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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 667 records · Page 37

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NASA NTRS1997

Statistical Modeling of Landscape Pattern and the Effects of Coarse Spatial Resolution

Analysis of classified satellite imagery was conducted to characterize errors in estimates of area based on coarse resolution satellite imagery which are due to distortions in sizes of small fragments, and to explore the feasibility of correcting for these errors using a statistical modeling approach. Sizes of bodies of open water on European Remote-Sensing (ERS-1) synthetic aperture radar (SAR) and fire scars on Landsat Multispectral Scanner (MSS) imagery were measured using geographic information system (GIS) software. Statistical analysis of the smaller scars and ponds as observed with this imagery of relatively fine resolution demonstrated that the distribution of the sizes could be modeled by either of two types of statistical distributions-a power distribution related to fractal processes or a simple exponential distribution. A comparison of the size distribution of small burn scars as observed with Landsat with the distribution observed with the much coarser Advanced Very High Resolution Radiometer (AVHRR) imagery revealed effects of coarse resolution, each of which were associated with a particular size range, and whose net effect accounted for the bias in total burn area due to coarse spatial resolution. Size dependent area correction procedures are therefore feasible. A statistical modeling approach to area estimation, based models of the underlying and observed size distributions of fragments in the scene, may lead to a procedure which requires little or no ancillary data.

Hlavka, C. A.↗

DOE OSTI2021

High-throughput virtual laboratory for drug discovery using massive datasets

Time-to-solution for structure-based screening of massive chemical databases for COVID-19 drug discovery has been decreased by an order of magnitude, and a virtual laboratory has been deployed at scale on up to 27,612 GPUs on the Summit supercomputer, allowing an average molecular docking of 19,028 compounds per second. Over one billion compounds were docked to two SARS-CoV-2 protein structures with full optimization of ligand position and 20 poses per docking, each in under 24 hours. GPU acceleration and high-throughput optimizations of the docking program produced 350× mean speedup over the CPU version (50× speedup per node). GPU acceleration of both feature calculation for machine-learning based scoring and distributed database queries reduced processing of the 2.4 TB output by orders of magnitude. The resulting 50× speedup for the full pipeline reduces an initial 43 day runtime to 21 hours per protein for providing high-scoring compounds to experimental collaborators for validation assays.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1980

Future plans for NASA's Oceanic Processes Program

NASA's Oceanic Processes Program has the objectives to develop a scientific basis for viewing the oceans from space and to demonstrate the utility of such an undertaking. There are currently four flight projects concerning the oceanic area. These projects are related to the National Oceanic Satellite System (NOSS), the Dynamic Ocean Topography Experiment (TOPEX), the Gravity Satellite (GRAVSAT), and a Synthetic Aperture Radar (SAR) mission. NOSS is being planned as a limited operational demonstration of viewing the oceans from space. It is to provide a capability to observe surface winds, waves, temperature, color, ice cover, and currents. It is scheduled for launch in 1986. TOPEX and GRAVSAT are being planned as research missions and are both scheduled for launch about 1986. The SAR mission is being planned to provide a spaceborne capability to observe the surface of the land and the oceans.

Wilson, W. S.↗

NASA NTRS2012

Radar Waveform Pulse Analysis Measurement System for High-Power GaN Amplifiers

This work presents a measurement system to characterize the pulsed response of high-power GaN amplifiers for use in space-based SAR platforms that require very strict amplitude and phase stability. The measurement system is able to record and analyze data on three different time scales: fast, slow, and long, which allows for greater detail of the mechanisms that impact amplitude and phase stability. The system is fully automated through MATLAB, which offers both instrument control capability and in-situ data processing. To validate this system, a high-power GaN HEMT amplifier operated in saturation was characterized. The fast time results show that variations to the amplitude and phase are correlated to DC supply transients, while long time characteristics are correlated to temperature changes.

high-power amplifier (HPA)↗

NASA NTRS2012

A Parameterized Inversion Model for Soil Moisture and Biomass from Polarimetric Backscattering Coefficients

