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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Probability of Decompression Sickness and Venous Gas Emboli from 49 NASA Hypobaric Chamber Tests with Reference to Exploration Atmosphere

Introduction: Decompression sickness (DCS) is a complex biophysical event; it combines human perception of pain, for instance, and the presence of a gas phase in the tissues. Living tissues are complex and dynamic. Micronuclei and later bubbles may or may not form given what appears to be the same conditions. Even when bubbles grow, symptoms may or may not develop under what appears to be the same conditions. Therefore, at this time it is appropriate to consider DCS as a probabilistic rather than a deterministic event. Methods: Probabilistic models about hypobaric DCS and venous gas emboli (VGE) require a large amount of quality research data, a definition of decompression dose using physical and physiologic variables, and a flexible analytical approach that can quantify the association between each outcome and all covariates of interest (assuming independence between DCS and VGE) and then ultimately be extended to acknowledge dependencies between DCS and VGE. Our DCS and VGE data are from 1,031 hypobaric decompressions from 1983 to 2016. A total of 577 humans participated in 49 hypobaric chamber tests to evaluate denitrogenation procedures used by astronauts in the Space Shuttle and International Space Station programs. We defined decompression dose as the ratio of computed nitrogen tension in a theoretical 360-minute half-time compartment to ambient pressure, which accounts for denitrogenation and exposure pressure as well as explanatory variables such as age, sex, body mass index, and the presence or absence of ambulation as part of exercise at the exposure pressure. A parametric survival model, using a log-logistic distribution, was used to quantify the time to development of DCS, VGE, and Grade IV VGE. Results: Our survival estimates are applicable to simple hypobaric decompressions, such as depressurizations in 5 to 30 minutes to exposure pressures between 4 and 10 pounds per square inch absolute (psia) and after minutes to hours of denitrogenation, either under resting or exercise conditions to accelerated denitrogenation. The regressions are applicable to exposures between 2 to 6 hours and under conditions of ambulation or no ambulation as part of exercise at the test pressure. We estimate that an exposure to 4.3 psia with simulated extravehicular activity (EVA) that includes ambulation after equilibration to the exploration atmosphere at 8.2 psia with a 34% oxygen atmosphere will result in 3.1% DCS (1.8% to 5.2 95% confidence interval), 23.2% VGE (16.7 to 31.2%), and 8.5% Grade IV VGE (4.7 to 14.7%) in equal samples of men and women exposed for 6 hours. Discussion: Probabilistic models for DCS, VGE, and Grade IV VGE can be used to inform those that plan future EVAs. Their applications are useful to quantify the risk of DCS and VGE in astronauts that perform EVAs in low-pressure space suits while in space or while exploring the surfaces of the moon or Mars.

Johnny Conkin↗
NASA NTRSDate not supplied

The Multirotor Test Bed – A New NASA Test Capability for Advanced VTOL Rotorcraft Configurations

In November 2019, NASA completed the first wind tunnel test entry of the Multirotor Test Bed (MTB), a new test capability for advanced VTOL rotorcraft configurations. The MTB had been under development since 2017 when the need arose for an easily reconfigurable test stand for multirotor aircraft configurations. With the wide-ranging assortment of aircraft currently targeted at Urban Air Mobility and Unmanned Aircraft System applications, there is a need for validation data that will increase confidence in the computational modeling tools being used to develop these platforms. The MTB fills this need. This paper describes the key features of the MTB as well as its first wind tunnel test entry. A selection of results from the test is presented here, demonstrating the flexible configuration of the MTB and the types of data researchers can generate using this new test capability.

Multirotor Test Bed↗
NASA NTRS2021

Topical: Reverse Translation Strategies to Support Cognitive and Behavioral Risk Characterization

A coordinated suite of measurements to assess humans and animals needs to be established to support the translation and harmonization of animal research data to the astronaut corps due to the necessity of using animal subjects for radiation testing. The identification of POLs and PELs for spaceflight stressors (i.e. space radiation, altered gravity, isolation and confinement, sleep disruption) individually and combined will depend on defining scaling factors or transfer functions that can be used to relate human and animal outcomes.

