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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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NASA NTRS2020

Development of VBA Tool for Document Term Search

Employees throughout different agencies such as NASA, have identified that the search of determined terms/words through documents, consume substantial research time of such. These types of searches are substantially limited towards one word in a one document identification; forward one, these usual types of searches lack efficiency & optimization through research aspects of work. Consequently, this reflects in the decrease productivity during work hours etc. The application of VBA (Visual Basic for Applications) is the programming language of Excel, which was conducted for the development of optimized tool for document term search. The project enables the search of single & multiple word/term search through single format documents for paragraph data extraction.

Ssytems Development↗
NASA NTRS2020

TESS Spots a Hot Jupiter with an Inner Transiting Neptune

Hot Jupiters are rarely accompanied by other planets within a factor of a few in orbital distance. Previously, only two such systems have been found. Here, we report the discovery of a third system using data from the Transiting Exoplanet Survey Satellite (TESS). The host star, TOI-1130, is an eleventh magnitude K-dwarf in Gaia G-band. It has two transiting planets: a Neptune-sized planet (3.65±0.10 Rꚛ) with a 4.1 days period, and a hot Jupiter (-1.50(+0.22,-0.27) R(J)) with an 8.4 days period. Precise radial-velocity observations show that the mass of the hot Jupiter is -0.974(+0.044, 0.043) M(J). For the inner Neptune, the data provide only an upper limit on the mass of 0.17M(J)(3σ). Nevertheless, we are confident that the inner planet is real, based on follow-up ground-based photometry and adaptive-optics imaging that rule out other plausible sources of the TESS transit signal. The unusual planetary architecture of and the brightness of the host star make TOI-1130 a good test case for planet formation theories, and an attractive target for future spectroscopic observations.

Exoplanet astronomy↗
NASA NTRSDate not supplied

Transform Your Search Capability Using Insight Engines

Enable rapid discovery of NASA’s open science data, software and documentation. Support NASA’s open science goals and infrastructure. Promote interdisciplinary science. Prototype emerging technologies and search techniques including Large Language Models.

Kaylin Bugbee↗
NASA NTRS2010

Hypersonic Navier-Stokes Comparisons to Orbiter Flight Data

During the STS-119 flight of Space Shuttle Discovery, two sets of surface temperature measurements were made. Under the HYTHIRM program3 quantitative thermal images of the windward side of the Orbiter with a were taken. In addition, the Boundary Layer Transition Flight Experiment 4 made thermocouple measurements at discrete locations on the Orbiter wind side. Most of these measurements were made downstream of a surface protuberance designed to trip the boundary layer to turbulent flow. In this paper, we use the US3D computational fluid dynamics code to simulate the Orbiter flow field at conditions corresponding to the STS-119 re-entry. We employ a standard two-temperature, five-species finite-rate model for high-temperature air, and the surface catalysis model of Stewart.1 This work is similar to the analysis of Wood et al . 2 except that we use a different approach for modeling turbulent flow. We use the one-equation Spalart-Allmaras turbulence model8 with compressibility corrections 9 and an approach for tripping the boundary layer at discrete locations. In general, the comparison between the simulations and flight data is remarkably good

Candler, Graham V.↗
NASA NTRS1985

Planetary image conversion task

The Planetary Image Conversion Task group processed 12,500 magnetic tapes containing raw imaging data from JPL planetary missions and produced an image data base in consistent format on 1200 fully packed 6250-bpi tapes. The output tapes will remain at JPL. A copy of the entire tape set was delivered to US Geological Survey, Flagstaff, Ariz. A secondary task converted computer datalogs, which had been stored in project specific MARK IV File Management System data types and structures, to flat-file, text format that is processable on any modern computer system. The conversion processing took place at JPL's Image Processing Laboratory on an IBM 370-158 with existing software modified slightly to meet the needs of the conversion task. More than 99% of the original digital image data was successfully recovered by the conversion task. However, processing data tapes recorded before 1975 was destructive. This discovery is of critical importance to facilities responsible for maintaining digital archives since normal periodic random sampling techniques would be unlikely to detect this phenomenon, and entire data sets could be wiped out in the act of generating seemingly positive sampling results. Reccomended follow-on activities are also included.

Martin, M. D.↗
NASA NTRS2004

Data Grid Management Systems

The "Grid" is an emerging infrastructure for coordinating access across autonomous organizations to distributed, heterogeneous computation and data resources. Data grids are being built around the world as the next generation data handling systems for sharing, publishing, and preserving data residing on storage systems located in multiple administrative domains. A data grid provides logical namespaces for users, digital entities and storage resources to create persistent identifiers for controlling access, enabling discovery, and managing wide area latencies. This paper introduces data grids and describes data grid use cases. The relevance of data grids to digital libraries and persistent archives is demonstrated, and research issues in data grids and grid dataflow management systems are discussed.

