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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Power-Law Template for Infrared Point-Source Clustering

We perform a combined fit to angular power spectra of unresolved infrared (IR) point sources from the Planck satellite (at 217, 353, 545, and 857 GHz, over angular scales 100 approx < l approx < 2200), the Balloon-borne Large-Aperture Submillimeter Telescope (BLAST; 250, 350, and 500 micron; 1000 approx < l approx < 9000), and from correlating BLAST and Atacama Cosmology Telescope (ACT; 148 and 218 GHz) maps. We find that the clustered power over the range of angular scales and frequencies considered is well fitted by a simple power law of the form C(sup clust)(sub l) varies as l (sub −n) with n = 1.25 +/- 0.06. While the IR sources are understood to lie at a range of redshifts, with a variety of dust properties, we find that the frequency dependence of the clustering power can be described by the square of a modified blackbody, ν(sup Beta)B(ν, T(sub eff) ), with a single emissivity index Beta = 2.20 +/- 0.07 and effective temperature T(sub eff) = 9.7 K. Our predictions for the clustering amplitude are consistent with existing ACT and South Pole Telescope results at around 150 and 220 GHz, as is our prediction for the effective dust spectral index, which we find to be alpha(sub 150-220) = 3.68 +/- 0.07 between 150 and 220 GHz. Our constraints on the clustering shape and frequency dependence can be used to model the IR clustering as a contaminant in cosmic microwave background anisotropy measurements. The combined Planck and BLAST data also rule out a linear bias clustering model.

cosmic background radiation↗
NASA NTRS2014

Magnetite as Possible Template for the Synthesis of Chiral Organics in Carbonaceous Chondrites

The main goal of the Japanese Aerospace Ex-ploration Agency (JAXA) Hayabusa-2 mission is to visit and return to Earth samples of a C-type asteroid (162173) 1999 JU3 in order to understand the origin and nature of organic materials in the Solar System. Life on Earth shows preference towards the set of organics with particular spatial arrangements, this 'selectivity' is a crucial criterion for life. With only rare exceptions, life 'determines' to use the left- (L-) form over the right- (D-) form of amino acids, resulting in a L-enantiomeric excess (ee). Recent studies have shown that L-ee is found within the alpha-methyl amino acids in meteorites [1, 2], which are amino acids with rare terrestrial occurrence, and thus point towards a plausible abiotic origin for ee. One of the proposed origins of chiral asymmetry of amino acids in meteorites is their formation with the presence of asymmetric catalysts [3]. The catalytic mineral grains acted as a surface at which nebular gases (CO, H2 and NH3) were allowed to condense and react through Fisher Tropsch type (FTT) syntheses to form the organics observed in meteorites [4]. Magnetite is shown to be an effective catalyst of the synthesis of amino acids that are commonly found in meteorites [5]. It has also taken the form as spiral magnetites (a.k.a. 'plaquettes'), which were found in various carbonaceous chondrites (CCs), including C2s Tagish Lake and Esseibi, CI Orgueil, and CR chondrites [e.g., 6, 7, 8]. In addition, L-ee for amino acids are common in the aqueously altered CCs, as opposed to the unaltered CCs [1]. It seems possible that the synthesis of amino acids with chiral preferences is correlated to the alteration process experienced by the asteroid parent body, and related to the configuration of spiral magnetite catalysts. Since C-type asteroids are considered to be enriched in organic matter, and the spectral data of 1999 JU3 indicates a certain de-gree of aqueous alteration [9], the Hayabusa-2 mission serves as a perfect chance to attest this argument. In order to understand the distribution of spiral magnetites among different meteorite classes, as well as to investigate their spiral configurations and correlation to molecular asymmetry, we observed polished thin sections of CCs using scanning electron microscope (SEM) imaging. Individual magnetite grains were picked, embedded in epoxy, thin-sectioned using an ultra-microtome, and studied with electron backscatter diffraction (EBSD) in order to reconstruct the crystal orientation along the stack of magnetite disks.