A semi-empirical algorithm for the retrieval of soil moisture, root mean square (RMS) height and biomass from polarimetric SAR data is explained and analyzed in this paper. The algorithm is a simplification of the distorted Born model. It takes into account the physical scattering phenomenon and has three major components: volume, double-bounce and surface. This simplified model uses the three backscattering coefficients ( sigma HH, sigma HV and sigma vv) at low-frequency (P-band). The inversion process uses the Levenberg-Marquardt non-linear least-squares method to estimate the structural parameters. The estimation process is entirely explained in this paper, from initialization of the unknowns to retrievals. A sensitivity analysis is also done where the initial values in the inversion process are varying randomly. The results show that the inversion process is not really sensitive to initial values and a major part of the retrievals has a root-mean-square error lower than 5% for soil moisture, 24 Mg/ha for biomass and 0.49 cm for roughness, considering a soil moisture of 40%, roughness equal to 3cm and biomass varying from 0 to 500 Mg/ha with a mean of 161 Mg/ha

soil moisture↗

DOE OSTI2021

Ultra-large-scale ab initio quantum chemical computation of bio-molecular systems: The case of spike protein of SARS-CoV-2 virus

The COVID-19 pandemic poses a severe threat to human health with an unprecedented social and economic disruption. Spike (S) glycoprotein of the SARS-CoV-2 virus is pivotal in understanding the virus anatomy, since it initiates the first contact with the ACE2 receptor in the human cell. We report results of ab initio computation of the spike protein, the largest ab initio quantum chemical computation to date on any bio-molecular system, using a divide and conquer strategy by focusing on individual structural domains. In this approach we divided the S-protein into seven structural domains: N-terminal domain (NTD), receptor binding domain (RBD), subdomain 1 (SD1), subdomain 2 (SD2), fusion peptide (FP), heptad repeat 1 with central helix (HR1-CH) and connector domain (CD). The entire Chain A has 14,488 atoms including the hydrogen atoms but excluding the amino acids with missing coordinates based on the PDB data (ID: 6VSB). The results include structural refinement, ab initio calculation of intramolecular bonding mechanism, 3- dimensional non-local inter-amino acid interaction with implications for the inter-domain interaction. Details of the electronic structure, interatomic bonding, partial charge distribution and the role played by hydrogen bond network are discussed. In the interaction among structural domains, we present new insights for crucial hinge-like movement and fusion process. Extension of such calculation to the interface between the S-protein binding domain and ACE2 receptor can provide a pathway for computational understanding of mutations and the design of therapeutic drugs to combat the COVID-19 pandemic.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1993

SAR terrain classifier and mapper of biophysical attributes

In preparation for the launch of SIR-C/X-SAR and design studies for future orbital SAR, a program has made considerable progress in the development of an SAR terrain classifier and algorithms for quantification of biophysical attributes. The goal of this program is to produce a generalized software package for terrain classification and estimation of biophysical attributes and to make this package available to the larger scientific community. The basic elements of the SAR (Synthetic Aperture Radar) terrain classifier are outlined. An SAR image is calibrated with respect to known system and processor gains and external targets (if available). A Level 1 classifier operates on the data to differentiate: urban features, surfaces and tall and short vegetation. Level 2 classifiers further subdivide these classes on the basis of structure. Finally, biophysical and geophysical inversions are applied to each class to estimate attributes of interest. The process used to develop the classifiers and inversions is shown. Radar scattering models developed from theory and from empirical data obtained by truck-mounted polarimeters and the JPL AirSAR are validated. The validated models are used in sensitivity studies to understand the roles of various scattering sources (i.e., surface trunk, branches, etc.) in determining net backscatter. Model simulations of sigma (sup o) as functions of the wave parameters (lambda, polarization and angle of incidence) and the geophysical and biophysical attributes are used to develop robust classifiers. The classifiers are validated using available AirSAR data sets. Specific estimators are developed for each class on the basis of the scattering models and empirical data sets. The candidate algorithms are tested with the AirSAR data sets. The attributes of interest include: total above ground biomass, woody biomass, soil moisture and soil roughness.

Ulaby, Fawwaz T.↗

NASA NTRS1981

Texture measurements from Seasat - SAR images for urban land use interpretation

Different grey tones in Seasat Synthetic Aperture Radar (SAR) images for the same type of urban land cover considerably impair the possibilities of establishing automatic classification procedures for these types of data. Since the orientation of the main features like street patterns and buildings with respect to the azimuth angle of the radar antenna is the crucial factor for the observed differences in grey tone, prior information on these elements and special processing of the data would be required to eliminate this effect. Another approach suggested in this paper is to make use of the textural information in the image rather than of its grey tone. For different study sites within the Los Angeles urbanized area texture measures could be derived which result in characteristic values for specific types of land cover and are largely independent of the azimuth angle effect. At the same time the results for the study area indicate an improvement of the overall separability for the different land cover types included in the analysis.