Moore, Reagan W.↗
NASA NTRS1974

Geologic and mineral and water resources investigations in western Colorado, using Skylab EREP data

The author has identified the following significant results. Discovery of three major north-trending, throughgoing faults in the Front Range, previously mapped only as isolated segments, demonstrates the utility of space photography and may lead to reinterpretation of the Front Range tectonic style. Faulting and alteration appear to be the most useful indicators of mineralization in central Colorado. These phenomena appear on Skylab photography as tonal lineaments and color anomalies. Twenty-three lineaments have been mapped in the San Juan Mountains, the longest of which is 156 km long. Twelve lineaments intersect or are tangent to calderas. Intrusive domes are aligned along lineaments, but calderas appear to occur at the intersections of major lineaments. Lineaments can be recognized on some EREP passes but not on other passes over the same area. The difference is attributed to solar elevation effects. Bedding attitudes can be photogeologically estimated down to surprisingly low dips, on the order of + or - 1-2 deg, and attitudes can be subdivided easily into quantitative groups. The primary application of Skylab photography to geologic mapping in montane areas is clearly limited to regional mapping at scales smaller than 1:24,000.

Lee, K.↗
NASA NTRS1974

The processing and transmission of EEG data

Interest in sleep research was stimulated by the discovery of a number of physiological changes that occur during sleep and by the observed effects of sleep on physical and mental performance and status. The use of the relatively new methods of EEG measurement, transmission, and automatic scoring makes sleep analysis and categorization feasible. Sleep research involving the use of the EEG as a fundamental input has the potential of answering many unanswered questions involving physical and mental behavior, drug effects, circadian rhythm, and anesthesia.

Schulze, A. E.↗
NASA NTRS2005

Joint Inversion and Forward Modeling of Gravity and Magnetic Data in the Ismenius Region of Mars

The unexpected discovery of remanent crustal magnetism on Mars was one of the most intriguing results from the Mars Global Surveyor mission. The origin of the pattern of magnetization remains elusive. Correlations with gravity and geology have been examined to better understand the nature of the magnetic anomalies. In the area of the Martian dichotomy between 50 and 90 degrees E (here referred to as the Ismenius Area), we find that both the Bouguer and the isostatic gravity anomalies appear to correlate with the magnetic anomalies and a buried fault, and allow for a better constraint on the magnetized crust].

Milbury, C. A.↗
NASA NTRS2005

STS-114: Discovery Mission Status Briefing

Paul Hill, STS-114 Lead Shuttle Flight Director, talks about the imagery that was captured during the first twenty four hours in orbit. He expresses that new data was captured during ascent of the Space Shuttle Discovery through imagery and in-orbit handheld photographs of the Orbital Maneuvering system (OMS) pods were taken. Laser surveys were also taken of both the wing leading edges and nose caps using the Orbiter Boom and Sensor System (OBSS) instrument package. He presents raw footage from the Laser Dynamic Range Imager (LDRI) at the end of the OBSS showing RCC panels and tiles. He also answers questions from the news media about the possible damage to the Orbiter and debris during lift-off.

Source record↗
NASA NTRSDate not supplied

The NASA Open Science Data Repository: Biomedical Data, Analysis Tools, and Informatic Collaborations

Increased biomedical risks and challenges associated with deep space missions require knowledge discovery, health countermeasures, and biomedical support capabilities. Maximally open-access and reusable data is needed by developers, scientists, and engineers to develop these systems. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database (ie., findable, accessible, interoperable, and reusable), and meets various scientific, technical, and operational needs. It offers users and submitters the ability to upload, download, search, share, analyze, cite, and visualize data across ‘omics, physiological, phenotypic, payload, hardware, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR is an expanded database, based upon the successes of NASA GeneLab. OSDR has >460 studies with datasets covering model organisms to non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets with raw files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) developed from industry norms. OSDR is collecting and curating biomedical human data from a new sub-orbital research flight and is open to more space life science/biomedical submissions from the international and commercial sectors. OSDR also recently began a collaboration with the European Space Agency (ESA) to collect and curate >200 terabytes of human and model organism data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics and ~50 physiological-phenotypic-imaging assay data types. Tools available for OSDR users include: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, and 3) a Multi-study visualization tool which enables users to look across and combine ‘omics datasets. There are ~600 volunteer OSDR Analysis Working Group (AWG) members providing feedback on scientific data/metadata standards and collaborating to mine-reuse OSDR in research. OSDR/GeneLab has enabled ~60 publications reusing data as of October 2023.

space biology↗
NASA NTRS1992

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multi parameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resources.

