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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Microlensing of x-ray pulsars: A method to detect primordial black hole dark matter

Primordial black holes (PBHs) with a mass from 10 -16 to 10 -11 M ⊙ may comprise 100% of dark matter. Due to a combination of wave and finite source size effects, the traditional microlensing of stars does not probe this mass range. Here, we point out that x-ray pulsars with higher photon energies and smaller source sizes are good candidate sources for microlensing for this mass window. Among the existing x-ray pulsars, the Small Magellanic Cloud (SMC) X-1 source is found to be the best candidate because of its apparent brightness and long distance from Earth. We have analyzed the existing observation data of SMC X-1 by the RXTE telescope (around 10 days) and found that PBH as 100% of dark matter is close to but not yet excluded. Lastly, future longer observation of this source by x-ray telescopes with larger effective areas such as AstroSat, Athena, Lynx, and eXTP can potentially close the last mass window where PBHs can make up all of dark matter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Optimal test selection for prediction uncertainty reduction

Economic factors and experimental limitations often lead to sparse and/or imprecise data used for the calibration and validation of computational models. This paper addresses resource allocation for calibration and validation experiments, in order to maximize their effectiveness within given resource constraints. When observation data are used for model calibration, the quality of the inferred parameter descriptions is directly affected by the quality and quantity of the data. This paper characterizes parameter uncertainty within a probabilistic framework, which enables the uncertainty to be systematically reduced with additional data. The validation assessment is also uncertain in the presence of sparse and imprecise data; therefore, this paper proposes an approach for quantifying the resulting validation uncertainty. Since calibration and validation uncertainty affect the prediction of interest, the proposed framework explores the decision of cost versus importance of data in terms of the impact on the prediction uncertainty. Often, calibration and validation tests may be performed for different input scenarios, and this paper shows how the calibration and validation results from different conditions may be integrated into the prediction. Then, a constrained discrete optimization formulation that selects the number of tests of each type (calibration or validation at given input conditions) is proposed. Furthermore, the proposed test selection methodology is demonstrated on a microelectromechanical system (MEMS) example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Physics-Informed Neural Networks for Heat Transfer Problems

Abstract Physics-informed neural networks (PINNs) have gained popularity across different engineering fields due to their effectiveness in solving realistic problems with noisy data and often partially missing physics. In PINNs, automatic differentiation is leveraged to evaluate differential operators without discretization errors, and a multitask learning problem is defined in order to simultaneously fit observed data while respecting the underlying governing laws of physics. Here, we present applications of PINNs to various prototype heat transfer problems, targeting in particular realistic conditions not readily tackled with traditional computational methods. To this end, we first consider forced and mixed convection with unknown thermal boundary conditions on the heated surfaces and aim to obtain the temperature and velocity fields everywhere in the domain, including the boundaries, given some sparse temperature measurements. We also consider the prototype Stefan problem for two-phase flow, aiming to infer the moving interface, the velocity and temperature fields everywhere as well as the different conductivities of a solid and a liquid phase, given a few temperature measurements inside the domain. Finally, we present some realistic industrial applications related to power electronics to highlight the practicality of PINNs as well as the effective use of neural networks in solving general heat transfer problems of industrial complexity. Taken together, the results presented herein demonstrate that PINNs not only can solve ill-posed problems, which are beyond the reach of traditional computational methods, but they can also bridge the gap between computational and experimental heat transfer.

Engineering↗
DOE OSTI2026

Financial Exposure After a Sealed-Source Release: Insurance Limits, Federal Cost Pathways, and Implications for Gamma Irradiator Substitution

This report assesses whether private insurance and existing federal authorities would likely provide meaningful financial protection to private operators of self-shielded gamma irradiators after a major sealed-source release. It does not answer this question quantitatively because publicly observable data on premiums, limits, uptake, and claims outcomes for this risk class appear sparse. Instead, it uses a qualitative structural analysis based on prior literature, review of relevant federal authorities, limited observable insurance-market evidence, expert outreach, and historical analogs. The analysis finds that available public and private mechanisms do not combine into a clear, dependable, or readily verifiable compensation structure for ordinary private sealed-source operators. Institutions therefore should not assume that either insurance or government response will make them financially whole after a severe incident. Source reduction and replacement remain more dependable than post-event financial mechanisms for reducing institutional exposure and broader radiological risk.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1979

