set of open-source libraries, tools, and packages for large-scale cosmology that allows scientists to visualize, analyze, and compare large-scale simulation and observational data sets. Developed software will provide a variety of methods for processing, visualization, and analysis of astronomical observation and cosmological simulation data. These tools are intended for deployment on multiple scientific computing platforms, including but not limited to personal computers, cloud computing, experimental sites (telescopes) and high performance supercomputers.

Wendelberger, Joanne↗
NASA NTRS1988

On the nature of the fragment environment created by the range destruction or random failure of solid rocket motor casings

Given here are predictions of fragment velocities and azimuths resulting from the Space Transportation System Solid Rocket Motor range destruct, or random failure occurring at any time during the 120 seconds of Solid Rocket Motor burn. Results obtained using the analytical methods described showed good agreement between predictions and observations for two specific events. It was shown that these methods have good potential for use in predicting the fragmentation process of a number of generically similar casing systems. It was concluded that coupled Eulerian-Lagrangian calculational methods of the type described here provide a powerful tool for predicting Solid Rocket Motor response.

Eck, M.↗
NASA NTRS1995

CME masses measured by the HELIOS spacecraft photometers

We have cataloged 160 CMEs detected in the HELIOS 1 and 2 90 deg zodiacal light photometers observed from 1975-1985. The HELIOS 1 and 2 spacecraft orbited from 0.3 to 1.0 AU on 6-month orbits. From the photometer observations of Thomson-scattered light in the inner heliosphere, we have determined CME masses for these events using two methods: (1) by integration over the contours drawn between the three photometers at a given time; and (2) by integration of the mass flow over time past a given photometer. The second method, not readily available using coronagraph observations, is derived from CME speeds measured by using the timing of the peak CME brightness from the 16 deg to 31 deg sets of photometers. The two different HELIOS methods of determining CME mass are consistent with one another for individual CMEs. We find that the CME mass values range from 10(exp 15)g to nearly 10(exp 17)g. We compare the mass distributions of HELIOS-measured CMEs with those from coronagraphs and find that CMEs measured by HELIOS over the same time interval are generally more massive. The solar cycle variation of the total CME mass present in the heliosphere varies by over a factor of approximately 15 from solar minimum to solar maximum. Slightly more massive CMEs carry the bulk of the CME mass during maximum. The total CME mass at solar maximum is found to be near 15% of the total solar wind mass.

Jackson, B. V.↗
NASA NTRS2016

Lunar Entry Downmode Options for Orion

For Exploration Missions 1 and 2, the Orion capsules will be entering the Earth's atmosphere with speeds in excess of 11 km/s. In the event of a degraded Guidance, Navigation, and Control system, attempting the nominal guided entry may be inadvisable due to the potential for failures that result in a loss of vehicle (or crew, when crew are aboard). In such a case, a method of assuring Earth capture, water landing, and observence of trajectory constraints (heating, loads) is desired. Such a method should also be robust to large state uncertainty and variations in entry interface states. This document will explore four approaches evaluated and their performance in ensuring a safe return of the Orion capsule in the event of onboard system degradation.

Smith, Kelly M.↗
DOE OSTI2014

In operando observation system for electrochemical reaction by soft X-ray absorption spectroscopy with potential modulation method

In order to investigate local structures of electrolytes in electrochemical reactions under the same scan rate as a typical value 100 mV/s in cyclic voltammetry (CV), we have developed an in operando observation system for electrochemical reactions by soft X-ray absorption spectroscopy (XAS) with a potential modulation method. XAS spectra of electrolytes are measured by using a transmission-type liquid flow cell with built-in electrodes. The electrode potential is swept with a scan rate of 100 mV/s at a fixed photon energy, and soft X-ray absorption coefficients at different potentials are measured at the same time. By repeating the potential modulation at each fixed photon energy, it is possible to measure XAS of electrochemical reaction at the same scan rate as in CV. We have demonstrated successful measurement of the Fe L-edge XAS spectra of aqueous iron sulfate solutions and of the change in valence of Fe ions at different potentials in the Fe redox reaction. The mechanism of these Fe redox processes is discussed by correlating the XAS results with those at different scan rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Spatially Mapping the CO 2 Alkaline Sorbent Diffuse Microenvironment Using Operando Raman Spectroscopy

