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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Lessons Learned From the Flight of the NASA In-Step Cryo System Experiment

The Cryo System Experiment was developed to validate in near zero-g space a 65 K cryogenic system for focal planes, optics, or other imaging instruments that require continuous cryogenic cooling. Two key cryogenic technologies, designed to improve performance of systems for scientific, commercial and defense applications in space, were successfully demonstrated on a February 1995 Shuttle mission. The two were a 2-watt 65 K long-life low- vibration Stirling cooler and a diode oxygen heat pipe thermal switch. Lessons learned are presented.

cryogenics↗
NASA NTRSDate not supplied

On the Notional Impact of Background Noise on the Human Response to UAVs

Proponents of UAV-based industries would like to think that their aircraft will be incapable of causing annoyance (among other negative responses) in the communities that they serve due to the noise of their vehicles simply not being heard over the existing soundscape. No measures of noise that are in wide use today for aviation take background sound into consideration, and thus would not predict this outcome. This work is an attempt to bridge this gap by looking at past results from psychoacoustic research in which background sounds appear to play a significant role (not just for aviation sources). It includes information on the problem of human auditory detection in general – what is the transductive mechanism of the ear, how does one quantify detectability, etc., and it attempts to make the connection between detectability and annoyance. A notional schematic version of how measures/predictions of these two aspects may be incorporated into a single assessment of noise is given. Overall, detectability is shown to be very complex to predict relative to conventional noise metrics that are used to correlate with human response. Given this, the outlook for the use of measures of detectability in scientific, industrial, and regulatory applications is discussed.

UAV↗
NASA NTRSDate not supplied

Hyper-Spectral Infrared Remote Sensing for Wildfire-Related Research and Air Quality Monitoring

The National Airborne Sounder Testbed-Interferometer (NAST-I) is an airborne FTS remote sensor that nominally flies on NASA high-altitude aircraft to serve as a spaceborne instrument simulator. NAST-I continues to serve as a pathfinder for future satellite FTS systems and the next generation advanced atmospheric sounders in general. NAST-I provides high resolution spectrally resolved infrared radiances. NAST-I retrieval products characterizing the surface (i.e., skin temperature and spectral emissivity), atmosphere (i.e., profiles of temperature, moisture, ozone, carbon monoxide, and other trace species), and clouds (e.g., optical depth, particle size, temperature, and height) can be used to support fire-related monitoring and research. NAST-I provided 3-d characterizations of wildfire-induced plumes of CO during the FIREX-AQ field campaign (conducted during 2019) which showed the intensity and size evolution of wildfire plumes at high spatial and temporal resolutions. Wildfire-induced CO plumes, in conjunction with their evolution, transport, and age have been identified and recently published in scientific journals. Other research applications, such as surface emissivity changes due to fire burning of ground landscape, have been under investigation. These products could be used in support of wildfire management to better inform decision making and operations for pre-, active, and post-fire environments.

remote sensing↗
NASA NTRSDate not supplied

PTD: Enabling New Space Technologies

Significant advances in the capabilities of small spacecraft over the past 20 years, coupled with improved access to space from a variety of launch platforms have created new opportunities for scientific exploration and commercial application using these high-value (and yet low cost) platforms. Continued development and demonstration of key technologies are improving the performance of the 3U and 6U class CubeSats while expanding the small spacecraft reach into larger platforms, such as 12U and ESPA class missions. The availability and relatively low cost of CubeSat spacecraft allows key technologies to be flight qualified, bridging the TRL 6/7 gap and making truly novel and enabling technologies available to much larger missions in the planning stages at NASA. The key is connecting the technologists with the flight opportunity in a time and cost efficient manner. NASA’s Small Satellite Technology (SST) program is using existing commercial spacecraft to provide a common bus for technology demonstration, taking advantage of their proven platforms and system with proven flight heritage and extensive infrastructure. In this paper we discuss the Pathfinder Technology Demonstrator (PTD) series of four spacecraft and the CubeSat Laser Infrared CrosslinK (CLICK) series of three spacecraft, the approach SST took in facilitating the missions, the successes of those missions as well as lessons learned in the process. NASA’s PTD spacecraft series is demonstrating a variety of new technologies on-orbit, providing proof of the maturity of these significant new technologies, and enhancing the performance of future CubeSats. Each of the four PTD mission consists of one 6-unit (6U) CubeSat weighing approximately 12 kilograms and measuring approximately 30 centimeters x 25 centimeters x 10 centimeters, characterizing its payload within 90 days of orbit insertion. The spacecraft bus, integration and test, and mission operations services are being provided by Terran Orbital. The PTD missions have demonstrated a novel nano-spacecraft compatible propulsion systems (enabling deep space and maneuverable Cubeat missions) and an optical communications system (enabling high data rate collection and communications) already. The CLICK missions are demonstrating compact space-to-space optical communications first with the CLICK A technology demonstrator (already flown) and finally with the CLICK BC dual spacecraft mission. Both projects are part of the SST program within the NASA Space Technology Mission Directorate. SST is chartered to develop and demonstrate technologies to enhance and expand the capabilities of small spacecraft with a particular focus on enabling new mission architectures through the use of small spacecraft, expanding the reach of small spacecraft to new destinations, and augmenting future missions with supporting small spacecraft.