Dynamical effects on the global distribution of thermospheric atomic oxygen

Results are presented of calculations pertaining to the effects of global-scale dynamical processes on the coupled seasonal and diurnal variations of atomic oxygen in the altitude range 90-500 km. The calculations are based on a three-dimensional numerical model of thermospheric dynamics which treats the three gases N2, O2, and O simultaneously, coupled together by collisional processes. The model is described, and the results of the calculations under both equinox and solstice conditions and a comparison with observational data are discussed. It is shown that none of these gases can be considered to be in hydrostatic equilibrium below about 200 km, and that global-scale winds cause the observed winter enhancement of atomic oxygen.

Straus, J. M.↗
NASA NTRS1980

Optical observations of interstellar molecules

Recent observational data are summarized on molecular species in diffuse interstellar clouds, and a comprehensive list of all species detected or sought is included. The discussion is focussed on the use of molecular observations to determine physical conditions in clouds, and on important species which provide constraints on cloud chemistry models. Directions for new research are suggested, including intensive work on the unidentified diffuse bands, which may have a molecular origin.

Snow, T. P., Jr.↗
NASA NTRS1985

Burst and Transient Source Experiment (BATSE) for the Gamma Ray Observatory (GRO)

The Burst and Transient Source Experiment (BATSE) on the Gamma Ray Observatory (GRO) is expected to provide new and better observational data on bursts to test current and future models of burst sources. These data will include: (1) the celestial distribution of hundreds of burst sources over the life of the mission, (2) burst locations within several degrees, within 2 days after their occurrence, (3) observations of weaker bursts and better observations of short timescale fluctuations and spectral variations, (4) observations by a single experiment over a much larger energy range than previously available, and (5) more sensitive measurements of the spectral features which have been observed in many bursts. This paper briefly describes the GRO mission, the BATSE instrumentation and the burst observational capabilities.

Fishman, G. J.↗
NASA NTRS1983

Satellite radiation observations and climate theory

The representative applications of satellite observations of the earth radiation budget in climate studies are discussed. Consideration is given to the use of satellite observational data for validating numerical estimates of the sensitivity of longwave radiation, surface temperature, and cloud amount to changes in the radiation budget. Particular emphasis is given to the application of satellite observations to the validation of temperature estimates obtained from the NOAA Seasonal Hemispheric Zonal Average Model (SZHAM).

Ohring, G.↗
NASA NTRS1991

The states of carbon and nitrogen atoms after photodissociation of CN, CH, CH(+), C2, C3, and CO in comets

The photodissociation of carbon compounds by solar UV radiation at a heliocentric distance of 1 AU is examined, comparing published observational data with the predictions of theoretical models and results from laboratory experiments. It is shown that species other than CO, including CN, CH, CH(+), C2, and C3, can contribute to the observed brightness of the VUV lines of C I (156.1, 165.7, and 193.1 nm) and C II (133.5 nm) in comet comae. CN photodissociation is also found to produce metastable 2D0 and 2P0 N I atoms, possibly leading (at heliocentric distances less than 0.25 AU) to 143.9-nm emission via resonance fluorescence.

Singh, P. D.↗
NASA NTRS1992

Variability in the outer planet aurorae

Multiwavelength observations of the aurorae of the outer planets are reviewed emphasizing the findings on physical processes derived from specific wavelengths. The review examines features of the auroral zones such as ionospheric currents, atmospheric heating, and compositional changes in the aurorae of Jupiter, Saturn, Uranus, Neptune, and the earth for comparison. Jupiter's multiwavelength aurora receives special attention since recent observations shed light on the distribution of the UV auroral ovals, the spectroscopy of the UV auroral emissions, auroral dynamics and ion upwelling, and IR emission from auroral latitudes. The observational data on Jupiter facilitate the modeling of variability and detailed thermospheric and magnetospheric processes. Saturn can be studied by extending findings fron Jupiter's aurora, and deficiencies are found in the observational datasets for Neptune and Uranus.

