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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

Region Spherical Harmonic Magnetic Modeling from Near-Surface and Satellite-Altitude Anomlaies

The compiled near-surface data and satellite crustal magnetic measured data are modeled with a regionally concentrated spherical harmonic presentation technique over Australia and Antarctica. Global crustal magnetic anomaly studies have used a spherical harmonic analysis to represent the Earth's magnetic crustal field. This global approach, however is best applied where the data are uniformly distributed over the entire Earth. Satellite observations generally meet this requirement, but unequally distributed data cannot be easily adapted in global modeling. Even for the satellite observations, due to the errors spread over the globe, data smoothing is inevitable in the global spherical harmonic presentations. In addition, global high-resolution modeling requires a great number of global spherical harmonic coefficients for the regional presentation of crustal magnetic anomalies, whereas a lesser number of localized spherical coefficients will satisfy. We compared methods in both global and regional approaches and for a case where the errors were propagated outside the region of interest. For observations from the upcoming Swarm constellation, the regional modeling will allow the production a lesser number of spherical coefficients that are relevant to the region of interest

Modeling↗

Automating Microbial Directed Evolution For Bioengineering Applications

From a micro-biology perspective, directed evolution is a technique that uses controlled environmental pressures to select for a desired phenotype. Directed evolution has the distinct advantage over rational design of not needing extensive knowledge of the genome or pathways associated with a microorganism to induce phenotypes. However, there are currently limitations to the applicability of this technique including being time-consuming, error-prone, and dependent on existing assays that may lack selectivity for the given phenotype. The AADEC (Autonomous Adaptive Directed Evolution Chamber) system is a proof-of-concept instrument to automate and improve the technique such that directed evolution can be used more effectively as a general bioengineering tool. A series of tests using the automated system and comparable by-hand survival assay measurements have been carried out using UV-C radiation and Escherichia coli cultures in order to demonstrate the advantages of the AADEC versus traditional implementations of directed evolution such as random mutagenesis. AADEC uses UV-C exposure as both a source of environmental stress and mutagenesis, so in order to evaluate the UV-C tolerance obtained from the cultures, a manual UV-C exposure survival assay was developed alongside the device to compare the survival fractions at a fixed dosage. This survival assay involves exposing E. coli to UV-C radiation using a custom-designed exposure hood to control the flux and dose. Surviving cells are counted then transferred to the next iteration and so on for several iterations to calculate the survival fractions for each exposure iteration.This survival assay primarily serves as a baseline for the AADEC device, allowing quantification of the differences between the AADEC system over the manual approach. The primary data of comparison is survival fractions; this is obtained by optical density and plate counts in the manual assay and by optical density growth curve fits pre- and post-exposure in the automated case. This data can then be compiled to calculate trends over the iterations to characterize increasing UV-C resistance of the E.coli strains. The observed trends are statistically indistinguishable through several iterations from both sources.

Bioengineering↗

Performance of JAXA’s SGLI standard ocean color products for oceanic to coastal waters: chlorophyll a concentration and light absorption coefficients of colored dissolved organic matter

We present the performance of JAXA’s SGLI standard algorithms for estimating chlorophyll a (chl a) concentration and the light absorption coefcients of colored dissolved organic matter (CDOM) using recently compiled high-quality data obtained from oceanic to coastal waters. Prior to the evaluation of the algorithms, we frst compare two forward models (Gordon et al. in J Geophys Res 93(D9):10909-10924, 1988: G88 and Park and Ruddick in Appl Opt 44(7):1236–1249, 2005: PR05) using a wide range of inherent optical properties (IOPs) to (1) examine if the water refectance is appropriately reproduced and (2) correct measured refectance in terms of its bidirectionality. Based on a good reproducibility of water refectance using the PR05, the optimized IOPs are further used for explaining errors in estimates of chl a concentration and CDOM absorption when using the SGLI, the GSM (Maritorena et al. in Appl Opt 41:2705–2714, 2002), and the QAA (Lee et al. in Appl Opt 41:5755, 2002) inversion algorithms. Results show that the mean error for estimating chl a concentration using the SGLI algorithm is 110% for our dataset. Although this error is lower than that of the GSM and the QAA algorithms, a signifcant underestimate at chl a higher than 2.0 mg m−3 is observed, which is further shown by independent match-up analyses. Another SGLI CDOM product includes the mean error of 50% and shows deviation at high CDOM range (>1.0 per m). A similar trend is observed for the GSM but not for the QAA when a global relationship of CDOM to colored detrital matter is applied. The sources of errors are discussed for potentially improving the retrievals

