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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Satellite and Reanalysis Air Quality Data and Services at NASA GES DISC for Public Health Study

Outbreaks of infectious diseases and health can be influenced by airborne and water-borne pollutants. Furthermore, air and water quality are associated with climate variability, industrialization, land use and land cover change, and water resource management. It is therefore crucial to understand environment-disease connections with existing long-term observed and modeled data, particularly for development of early warning systems for infectious disease outbreaks. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) (https://disc.gsfc.nasa.gov) archives large volumes of global environment data that are useful for research and applications regarding environmental factors and public health. Examples of air quality measurements are: Daily satellite remotely sensed data, including Aerosol Index (AI), O3, SO2, CO, and NO2 from Aura/OMI (October 2014 to present), and OMPS-NPP (January 2012 to present, currently research data products only) Hourly and monthly reanalysis modeled data, including PM2.5, O3, CO, SO2, BC, dust, AOD, and aerosol types from MERRA-2 (January 1980 to present) Examples of surface meteorology and land surface measurements are: hourly, daily, and monthly satellite precipitation from TRMM (December 1997 to March 2015) 30-minute and monthly satellite precipitation from GPM (March 2014 to present); Hourly and monthly modeled surface meteorology and land surface condition from MERRA-2 (January 1980 to present) and land surface assimilation models (January 1948 to present), including precipitation, surface temperature, relative humidity, wind, and soil moisture.This presentation will give an overview of relevant environmental data at the NASA GES DISC. Through a number of use cases, such as dust events and active fires, we will introduce data services that assist in finding the right data, enable visualization and analysis of the data online, and allow downloading of data in user-preferred format.

remote sensing data↗
DOE OSTI2024

Detection of a Cobalt-Containing Interphase at the Li 6 PS 5 Cl-NMC111 Interface by In Situ μ XANES and EIS

Sulfide electrolyte all-solid-state lithium batteries (ASLBs) with uncoated Li-Ni x Mn y Co 1–x–y O 2 (NMC) cathodes suffer from a large capacity loss during initial cycling and an increase in cell impedance. Decomposition reactions are known to occur at the Li 6 PS 5 Cl-NMC111 interface due to incompatibility between the two materials. If a stabilizing coating is applied to the NMC, it delivers full capacity during initial charge. However, the loss in capacity during discharge still occurs. The interface was studied by μ XANES and through EIS analysis. A chemically-formed interphase was detected by μ XANES, evident from reduction of Co at an uncoated NMC particle surface. This interphase was produced by decomposition at rest. To study the effect of the interphase on electrochemically active surface area, piecewise in situ EIS was performed and the data was modeled using a transmission line model (TLM). The charge transfer resistance R CT was used to estimate the volume specific active surface area (a act ). The median value for a act was 296 cm –1 , a factor of 7.5 lower than the theoretical value of 2216 cm –1 . This provided evidence of a lower electrochemically active surface area in the ASLB.

36 MATERIALS SCIENCE↗
DOE OSTI2026

3D Gaussian Splatting for Volume Compression

This codebase uses machine learning to train a collection of 3D Gaussian distributions to approximate scientific volume data. Because this collection uses less memory than the original dataset, it can be used as a compressed model of the original data for applications such as visualization.

Dyken, Landon↗
NASA NTRS1987

An evaluation of active noise control in a cylindrical shell

The physical mechanisms governing the use of active noise control in an extended volume of a cylindrical shell are discussed. Measured data was compared with computer results from a previously derived analytical model based on an infinite shell theory. For both the analytical model and experiment, the radiation of the external monopoles is coupled to the internal acoustic field through the radial displacement of the thin, elastic cylindrical shell. An active noise control system was implemented in the cylinder using a fixed array of discrete monopole sources, all of which lie in the plane of the exterior noise sources. Good agreement between measurement and prediction was obtained for both internal pressure response and overall noise reduction. Attenuations in the source plane greater than 15 dB were recorded along with a uniformly quieted noise environment over the entire length of the experimental model. Results indicate that for extended axial forcing distributions or very low shell damping, axial arrays of control sources may be required. Finally, the Nyquist criteria for the number of azimuthal control sources is shown to provide for effective control over the full cylinder cross section.