Gregory Nelson↗
NASA NTRSDate not supplied

Generalized Predictive Control for Active Stability Augmentation and Vibration Reduction on an Aeroelastic Tiltrotor Model

Tiltrotor aircraft are defining the state-of-the-art in vertical lift technology as they have the potential to greatly expand rotary-wing operational boundaries. However, they are often limited in forward flight speed due to complex coupled rotor and wing dynamic instabilities. The U.S. Army and NASA have been developing a new wind tunnel model, the TiltRotor Aeroelastic Stability Testbed(TRAST), to test proprotors in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT) to investigate aeroelastic stability in cruise. The test is intended to provide high-quality research data for analytical tool development and validation. In addition, the TRAST model will support, develop, and mature new technologies for the design of advanced proprotor aircraft. Stability augmentation and vibration reduction during testing is planned with the use of an active control methodology known as Generalized Predictive Control(GPC). GPC is an autoregressive control law that experimentally acquires a system identification to derive the input-output relation of controls and corresponding sensors. This type of control law is especially useful for complex dynamic interactions that are difficult to explicitly model such as proprotor pylon instability, often referred to as whirl flutter. GPC has been successfully employed on other tiltrotor vehicles to suppress whirl flutter instabilities and vibrations. To aid in the characterization of the wind-tunnel model and in tool development, an analytical representation of the wind-tunnel model was developed using the rotorcraft comprehensive analysis system (RCAS) that simulates structural dynamics and aerodynamics. RCAS was used to derive state-space estimates of the physical plant at various flight conditions to test control law effectiveness. This paper will present an overview of the test article development, a description of RCAS, an explanation of the GPC methodology, and results of GPC being applied to state-space plant estimates of the TRAST model. In these simulations, GPC was effective at stabilizing the aircraft beyond the whirl-flutter boundary while simultaneously reducing vibrations across the flight regime. Additionally, a modern advancement to GPC, termed advanced GPC (AGPC), is introduced that enables a self-adapting system identification. Preliminary results show that AGPC is successful at self-correction as the plant changes from what was used for system identification.

tiltrotor↗
NASA NTRSDate not supplied

Game-Changing Science with SmallSats and Hosted Payloads

This talk outlines the opportunities using space-based remote sensing to collect the basic climate research data that will serve as the foundation of our science, our models, and our predictive capabilities. With SmallSats and hosted payloads to supplement data from our traditional large spacecraft, and with constellations of SmallSats and with hosted payloads, the Science Mission Directorate is able to make new types of observations, such as synchronic temporal and spatial measurements of the same events. Our data enables science-based decision making. Our models and predictions inform and educate our decision makers at every level.

remote sensing↗
DOE OSTI2022

It's All About the Envelope: Prioritizing Envelope Upgrades for Electrification of Cold Climate Homes

Building decarbonization via electrification on a clean grid is the most promising climate solution proposed to date for the building sector. In cold climate zones, building electrification will be driven in large part by moving from natural gas space heating to cold climate heat pumps (CCHPs). CCHPs are commercially available today, including economical cold climate air source heat pumps (ccASHPs). But there's one big problem - wide-scale adoption of ccASHPs will dramatically increase winter peak electricity demand, even with the highest efficiency ccASHP products. Furthermore, cold climate space heating loads will drive unprecedented electric system peaks during the lowest periods of renewable generation and are likely to overwhelm existing distribution systems. This scenario is avoidable by coupling electrification with building envelope upgrades to reduce peak heating loads. This paper presents a model, built from home energy audit and research data sets, that quantifies the above challenges. Results demonstrate how weatherization efforts coupled with additional high-performance envelope upgrade measures can prepare the building stock for electrification and show the benefit these measures can bring to future utility operations. Much of this envelope upgrade work is cost-effective, according to conservative cost-benefit testing and program successes to date, and is coupled with substantial non-energy benefits. However, persistent market barriers have made scaling of envelope retrofit work challenging for decades, suggesting additional policy support is required. Lessons learned from previous policy experience, combined with new technology and administrative support, create exciting potential for this decarbonization climate solution.

air sealing↗
NASA NTRSDate not supplied

Harmonizing Multi-Disciplinary Data for Applied Research: A Comprehensive Analysis of GES DISC Datasets through NLP and TF-IDF Techniques