Second-generation GLobal Imager (SGLI)↗

Compiler analysis for irregular problems in FORTRAN D

We developed a dataflow framework which provides a basis for rigorously defining strategies to make use of runtime preprocessing methods for distributed memory multiprocessors. In many programs, several loops access the same off-processor memory locations. Our runtime support gives us a mechanism for tracking and reusing copies of off-processor data. A key aspect of our compiler analysis strategy is to determine when it is safe to reuse copies of off-processor data. Another crucial function of the compiler analysis is to identify situations which allow runtime preprocessing overheads to be amortized. This dataflow analysis will make it possible to effectively use the results of interprocedural analysis in our efforts to reduce interprocessor communication and the need for runtime preprocessing.

Vonhanxleden, Reinhard↗

The radial and longitudinal propagation characteristics of substorm injections

This paper presents a statistical study of the radial and azimuthal propagation of substorm effects in the near-geosynchronous magnetotail. Data from five spacecraft (AMPTE/CCE, 1979-053, 1982-019, GOES-5, and GOES-6) have been used in the study. Since CCE has an apogee of 8.8 earth radii, those data allow for the study of both the radial and azimuthal propagation characteristics of substorm events. A list of ion injections was compiled from CCE energetic particle data obtained in 1985 and 1986. Those injections are dispersionless over an energy range of 25 to 285 keV on a 72-sec time scale. Dispersionless injections during which 1979-053 or 1982-019 were on the nightside in close longitudinal proximity to CCE were selected for the study. The most significant correlation in the data is between the local time separation between any two spacecraft and the time delay between the local onsets.

Lopez, R. E.↗

The Steward Observatory asteroid relational database

The Steward Observatory Asteroid Relational Database (SOARD) was created as a flexible tool for undertaking studies of asteroid populations and sub-populations, to probe the biases intrinsic to asteroid databases, to ascertain the completeness of data pertaining to specific problems, to aid in the development of observational programs, and to develop pedagogical materials. To date, SOARD has compiled an extensive list of data available on asteroids and made it accessible through a single menu-driven database program. Users may obtain tailored lists of asteroid properties for any subset of asteroids or output files which are suitable for plotting spectral data on individual asteroids. The program has online help as well as user and programmer documentation manuals. The SOARD already has provided data to fulfill requests by members of the astronomical community. The SOARD continues to grow as data is added to the database and new features are added to the program.

Sykes, Mark V.↗

The Steward Observatory asteroid relational database

The Steward Observatory Asteroid Relational Database (SOARD) was created as a flexible tool for undertaking studies of asteroid populations and sub-populations, to probe the biases intrinsic to asteroid databases, to ascertain the completeness of data pertaining to specific problems, to aid in the development of observational programs, and to develop pedagogical materials. To date SOARD has compiled an extensive list of data available on asteroids and made it accessible through a single menu-driven database program. Users may obtain tailored lists of asteroid properties for any subset of asteroids or output files which are suitable for plotting spectral data on individual asteroids. A browse capability allows the user to explore the contents of any data file. SOARD offers, also, an asteroid bibliography containing about 13,000 references. The program has online help as well as user and programmer documentation manuals. SOARD continues to provide data to fulfill requests by members of the astronomical community and will continue to grow as data is added to the database and new features are added to the program.