Silcox, R. J.↗
NASA NTRS1987

Forest biomass, canopy structure, and species composition relationships with multipolarization L-band synthetic aperture radar data

The effect of forest biomass, canopy structure, and species composition on L-band synthetic aperature radar data at 44 southern Mississippi bottomland hardwood and pine-hardwood forest sites was investigated. Cross-polarization mean digital values for pine forests were significantly correlated with green weight biomass and stand structure. Multiple linear regression with five forest structure variables provided a better integrated measure of canopy roughness and produced highly significant correlation coefficients for hardwood forests using HV/VV ratio only. Differences in biomass levels and canopy structure, including branching patterns and vertical canopy stratification, were important sources of volume scatter affecting multipolarization radar data. Standardized correction techniques and calibration of aircraft data, in addition to development of canopy models, are recommended for future investigations of forest biomass and structure using synthetic aperture radar.

Sader, Steven A.↗
NASA NTRS1989

An evaluation of active noise control in a cylindrical shell

The physical mechanisms governing the use of active noise control in an extended volume of a cylindrical shell are discussed. Measured data was compared with computer results from a previously derived analytical model based on an infinite shell theory. For both the analytical model and experiment, the radiation of the external monopoles is coupled to the internal acoustic field through the radial displacement of the thin, elastic cylindrical shell. An active noise control system was implemented in the cylinder using a fixed array of discrete monopole sources, all of which lie in the plane of the exterior noise sources. Good agreement between measurement and prediction was obtained for both internal pressure response and overall noise reduction. Attenuations in the source plane greater than 15 dB were recorded along with a uniformly quieted noise environment over the entire length of the experimental model. Results indicate that for extended axial forcing distributions or very low shell damping, axial arrays of control sources may be required. Finally, the Nyquist criteria for the number of azimuthal control sources is shown to provide for effective control over the full cylinder cross section.

Silcox, R. J.↗
NASA NTRS1990

Absorption Of Gases By Glassy Polymers

Report discusses solubility of gas in glassy polymer, both above and below glass-transition temperature (Tg). Thermodynamic arguments brought to bear on previously-developed mathematical models, result being new model that enables calculation of infinite-dilution partial molar volume of solvent in glass or liquid solvent from data on pressure, volume, and temperature of solute in equilibrium with solvent.

Fedors, Robert F.↗
NASA NTRS2006

The International Reference Ionosphere - Climatological Standard for the Ionosphere

The International Reference Ionosphere (IRI) a joint project of URSI and COSPAR is the defacto standard for a climatological specification of ionospheric parameters. IRI is based on a wide range of ground and space data and has been steadily improved since its inception in 1969 with the ever-increasing volume of ionospheric data and with better mathematical descriptions of the observed global and temporal variation patterns. The IRI model has been validated with a large amount of data including data from the most recent ionospheric satellites (KOMPSAT, ROCSAT and TIMED) and data from global network of ionosondes. Several IRI teams are working on specific aspects of the IRI modeling effort including an improved representation of the topside ionosphere with a seamless transition to the plasmasphere, a new effort to represent the global variation of F2 peak parameters using the Neural Network (NN) technique, and the inclusion of several additional parameters in IRI, e.g., spread-F probability and ionospheric variability. Annual IRI workshops are the forum for discussions of these efforts and for all science activities related to IRI as well as applications of the IRI model in engineering and education. In this paper I will present a status report about the IRI effort with special emphasis on the presentations and results from the most recent IRI Workshops (Paris, 2004; Tortosa, 2005) and on the most important ongoing IRI activities. I will discuss the latest version of the IRI model, IRI-2006, highlighting the most recent changes and additions. Finally, the talk will review some of the applications of the IRI model with special emphasis on the use for radiowave propagation studies and communication purposes.

Bilitza, Dieter↗
NASA NTRS2011

Reynolds-Averaged Navier-Stokes Solutions to Flat Plate Film Cooling Scenarios

The predictions of several Reynolds-Averaged Navier-Stokes solutions for a baseline film cooling geometry are analyzed and compared with experimental data. The Fluent finite volume code was used to perform the computations with the realizable k-epsilon turbulence model. The film hole was angled at 35 to the crossflow with a Reynolds number of 17,400. Multiple length-to-diameter ratios (1.75 and 3.5) as well as momentum flux ratios (0.125 and 0.5) were simulated with various domains, boundary conditions, and grid refinements. The coolant to mainstream density ratio was maintained at 2.0 for all scenarios. Computational domain and boundary condition variations show the ability to reduce the computational cost as compared to previous studies. A number of grid refinement and coarsening variations are compared for further insights into the reduction of computational cost. Liberal refinement in the near hole region is valuable, especially for higher momentum jets that tend to lift-off and create a recirculating flow. A lack of proper refinement in the near hole region can severely diminish the accuracy of the solution, even in the far region. The effects of momentum ratio and hole length-to-diameter ratio are also discussed.