Data centers distribute data encompassing multiple disciplines, making it necessary to evaluate dataset applicability to applied research. Typically, these datasets are generated by specialized science teams and consist of single-discipline data, such as atmospheric temperature, pressure, and precipitation, leading to unique dataset formats and access services. However, in applied research, the utilization of datasets from multiple disciplines is commonly necessary. The increasing availability of research literature citing Earth Science datasets presents an opportunity to analyze the usage of datasets in multi-disciplinary research. This study proposes a novel approach wherein research publications citing datasets archived at the GES DISC (Goddard Earth Sciences Data and Information Services Center) are collected, and each publication is associated with specific research topics through the application of Natural Language Processing (NLP), using the Term Frequency Inverse Document Frequency (TF-IDF) technique on the publication titles and abstracts. Through this analysis, we gain insights into the distribution of dataset disciplines as they are being used in various applied research areas. This knowledge is essential for the development of dataset tools and services tailored to effectively support applied research studies, as it enhances a data center's comprehension of how datasets from multiple disciplines are integrated into research endeavors.

Infometrics↗
DOE OSTI2024

RCSB Protein Data Bank: supporting research and education worldwide through explorations of experimentally determined and computationally predicted atomic level 3D biostructures

The Protein Data Bank (PDB) was established as the first open-access digital data resource in biology and medicine in 1971 with seven X-ray crystal structures of proteins. Today, the PDB houses >210 000 experimentally determined, atomic level, 3D structures of proteins and nucleic acids as well as their complexes with one another and small molecules ( e.g. approved drugs, enzyme cofactors). These data provide insights into fundamental biology, biomedicine, bioenergy and biotechnology. They proved particularly important for understanding the SARS-CoV-2 global pandemic. The US-funded Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and other members of the Worldwide Protein Data Bank (wwPDB) partnership jointly manage the PDB archive and support >60 000 `data depositors' (structural biologists) around the world. wwPDB ensures the quality and integrity of the data in the ever-expanding PDB archive and supports global open access without limitations on data usage. The RCSB PDB research-focused web portal at https://www.rcsb.org/ (RCSB.org) supports millions of users worldwide, representing a broad range of expertise and interests. In addition to retrieving 3D structure data, PDB `data consumers' access comparative data and external annotations, such as information about disease-causing point mutations and genetic variations. RCSB.org also provides access to >1 000 000 computed structure models (CSMs) generated using artificial intelligence/machine-learning methods. To avoid doubt, the provenance and reliability of experimentally determined PDB structures and CSMs are identified. Related training materials are available to support users in their RCSB.org explorations.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1975

Low-cost data analysis systems for processing multispectral scanner data

A research-oriented data analysis system was developed which is used for evaluating complex remote sensor systems and for development of techniques for application of remotely sensed data. Some modular hardware components were developed which may be added to one's existing facilities to establish a low-cost data analysis system for processing multispectral scanner data. Software modules which are compatible with small general purpose digital computers process and analyze remote sensor data, and convert it to information needed by users. The software modules are written in FORTRAN IV language for ease of transfer to other computer systems. The basic hardware and software system requirements are defined for some low-cost data analysis systems consisting of an image display system, a small general purpose digital computer, and an output recording device. The hardware modules consist of: a LANDSAT MSS data reformatting program; a series of spectral pattern recognition programs required to generate surface classification maps and tabular information; programs to convert computer generated maps from image space to a geographically referenced base; programs to extract data and irregularly shaped areas and to produce thematic maps of the designated areas; and programs to tabulate acreages of selected classification categories. Some off-the-shelf, inexpensive digital image display systems are described.

Whitley, S. L.↗
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 NTRS1989

Comparison of Landsat Thematic Mapper and Geophysical and Environmental Research Imaging Spectrometer data for the Cuprite mining district, Esmeralda, and Nye counties, Nevada

Landsat TM images and Geophysical and Environmental Research Imaging Spectrometer (GERIS) data were analyzed for the Cuprite mining district and compared to available geologic and alteration maps of the area. The TM data, with 30 m resolution and 6 broadbands, allowed discrimination of general mineral groups. Clay minerals, playa deposits, and unaltered rocks were mapped as discrete spectral units using the TM data, but specific minerals were not determined, and definition of the individual alteration zones was not possible. The GERIS, with 15 m spatial resolution and 63 spectral bands, permitted construction of complete spectra and identification of specific minerals. Detailed spectra extracted from the images provided the ability to identify the minerals alunite, kaolinite, hematite, and buddingtonite by their spectral characteristics. The GERIS data show a roughly concentrically zoned hydrothermal system. The mineralogy mapped with the aircraft system conforms to previous field and multispectral image mapping. However, identification of individual minerals and spatial display of the dominant mineralogy add information that can be used to help determine the morphology and genetic origin of the hydrothermal system.