Sykes, Mark V.↗

Optimizing Deep Learning Models for Climate-Related Natural Disaster Detection from UAV Images and Remote Sensing Data

This research study utilized artificial intelligence (AI) to detect natural disasters from aerial images. Flooding and desertification were two natural disasters taken into consideration. The Climate Change Dataset was created by compiling various open-access data sources. This dataset contains 6334 aerial images from UAV (unmanned aerial vehicles) images and satellite images. The Climate Change Dataset was then used to train Deep Learning (DL) models to identify natural disasters. Four different Machine Learning (ML) models were used: convolutional neural network (CNN), DenseNet201, VGG16, and ResNet50. These ML models were trained on our Climate Change Dataset so that their performance could be compared. DenseNet201 was chosen for optimization. All four ML models performed well. DenseNet201 and ResNet50 achieved the highest testing accuracies of 99.37% and 99.21%, respectively. This research project demonstrates the potential of AI to address environmental challenges, such as climate change-related natural disasters. This study’s approach is novel by creating a new dataset, optimizing an ML model, cross-validating, and presenting desertification as one of our natural disasters for DL detection. Three categories were used (Flooded, Desert, Neither). Our study relates to AI for Climate Change and Environmental Sustainability. Drone emergency response would be a practical application for our research project.

AI↗

Aerodynamics of Stardust Sample Return Capsule

Successful return of interstellar dust and cometary material by the Stardust Sample Return Capsule requires an accurate description of the Earth entry vehicle's aerodynamics. This description must span the hypersonic-rarefied, hypersonic-continuum, supersonic, transonic, and subsonic flow regimes. Data from numerous sources are compiled to accomplish this objective. These include Direct Simulation Monte Carlo analyses, thermochemical nonequilibrium computational fluid dynamics, transonic computational fluid dynamics, existing wind tunnel data, and new wind tunnel data. Four observations are highlighted: 1) a static instability is revealed in the free-molecular and early transitional-flow regime due to aft location of the vehicle s center-of-gravity, 2) the aerodynamics across the hypersonic regime are compared with the Newtonian flow approximation and a correlation between the accuracy of the Newtonian flow assumption and the sonic line position is noted, 3) the primary effect of shape change due to ablation is shown to be a reduction in drag, and 4) a subsonic dynamic instability is revealed which will necessitate either a change in the vehicle s center-of-gravity location or the use of a stabilizing drogue parachute.

Mitcheltree, R. A.↗

Structure–Composition Relationships for Mg–Ni and Mg–Fe Olivine

Olivine is a dynamic and important mineral in the crust and mantle with relevance to processes important to climate change technology, such as geologic carbon storage and critical mineral recovery. In this work, we critically evaluated and compiled a new database of olivine diffraction data, lattice parameters, and composition to enable rapid Ni-Mg-Fe olivine composition determination. A compilation of olivine X-ray diffraction data and chemical compositions from both the literature and the International Centre for Diffraction Data (ICDD) powder database was assembled to plot both the forsterite-fayalite and forsterite-liebenbergite solid solution lines. Here we present an expanded dataset to delineate equations and relationships used for quantifying the correlations between olivine lattice parameters and chemical compositions in Mg 2 SiO 4 -Fe 2 SiO 4 (forsterite-fayalite) and Mg 2 SiO 4 -Ni 2 SiO 4 (forsterite-liebenbergite) olivine solid solution series.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atlas of Archived Vegetation, Land-use and Seasonal Albedo Data Sets

Global digital data bases of natural vegetation and land use were compiled, for use in climate studies, at 1 deg resolution from over 100 published sources. A series of 6 data sets, derived from the original compilations, was prepared and archived on tape at the National Center for Atmospheric Research (NCAR) (Matthews, 1984). The first is a vegetation data set representing natural (pre-agricultural) vegetation based on the UNESCO classification system. The second, derived from the land-use compilation, is a cultivation-intensity data set defining the areal extent of presently-cultivated land in the 1 deg cells. The last four are integrated surface-albedo data sets (January, April, July, October) for snow-free conditions, incorporating natural-vegetation and cultivation characteristics from the vegetation and cultivation-intensity data sets. Each of these data sets covers the entire surface of the earth. They include non-zero data for permanent land only, including continental ice; water, including oceans and lakes, is zero. The present report includes maps, presented by continent, of the complete archived data, with the exception of Antarctica.