Clarke, John T.↗
NASA NTRS2011

Lateral-Directional Parameter Estimation on the X-48B Aircraft Using an Abstracted, Multi-Objective Effector Model

The problem of parameter estimation on hybrid-wing-body aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aerodynamic control effectors that act in coplanar motion. This adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of flight and simulation data must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, time-decorrelation techniques are applied to a model structure selected through stepwise regression for simulated and flight-generated lateral-directional parameter estimation data. A virtual effector model that uses mathematical abstractions to describe the multi-axis effects of clamshell surfaces is developed and applied. Comparisons are made between time history reconstructions and observed data in order to assess the accuracy of the regression model. The Cram r-Rao lower bounds of the estimated parameters are used to assess the uncertainty of the regression model relative to alternative models. Stepwise regression was found to be a useful technique for lateral-directional model design for hybrid-wing-body aircraft, as suggested by available flight data. Based on the results of this study, linear regression parameter estimation methods using abstracted effectors are expected to perform well for hybrid-wing-body aircraft properly equipped for the task.

Ratnayake, Nalin A.↗
NASA NTRS2022

The TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI). Part II: Moist Cases - The Two Waterworlds

To identify promising exoplanets for atmospheric characterization and to make the best use of observational data, a thorough understanding of their atmospheres is needed. 3D general circulation models (GCMs) are one of the most comprehensive tools available for this task and will be used to interpret observations of temperate rocky exoplanets. Due to parameterization choices made in GCMs, they can produce different results, even for the same planet. Employing four widely-used exoplanetary GCMs - ExoCAM, LMD-G, ROCKE-3D and the UM - we continue the TRAPPIST-1 Habitable Atmosphere Intercomparison by modeling aquaplanet climates of TRAPPIST-le with a moist atmosphere dominated by either nitrogen or carbon dioxide. Although the GCMs disagree on the details of the simulated regimes, they all predict a temperate climate with neither of the two cases pushed out of the habitable state. Nevertheless, the inter-model spread in the global mean surface temperature is non-negligible: 14 K and 24 K in the nitrogen and carbon dioxide dominated case, respectively. We find substantial inter-model differences in moist variables, with the smallest amount of clouds in LMDGeneric and the largest in ROCKE-3D. ExoCAM predicts the warmest climate for both cases and thus has the highest water vapor content and the largest amount and variability of cloud condensate. The UM tends to produce colder conditions, especially in the nitrogen-dominated case due to a strong negative cloud radiative effect on the day side of TRAPPIST-le. Our study highlights various biases of GCMs and emphasizes the importance of not relying solely on one model to understand exoplanet climates.

TRAPPIST↗
NASA NTRSDate not supplied

First Optical Constants from 0.4 to 1.6 µm of Titan Aerosol Analogs Produced in the NASA Ames COSmIC Facility and Their Use in a New Analysis of Cassini VIMS Observations

We have determined the real and imaginary refractive indices (n and k, respectively), from the visible to the near infrared (0.4 to 1.6 μm), of five laboratory-generated organic refractory materials produced from gas-phase chemistry with the NASA Ames COSmIC facility. The solid samples were produced using a plasma discharge in the stream of a 200-K supersonic jet-cooled expansion of different gas mixtures to study the impact of the molecular precursors on the solid sample optical properties. Three samples were produced from N2:CH4 (95:5) gas mixtures using three different high voltages (700V, 800V and 1000V) to vary the energy in the plasma discharge. One sample was produced from a N2:CH4:C2H2 (94:5:5:0.5) gas mixture, with a high voltage of 1000 V. The fifth sample was produced in an Ar:CH4 (95:5) gas mixture with a high voltage of 1000 V to produce a nitrogen-free hydrocarbon sample. The optical constants, n and k, of these five samples were determined using spectral reflectance measurements. They appear to be positively correlated with the nitrogen content in the solid sample, i.e., a sample with larger nitrogen content exhibits higher n and k values. We have used these refractive indices as input parameters in a radiative transfer model to analyze Cassini Visible Infrared Mapping Spectrometer (VIMS) observations of Titan’s atmosphere. The results show that using the tholin samples with higher n and k values (higher nitrogen content) provides a better fit to the observational data than using the samples with lower n and k values (lower nitrogen content). The Titan tholins with higher nitrogen content therefore appear to be more representative of the Titan aerosols observed by VIMS.