Chan, Q. H. S.↗
NASA NTRS2020

Metal-Templated Design of Chemically Switchable Protein Assemblies with High-Affinity Coordination Sites

To mimic a hypothetical pathway for protein evolution, we previously tailored a monomeric protein (cyt cb562) for metal-mediated self-assembly, followed by re-design of the resulting oligomers for enhanced stability and metal-based functions. We show that a single hydrophobic mutation on the cyt cb562 surface drastically alters the outcome of metal-directed oligomerization to yield a new trimeric architecture, (TriCyt1)3. This nascent trimer was redesigned into second and third-generation variants (TriCyt2)3 and (TriCyt3)3 with increased structural stability and preorganization for metal coordination. The three TriCyt variants combined furnish a unique platform to 1) provide tunable coupling between protein quaternary structure and metal coordination, 2) enable the construction of metal/pH-switchable protein oligomerization motifs, and 3) generate a robust metal coordination site that can coordinate all mid-to-late first-row transition-metal ions with high affinity.

Albert Kakkis↗
NASA NTRS1999

Field Encapsulation Library The FEL 2.2 User Guide

This document describes version 2.2 of the Field Encapsulation Library (FEL), a library of mesh and field classes. FEL is a library for programmers - it is a "building block" enabling the rapid development of applications by a user. Since FEL is a library intended for code development, it is essential that enough technical detail be provided so that one can make full use of the code. Providing such detail requires some assumptions with respect to the reader's familiarity with the library implementation language, C++, particularly C++ with templates. We have done our best to make the explanations accessible to those who may not be completely C++ literate. Nevertheless, familiarity with the language will certainly help one's understanding of how and why things work the way they do. One consolation is that the level of understanding essential for using the library is significantly less than the level that one should have in order to modify or extend the library. One more remark on C++ templates: Templates have been a source of both joy and frustration for us. The frustration stems from the lack of mature or complete implementations that one has to work with. Template problems rear their ugly head particularly when porting. When porting C code, successfully compiling to a set of object files typically means that one is almost done. With templated C++ and the current state of the compilers and linkers, generating the object files is often only the beginning of the fun. On the other hand, templates are quite powerful. Used judiciously, templates enable more succinct designs and more efficient code. Templates also help with code maintenance. Designers can avoid creating objects that are the same in many respects, but not exactly the same. For example, FEL fields are templated by node type, thus the code for scalar fields and vector fields is shared. Furthermore, node type templating allows the library user to instantiate fields with data types not provided by the FEL authors. This type of flexibility would be difficult to offer without the support of the language. For users who may be having template-related problems, we offer the consolation that support for C++ templates is destined to improve with time. Efforts such as the Standard Template Library (STL) will inevitably drive vendors to provide more thorough, optimized tools for template code development. Furthermore, the benefits will become harder to resist for those who currently subscribe to the least-common-denominator "code it all in C" strategy. May FEL bring you both increased productivity and aesthetic satisfaction.

Moran, Patrick J.↗
DOE OSTI2026

Location Identifiers, Metadata, and Map for Field Measurements at the East-Taylor Watershed Community Observatory, Colorado, USA (Version 3.3)

This dataset contains identifiers, metadata, and a map of the locations where field measurements have been conducted at the East-Taylor Watershed Community Observatory located in the Upper Colorado River Basin, United States. This is version 3.3 of the dataset and replaces the prior version 3.2 (see below for details on changes between the versions). Dataset description: The East River-Taylor Watershed is the primary field site of the Watershed Function Scientific Focus Area (WFSFA) and the Rocky Mountain Biological Laboratory. Researchers from several institutions generate highly diverse hydrological, biogeochemical, climate, vegetation, geological, remote sensing, and model data at the East-Taylor Watershed in collaboration with the WFSFA. Thus, the purpose of this dataset is to maintain an inventory of the field locations and instrumentation to provide information on the field activities in the East-Taylor Watershed and coordinate data collected across different locations, researchers, and institutions. The dataset contains (1) a README file with information on the various files, (2) three csv files describing the metadata collected for each surface point location, plot and region registered with the WFSFA, (3) csv files with metadata and contact information for each surface point location registered with the WFSFA, (4) a csv file with with metadata and contact information for plots, (5) a csv file with metadata for geographic regions and sub-regions within the watershed, (6) a compiled xlsx file with all the data and metadata which can be opened in Microsoft Excel, (7) a kml map of the locations plotted in the watershed which can be opened in Google Earth, (8) a jpg image of the kml map which can be viewed in any photo viewer, and (9) a zipped file with the registration templates used by the SFA team to collect location metadata. The zipped template file contains two csv files with the blank templates (point and plot), two csv files with instructions for filling out the location templates, and one compiled xlsx file with the instructions and blank templates together. Additionally, the templates in the xlsx include drop down validation for any controlled metadata fields. Persistent location identifiers (Location_ID) are determined by the WFSFA data management team and are used to track data and samples across locations. Dataset uses: This location metadata is used to update the Watershed SFA’s publicly accessible Field Information Portal (an interactive field sampling metadata exploration tool; https://wfsfa-data.lbl.gov/watershed/), the kml map file included in this dataset, and other data management tools internal to the Watershed SFA team. Version Information: The latest version of this dataset publication is version 3.3. This version contains 167 new point locations, 1 new plot, and 2 new geographic regions. Overall, there are a total of 1439 point locations, 75 plots, and 54 geographic regions. Additionally, the kml map of locations and image now includes two boundaries (Upper Ohio Creek (UO) and Carbon Creek (CA)) outside of the East River watershed (USGS HUC-10) and accompanying stream network that represents areas of focus. Refer to methods for further details on the version history. This dataset will be updated on a periodic basis with new measurement location information. Researchers interested in having their East-Taylor Watershed measurement locations added to this list should reach out to the WFSFA data management team at wfsfa-data@googlegroups.com. Acknowledgments: Please cite this dataset if using any of the location metadata in other publications or derived products. If using the location metadata for the 2018 NEON hyperspectral campaign, additionally cite Chadwick et al. (2020). doi:10.15485/1618130. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

