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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 109 records · Page 6

Hidden Identification on Parts: Magnetic Machine-Readable Matrix Symbols

All NASA parts have identification, usually expressed in terms of part number, serial number, and the like. In most cases, this identification is permanently marked directly on the part for tracking throughout its life cycle. NASA has developed a method for reading the matrix symbol through up to 15 mils (25 m) of paint (5 or 6 layers). This method of part identification involves coating selected patches on the objects with magnetic materials in matrix symbol patterns and reading the patterns by use of magneto-optical imaging equipment.

Schramm, Harry F.↗

Toolsets for Airborne Data (TAD): Improving Machine Readability for ICARTT Data Files

The Atmospheric Science Data Center (ASDC) at NASA Langley Research Center is responsible for the ingest, archive, and distribution of NASA Earth Science data in the areas of radiation budget, clouds, aerosols, and tropospheric chemistry. The ASDC specializes in atmospheric data that is important to understanding the causes and processes of global climate change and the consequences of human activities on the climate. The ASDC currently supports more than 44 projects and has over 1,700 archived data sets, which increase daily. ASDC customers include scientists, researchers, federal, state, and local governments, academia, industry, and application users, the remote sensing community, and the general public.

Early, Amanda Benson↗

Methods, systems, and computer-readable storage media for enhanced phase-contrast x-ray imaging

Systems and methods that directly image attenuation-based object grid, use a source grid to improve imaging of the object grid using a high-energy polychromatic source, and use a detector grid having gratings oriented substantially orthogonally to that of the object grid, can address artifacts and beam hardening effects that limit the quality and discriminatory power of high-energy x-ray imaging that includes phase contrast.

Miller, Erin A.↗

Methods, systems, and computer-readable storage media for enhanced phase-contrast x-ray imaging

Systems and methods that directly image attenuation-based object grid, use a source grid to improve imaging of the object grid using a high-energy polychromatic source, and use a detector grid having gratings oriented substantially orthogonally to that of the object grid, can address artifacts and beam hardening effects that limit the quality and discriminatory power of high-energy x-ray imaging that includes phase contrast.

Miller, Erin A.↗

PDF Entity Annotation Tool (PEAT)

While different text mining approaches – including the use of Artificial Intelligence (AI) and other machine based methods - continue to expand at a rapid pace, the tools used by researchers to create the labeled datasets required for training, modeling, and evaluation remain rudimentary. Labeled datasets contain the target attributes the machine is going to learn; for example, training an algorithm to delineate between images of a car or truck would generally require a set of images with a quantitative description of the underlying features of each vehicle type. Development of labeled textual data that can be used to build natural language machine learning models for scientific literature is not currently integrated into existing manual workflows used by domain experts. Published literature is rich with important information, such as different types of embedded text, plots, and tables that can all be used as inputs to train ML/natural language processing (NLP) models, when extracted and prepared in machine readable formats. Currently, both normalized data extraction of use to domain experts and extraction to support development of ML/NLP models are labor intensive and cumbersome manual processes. Automatic extraction of data and information from formats such as PDFs that are optimized for layout and human readability, not machine readability. The PDF (Portable Document Format) Entity Annotation Tool (PEAT) was developed with the goal of allowing users to annotate publications within their current print format, while also allowing those annotations to be captured in a machine-readable format. One of the main issues with traditional annotation tools is that they require transforming the PDF into plain text to facilitate the annotation process. While doing so lessens the technical challenges of annotating data, the user loses all structure and provenance that was inherent in the underlying PDF. Also, textual data extraction from PDFs can be an error prone process. Challenges include identifying sequential blocks of text and a multitude of document formats (multiple columns, font encodings, etc.). As a result of these challenges, using existing tools for development of NLP/ML models directly from PDFs is difficult because the generated outputs are not interoperable. We created a system that allows annotations to be completed on the original PDF document structure, with no plain text extraction. The result is an application that allows for easier and more accurate annotations. In addition, by including a feature that grants the user the ability to easily create a schema, we have developed a system that can be used to annotate text for different domain-centric schemas of relevance to subject matter experts. Different knowledge domains require distinct schemas and annotation tags to support machine learning.

97 MATHEMATICS AND COMPUTING↗

Mist

Determining the appropriate material data is often a bottleneck for performing calculations/simulations of industrial/experimental processes and resulting material structures and properties. Beyond the time it takes to find the appropriate values in the literature, many judgement calls are involved in choosing the values. These judgement calls can lead to inconsistencies between steps in research workflow, where different material parameter values are used. Mist solves this problem by providing a mechanism to store, share, and use material information in convenient human-readable and machine-readable formats. Mist has an extensible ontology for defining a wide variety of material information, currently focused on metal alloy applications. Examples include: alloy composition, density, liquidus temperature, and the coefficient of thermal expansion. Mist converts between standardized machine-readable data formats (e.g. JSON), specialized input format for simulation tools, and human-readable documents (e.g. LaTeX, Markdown). For parameters defined by an equation (e.g. a polynomial function) or a list of tabulated values, Mist can evaluate parameter values at requested conditions. Mist also provides an API for direct usage of the Mist data structures in calculations, if supported.