Titan Aerosol Analogs↗
NASA NTRSDate not supplied

FloodPlanet: High-Resolution Commercial Imagery for Training and Validation of Deep Learning-Based Models of Inundation Extent

Flooding events are becoming increasingly frequent worldwide and are known to cause extensive damage. Public optical and radar satellite imagery can be used to detect large areas of inundation in rural areas, however, long revisit times and coarse spatial resolution limit applications for short-lived events and urban areas. Commercial constellations such as those operated by Planet offer increased spatial and temporal resolution and can supplement mapping efforts to provide more information to disaster response, relief, and mitigation efforts. Deep learning requires high quality labeled data for training across coincident sensors. The FloodPlanet dataset presented here contains labeled surface water for 18 events across the world based on Planetscope imagery with coincident Harmonized Landsat Sentinel-2 ( HLS) or Sentinel-1 and builds upon the previously existing Sen1Floods11, xBD, and NASA Sentinel-1 datasets. Sen1Floods11 includes 4,831 512x512 pixel overlapping tiles of coincident Sentinel-1 and Sentinel-2 data observing 11 flood events across the world from 2017-2019. The dataset contains a combination of automated and hand-labeled surface water for use in training and validation of inundation modeling efforts. The xBD dataset identifies flood-damaged buildings and indicates the scale of damage to each (none, minor, moderate, and major) from four flood events which occurred in the United States, India, Nepal, and Bangladesh from the same time period. The NASA dataset contains hand-labeled water bodies observed in Sentinel-1 imagery during five flood events within the 2017-2019 period. The effort presented here utilizes observations from these previously investigated flood events to generate labels of surface water at the 3-5m spatial resolution provided by Planetscope and facilitate the comparison between public and commercial data. A data pipeline was built which uses clustering algorithms to pick the most suitable overlapping chips between the public data and PlanetScope data for manual labeling. Labels were created manually using NASA’s ImageLabeler tool and include areas of high- and low-confidence water. The high confidence designation is reserved for areas of open, unobstructed water while low confidence is used for areas of suspected water beneath vegetation, clouds, or cloud shadows. Expected to be released in late 2022, the FloodPlanet dataset will include tiled imagery with a unique ID for each 1024x1024 pixel tile, 7 bands of HLS data, and high- and low-confidence flood labels in both shapefile and tiff formats. The authors will follow Spatial Temporal Access Catalog (STAC) guidelines to release FloodPlanet on the Radiant Earth ML hub, which hosts public datasets for machine learning.

Alexander Melancon↗
NASA NTRSDate not supplied

Additional Metadata Guidelines to Improve the Structure and Usability of HDF and NetCDF Files

The Hierarchical Data Format (HDF) and Network Common Data Form (NetCDF) are data file formats created to aid users in the creation or use of scientific data. These file formats are useful for handling large data volumes and hosting extensive metadata as global attributes or variables and are popular with the modeling community. HDF and NetCDF files are largely used with remote sensing data and have been used to support measurements from numerous campaigns, from satellite to aircraft or ground and mobile based measurements. The files from airborne field studies, however, vary greatly in terms of the file structure and the amount and content of metadata. Information relevant to the file that can be useful to the user such as the data producer, location where data was taken, variable descriptions, or information about the instrument might not be included in the file. This metadata might be present in another file in the dataset containing the same data using the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) format. Recently, the Aerosols, Clouds, and their Interactions for Earth System Models (MACIE) group started a grassroots effort to develop a set of requirements for the HDF and NetCDF files for field studies, aiming to make the data products more interoperable and usable. Particularly, these requirements seek to make the files more compliant to Climate and Forecast (CF) metadata conventions and to standardize the file structure and the global and variable attributes. These requirements would help to ensure that HDF and NetCDF files contain adequate metadata to better support their use for research, e.g., the modeling community, and to enhance the usability and interoperability of data for research communities at large. To be presented are the details of the MACIE requirements as well as examples of the implementation of these requirements for merge files and lidar observation data files.