Matthews, E.↗

Chemical kinetics and photochemical data for use in stratospheric modeling

As part of a series of evaluated sets, rate constants and photochemical cross sections compiled by the NASA Panel for Data Evaluation are provided. The primary application of the data is in the modeling of stratospheric processes, with particular emphasis on the ozone layer and its possible perturbation by anthropogenic and natural phenomena. Copies of this evaluation are available from the Jet Propulsion Laboratory.

Demore, W. B.↗

Far infrared supplement. Third edition: Catalog of infrared observations (lambda greater than or equal to 4.6 micrometers)

The Far Infrared Supplement contains a subset of the data in the full Catalog of Infrared Observations (all observations at wavelengths greater than 4.6 microns). The Catalog of Infrared Observations (CIO), NASA RP-1294, is a compilation of infrared astronomical observational data obtained from an extensive literature search of scientific journals and major astronomical catalogs and surveys. The literature search is complete for years 1965 through 1990 in this third edition. The catalog contains about 210,000 observations of roughly 20,000 individual sources, and supporting appendices. The expanded third edition contains coded IRAS 4-band data for all CIO sources detected by IRAS. The appendices include an atlas of infrared source positions (also included in this volume), two bibliographies of catalog listings, and an atlas of infrared spectral ranges. The complete CIO database is available to qualified users in printed, microfiche, and magnetic tape formats.

Gezari, Daniel Y.↗

Catalog of Infrared Observations, Third Edition

The Far Infrared Supplement contains a subset of the data in the full Catalog of Infrared Observations (all observations at wavelengths greater than 4.6 microns). The Catalog of Infrared Observations (CIO), NASA RP-1294, is a compilation of infrared astronomical observational data obtained from an extensive literature search of scientific journals and major astronomical catalogs and surveys. The literature search is complete for years 1965 through 1990 in this Third Edition. The Catalog contains about 210,000 observations of roughly 20,000 individual sources and supporting appendices. The expanded Third Edition contains coded IRAS 4-band data for all CIO sources detected by IRAS. The appendices include an atlas of infrared source positions (also included in this volume), two bibliographies of Catalog listings, and an atlas of infrared spectral ranges. The complete CIO database is available to qualified users in printed, microfiche, and magnetic-tape formats.

Gezari, Daniel Y.↗

Gamma ray astronomy

Miscellaneous tasks related to mission operations and data analysis for the Burst and Transient Source Experiment on the Gamma Ray Observatory, to collection, analysis, and interpretation of data from the Marshall Space Flight Center Very Low Frequency transient monitoring program, and to compilation and analysis of induced radioactivity data were performed. The results are summarized and relevant references are included.

Paciesas, William S.↗

A Modified Algorithm and Open-Source Computational Package for the Determination of Infrared Optical Constants Relevant to Astrophysics

Infrared (IR) telescopes, such as Spitzer and SOFIA, have revealed a rich variety of chemical species trapped in interstellar ices. The most fundamental parameters to be derived from observed IR spectra are the identity and abundance of each component. Several compounds have been conclusively or tentatively identified, but the band strengths and optical constants needed to derive accurate abundances for many of these are poorly constrained. We have developed a modified approach to the extraction of the real and imaginary parts of the refractive index (optical constants) of a thin film from a single transmission spectrum measured in the IR spectral range. Our algorithm is similar to those implemented by previous authors, with some major changes that yield results for strong absorptions where previous approaches fail: (1) an adaptive k-correction step size, (2) the use of a root-finding algorithm to obtain a more accurate k-correction at each iteration, and (3) a k-correction step that prevents non-physical results such as negative n-values that prevent convergence in the calculation algorithm. The algorithm is presented and described, with examples to show agreement with some existing results and improvements upon others. New optical-constants calculations for CH3OH, CO2, N2O, and CH4 are presented, and potential implications for the modeling of interstellar and planetary ice data from space telescopes are discussed. With the objective of being open-source and transparent, the full source code in the free Python programming language is made available along with the compiled version and the laboratory data used to produce the results shown.

Perry A. Gerakines↗