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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 NTRS1978

Communication system analysis for manned space flight

The development of adaptive delta modulators capable of digitizing a video signal is summarized. The delta modulator encoder accepts a 4 MHz black and white composite video signal or a color video signal and encodes it into a stream of binary digits at a rate which can be adjusted from 8 Mb/s to 24 Mb/s. The output bit rate is determined by the user and alters the quality of the video picture. The digital signal is decoded using the adaptive delta modulator decoder to reconstruct the picture.

Schilling, D. L.↗

NASA NTRS2009

Acquisition and Pointing for Mars Optical Access Link

Optical characteristics can potentially benefit "access" links at Mars when transmitting data from surface to orbiting assets because of the higher gain and modulation bandwidth, compared to radio frequency (RF). Furthermore, higher bits/kg/W can be realized with low mass and power optical systems, enabling the streaming of high definition imagery. In this paper we present a conceptual design for a low complexity, autonomous optical communications link for returning data at 50-200 Mb/s from the Martian surface and for lower forward data rates of 50 kb/s to the surface. The pointing control is simplified by widening the transmitted laser beams (0.5 - 2.0 mrad) for the short distance (400-1200 Km) links. Link acquisition is based on the orbiter transceiver (OT) "blind"-pointing a laser beam to illuminate the lander transceiver (LT) on the surface. The LT acquires the link with a spectrally-filtered wide-field-of-view camera and subsequently tracks the orbiter transceiver with a two-axis, stepper-motor-actuator, to send back a laser modulated with high-rate data to the orbiting asset. The system design also has a provision for the OT transitioning from blind-pointing to closed loop tracking once it acquires the signal from the lander transceiver. Results from successful ground-based demonstrations performed at JPL, in which the pointing rate required to track an orbiter was emulated by mounting both transceivers on rotating stages, and in which we transmitted live video and pseudo-random data streams, are presented.

Optical Communication↗

NASA NTRS2008

Numerically Modeling the Erosion of Lunar Soil by Rocket Exhaust Plumes

In preparation for the Apollo program, Leonard Roberts of the NASA Langley Research Center developed a remarkable analytical theory that predicts the blowing of lunar soil and dust beneath a rocket exhaust plume. Roberts assumed that the erosion rate was determined by the excess shear stress in the gas (the amount of shear stress greater than what causes grains to roll). The acceleration of particles to their final velocity in the gas consumes a portion of the shear stress. The erosion rate continues to increase until the excess shear stress is exactly consumed, thus determining the erosion rate. Roberts calculated the largest and smallest particles that could be eroded based on forces at the particle scale, but the erosion rate equation assumed that only one particle size existed in the soil. He assumed that particle ejection angles were determined entirely by the shape of the terrain, which acts like a ballistic ramp, with the particle aerodynamics being negligible. The predicted erosion rate and the upper limit of particle size appeared to be within an order of magnitude of small-scale terrestrial experiments but could not be tested more quantitatively at the time. The lower limit of particle size and the predictions of ejection angle were not tested. We observed in the Apollo landing videos that the ejection angles of particles streaming out from individual craters were time-varying and correlated to the Lunar Module thrust, thus implying that particle aerodynamics dominate. We modified Roberts theory in two ways. First, we used ad hoc the ejection angles measured in the Apollo landing videos, in lieu of developing a more sophisticated method. Second, we integrated Roberts equations over the lunar-particle size distribution and obtained a compact expression that could be implemented in a numerical code. We also added a material damage model that predicts the number and size of divots which the impinging particles will cause in hardware surrounding the landing rocket. Then, we performed a long-range ballistics analysis for the ejected particulates.

Source record↗

DOE OSTI2022

Apparatus and amendment of wind turbine blade impact detection and analysis

A multisensory system provides both temporal and spatial coverage capacities for auto-detection of bird collision events. The system includes an apparatus having a first circuitry to capture and store a series of images or video of a blade of a wind turbine; and a memory to store the images from the first circuitry. The apparatus also has one or more sensors to continuously sense vibration of the blade or for acoustic recordings; and a second circuitry to analyze the sensor data stream and/or the series of images or video to identify a cause of the vibration and to trigger the camera(s). A communication interface transmits data from the second circuitry to another device, wherein the second circuitry applies artificial intelligence or machine learning to control sensitivity of the one or more sensors.