Fasler, F.↗

NASA NTRS1990

Processing Of Multispectral Data For Identification Of Rocks

Linear discriminant analysis and supervised classification evaluated. Report discusses processing of multispectral remote-sensing imagery to identify kinds of sedimentary rocks by spectral signatures in geological and geographical contexts. Raw image data are spectra of picture elements in images of seven sedimentary rock units exposed on margin of Wind River Basin in Wyoming. Data acquired by Landsat Thematic Mapper (TM), Thermal Infrared Multispectral Scanner (TIMS), and NASA/JPL airborne synthetic-aperture radar (SAR).

Evans, Diane L.↗

NASA NTRS2011

Compact Polarimetry Potentials

The goal of this study is to show the potential of a compact-pol SAR system for vegetation applications. Compact-pol concept has been suggested to minimize the system design while maximize the information and is declined as the ?/4, ?/2 and hybrid modes. In this paper, the applications such as biomass and vegetation height estimates are first presented, then, the equivalence between compact-pol data simulated from full-pol data and compact-pol data processed from raw data as such is shown. Finally, a calibration procedure using external targets is proposed.

vegetation height↗

NASA NTRS2017

The Design of the Reference Orbit for NISAR, the NASA-ISRO Synthetic Aperture Radar Mission

The NISAR mission plans to use a 12-day-repeating sun-synchronous orbit for repeat-pass interferometry at multiple time scales using SAR data. For the interferometry to work the radar measurements must be made from within a critical baseline, which happens if all of the orbits are maintained to be within a fixed tube around a reference orbit. This paper describes the choice of dynamical models used in defining such a reference orbit, the perturbative effects of dynamics not considered in the repeat orbit, and the process of designing the orbit to repeat. We also describe our method for sharing the repeat orbit among multiple mission participants who use different models and software.

Hatch, Sara J.↗

NASA NTRS2017

The Design of the Reference Orbit for NISAR, the NASA-ISRO Synthetic Aperture Radar Mission

Hatch, Sara J.↗

NASA NTRS1995

Program Classifies Multiple-Frequency Polarimetric SAR Data

POLMAP computer program classifies multifrequency, polarimetric synthetic-aperture-radar (SAR) data into homogeneous classes of radar back-scatter. Software implements maximum-a-posteriori classification scheme. Performs by use of simulated-annealing procedure, takes much longer to compute than ICM solution, but it maximizes posteriori distribution of classes for whole scene. Input statistics of image classes must be created by some independent means, and supplied as input to POLMAP. Used as input to image processing application program. Written in FORTRAN 77.

Rignot, Eric↗

NASA NTRS2015

Design of an 8-40 GHz Antenna for the Wideband Instrument for Snow Measurements (WISM)

Measurement of land surface snow remains a significant challenge in the remote sensing arena. Developing the tools needed to remotely measure Snow Water Equivalent (SWE) is an important priority. The Wideband Instrument for Snow Measurements (WISM) is being developed to address this need. WISM is an airborne instrument comprised of a dual-frequency (X- and Ku-bands) Synthetic Aperture Radar (SAR) and dual-frequency (K- and Ka-bands) radiometer. A unique feature of this instrument is that all measurement bands share a common antenna aperture consisting of an array feed reflector that covers the entire bandwidth. This paper covers the design and fabrication of the wideband array feed which is based on tightly coupled dipole arrays. Implementation using a relatively new multi-layer microfabrication process results in a small, 6x6 element, dual-linear polarized array with beamformer that operates from 8 to 40 gigahertz.

8-40 GHz↗

NASA NTRS2003

Application of Satellite SAR Imagery in Mapping the Active Layer of Arctic Permafrost

The objective of this project is to map the spatial variation of the active layer over the arctic permafrost in terms of two parameters: (i) timing and duration of thaw period and (ii) differential frost heave and thaw settlement of the active layer. To achieve this goal, remote sensing, numerical modeling, and related field measurements are required. Tasks for the University of Colorado team are to: (i) determine the timing of snow disappearance in spring through changes in surface albedo (ii) simulate the freezing and thawing processes of the active layer and (iii) simulate the impact of snow cover on permafrost presence.

