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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Remote Sensing in Geography in the New Millennium: Prospects, Challenges, and Opportunities

Remote sensing science contributes greatly to our understanding of the Earth's ecosystems and cultural landscapes. Almost all the natural and social sciences, including geography, rely heavily on remote sensing to provide quantitative, and indispensable spatial information. Many geographers have made significant contributions to remote sensing science since the 1970s, including the specification of advanced remote sensing systems, improvements in analog and digital image analysis, biophysical modeling, and terrain analysis. In fact, the Remote Sensing Specialty Group (RSSG) is one of the largest specialty groups within the AAG with over 500 members. Remote sensing in concert with a geographic information systems, offers much value to geography as both an incisive spatial-analytical tool and as a scholarly pursuit that adds to the body of geographic knowledge on the whole. The "power" of remote sensing as a research endeavor in geography lies in its capabilities for obtaining synoptic, near-real time data at many spatial and temporal scales, and in many regions of the electromagnetic spectrum - from microwave, to RADAR, to visible, and reflective and thermal infrared. In turn, these data present a vast compendium of information for assessing Earth attributes and characte6stics that are at the very core of geography. Here we revisit how remote sensing has become a fundamental and important tool for geographical research, and how with the advent of new and improved sensing systems to be launched in the near future, remote sensing will further advance geographical analysis in the approaching New Millennium.

Quattrochi, Dale A.↗
NASA NTRS2006

YAM- A Framework for Rapid Software Development

YAM is a software development framework with tools for facilitating the rapid development and integration of software in a concurrent software development environment. YAM provides solutions for thorny development challenges associated with software reuse, managing multiple software configurations, the development of software product-lines, multiple platform development and build management. YAM uses release-early, release-often development cycles to allow developers to incrementally integrate their changes into the system on a continual basis. YAM facilitates the creation and merging of branches to support the isolated development of immature software to avoid impacting the stability of the development effort. YAM uses modules and packages to organize and share software across multiple software products. It uses the concepts of link and work modules to reduce sandbox setup times even when the code-base is large. One side-benefit is the enforcement of a strong module-level encapsulation of a module s functionality and interface. This increases design transparency, system stability as well as software reuse. YAM is in use by several mid-size software development teams including ones developing mission-critical software.

simulations↗
NASA NTRS2007

Mission Simulation Toolkit

The Mission Simulation Toolkit (MST) is a flexible software system for autonomy research. It was developed as part of the Mission Simulation Facility (MSF) project that was started in 2001 to facilitate the development of autonomous planetary robotic missions. Autonomy is a key enabling factor for robotic exploration. There has been a large gap between autonomy software (at the research level), and software that is ready for insertion into near-term space missions. The MST bridges this gap by providing a simulation framework and a suite of tools for supporting research and maturation of autonomy. MST uses a distributed framework based on the High Level Architecture (HLA) standard. A key feature of the MST framework is the ability to plug in new models to replace existing ones with the same services. This enables significant simulation flexibility, particularly the mixing and control of fidelity level. In addition, the MST provides automatic code generation from robot interfaces defined with the Unified Modeling Language (UML), methods for maintaining synchronization across distributed simulation systems, XML-based robot description, and an environment server. Finally, the MSF supports a number of third-party products including dynamic models and terrain databases. Although the communication objects and some of the simulation components that are provided with this toolkit are specifically designed for terrestrial surface rovers, the MST can be applied to any other domain, such as aerial, aquatic, or space.