When designing a chemical process, the local balance of transport and kinetics, collectively referred to as the diffuse microenvironment, plays a critical role in performance but is difficult to directly observe. This work demonstrates a method of two-dimensional spatial chemical mapping of the diffuse microenvironment in the context of alkali metal hydroxide direct air capture of carbon dioxide using a custom operando gas-absorption flow cell along with confocal Raman spectroscopy. Notably, we observe the concentration boundary layer near the gas–liquid interface and elucidate the interplay of carbonate and bicarbonate ions within it while inferring local hydroxide depletion through continuum modeling. These first of their kind observations provide a technique to compare the performance of direct air capture solvents based on diffuse microenvironment dynamics while also providing metrics important for air contactor design such as boundary layer thickness. Overall, this work showcases a new experimental platform to study interfacial diffuse microenvironments in and outside of the field of direct air capture of carbon dioxide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Deep learning methods for drug response prediction in cancer: Predominant and emerging trends

Cancer claims millions of lives yearly worldwide. While many therapies have been made available in recent years, by in large cancer remains unsolved. Exploiting computational predictive models to study and treat cancer holds great promise in improving drug development and personalized design of treatment plans, ultimately suppressing tumors, alleviating suffering, and prolonging lives of patients. A wave of recent papers demonstrates promising results in predicting cancer response to drug treatments while utilizing deep learning methods. These papers investigate diverse data representations, neural network architectures, learning methodologies, and evaluations schemes. However, deciphering promising predominant and emerging trends is difficult due to the variety of explored methods and lack of standardized framework for comparing drug response prediction models. To obtain a comprehensive landscape of deep learning methods, we conducted an extensive search and analysis of deep learning models that predict the response to single drug treatments. A total of 61 deep learning-based models have been curated, and summary plots were generated. Based on the analysis, observable patterns and prevalence of methods have been revealed. This review allows to better understand the current state of the field and identify major challenges and promising solution paths.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1987

Variability analysis in low count rate sources

A method, based on the chi-square statistics, is described for detecting pulselike time variability in low count rate sources observed with photon-counting instruments. This method can be used even in the presence of observational gaps, takes full advantage of the filtering effect due to binning with different bin sizes, and takes into account the arbitrariness introduced by the binning phase. The procedure developed to limit the dependence of the results on the binning phase and ensure statistically correct results is described along with the application of the proposed procedure to a model of a variable source. Monte Carlo simulations are used to show how the method can be used to derive the characteristic variability time scales and that the method is more sensitive than the nonparametric Kolmogorov-Smirnov test in detecting variability to a given confidence level.

Collura, A.↗
DOE OSTI2024

Observation of d(t,n) α Neutrons Following d(d,p)t Reactions in a Deuterium Gas Cell: An Attempt to Repeat Ruhlig’s 1938 Observation of Secondary Reactions

In order to benchmark methods used to calculate reaction-in-flight fusion reactions in inertial confinement fusion and address issues related to the first claimed observation of d(t,n)α reactions in 1938, secondary d(t,n)α reactions have been observed following d(d,p)t reactions in deuterium gas. A pulsed 200-nA, 2.2-MeV deuterium beam from the Triangle Universities Nuclear Laboratory FN tandem accelerator was injected into a cylindrical multiatmosphere deuterium gas target. The incident beam traversed along the target cylinder’s 3-cm symmetry axis after its passage through a Havar entrance foil. Two different Havar foil thicknesses were used to obtain 1.5- and 0.6-MeV deuteron beams entering the deuterium cell. The cylinder’s radius was 2 cm to allow for d(d,p)t tritons emitted perpendicular to the beam to range out in the deuterium gas. The neutron emission from the cell was observed via its time of flight to a liquid scintillator placed at various angles to the beam direction, at a distance of 243 cm. Pulse-shape-discrimination techniques were used to separate neutron and gamma-ray signals seen in the liquid scintillator. The observed probability of ~2 × 10 –4 for inducing secondary d(t,n)α fusion in the gas cell per d(d,p)t reaction is consistent with theoretical expectations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Bayesian inverse modeling of the atmospheric transport and emissions of a controlled tracer release from a nuclear power plant