Johnston, Matthew↗

NASA NTRS2022

Bringing Planetary Science Mission Outreach to the Deaf and Blind Communities

Introduction: Technology for enhancing outreach, like 3D printing, and science communication products, such as videos and podcasts, can be utilized within the planetary science community, especially for the engagement and excitement of current or upcoming planetary exploration missions. However, these communication products can also be further enhanced for the benefit of the blind and deaf communities. While such products may already be readily available, such projects are not easily accessible to blind and/or deaf certified educators, which often rely on making their own resources or do not have the funds to provide such resources (e.g., cost of 3D printers or cost of braille books). The planetary science community can have better practices to reach these broader audiences. Best practices can include transcripts from podcasts, transcripts in videos, and large-font captions. Images on websites and social media accounts should also include alt-text descriptive captions. 3D printing can also enhance planetary science for the blind community, through tactile posters, maps, and pamphlets. Planetary data can also be augmented by providing different tactile geological maps (e.g., topography or various datasets), and audio-visual videos freely available for educators. Visual Engagement: Visual engagement consists of several avenues to consider, the three main themes includes: 1) swag; 2) videos; 3) interactive exploration. Swag can include the fun visual take-home materials, such as stickers, posters, bookmarks, etc. Videos can include educational-specific videos (available freely via YouTube or by other educational-specific streaming avenues, such as Nebula or Curiosity Stream), provided they have Closed Captioning (CC). The use of QR codes to such videos or websites can also benefit to being added on swag. Interactive exploration can also be sub-divided by different types of engagement. A popular and still fairly new technology for public engagement is the use of virtual reality (VR). While this has been mainly for martian and lunar surface exploration [1], the deaf communities can benefit from VR through a more extensive look at our solar system and beyond (for example, a VR experience of the flight path, or visual map of the heliosphere/dynamics of our Sun). Audio Engagement: Audio tools can also be a useful avenue of communication, especially for the blind communities. Audio archiving can certainly be transcripts from the video engagements, but also the use of podcasts can also be a benefit. Podcasting can take on two forms: 1) interview engagement; and 2) update engagement. For interviews, scientists can communicate with STEM-specific podcast platforms to make other listener-bases aware of what is going on with a specific mission. For update-type communication, missions may opt to have an archived podcast of news, updates, and the teams involved. The most important aspect of such podcasts would be for the need of complimentary transcripts (including descriptive transcripts if sounds are included), and the limited use of jargon. Research Engagement: There have been several examples of involving the blind and low-vision communities in citizen science, such as through the NASA Heliophysics division. Examples include the NASA PUNCH (Polarimeter to Unify the Corona and Heliosphere) mission led by the Southwest Research Institute [2], which include blind and visually-impaired citizens to assist in the Sun’s coronal rhythms.” Another example is the Eclipse Soundscapes: Citizen Science Project (ES:CSP), which documents observations of acoustical changes of nature and ecosystems during solar eclipse events [3]. Inclusivity: A major theme that is necessary for public engagement is inclusivity and the awareness of reaching broader audiences. Outreach to include hearing/seeing impaired communities are still lacking in the sciences. There are several opportunities that the planetary sciences could take. Other projects that have emerged from the space sciences include adding transcripts to visual engagement [4], and the use of 3D printing for the visually-impaired [5]. References: [1] Olgin, J. (2020) 51st LPSC, Abstract 2137. [2] https://scitechdaily.com/outreach-for-nasa-punch-mission-embraces-ancient-and-modern-sun-watching-theme/ [3] https://science.nasa.gov/science-activation-team/eclipse-soundscapes [4] NASA International Observe the Moon Night (Blind and Deaf Accessible), Youtube Video ( https://www.youtube.com/watch?v=neHCfg0S3-Q) [5] Richardson, J., et al. (2018) AGU Fall Meeting, Abstract ED23F-0963.

C J Ahrens↗

NASA NTRS2003

Aerospace Communications Security Technologies Demonstrated

In light of the events of September 11, 2001, NASA senior management requested an investigation of technologies and concepts to enhance aviation security. The investigation was to focus on near-term technologies that could be demonstrated within 90 days and implemented in less than 2 years. In response to this request, an internal NASA Glenn Research Center Communications, Navigation, and Surveillance Aviation Security Tiger Team was assembled. The 2-year plan developed by the team included an investigation of multiple aviation security concepts, multiple aircraft platforms, and extensively leveraged datalink communications technologies. It incorporated industry partners from NASA's Graphical Weather-in-the-Cockpit research, which is within NASA's Aviation Safety Program. Two concepts from the plan were selected for demonstration: remote "black box," and cockpit/cabin surveillance. The remote "black box" concept involves real-time downlinking of aircraft parameters for remote monitoring and archiving of aircraft data, which would assure access to the data following the loss or inaccessibility of an aircraft. The cockpit/cabin surveillance concept involves remote audio and/or visual surveillance of cockpit and cabin activity, which would allow immediate response to any security breach and would serve as a possible deterrent to such breaches. The datalink selected for the demonstrations was VDL Mode 2 (VHF digital link), the first digital datalink for air-ground communications designed for aircraft use. VDL Mode 2 is beginning to be implemented through the deployment of ground stations and aircraft avionics installations, with the goal of being operational in 2 years. The first demonstration was performed December 3, 2001, onboard the LearJet 25 at Glenn. NASA worked with Honeywell, Inc., for the broadcast VDL Mode 2 datalink capability and with actual Boeing 757 aircraft data. This demonstration used a cockpitmounted camera for video surveillance and a coupling to the intercom system for audio surveillance. Audio, video, and "black box" data were simultaneously streamed to the ground, where they were displayed to a Glenn audience of senior management and aviation security team members.