J. Hanson↗
NASA NTRS2023

Uncovering Unique Molecular Adaptations in the Arabidopsis Thaliana Cvi-0 Ecotype

This research proposal aims to investigate the unique molecular adaptations exhibited by Arabidopsis Thaliana, specifically focusing on the Cape Verde Islands (Cvi-0) ecotype, in response to microgravity conditions. The study examines data from NASA’s Open Science Data Repository and applies a multifaceted RNAseq analysis pipeline using tools in the UseGalaxy.org open platform. Through transcriptomic analysis, differential gene expression patterns were identified in Cvi-0, revealing an absence of heat shock protein (HSP) upregulation and an upregulation of Rubisco Activase (RCA) and chloroplast-related pathways. To test the hypothesis that these adaptations may contribute to Cvi-0’s increased adaptability in microgravity, a three-fold experimental design is proposed. Four experimental groups will be cultivated under simulated microgravity and ground control conditions, including Cvi-0, Col-0, and genetically modified Col-0 with silenced HSP genes, and genetically modified Col-0 with upregulated RCA gene. Growth parameters will be measured to assess plant resilience, and RNA sequencing will provide transcriptomic data for pathway analysis. Anticipated outcomes include improved markers of plant health (mass, growth, etc.) of Cvi-0 in simulated microgravity and enhanced resilience in genetically altered Col-0 variants, providing insights into potential mechanisms of adaptation. This research would bear significance for space agriculture, nutrition for extended space missions, and sustainable terrestrial crop enhancement. Moreover, the insights gained could reshape crop engineering on Earth, enhancing robustness to climate induced stresses and bolstering global food security. The proposal’s trajectory blends scientific curiosity with practical applicability, forging a path towards sustainable food production and improving human exploration beyond our planet.

GL4HS↗
NASA NTRSDate not supplied

Integrated Multi-Satellite Retrievals for GPM (IMERG)

The Integrated Multi-satellitE Retrievals for GPM (IMERG) product from the U.S. Science Team of the NASA-JAXA Global Precipitation Measurement (GPM) mission provides global satellite precipitation estimates for a wide range of scientific research and societal applications. By adopting a constellation approach using low-Earth orbit passive microwave and geosynchronous-orbit infrared observations from domestic and international partners, IMERG is able to achieve a high resolution of 0.1° every half-hour globally, with three Runs to cater to applications with different latency requirements. With the completion of the reprocessing of the latest version, IMERG V07 now provides improved global satellite precipitation estimates for a period of more than 20 years. This presentation summarizes background on retrievals, the IMERG algorithm, and access to the data. As well, it showcases select results from the data, which might give participants ideas about how they can analyze the data themselves. The presentation ends with a prospectus for the timeline for the upcoming Version 08 and provides a list of references.

IMERG↗
DOE OSTI2020

Measurements of an AC-LGAD strip sensor with a 120 GeV proton beam

The development of detectors that provide high resolution in four dimensions has attracted wide-spread interest in the scientific community for several applications in high-energy physics, nuclear physics, medical imaging, mass spectroscopy as well as quantum information. In addition to high time resolution and thanks to the AC-coupling of the electrodes, LGAD silicon sensors can provide high resolution in the measurement of spatial coordinates of an incident minimum ionizing particle. Such AC-coupled LGADs, also known as AC-LGADs, are therefore considered as candidates for future detectors to provide 4-dimensional measurements in a single sensing device with 100$\%$ fill factor. This article presents the first characterization of an AC-LGAD sensor with a proton beam of 120 GeV momentum at Fermilab. The sensor consists of strips with 80 $\mu$m width, fabricated at Brookhaven National Laboratory. The signal properties, efficiency, spatial, and time resolution are presented. The experimental results show that the time resolution of such an AC-LGAD is compatible to standard LGADs with similar gain, and that AC-LGADs can be segmented with fine pitches as standard strip or pixel detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1992

Precise Applications Of The Global Positioning System

Report represents overview of Global Positioning System (GPS). Emphasizes those aspects of theory, history, and status of GPS pertaining to potential utility for highly precise scientific measurements. Current and anticipated applications include measurements of crustal motions in seismically active regions of Earth, measurements of rate of rotation of Earth and orientation of poles, tracking of non-GPS spacecraft in orbit around Earth, surveying, measurements of radio-signal-propagation delays, determinations of coordinates of ground stations, and transfer of precise time signals worldwide.