Johnson, Perry L.↗
DOE OSTI2024

Scaling Ensembles of Data-Intensive Quantum Chemical Calculations for Millions of Molecules

Deep learning models are efficient computational tools that can accelerate the inverse design of molecules with desired functional properties by generating predictions at a fraction of the time required by traditional quantum chemical approaches. To ensure that a model maintains accuracy and transferability across broad regions of the chemical space explored during the inverse design, it must be trained on massively large volumes of simulation data. This requires running large-scale ensemble quantum chemical calculations on high-performance computing (HPC) systems for data collection. However, the efficient execution of such large ensemble calculations and the management of large volumes of output data require tools that can judiciously utilize computational resources and manage metadata overhead on the file system. Therefore, we present a high-performance, scalable, ensemble management framework for performing data-intensive quantum chemical electronic structure calculations for organic molecules. This framework provides abstractions to plug different ab initio, first principles, and first principles-based semi-empirical methods and executes them efficiently at large scale on HPC systems. It dynamically distributes tasks to resources and uses tiered storage for managing large collections of files. We employed this framework to process over ten million organic molecules and generate open-source datasets that provide UV-vis absorption spectra by running time-dependent density-functional tight-binding calculations. It is the largest database containing molecular optical spectra that were simulated with quantum chemical methods in a consistent manner.

Mehta, Kshitij↗
NASA NTRS2007

High-LET Patterns of DSBs in DNA Loops, the HPRT Gene and Phosphorylation Foci

We present new results obtained with our model based on the track structure and chromatin geometry that predicts the DSB spatial and genomic distributions in a cell nucleus with the full genome represented. The model generates stochastic patterns of DSBs in the physical space of the nucleus filled with the realistic configuration of human chromosomes. The model was re-used to find the distribution of DSBs in a physical volume corresponding to a visible phosphorylation focus believed to be associated with a DSB. The data shows whether there must more than one DSB per foci due to finite size of the visible focus, even if a single DSB is radiochemically responsible for the phosphorylation of DNA in its vicinity. The same model can predict patterns of closely located DSBs in a given gene, or in a DNA loop, one of the large-scale chromatin structures. We demonstrated for the example of the HPRT gene, how different sorts of radiation lead to proximity effect in DSB locations, which is important for modeling gene deletions. The spectrum of intron deletions and total gene deletions was simulated for the HPRT gene. The same proximity effect of DSBs in a loop can hinder DSB restitutions, as parts of the loop between DSBs is deleted with a higher likelihood. The distributions of DSBs and deletions of DNA in a loop are presented.

Ponomarev, Artem L.↗
NASA NTRS1985

Simulation of a G-tolerance curve using the pulsatile cardiovascular model

A computer simulation study, performed to assess the ability of the cardiovascular model to reproduce the G tolerance curve (G level versus tolerance time) is reported. A composite strength duration curve derived from experimental data obtained in human centrifugation studies was used for comparison. The effects of abolishing automomic control and of blood volume loss on G tolerance were also simulated. The results provide additional validation of the model. The need for the presence of autonomic reflexes even at low levels of G is pointed out. The low margin of safety with a loss of blood volume indicated by the simulation results underscores the necessity for protective measures during Shuttle reentry.

Solomon, M.↗
DOE OSTI2024

Phase Identification in Synchrotron X-ray Diffraction Patterns of Ti–6Al–4V Using Computer Vision and Deep Learning