Griner, James H.↗

NASA NTRS2006

Wireless augmented reality communication system

The system of the present invention is a highly integrated radio communication system with a multimedia co-processor which allows true two-way multimedia (video, audio, data) access as well as real-time biomedical monitoring in a pager-sized portable access unit. The system is integrated in a network structure including one or more general purpose nodes for providing a wireless-to-wired interface. The network architecture allows video, audio and data (including biomedical data) streams to be connected directly to external users and devices. The portable access units may also be mated to various non-personal devices such as cameras or environmental sensors for providing a method for setting up wireless sensor nets from which reported data may be accessed through the portable access unit. The reported data may alternatively be automatically logged at a remote computer for access and viewing through a portable access unit, including the user's own.

Devereaux, Ann↗

NASA NTRS2014

Wireless Augmented Reality Communication System

Devereaux, Ann↗

NASA NTRS2014

Wireless Augmented Reality Communication System

Devereaux, Ann↗

NASA NTRS2016

Wireless Augmented Reality Communication System

Devereaux, Ann↗

NASA NTRS2019

Using Science Operations Tools and Methods from NASA for Remote Presence Ocean Exploration on Earth: E/V Nautilus Cruise NA108

NASA Ames' Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade.In the last two years, we have participated in SUBSEA, a multi-institution collaborative project. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC). In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule.The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team's ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA's Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island's Graduate School of Oceanography (GSO). ISC is GSO's telepresence operations facility.

Lees, David S.↗

NASA NTRS2020

Conducting Efficient Remote Science and Planning Operations for Ocean Exploration Using Exploration Ground Data Systems (xGDS)

NASA Ames’ Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade. In the last two years, we have participated in SUBSEA, a multi-institution collaborative project*. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC)**. In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule. The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team’s ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. * SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA’s Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island’s Graduate School of Oceanography (GSO).

Cohen, Tamar E.↗

NASA NTRS1996

VLSI Neural Networks Help To Compress Video Signals

Advanced analog/digital electronic system for compression of video signals incorporates artificial neural networks. Performs motion-estimation and image-data-compression processing. Effectively eliminates temporal and spatial redundancies of sequences of video images; processes video image data, retaining only nonredundant parts to be transmitted, then transmits resulting data stream in form of efficient code. Reduces bandwidth and storage requirements for transmission and recording of video signal.

Fang, Wai-Chi↗

DOE OSTI2022

Overview and How-to Tutorial Videos for Using NEWTS Data

Overview and How-to Tutorial Videos for Using NEWTS Data Video 1: Overview of NEWTS Database Video 2: How-to tutorial for EPA Flue Gas Desulfurization (FGD) Effluent NEWTS dataset Video 3: How-to tutorial for USGS Produced Waters NEWTS dataset Video 4: How-to tutorial for EPA Ash NEWTS dataset Video 5: How-to tutorial for Quillinan, et al 2018 DOE Geothermal Technology Office REE dataset Video 6: Tutorial video on navigating the NEWTS Dashboard, with an overview of NEWTS and navigating between the NEWTS Dashboard and Datasets (https://netl-doe.maps.arcgis.com/apps/dashboards/a5fa4192f7c6478dab3d6180d9c30b84) Video 7: Additional tutorial video on navigating the NEWTS Dashboard and investigating specific data points in the Dashboard and Datasets Video 8: Re-record of recent webinar giving an overview of the NEWTS Database and Dashboard, including interacting with the NEWTS Dashboard, locating specific data points, and finding the relevant streams in the NEWTS Database and datasets on EDX. Includes overview of the datasets, case studies, and steps for taking stream data from the database and modeling stream data in OLI Studio and Geochemist's Workbench. Note: Video 3 tutorial is also applicable to the USGS Brackish Water NEWTS dataset.