2018 NEON and 2025 CHESS Campaigns↗
NASA NTRS1976

A multilevel approach to sequential detection of pictorial features

The problem of detecting the local similarity between templates in a given class and a given image using a hierarchically ordered sequential decision rule is examined. It is proposed that the set of templates be partitioned and a 'representative template' be defined for each of the partitions. Several levels of partitioning are defined. Elimination of mismatching locations and termination of computation can take place at each level of detection. Each level of testing is over a more restrictive subset of the template class than the previous level. Criteria are given for selecting representative templates, the ordering of components of a template vector for error evaluation, and the threshold sequences to be used in deciding about a 'match'. Suboptimal solutions are given satisfying these criteria. Examples showing recognition of linear features in test patterns and photographs obtained by aerial and spaceborne sensors are provided.

Ramapriyan, H. K.↗
NASA NTRS2006

Improvement in Visual Target Tracking for a Mobile Robot

In an improvement of the visual-target-tracking software used aboard a mobile robot (rover) of the type used to explore the Martian surface, an affine-matching algorithm has been replaced by a combination of a normalized- cross-correlation (NCC) algorithm and a template-image-magnification algorithm. Although neither NCC nor template-image magnification is new, the use of both of them to increase the degree of reliability with which features can be matched is new. In operation, a template image of a target is obtained from a previous rover position, then the magnification of the template image is based on the estimated change in the target distance from the previous rover position to the current rover position (see figure). For this purpose, the target distance at the previous rover position is determined by stereoscopy, while the target distance at the current rover position is calculated from an estimate of the current pose of the rover. The template image is then magnified by an amount corresponding to the estimated target distance to obtain a best template image to match with the image acquired at the current rover position.

Kim, Won↗
NASA NTRS2017

Collaborative Data Publication Utilizing the Open Data Repository's (ODR) Data Publisher

Introduction: For small communities in diverse fields such as astrobiology, publishing and sharing data can be a difficult challenge. While large, homogenous fields often have repositories and existing data standards, small groups of independent researchers have few options for publishing standards and data that can be utilized within their community. In conjunction with teams at NASA Ames and the University of Arizona, the Open Data Repository's (ODR) Data Publisher has been conducting ongoing pilots to assess the needs of diverse research groups and to develop software to allow them to publish and share their data collaboratively. Objectives: The ODR's Data Publisher aims to provide an easy-to-use and implement software tool that will allow researchers to create and publish database templates and related data. The end product will facilitate both human-readable interfaces (web-based with embedded images, files, and charts) and machine-readable interfaces utilizing semantic standards. Characteristics: The Data Publisher software runs on the standard LAMP (Linux, Apache, MySQL, PHP) stack to provide the widest server base available. The software is based on Symfony (www.symfony.com) which provides a robust framework for creating extensible, object-oriented software in PHP. The software interface consists of a template designer where individual or master database templates can be created. A master database template can be shared by many researchers to provide a common metadata standard that will set a compatibility standard for all derivative databases. Individual researchers can then extend their instance of the template with custom fields, file storage, or visualizations that may be unique to their studies. This allows groups to create compatible databases for data discovery and sharing purposes while still providing the flexibility needed to meet the needs of scientists in rapidly evolving areas of research. Research: As part of this effort, a number of ongoing pilot and test projects are currently in progress. The Astrobiology Habitable Environments Database Working Group is developing a shared database standard using the ODR's Data Publisher and has a number of example databases where astrobiology data are shared. Soon these databases will be integrated via the template-based standard. Work with this group helps determine what data researchers in these diverse fields need to share and archive. Additionally, this pilot helps determine what standards are viable for sharing these types of data from internally developed standards to existing open standards such as the Dublin Core (http://dublincore.org) and Darwin Core (http://rs.twdg.org) metadata standards. Further studies are ongoing with the University of Arizona Department of Geosciences where a number of mineralogy databases are being constructed within the ODR Data Publisher system. Conclusions: Through the ongoing pilots and discussions with individual researchers and small research teams, a definition of the tools desired by these groups is coming into focus. As the software development moves forward, the goal is to meet the publication and collaboration needs of these scientists in an unobtrusive and functional way.