X-ray diffraction patterns contain information about the atomistic structure and microstructure (defect population) of materials, extracting detailed information from diffraction patterns is complex, demanding and relies on prior knowledge. Here, we hypothesize that deep-learning techniques can help to perform an effective and accurate analysis with high throughput rates. To demonstrate this concept, we applied a novel deep learning framework to determine the evolution of the β-phase volume fraction in a Ti–6Al–4V alloy during heat-treatment from video sequences of 2D diffraction patterns recorded in transmission and with highly monochromatic radiation in a synchrotron beamline. In particular, we studied the impact of network design on prediction reliability and computational performance. Networks of different architectures were trained using 3008 experimental 2D patterns. A well-tuned model was found to reproduce the phase fractions of another experimental data set, consisting of 1100 diffraction patterns, with a mean-square error as small as 2.6 x 10 -4 . The average prediction error of β-phase volume fraction was within 1.6 x 10 -2 (in each diffraction pattern) of the values obtained by conventional methods. Our work demonstrates that convolutional neural networks can evaluate high energy X-ray diffraction patterns with a remarkable level of reliability. Furthermore, it demonstrates the significance of network design on the reliability of predictions and computational performance. The most complex models do not necessarily result in highest accuracy and may even fail to learn from the data.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Modeling Self-Pressurization and Spray Bar Pressure Control of A Cryogenic Storage Tank in Normal Gravity

This paper presents computational fluid dynamics (CFD) models for simulating self-pressurization and spray-bar pressure control processes in a large-scale liquid hydrogen storage tank under normal gravity conditions. For self-pressurization, the model employs the kinetics-based Schrage equation alongside the volume-of-fluid (VOF) method to account for interfacial mass transfer. The CFD predictions of pressure and temperature are compared with experimental data from the Multipurpose Hydrogen Test Bed (MHTB) experiment, and the predicted interfacial mass transfer rates are also presented. A CFD model simulating pressure control using a spray bar has also been developed. An Eulerian-Lagrangian approach models the interactions between discrete droplets and the continuous ullage (vapor) phase. The spray model is coupled with the VOF method by tracking droplets in the ullage and removing them when they reach the liquid interface. The T-sat model calculates droplet-ullage heat and mass transfer, where droplets warm up to the saturation temperature corresponding to the ullage vapor pressure before evaporating while remaining at the saturation temperature. The evolution of tank pressure, vapor temperature, and liquid temperature predicted by the CFD model is validated against data from the MHTB spray-bar mixing experiment. Overall, the CFD models agree with experimental data, demonstrating their capability to simulate self-pressurization and pressure control processes in large-scale cryogenic storage tanks. These models can be valuable tools for designing and optimizing cryogenic fluid management systems in future applications.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Modeling Self-Pressurization and Spray Bar Pressure Control of A Cryogenic Storage Tank in Normal Gravity

This paper presents computational fluid dynamics (CFD) models for simulating self-pressurization and spray-bar pressure control processes in a large-scale liquid hydrogen storage tank under normal gravity conditions. For self-pressurization, the model employs the kinetics-based Schrage equation alongside the volume-of-fluid (VOF) method to account for interfacial mass transfer. The CFD predictions of pressure and temperature are compared with experimental data from the Multipurpose Hydrogen Test Bed (MHTB) experiment, and the predicted interfacial mass transfer rates are also presented. A CFD model simulating pressure control using a spray bar has also been developed. An Eulerian-Lagrangian approach models the interactions between discrete droplets and the continuous ullage (vapor) phase. The spray model is coupled with the VOF method by tracking droplets in the ullage and removing them when they reach the liquid interface. The T-sat model calculates droplet-ullage heat and mass transfer, wherein droplets warm up to the saturation temperature corresponding to the ullage vapor pressure before evaporating while remaining at the saturation temperature. The evolution of tank pressure, vapor temperature, and liquid temperature predicted by the CFD model is validated against data from the MHTB spray-bar mixing experiment. Overall, the CFD models agree with experimental data, demonstrating their capability to simulate self-pressurization and pressure control processes in large-scale cryogenic storage tanks. These models can be valuable tools for designing and optimizing cryogenic fluid management systems in future applications.

Self-Pressurization↗
NASA NTRS2018

Application of Machine-Learning Algorithms for On-Board Asteroid Shape Model Determination

The Application of Machine-learning Algorithms for On-board Asteroid Shape Model Determination project will develop an innovative system for spacecraft navigation to expand the capability of small spacecraft to meet the critical challenges associated with small-body exploration. Such challenges include accurate navigation in a microgravity environment and precision targeting of particular locations on an asteroid surface for sample collection. This on-board system will cut the computational "umbilical" back to Earth-currently necessary for the generation of a global shape model that requires thousands of images with sufficient resolution and adequate variation of incidence and emission angles, processed manually by a team of experts on Earth for several months. Small satellites have limited bandwidth and are unable to downlink the data volume required for this processing, restricting their ability to perform deep-space asteroid exploration.

Machine learning algorithms↗