Sean Leavor↗
NASA NTRS2001

Remote Sensing of Ocean Color in the Arctic: Algorithm Development and Comparative Validation

The overall goal of this effort is to acquire a large bio-optical database, encompassing most environmental variability in the Arctic, to develop algorithms for phytoplankton biomass and production and other optically active constituents. A large suite of bio-optical and biogeochemical observations have been collected in a variety of high latitude ecosystems at different seasons. The Ocean Research Consortium of the Arctic (ORCA) is a collaborative effort between G.F. Cota of Old Dominion University (ODU), W.G. Harrison and T. Platt of the Bedford Institute of Oceanography (BIO), S. Sathyendranath of Dalhousie University and S. Saitoh of Hokkaido University. ORCA has now conducted 12 cruises and collected over 500 in-water optical profiles plus a variety of ancillary data. Observational suites typically include apparent optical properties (AOPs), inherent optical property (IOPs), and a variety of ancillary observations including sun photometry, biogeochemical profiles, and productivity measurements. All quality-assured data have been submitted to NASA's SeaWIFS Bio-Optical Archive and Storage System (SeaBASS) data archive. Our algorithm development efforts address most of the potential bio-optical data products for the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and GLI, and provides validation for a specific areas of concern, i.e., high latitudes and coastal waters.

Cota, Glenn F.↗
NASA NTRS1999

Observations of Smoke Aerosol from Biomass Burning in Mexico: Effect of Particle Aging on Radiative Forcing and Remote Sensing

We take advantage of the May 1998 biomass burning event in Southern Mexico to test the global applicability of a smoke aerosol size model developed from data observed in South America. The Mexican event is an unique opportunity to observe well-aged, residual smoke. Observations of smoke aerosol size distribution made from vertical profiles of airborne in situ measurements show an inverse relationship between concentration and particle size that suggests the aging process continues more than a week after the smoke is separated from its fire sources. The ground-based radiometer retrievals show that the column-averaged, aged, Mexican smoke particles are larger (diameter = 0.28 - 0.33 micrometers) than the mean smoke particles in South America (diameter = 0.22 - 0.30 micrometers). However, the difference (delta - 0.06 micrometer) translates into differences in backscattering coefficient of only 4-7% and an increase of direct radiative forcing of only 10%.

Remer, Lorraine A.↗
NASA NTRS2021

Optimizing GRACE/GRACE-FO Data and A priori Hydrological Knowledge for Improved Global Terrestial Water Storage Component Estimates

The comprehensive information of global terrestrial water storage (TWS) components (soil moisture, groundwater, snow, surface water) is essential for effective assessment of water resource availability, climate variation, and disaster mitigation measures. Observational data provided by the Gravity Recovery And Climate Experiment (GRACE) and GRACE Follow-On satellite missions offer global TWS variation (ΔTWS) in terms of an integrated water column. However, GRACE spatial resolution is relatively coarse (i.e., 3°), and the vertically integrated value cannot be separated into ΔTWS components directly. This study demonstrates the feasibility to estimate ΔTWS components at any desired spatial-vertical resolution by effectively maintaining the native resolution of the employed hydrological knowledge. It utilizes a least-squares with constraints (LSC) approach to rigorously incorporate GRACE and GRACE-FO data and a priori hydrological knowledge, with the aim to improve global ΔTWS components’ accuracy and spatial resolution. The 3°×3° GRACE mascon derived ΔTWS data is disaggregated into the 0.5°×0.5° anomalous soil moisture storage (ΔSMS), groundwater storage (ΔGWS), snow water equivalent (ΔSWE), and surface water storage (ΔSWS) based on the covariance information obtained from the Community Atmosphere Biosphere Land Exchange (CABLE) and the PCRaster Global Water Balance (PCR-GLOBWB) models. Evaluation with different ground measurements and satellite products between 2002 and 2019 exhibits significantly improved accuracy in all individual ΔTWS components. This improvement is of particular note in ΔGWS and ΔSWS, where the LSC approach increases the globally averaged correlation values by approximately 0.13 and 0.05, respectively. Reliable prior knowledge leads to a more accurate ΔTWS component estimate, and the use of ensemble-mean knowledge yields the best result.

GRACE↗