Lichten, Stephen M.↗
NASA NTRS2000

A Language for Probabilistic Modeling of Scientific Data

We describe a portable container which allows specification of the probabilistic relations between several variables. The applications motivating this work are mainly scientific inference problems.

probabilistic modeling scientific data↗
NASA NTRS2022

MLtool: Universal Supervised Machine Learning Tool to Model Tabulated Data

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine learning↗
NASA NTRS2022

MLtool Python Code

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine Learning↗
DOE OSTI2024

Exploiting Modern C++ for Portable Parallel Programming in Lattice QCD Applications

The evolution of ISO C++ standards increasingly serves the needs of scientific computing, offering potential benefits for developing portable applications. The recent revisions of C++ programming language, for instance, introduces a suite of algorithms capable of being executed on accelerators. Although this approach may not yield best performance, it can present a viable balance between code productivity and computational efficiency. In this report, we discuss the implementation of the HISQ operator utilizing a range of features from the C++17/20/23 standards and include an assessment of their performance.

Strelchenko, Alexei↗
NASA NTRS1988

Fourth Conference on Artificial Intelligence for Space Applications

Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming.

Odell, Stephen L.↗
NASA NTRS1990

Fifth Conference on Artificial Intelligence for Space Applications

The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration.

Odell, Steve L.↗
DOE OSTI2022

Surface and Optoelectronic Properties of Ultrathin Trigonal Selenium: A Density Functional Theory Study with van der Waals Correction

Selenium is a crucial earth-abundant and non-toxic semiconductor with a wide range of applications across the semiconductor industries. Selenium has drawn attention from scientific communities for its wide range of applicability: from photovoltaics to imaging devices. Its usage as a photosensitive material largely involves the synthesis of the amorphous phase (a-Se) via various experimental techniques. However, the ground state crystalline phase of this material, known as the trigonal selenium (\textit{t}-Se), is not extensively studied for its optimum electronic and optical properties. In this work, we present density functional theory (DFT) based systematic studies on the ultra-thin $(10\overline{1}0)$ surface slabs of \textit{t}-Se. We report the surface energies, work function, electronic and optical properties as a function of number of layers for $(10\overline{1}0)$ surface slabs to access its suitability for applications as a photosensitive material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2019

NASA’s Next Generation Surface Deformation and Change Observing System Architecture

The United States National Aeronautics and Space Administration (NASA) has initiated a five-year study of a Surface Deformation and Change Observing System Architecture. The goal of the study is to define an observing system that would meet the recommendations of the 2017 US National Academy of Sciences, Engineering, and Medicine Decadal Survey for developing an affordable synthetic aperture radar-based system or systems that can address fundamental scientific questions about the nature of hazards, disasters, landscape change, and serve applications communities as well. The study is to consider the existing international constellation of SAR systems, both civil and commercial, as well as new technologies that could be employed to address scientific and applications objectives and to improve affordability. The study will be conducted in four phases: 1) expanding the architectural trade space; 2) assessing the science and applications value of each identified architecture; 3) down selecting to three final candidates and performing detailed assessments; 4) final reporting and preparation for mission formulation. The first phase is approximately 2 years in duration, and will concentrate on the scope of research and application areas to be addressed, defining the possible architectures to consider, and beginning the assessment of their performance. The study team comprises five NASA centers. Broad participation from the research, applications, technology, and commercial sectors is planned.

Paul A Rosen↗
DOE OSTI2022

Graph coarsening: from scientific computing to machine learning

Abstract The general method of graph coarsening or graph reduction has been a remarkably useful and ubiquitous tool in scientific computing and it is now just starting to have a similar impact in machine learning. The goal of this paper is to take a broad look into coarsening techniques that have been successfully deployed in scientific computing and see how similar principles are finding their way in more recent applications related to machine learning. In scientific computing, coarsening plays a central role in algebraic multigrid methods as well as the related class of multilevel incomplete LU factorizations. In machine learning, graph coarsening goes under various names, e.g., graph downsampling or graph reduction. Its goal in most cases is to replace some original graph by one which has fewer nodes, but whose structure and characteristics are similar to those of the original graph. As will be seen, a common strategy in these methods is to rely on spectral properties to define the coarse graph.

Chen, Jie↗