Kierein-Young, Kathryn S.↗
NASA NTRS2018

Retrievals of Cloud Droplet Size from the Research Scanning Polarimeter Data: Validation Using In Situ Measurements

We present comparisons of cloud droplet size distributions (DSDs) retrieved from the research scanning polarimeter (RSP) data with correlative in situ measurements made during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). The airborne portion of this field experiment was based out of St. John's airport, Newfoundland, Canada with the focus of this paper being on the deployment in May - June 2016. RSP was onboard the NASA C-130 aircraft together with an array of in situ and other remote sensing instrumentation. The RSP is an along-track scanner measuring the polarized and total reflectance in 9 spectral channels. Its uniquely high angular resolution allows for characterization of liquid water droplet sizes using the rainbow structure observed in the polarized reflectance over the scattering angle range from 135 to 165.degrees The rainbow is dominated by single scattering of light by cloud droplets, so its structure is characteristic specifically of the droplet sizes at cloud top (within unit optical depth into the cloud, equivalent to approximately 50m). A parametric fitting algorithm applied to the polarized reflectance provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, the Rainbow Fourier Transform (RFT), which allows us to retrieve the droplet size distribution itself. The latter is important in the case of clouds with complex microphysical structure, or multiple layers of cloud, which result in multi-modal DSDs. During NAAMES the aircraft performed a number of flight patterns specifically designed for comparisons between remote sensing retrievals and in situ measurements. These patterns consisted of two flight segments above the same straight ground track. One of these segments was flown above clouds allowing for remote sensing measurements, while the other was near the cloud top where cloud droplets were sampled. We compare the DSDs retrieved from the RSP data with in situ measurements made by the Cloud Droplet Probe (CDP). The comparisons generally show good agreement (better than 1 micron for effective radius and in most cases better than 0.02 for effective variance) with deviations explainable by the position of the aircraft within the cloud, or by the presence of additional cloud layers between the cloud being sampled by the in situ instrumentation and the altitude of the remote sensing segment. In the latter case, the multi-modal DSDs retrieved from the RSP data were consistent with the multi-layer cloud structures observed in the correlative High Spectral Resolution Lidar (HSRL) profiles. The results of these comparisons provide a rare validation of polarimetric droplet size retrieval techniques, demonstrating their accuracy and robustness and the potential of satellite data of this kind on a global scale.

Remote Sensing↗
NASA NTRS1974

Automated system for measurement, collection and processing of hydrometeorological data aboard scientific research vessels of the GUGMS (SIGMA-s)

A report is made on the automated system known as SIGMA-s for the measurement, collection, and processing of hydrometeorological data aboard scientific research vessels of the Hydrometeorological Service. The various components of the system and the interfacing between them are described, as well as the projects that the system is equipped to handle.

Borisenkov, Y. P.↗
DOE OSTI2021

Data Reduction for Science: Brochure from the Advanced Scientific Computing Research Workshop

Data reduction for science holds promise for addressing the challenges of moving, storing, and processing massive data sets produced by the scientific community. Pursuing the PRDs outlined here will enable advances in data streaming, fast feedback and/or autonomous control of experiments, and faster time to scientific insight. These advances will result in a significant improvement in the ability to transport, store, process and interpret experimental, observational, and computational data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1988

Research In Optical Processing Of Data

Report describes current research in optical processing of data at NASA's Ames Research Center. Describes advanced optical feature extractor performing Fourier-Mellin transform to generate feature vector invariant under changes of scale and position and responds to rotation with simple translation. Potential advantages include high speed and low cost.

Ennis, David↗
NASA NTRS1988

Data base development and research and editorial support

The Life Sciences Bibliographic Data Base was created in 1981 and subsequently expanded. A systematic, professional system was developed to collect, organize, and disseminate information about scientific publications resulting from research. The data base consists of bibliographic information and hard copies of all research papers published by Life Sciences-supported investigators. Technical improvements were instituted in the database. To minimize costs, take advantage of advances in personal computer technology, and achieve maximum flexibility and control, the data base was transferred from the JSC computer to personal computers at George Washington University (GWU). GWU also performed a range of related activities such as conducting in-depth searches on a variety of subjects, retrieving scientific literature, preparing presentations, summarizing research progress, answering correspondence requiring reference support, and providing writing and editorial support.

Source record↗