Probability distribution functions (PDFs) of model inputs that affect the transport and dispersion of a trace gas released from a coastal California nuclear power plant are quantified using ensemble simulations, machine-learning algorithms, and Bayesian inversion. The PDFs are constrained by observations of tracer concentrations and account for uncertainty in meteorology, transport, diffusion, and emissions. Meteorological uncertainty is calculated using an ensemble of simulations of the Weather Research and Forecasting (WRF) model that samples five categories of model inputs (initialization time, boundary layer physics, land surface model, nudging options, and reanalysis data). The WRF output is used to drive tens of thousands of FLEXPART dispersion simulations that sample a uniform distribution of six emissions inputs. Machine-learning algorithms are trained on the ensemble data and used to quantify the sources of ensemble variability and to infer, via inverse modeling, the values of the 11 model inputs most consistent with tracer measurements. We find a substantial ensemble spread in tracer concentrations (factors of 10 to 10 3 ), most of which is due to changing emissions inputs (about 80%), though the cumulative effects of meteorological variations are not negligible. The performance of the inverse method is verified using synthetic observations generated from arbitrarily selected simulations. When applied to measurements from a controlled tracer release experiment, the inverse method satisfactorily determines the location, start time, duration and amount. In a 2 km × 2 km area of possible locations, the actual location is determined to within 200m. The start time is determined to within 5min out of 2h, and the duration to within 50min out of 4h. Over a range of release amounts of 10 to 1000kg, the estimated amount exceeds the actual amount of 146kg by only 32kg. The inversion also estimates probabilities of different WRF configurations. In conclusion, to best match the tracer observations, the highest-probability cases in WRF are associated with using a late initialization time and specific reanalysis data products.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Interplanetary Propagation of Coronal Mass Ejections

Although more than ten thousand coronal mass ejections (CMEs) are produced during each solar cycle at the Sun, only a small fraction hits the Earth. Only a small fraction of the Earth-directed CMEs ultimately arrive at Earth depending on their interaction with the solar wind and other large-scale structures such as coronal holes and CMEs. The interplanetary propagation is essentially controlled by the drag force because the propelling force and the solar gravity are significant only near the Sun. Combined remote-sensing and in situ observations have helped us estimate the influence of the solar wind on the propagation of CMEs. However, these measurements have severe limitations because the remote-sensed and in-situ observations correspond to different portions of the CME. Attempts to overcome this problem are made in two ways: the first is to model the CME and get the space speed of the CME, which can be compared with the in situ speed. The second method is to use stereoscopic observation so that the remote-sensed and in-situ observations make measurements on the Earth-arriving part of CMEs. The Solar Terrestrial Relations Observatory (STEREO) mission observed several such CMEs, which helped understand the interplanetary evolution of these CMEs and to test earlier model results. This paper discusses some of these issues and updates the CME/shock travel time estimates for a number of CMEs.

Gopalswamy, Nat↗
DOE OSTI2015

Oscillator strength measurement for the A(0–6)–X(0), C(0)–X(0), and E(0)–X(0) transitions of CO by the dipole (γ, γ) method

The oscillator strengths of CO, especially for the excitations to the predissociating levels C{sup 1}Σ{sup +} and E{sup 1}Π, have significant applications in the studies of interstellar gases. A large number of investigations, applying a variety of experimental and calculational methods, have focused on the determination of these oscillator strengths. However, deviations of more than 10% have been observed, even for the same experimental method. In this case, we introduce a new technique, the dipole (γ, γ), to measure the oscillator strengths. The obtained oscillator strengths of the strong bands C{sup 1}Σ{sup +}(ν{sup ′}=0)−X{sup 1}Σ{sup +} and E{sup 1}Π(ν{sup ′}=0)−X{sup 1}Σ{sup +} in this work reach high accuracy and are in excellent agreement with some previous results, although they are different from the recommended values in other works. In addition, we measured the oscillator strengths of the A{sup 1}Π(ν{sup ′}=0−6)−X{sup 1}Σ{sup +} bands, and the electronic transition moment dependence on r-centroid was derived.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Combined $\mathrm{APOGEE}$-$\mathrm{GALAH}$ stellar catalogues using the Cannon