Zhang, Ting-Jun↗

DOE OSTI2016

Rain footprints on C-band synthetic aperture radar images of the ocean - Revisited

It is well known that rain leaves footprints on the sea surface that sometimes become visible on synthetic aperture radar (SAR) images. Rain cells can easily be detected on SAR images at all radar frequencies when they are associated with a downdraft pattern. But rain cells are not always associated with downdraft and rain can also occur in other forms, as stratified rain, rain bands, and squall lines. It turns out that radar signatures of rain at C-band are much more complex than at L- or X-band radar and that it is particularly difficult to identify unambiguously rain events on C-band SAR images acquired over the ocean. This is because C-band lies in the transition region where raindrops impinging onto the sea surface can increase (usually) or decrease the backscattered radar power and where volume scattering and attenuation by rain drops in the atmosphere are not always negligible (at very high rain rates). In order to get an insight into the physical mechanisms causing the C-band radar signatures of rain, we first revisit results obtained from historic laboratory and field experiments and multi-frequency/multi-polarization SAR data acquired during the SIR-C/X-SAR spaceshuttle mission in 1994. Then we analyze several C-band SAR images acquired by the European satellites Envisat and Sentinel-1A, and the Canadian satellite Radarsat-2 and compare them, whenever possible, with quasi-coincident and collocated weather radar images. The observational data show that, at low to medium rain rates, the main physical mechanism causing C-band radar signatures of rain is Bragg scattering at ring waves generated by the rain drops impinging onto the sea surface, which increase the radar backscatter. However, areas of increased radar backscatter are often accompanied by adjacent areas of decreased radar backscatter, which is due to attenuation of the Bragg waves by turbulence also generated by the impinging rain drops. Furthermore, we present a full-polarimetric Radarsat-2 SAR image of a rain cell together with a polarimetric decomposition analysis, which shows that the C-band radar signature of a rain cell is caused by surface scattering. The observation show that radar signatures of rain cells often contain segments, where the co-polarized as well the cross-polarized radar backscatter are strongly enhanced, which indicates non-Bragg scattering contributions to the scattering process. Furthermore, the polarimetric decomposition analysis shows that the C-band radar signature of a rain cell is dominated by surface scattering. Possible mechanisms, like scattering at splash products, are discussed. Whether the normalized radar cross section (NRCS) due to rain is increased or decreased depends on rain rate, wind speed, incidence angle, and history of the rain event. At low to moderate wind speeds (< 10 ms - 1 ) and low to medium high rain rates (< 50 mm h - 1 ), the NRCS is usually increased by up to 8 dB, and at high wind speeds (> 10 m s - 1 ) and low to high rain rates (but < 50 mm h - 1 ), the NRCS is usually decreased by up to 3 dB.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Towards Quantum-Chemical Level Calculations of SARS-CoV-2 Spike Protein Variants of Concern by First Principles Density Functional Theory

The spike protein (S-protein) is a crucial part of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with its many domains responsible for binding, fusion, and host cell entry. In this review we use the density functional theory (DFT) calculations to analyze the atomic-scale interactions and investigate the consequences of mutations in S-protein domains. We specifically describe the key amino acids and functions of each domain, which are essential for structural stability as well as recognition and fusion processes with the host cell; in addition, we speculate on how mutations affect these properties. Such unprecedented large-scale ab initio calculations, with up to 5000 atoms in the system, are based on the novel concept of amino acid–amino acid-bond pair unit (AABPU) that allows for an alternative description of proteins, providing valuable information on partial charge, interatomic bonding and hydrogen bond (HB) formation. In general, our results show that the S-protein mutations for different variants foster an increased positive partial charge, alter the interatomic interactions, and disrupt the HB networks. We conclude by outlining a roadmap for future computational research of biomolecular virus-related systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Cooperative multivalent receptor binding promotes exposure of the SARS-CoV-2 fusion machinery core

The molecular events that permit the spike glycoprotein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to bind and enter cells are important to understand for both fundamental and therapeutic reasons. Spike proteins consist of S1 and S2 domains, which recognize angiotensin-converting enzyme 2 (ACE2) receptors and contain the viral fusion machinery, respectively. Ostensibly, the binding of spike trimers to ACE2 receptors promotes dissociation of the S1 domains and exposure of the fusion machinery, although the molecular details of this process have yet to be observed. We report the development of bottom-up coarse-grained (CG) models consistent with cryo-electron tomography data, and the use of CG molecular dynamics simulations to investigate viral binding and S2 core exposure. We show that spike trimers cooperatively bind to multiple ACE2 dimers at virion-cell interfaces in a manner distinct from binding between soluble proteins, which processively induces S1 dissociation. We also simulate possible variant behavior using perturbed CG models, and find that ACE2-induced S1 dissociation is primarily sensitive to conformational state populations and the extent of S1/S2 cleavage, rather than ACE2 binding affinity. These simulations reveal an important concerted interaction between spike trimers and ACE2 dimers that primes the virus for membrane fusion and entry.

59 BASIC BIOLOGICAL SCIENCES↗