easy to use and implement software tool↗
NASA NTRS2016

Storage of Physical Sample Metadata in the Astrobiology Habitable Environments Database (AHED)

The National Aeronautics and Space Administration has begun an effort to store, curate, and publish information about physical samples collected and analyzed in conjunction with NASA-funded astrobiology research. Astrobiology is a multidisciplinary area of scientific research being conducted by collaborating teams of biologists, chemists, geologists, atmospheric scientists, oceanographers, astrophysicists, astronomers, and other specialists. Astrobiology studies the origin, evolution, and distribution of life in the Universe. NASA uses the results of astrobiology research to focus its future missions on targets of opportunity for the discovery of life off Earth. Astrobiology researchers conduct both field-based and laboratory-based research, during which physical samples are collected, processed, and catalogued. The cataloguing practices employed by different teams of astrobiologists vary widely, and there are no specific standards available to guide the collection and recording of astrobiology sample data. The disparity in data collection approaches and the lack of a centralized sample repository makes it difficult for astrobiology teams to share data and benefit from resultant synergies.To facilitate data sharing within the astrobiology community, NASA is developing a prototype database the Astrobiology Habitable Environments Database (AHED) and an associated set of data collection templates. The database will store information about samples, along with associated measurements and analyses, including information about biological cultures enriched or isolated from samples, and the results of analyses performed on the samples (e.g., via spectrography, microscopy, etc.). In addition, the system will store contextual information about field sites where samples were collected, the instruments or equipment used for analysis, and people and institutions involved in their collection. AHED is being implemented on top of Open Data Repository's Data Publisher [1], an open source software platform for the publication of scientific datasets. The data collection templates under development represent an initial attempt to propose a set of metadata for capture and storage within AHED. The design of these templates is being conducted by a consolidated group of astrobiologists from active research teams at NASA Ames Research Center, assisted by data science and software engineering specialists. These initial templates must be vetted with the broader astrobiology community through a defined process to ensure that they meet community needs. Each template captures a different type of data collection record. For each template, we are developing a list of fields to be captured, including a set of required entry fields, a set of recommended but optional fields, and a set of discretionary fields. A datatype selected from a variety of text and numeric types is specified for each field. Included is a 'choice' type that restricts user input to an enumerated list of values. Many of the fields and field values capture information of particular interest to the astrobiology community, and are intended to facilitate search and retrieval of relevant data across multiple datasets.

Keller, Rich↗
DOE OSTI2024

Clear Sky Toolkit: Decision Support User Guide

The Clear Sky Decision Support Template is a Microsoft Excel-based resource that enables users to screen and prioritize critical facilities for the addition of solar + storage. The Decision Support Template consolidates and streamlines the most relevant resources from the emergency management discipline, the electric utility sector, and national energy research institutions to assist in further site analysis and decision-making. The Decision Support Template is intended for use by local government and private sector decision-makers who aim to mitigate the effects of power outages on critical infrastructure, understand the potential for deploying photovoltaic (PV) and storage solutions on critical facilities, and align emergency management planning processes and utility needs with community resilience objectives. The Decision Support Template is divided into five modules that provide a structured, step-by-step approach users can follow and apply to unique circumstances. This process guides a more thorough and accurate assessment of a site's potential to accommodate a solar + storage system, provide grid benefits to utilities, and support community resilience and disaster mitigation for the broader region. After identifying potentially viable and preferred sites for solar + storage using the Decision Support Template, users should conduct a more detailed evaluation and consultation with a solar professional.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