APOGEE and GALAH are two high resolution multi-object spectroscopic surveys that provide fundamental stellar parameters and multiple elemental abundance estimates for about half a million stars in the Milky Way. Both surveys observe in different wavelength regimes and use different data reduction pipelines leading to significant offsets and trends in stellar parameters and abundances for the common stars observed in both surveys. Such systematic differences/offsets in stellar parameters and abundances make it difficult to effectively utilize them to investigate Galactic abundance trends in spite of the unique advantage provided by their complementary sky coverage and different Milky Way components they observe. Hence, we use the Cannon data-driven method selecting a training set of 4418 common stars observed by both surveys. This enables the construction of two catalogues, one with the APOGEE-scaled and the other with the GALAH-scaled stellar parameters. Using repeat observations in APOGEE and GALAH, we find high precision in metallicity (~0.02–0.4 dex) and alpha abundances (~0.02–0.03 dex) for spectra with good signal-to-noise ratio (SNR >; 80 for APOGEE and SNR > 40 for GALAH). We use open and globular clusters to validate our parameter estimates and find small scatter in metallicity (0.06 dex) and alpha abundances (0.03 dex) in APOGEE-scaled case. The final catalogues have been cross-matched with the Gaia EDR3 catalogue to enable their use to carry out detailed chemo-dynamic studies of the Milky Way from perspectives of APOGEE and GALAH.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

Software reliability: Additional investigations into modeling with replicated experiments

The effects of programmer experience level, different program usage distributions, and programming languages are explored. All these factors affect performance, and some tentative relational hypotheses are presented. An analytic framework for replicated and non-replicated (traditional) software experiments is presented. A method of obtaining an upper bound on the error rate of the next error is proposed. The method was validated empirically by comparing forecasts with actual data. In all 14 cases the bound exceeded the observed parameter, albeit somewhat conservatively. Two other forecasting methods are proposed and compared to observed results. Although demonstrated relative to this framework that stages are neither independent nor exponentially distributed, empirical estimates show that the exponential assumption is nearly valid for all but the extreme tails of the distribution. Except for the dependence in the stage probabilities, Cox's model approximates to a degree what is being observed.

Nagel, P. M.↗
NASA NTRS1990

Modeling of solar oscillation power spectra

To produce accurate estimates of the line-profile parameters of a model used to represent the spectral features in a solar oscillation power spectrum, it is necessary to (1) select the appropriate probability density function when deriving the maximum-likelihood function to be employed for the parameter estimation and (2) allow for the redistribution of spectral power caused by gaps in the data string. This paper describes a maximum-likelihood method for estimating the model parameters (based on the observed power spectrum statistics) that accounts for redistribution of spectral power caused by gaps in the data string, by convolving the model with the power spectrum of the observed window function. The accuracy and reliability of the method were tested using both artificial and authentic solar oscillation power spectrum data. A comparison of this method with various least-squares techniques is also presented.

Anderson, Edwin R.↗
NASA NTRSDate not supplied

A Novel Framework for Multi-Path Data Fusion in Earth Observation and New Observing Strategies: Applications to Predicting Forest Canopy Height

Exponential growth of data from Earth Observation (EO) assets has necessitated the development of sophisticated methods for data interpretation and management. NASA’s New Observing Strategy (NOS) approach aims to coordinate operations among complex heterogenous systems of constellations, requiring advanced Artificial Intelligence and Machine Learning (AI/ML) techniques. Despite significant advancements in AI/ML across various domains, the EO and machine learning for satellite (SatML) fields remain fragmented, often relying on adapted techniques rather than domain-specific solutions. We present a novel end-to-end data fusion framework tailored specifically for EO and SatML, addressing this gap by facilitating rapid development of AI/ML applications. This framework, called, Multimodal Earth Observation Workflow for Machine Learning (MEOW-ML), sup- ports the entire AI/ML lifecycle, from dataset manipulation, to model training, evaluation, and logging, and is designed to expedite the development of next-generation NOS deployments and SOTA in EO. We apply our framework to predict canopy height model (CHM) derived from lidar data. We integrate multiple data modalities through a hierarchical, multi-path model architecture, effectively identifying and leveraging the unique strengths of each data source to enhance predictive accuracy. Our experiments demonstrate that the multi-path architecture outperforms traditional single-path models and provides significant advantages in both accuracy and computational efficiency.

Mark Moussa↗
DOE OSTI2014

Fibre Diffraction Analysis of Skin Offers a Very Early and Extremely Accurate Diagnostic Test for Prostate Cancer

Double blind analysis of a batch of thirty skin tissue samples from potential prostate cancer sufferers correctly identified all “control” patients, patients with high and low grade prostate cancers, the presence of benign prostate hyperplasia (BPH), perineural invasions, and the one lymphatic invasion. Identification was by analysis of fibre diffraction patterns interpreted using a schema developed from observations in nine previous studies. The method, schema, and specific experiment results are reported in this paper, with some implications then drawn.

James, Veronica J.↗