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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Automatic Aircraft Collision Avoidance System and Method

The invention is a system and method of compressing a DTM to be used in an Auto-GCAS system using a semi-regular geometric compression algorithm. In general, the invention operates by first selecting the boundaries of the three dimensional map to be compressed and dividing the three dimensional map data into regular areas. Next, a type of free-edged, flat geometric surface is selected which will be used to approximate terrain data of the three dimensional map data. The flat geometric surface is used to approximate terrain data for each regular area. The approximations are checked to determine if they fall within selected tolerances. If the approximation for a specific regular area is within specified tolerance, the data is saved for that specific regular area. If the approximation for a specific area falls outside the specified tolerances, the regular area is divided and a flat geometric surface approximation is made for each of the divided areas. This process is recursively repeated until all of the regular areas are approximated by flat geometric surfaces. Finally, the compressed three dimensional map data is provided to the automatic ground collision system for an aircraft.

Skoog, Mark↗
NASA NTRS2015

Method and System for Dynamic Automated Corrections to Weather Avoidance Routes for Aircraft in En Route Airspace

A dynamic weather route system automatically analyzes routes for in-flight aircraft flying in convective weather regions and attempts to find more time and fuel efficient reroutes around current and predicted weather cells. The dynamic weather route system continuously analyzes all flights and provides reroute advisories that are dynamically updated in real time while the aircraft are in flight. The dynamic weather route system includes a graphical user interface that allows users to visualize, evaluate, modify if necessary, and implement proposed reroutes.

McNally, B. David↗
NASA NTRS2015

Joint Detect and Avoid Flight Testing

This presentation gives insight into a joint flight testing effort that included participation from NASA, Honeywell, and General Atomics. The presentation includes roles and responsibilities, test flow, and encounter requirements and summary.

flight tests↗
NASA NTRS2016

Avoiding Stair-Step Artifacts in Image Registration for GOES-R Navigation and Registration Assessment

In developing software for independent verification and validation (IVV) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

stair-step artifact↗
NASA NTRS2016

Frequency-Range Distribution of Boulders Around Cone Crater: Relevance to Landing Site Hazard Avoidance

Boulders represent a landing hazard that must be addressed in the planning of future landings on the Moon. A boulder under a landing leg can contribute to deck tilt and boulders can damage spacecraft during landing. Using orbital data to characterize boulder populations at locations where landers have safely touched down (Apollo, Luna, Surveyor, and Chang'e-3 sites) is important for determining landing hazard criteria for future missions. Additionally, assessing the distribution of boulders can address broader science issues, e.g., how far craters distribute boulders and how this distribution varies as a function of crater size and age. The availability of new Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images [1] enables the use of boulder size- and range frequency distributions for a variety of purposes [2-6]. Boulders degrade over time and primarily occur around young or fresh craters that are large enough to excavate bedrock. Here we use NAC images to analyze boulder distributions around Cone crater (340 m diameter) at the Apollo 14 site. Cone crater (CC) was selected because it is the largest crater where astronaut surface photography is available for a radial traverse to the rim. Cone crater is young (approximately 29 Ma [7]) relative to the time required to break down boulders [3,8], giving us a data point for boulder range-frequency distributions (BRFDs) as a function of crater age.

Clegg-Watkins, R. N.↗
NASA NTRS2016

Making Debris Avoidance Decisions for ESMO's EOS Mission Set

The presentation will cover the aspects of making debris risk decisions from the NASA Mission Director's perspective, specifically for NASA Earth Science Mission Operations (ESMO) Earth Observing System (EOS) mission set. ESMO has been involved in analyzing potential debris risk conjunctions with secondary objects since the inception of this discipline. Through the cumulated years of experience and continued exposure to various debris scenarios, ESMO's understanding of the problem and process to deal with this issue has evolved. The presentation will describe the evolution of the ESMO process, specifically as it relates to the maneuver execution and spacecraft risk management decision process. It will briefly cover the original Drag Make-Up Maneuver, several day, methodical manually intensive, ramp up waive off approach, to the present day more automated, pre-canned onboard command, tools based approach. The presentation will also cover the key information needed to make debris decisions and challenges in doing so while still trying to meet science goals, constellation constraints and manage resources. A slide or two at the end of the presentation, will be devoted to discussing what further improvements could be helpful to improve decision making and future process improvement plans challenges.

debris↗
NASA NTRS2017

Implicitly Coordinated Detect and Avoid Capability for Safe Autonomous Operation of Small UAS

As the airspace becomes increasingly shared by autonomous small Unmanned Aerial Systems (UAS), there would be a pressing need for coordination strategies so that aircraft can safely and independently maneuver around obstacles, geofences, and traffic aircraft. Explicitly coordinating resolution strategies for small UAS would require additional components such as a reliable vehicle-to-vehicle communication infrastructure and standardized protocols for information exchange that could significantly increase the cost of deploying small UAS in a shared airspace. This paper explores a novel approach that enables multiple aircraft to implicitly coordinate their resolution maneuvers. By requiring all aircraft to execute the proposed approach deterministically, it is possible for all of them to implicitly agree on the region of airspace each will be occupying in a given time interval. The proposed approach lends itself to the construction of a suitable feedback mechanism that enables the real-time execution of an implicitly conflict-free path in a closed-loop manner dealing with uncertainties in aircraft speed. If a network infrastructure is available, the proposed approach can also exploit the benefits of explicit information.

Balachandran, Swee↗
NASA NTRS2018

The Probability of False Go/No-Go Determined by GOES Proton Flux: Proposed Launch Constraints for Avoiding Damaging Solar Energetic Particle Events

The space environment is full of harmful radiation and high energy particles that can cause damage to materials and affect computer systems by e.g., single event effects (SEEs), total ionizing dose (TID), etc. There are three main sources of high energy particles: Trapped radiation in Earth's Van Allen belts (electrons and protons); Solar energetic particles (SEPs) (protons and heavy ions); Galactic cosmic rays (GCRs) (protons and heavy ions). In this study, we focus on the SEPs and their time series and energy spectrum to quantify probabilities of launch go/no-go. The SEPs originate from solar particle events (SPEs) that are associated with a solar flare and/or a coronal mass ejection (CME). These events are difficult to predict. Recent work has been done on these prediction techniques. The Geostarionary Operational Environmental Satellite (GOES) has been observing SEPs for decades. The greater than 10 megaelectronvolt proton flux is shown in Figure 2 since 1986. The SEPs are influenced by the 11-year solar cycle and typically come from active regions on the Sun.

DeStefano, Anthony M.↗
NASA NTRS2016

Avoiding Stair-Step Artifacts in Image Registration for GOES-R Navigation and Registration Assessment

In developing software for independent verification and validation (IVV) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

image registration↗
NASA NTRS2019

Overview of Developments in Voluntary Consensus Standards for Counterfeit Parts Avoidance

The presentation provides an introduction to the electronic parts supply chain and various standards used for preventing counterfeit parts. The presentation provides detailed instruction on various non-destructive techniques, destructive and analytical steps for inspecting suspect counterfeit parts. The techniques are based on the AS6171 Aerospace Standard which standardizes the test and inspection procedures, workmanship criteria, and minimum training and certification requirements to detect counterfeit electrical, electronic, and electromechanical parts. Also included are discussions of other inspection, sampling and distribution standards.

Sood, Bhanu↗