DeWitt, Stephen [Oak Ridge National Laboratory (OR↗

Influence of Combined Whole-Body Vibration Plus G-Loading on Visual Performance

Recent engineering analyses of the integrated Ares-Orion stack show that vibration levels for Orion crews have the potential to be much higher than those experienced in Gemini, Apollo, and Shuttle vehicles. Of particular concern to the Constellation Program (CxP) is the 12 Hz thrust oscillation (TO) that the Ares-I rocket develops during the final ~20 seconds preceding first-stage separation, at maximum G-loading. While the structural-dynamic mitigations being considered can assure that vibration due to TO is reduced to below the CxP crew health limit, it remains to be determined how far below this limit vibration must be reduced to enable effective crew performance during launch. Moreover, this "performance" vibration limit will inform the operations concepts (and crew-system interface designs) for this critical phase of flight. While Gemini and Apollo studies provide preliminary guidance, the data supporting the historical limits were obtained using less advanced interface technologies and very different operations concepts. In this study, supported by the Exploration Systems Mission Directorate (ESMD) Human Research Program, we investigated display readability-a fundamental prerequisite for any interaction with electronic crew-vehicle interfaces-while observers were subjected to 12 Hz vibration superimposed on the 3.8 G loading expected for the TO period of ascent. Two age-matched groups of participants (16 general population and 13 Crew Office) performed a numerical display reading task while undergoing sustained 3.8 G loading and whole-body vibration at 0, 0.15, 0.3, 0.5, and 0.7 g in the eyeballs in/out (x-axis) direction. The time-constrained reading task used an Orion-like display with 10- and 14-pt non-proportional sans-serif fonts, and was designed to emulate the visual acquisition and processing essential for crew system monitoring. Compared to the no-vibration baseline, we found no significant effect of vibration at 0.15 and 0.3 g on task error rates (ER) or response times (RT). Significant degradations in both ER and RT, however, were observed at 0.5 and 0.7 g for 10-pt, and at 0.7 g for 14-pt font displays. These objective performance measures were mirrored by participants' subjective ratings. Interestingly, we found that the impact of vibration on ER increased with distance from the center of the display, but only for vertical displacements. Furthermore, no significant ER or RT aftereffects were detected immediately following vibration, regardless of amplitude. Lastly, given that our reading task required no specialized spaceflight expertise, our finding that effects were not statistically distinct between our two groups is not surprising. The results from this empirical study provide initial guidance for evaluating the display readability trade-space between text-font size and vibration amplitude. However, the outcome of this work should be considered preliminary in nature for a number of reasons: 1. The single 12 Hz x-axis vibration employed was based on earlier load-cycle models of the induced TO environment at the end of Ares-I first stage flight. Recent analyses of TO mitigation designs suggest that significant concurrent off-axis vibration may also occur. 2. The shirtsleeve environment in which we tested fails to capture the full kinematic and dynamic complexity of the physical interface between crewmember and the still-to-bematured helmet-suit-seat designs, and the impact these will have for vibration transmission and consequent performance. 3. By examining performance in this reading and number processing task, we are only assessing readability, a first and necessary step that in itself does not directly address the performance of more sophisticated operational tasks such as vehicle-health monitoring or manual control of the vehicle.

readability↗

The critical evaluation of stellar data

The paper discusses the importance of evaluating a catalog of stellar data, whether it is an old catalog being made available in machine-readable form, or a new catalog written expressly in machine-readable form, and discusses some principles to be followed in the evaluation of such data. A procedure to be followed when checking out an astronomical catalog on magnetic tape is described. A cross index system which relates the different identification numbers of a star or other astronomical object as they appear in different catalogs in machine-readable form is described.

Underhill, A. B.↗

Astronomical Data Center Bulletin, volume 1, number 2

Work in progress on astronomical catalogs is presented in 16 papers. Topics cover astronomical data center operations; automatic astronomical data retrieval at GSFC; interactive computer reference search of astronomical literature 1950-1976; formatting, checking, and documenting machine-readable catalogs; interactive catalog of UV, optical, and HI data for 201 Virgo cluster galaxies; machine-readable version of the general catalog of variable stars, third edition; galactic latitude and magnitude distribution of two astronomical catalogs; the catalog of open star clusters; infrared astronomical data base and catalog of infrared observations; the Air Force geophysics laboratory; revised magnetic tape of the N30 catalog of 5,268 standard stars; positional correlation of the two-micron sky survey and Smithsonian Astrophysical Observatory catalog sources; search capabilities for the catalog of stellar identifications (CSI) 1979 version; CSI statistics: blue magnitude versus spectral type; catalogs available from the Astronomical Data Center; and status report on machine-readable astronomical catalogs.