Djorgovski, Stanislav↗
NASA NTRS1993

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multiparameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resource.

Djorgovski, George↗
NASA NTRS2003

A Virtual Bioinformatics Knowledge Environment for Early Cancer Detection

Discovery of disease biomarkers for cancer is a leading focus of early detection. The National Cancer Institute created a network of collaborating institutions focused on the discovery and validation of cancer biomarkers called the Early Detection Research Network (EDRN). Informatics plays a key role in enabling a virtual knowledge environment that provides scientists real time access to distributed data sets located at research institutions across the nation. The distributed and heterogeneous nature of the collaboration makes data sharing across institutions very difficult. EDRN has developed a comprehensive informatics effort focused on developing a national infrastructure enabling seamless access, sharing and discovery of science data resources across all EDRN sites. This paper will discuss the EDRN knowledge system architecture, its objectives and its accomplishments.

knowledge systems↗
NASA NTRS1997

Rosat X-Ray Observations

This grant has supported ongoing analysis of ROSAT X-Ray observations. Publications resulting in whole or in part from this grant include: X-Rays and Activity in Pre-Main Sequence Stars. The Rest of Orion: Low Mass Pre-Main Sequence Stars Outside the Orion Nebula. Star Formation in Orion (the Constellation). Discovery of a New Cataclysmic Variable System. An IDL-based ROSAT Data Analysis Package. The Long Period AM Her-like Cataclysmic Variable RXJ051541+0104.611. Discovery of A Nearby Isolated Neutron Star. A candidate isolated old neutron star. On the X-ray Position and Deep Optical Imaging of the Neutron Star Candidate RXJ1856.5-375411. The Spectral Energy Distribution of the Isolated Neutron Star RXJ185635-3754. A Most Unusual, Highly-X-ray-Variable Cataclysmic Variable.

Walter, F. M.↗
NASA NTRS2002

XTE J1946+274: An Enigmatic X-Ray Pulsar

XTE J1946+274 = GRO J1944+26 is a 15.8-s X-ray pulsar discovered simultaneously by the Rossi X-ray Timing Explorer (RXTE) and the Burst and Transient Source Experiment (BATSE) in September 1998. Follow-up optical/IR observations resulted in the discovery of a Be star companion. Our pulse timing analysis of BATSE and RXTE data indicates that the orbital period is approximately 169 days. Since its discovery in 1998, XTE J1946+274 has undergone 13 outbursts. These outbursts axe not regularly spaced. They occur approximately twice per orbit and are not locked in orbital phase, unlike most Be/X-ray transient systems. A possible explanation for this is a global-one armed oscillation or density perturbation propagating rapidly in the Be star's disk. We will investigate radial velocity variations in the central peak of the H-alpha line to look for evidence of such a perturbation. From 2001 March-September, we regularly monitored XTE J1946+274 with the RXTE PCA. We will demonstrate that the spectrum appears to be varying with orbital phase, based on the 2001 and 1998 RXTE PCA observations. We will also present histories of pulsed frequency and flux.

Wilson, Colleen A.↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth independence and autonomy of mission operations. Here we present an overview of AI/ML architecture to support deep space mission goals, developed with leaders in the field. First, we focus on the fundamental biological research that supports our understanding of physiological responses to spaceflight, and we describe current efforts to support AI/ML research including data standardization and data engineering through maximally open and FAIR (findable, accessible, interoperable, reusable) databases and the generation of AI-ready datasets for reuse and analysis. We also discuss remote data management frameworks for research data as well as environmental and health data that are generated during deep space missions. We highlight several research projects that leverage data standardization and management for fundamental biological discovery to uncover the complex effects of space travel on living systems. Next, we provide an overview of cutting-edge AI/ML approaches that can be integrated to support remote monitoring and analysis during deep space missions, including generative models and large language models to learn the underlying biomedical patterns and predict outcomes or answer questions during off world medical scenarios. We also describe current AI/ML methods to support this research and monitoring through automated cloud-based labs which enable limited human intervention and closed-loop experimentation in remote settings. These labs could support mission autonomy by analyzing environmental data streams, and would be facilitated through in situ analytics capabilities to avoid sending large raw data files through low bandwidth communications. Finally, in the context of deep space missions with limited communications or access to medical advice from Earth, we describe a solution for integrated, real-time mission biomonitoring across hierarchical levels from continuous environmental monitoring, to wearables and point-of-care devices, to molecular and physiological monitoring. We introduce a precision space health system that will ensure that the future of space health is predictive, preventative, participatory and personalized.

artificial intelligence↗