Aqueous Chemistry↗

DOE OSTI2024

Event-to-Video Conversion for Overhead Object Detection

Collecting overhead imagery using an event camera is desirable due to the energy efficiency of the image sensor compared to standard cameras. However, event cameras complicate downstream image processing, especially for complex tasks such as object detection. In this paper, we investigate the viability of event streams for overhead object detection. We demonstrate that across a number of standard modeling approaches, there is a significant gap in performance between dense event representations and corresponding RGB frames. We establish that this gap is, in part, due to a lack of overlap between the event representations and the pre-training data that the object detectors were initially trained on through a number of experiments. Then, apply an off-the-shelf event-to-video conversion tool that converts event streams into gray-scale video to close this gap. We demonstrate that this approach results in a large performance increase, outperforming even event-specific object detection techniques on our overhead target task. These results suggest that better aligning event representations with existing large pre-trained models may result in greater short-term performance gains compared to end-to-end event-specific architectural improvements.

machine learning (ML), computer vision, Neuromorph↗

DOE OSTI2021

Advanced Computing, Data Science, and Artificial Intelligence Research Opportunities for Energy-Focused Transportation Science

The Energy Efficient Mobility Systems (EEMS) technology landscape is complex and rapidly evolving, which provides both tremendous opportunities and formidable challenges. Significant alterations to the mobility landscape are underway due to the advent of vehicle and infrastructure connectivity, autonomous driving, and rapid passenger- and freight-vehicle electrification. Advanced computing will play an increasingly important role in enabling the EEMS program to understand and identify the most important levers to improve the energy productivity of future integrated mobility systems. It is also driving new approaches to mobility and the research to unlock an affordable, efficient, safe, and accessible transportation future. Driving much of this change is the collection, analysis, and strategic use of massive amounts of diverse, complex data from infrastructure and vehicles with on-board sensors and data storage and transmission capabilities. Diverse and representative data are key to implementing approaches to maximize mobility energy productivity. While high-fidelity modeling of integrated transportation networks has strengthened our understanding of dynamic movement and behavior patterns, existing tools must be expanded beyond their current focus. This work necessitates data infrastructure investments (e.g., secure-streaming data platforms driven by ubiquitous sensors and video analytics) as well as investments in critical capabilities for large-scale automated analysis and organization using modern machine learning, statistics, and artificial intelligence. Other chief needs include agile, large-scale storage that can be quickly searched and queried for relevant data to support validation and model development, data-sharing agreements, and formatting standards for key data types. The future of public transit must be explored in greater detail, research must inform design, and opportunities must be identified for improving the mobility productivity of public transit in both urban and rural America.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

A dictionary learning algorithm for compression and reconstruction of streaming data in preset order

There has been an emerging interest in developing and applying dictionary learning (DL) to process massive datasets in the last decade. Many of these efforts, however, focus on employing DL to compress and extract a set of important features from data, while considering restoring the original data from this set a secondary goal. On the other hand, although several methods are able to process streaming data by updating the dictionary incrementally as new snapshots pass by, most of those algorithms are designed for the setting where the snapshots are randomly drawn from a probability distribution. In this paper, we present a new DL approach to compress and denoise massive dataset in real time, in which the data are streamed through in a preset order (instances are videos and temporal experimental data), so at any time, we can only observe a biased sample set of the whole data. Here, our approach incrementally builds up the dictionary in a relatively simple manner: if the new snapshot is adequately explained by the current dictionary, we perform a sparse coding to find its sparse representation; otherwise, we add the new snapshot to the dictionary, with a Gram-Schmidt process to maintain the orthogonality. To compress and denoise noisy datasets, we apply the denoising to the snapshot directly before sparse coding, which deviates from traditional dictionary learning approach that achieves denoising via sparse coding. Compared to full-batch matrix decomposition methods, where the whole data is kept in memory, and other mini-batch approaches, where unbiased sampling is often assumed, our approach has minimal requirement in data sampling and storage: i) each snapshot is only seen once then discarded, and ii) the snapshots are drawn in a preset order, so can be highly biased. Through experiments on climate simulations and scanning transmission electron microscopy (STEM) data, we demonstrate that the proposed approach performs competitively to those methods in data reconstruction and denoising.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1998

Satellite/Terrestrial Networks: End-to-End Communication Interoperability Quality of Service Experiments

Various issues associated with satellite/terrestrial end-to-end communication interoperability are presented in viewgraph form. Specific topics include: 1) Quality of service; 2) ATM performance characteristics; 3) MPEG-2 transport stream mapping to AAL-5; 4) Observation and discussion of compressed video tests over ATM; 5) Digital video over satellites status; 6) Satellite link configurations; 7) MPEG-2 over ATM with binomial errors; 8) MPEG-2 over ATM channel characteristics; 8) MPEG-2 over ATM over emulated satellites; 9) MPEG-2 transport stream with errors; and a 10) Dual decoder test.

Ivancic, William D.↗