Nagy, T. A.↗

C++ Coding Standards and Style Guide

This document is based on the "C Style Guide" (SEL-94-003). It contains recommendations for C++ implementations that build on, or in some cases replace, the style described in the C style guide. Style guidelines on any topics that are not covered in this document can be found in the "C Style Guide." An attempt has been made to indicate when these recommendations are just guidelines or suggestions versus when they are more strongly encouraged. Using coding standards makes code easier to read and maintain. General principles that maximize the readability and maintainability of C++ are: (1) Organize classes using encapsulation and information hiding techniques. (2) Enhance readability through the use of indentation and blank lines. (3) Add comments to header files to help users of classes. (4) Add comments to implementation files to help maintainers of classes. (5) Create names that are meaningful and readable.

Hughes, Steven↗

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↗

Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models

Abstract We evaluate the ability of machine learning to predict whether a hypothetical crystal structure can be synthesized and explain those predictions to scientists. Fine‐tuned large language models (LLMs) trained on a human‐readable text description of the target crystal structure perform comparably to previous bespoke convolutional graph neural network methods, but better prediction quality can be achieved by training a positive‐unlabeled learning model on a text‐embedding representation of the structure. An LLM‐based workflow can then be used to generate human‐readable explanations for the types of factors governing synthesizability, extract the underlying physical rules, and assess the veracity of those rules. These explanations can guide chemists in modifying or optimizing non‐synthesizable hypothetical structures to make them more feasible for materials design.

Kim, Seongmin [Department of Chemical and Biologic↗

Explainable Synthesizability Prediction of Inorganic Crystal Polymorphs Using Large Language Models

Abstract We evaluate the ability of machine learning to predict whether a hypothetical crystal structure can be synthesized and explain those predictions to scientists. Fine‐tuned large language models (LLMs) trained on a human‐readable text description of the target crystal structure perform comparably to previous bespoke convolutional graph neural network methods, but better prediction quality can be achieved by training a positive‐unlabeled learning model on a text‐embedding representation of the structure. An LLM‐based workflow can then be used to generate human‐readable explanations for the types of factors governing synthesizability, extract the underlying physical rules, and assess the veracity of those rules. These explanations can guide chemists in modifying or optimizing non‐synthesizable hypothetical structures to make them more feasible for materials design.

Kim, Seongmin [Department of Chemical and Biologic↗

ENDFtk: A robust tool for reading and writing ENDF-formatted nuclear data

ENDFtk is a recently developed C++ and Python interface to interact with ENDF-6 formatted nuclear data files. It provides a robust and complete interface, allowing the reading and writing of all formats currently part of the ENDF-6 formats manual, as well as some non-ENDF formats used by the NJOY processing code. It provides an interface that mimics the names in the ENDF-6 formats manual as well as an equivalent interface using human-readable attribute names. It is robust and powerful enogh for nuclear data experts to develop complex applications, while also simple enough to be used non-experts to retrieve and manipulate evaluated nuclear data. ENDFtk offers the ability to easily interrogate and manipulate data either in large-scale code projects or in simple Python scripts. Here, in this paper, a brief overview of the interface is given, as well as more substantial examples demonstrating plotting simple data, interacting with more complex data, and writing new data to files. ENDFtk is open source and available for download via GitHub (https://github.com/njoy/ENDFtk).

97 MATHEMATICS AND COMPUTING↗

Exploiting Colorimetry for Fidelity in Data Visualization

Advances in multimodal characterization methods fuel the generation of increasing immense hyper-dimensional data sets. Color mapping is employed for conveying higher dimensional data in two-dimensional (2D) representations for human consumption without relying on multiple projections. How one constructs these color maps, however, critically affects how accurately one perceives data. For simple scalar fields, perceptually uniform color maps and color selection have been shown to improve data readability and interpretation across research fields. In this work, we review core concepts underlying the design of perceptually uniform color maps and extend the concepts from scalar fields to two-dimensional vector fields and three-component composition fields frequently found in materials-chemistry research to enable high-fidelity visualization. Additionally, we develop the software tools PAPUC and CMPUC to enable researchers to utilize these colorimetry principles and employ perceptually uniform color spaces for rigorously meaningful color mapping of higher dimensional data representations. Last, we demonstrate how these approaches deliver immediate improvements in data readability and interpretation in microscopies and spectroscopies routinely used in discerning materials structure, chemistry, and properties.

36 MATERIALS SCIENCE↗