Pisaich, Gregory↗
NASA NTRS2011

Developing a Prototype ALHAT Human System Interface for Landing

The goal of the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project is to safely execute a precision landing anytime/anywhere on the moon. This means the system must operate in any lighting conditions, operate in the presence of any thruster generated regolith clouds, and operate without the help of redeployed navigational aids or prepared landing site at the landing site. In order to reach this ambitious goal, computer aided technologies such as ALHAT will be needed in order to permit these landings to be done safely. Although there will be advanced autonomous capabilities onboard future landers, humans will still be involved (either onboard as astronauts or remotely from mission control) in any mission to the moon or other planetary body. Because many time critical decisions must be made quickly and effectively during the landing sequence, the Descent and Landing displays need to be designed to be as effective as possible at presenting the pertinent information to the operator, and allow the operators decisions to be implemented as quickly as possible. The ALHAT project has established the Human System Interface (HSI) team to lead in the development of these displays and to study the best way to provide operators enhanced situational awareness during landing activities. These displays are prototypes that were developed based on multiple design and feedback sessions with the astronaut office at NASA/ Johnson Space Center. By working with the astronauts in a series of plan/build/evaluate cycles, the HSI team has obtained astronaut feedback from the very beginning of the design process. In addition to developing prototype displays, the HSI team has also worked to provide realistic lunar terrain (and shading) to simulate a "out the window" view that can be adjusted to various lighting conditions (based on a desired date/time) to allow the same terrain to be viewed under varying lighting terrain. This capability will be critical to determining the effect of terrain/lighting on the human pilot, and how they use windows and displays during landing activities. The Apollo missions were limited to about 28 possible launch days a year due to lighting and orbital constraints. In order to take advantage of more landing opportunities and venture to more challenging landing locations, future landers will need to utilize sensors besides human eyes for scanning the surface. The ALHAT HSI system must effectively convey ALHAT produced information to the operator, so that landings can occur during less "optimal" conditions (lighting, surface terrain, slopes, etc) than was possible during Apollo missions. By proving this capability, ALHAT will simultaneously provide more flexible access to the moon, and greater safety margins for future landers. This paper will specifically focus on the development of prototype displays (the Trajectory Profile Display (TPD), Landing Point Designation (LPD), and Crew Camera View (CCV) ), implementation of realistic planetary terrain, human modeling, and future HSI plans.

Hirsh, Robert L.↗
NASA NTRS2017

Sound Diffraction Modeling of Rotorcraft Noise Around Terrain

A new computational technique, Wave Confinement (WC), is extended here to account for sound diffraction around arbitrary terrain. While diffraction around elementary scattering objects, such as a knife edge, single slit, disc, sphere, etc. has been studied for several decades, realistic environments still pose significant problems. This new technique is first validated against Sommerfeld's classical problem of diffraction due to a knife edge. This is followed by comparisons with diffraction over three-dimensional smooth obstacles, such as a disc and Gaussian hill. Finally, comparisons with flight test acoustics data measured behind a hill are also shown. Comparison between experiment and Wave Confinement prediction demonstrates that a Poisson spot occurred behind the isolated hill, resulting in significantly increased sound intensity near the center of the shadowed region.

Stephenson, James H.↗
NASA NTRS2020

A New Glacial Varve Chronology Along the Southern Laurentide Ice Sheet That Spans the Younger Dryas–Holocene Boundary

Glacial varves can detail ice-margin positions and provide a proxy for meltwater discharge at resolutions comparable to those of the Greenland ice core archives, and thus they can be critical paleorecords for assessing the response of both ancient and modern ice sheets to climate change. Here we provide an ~1500 yr varve chronology straddling the Younger Dryas (YD)–Holocene boundary (11.65 cal. kyr B.P.), the first such chronology in North America. The varves are from glacial Lake Agassiz (central North America). The chronology is pinned on accelerator mass spectrometry radiocarbon-dated terrestrial macrofossils at the base of a widespread red-clay bed deposited during flooding from the Lake Superior basin. We illustrate the utility of this record by examining ice-margin retreat and melting through the late Younger Dryas and across the Holocene boundary. The ice margin receded at a constant rate, not only during the late YD, but for at least 300 yr after the onset of the Holocene. In contrast, varve thicknesses increased at the boundary, and a moraine formed over a 50 yr period, perhaps in response to the warming climate. Our expectation is that this time series will continue to be developed, expanded, and refined because it promises to be the longest and most geographically extensive glacial varve data set in North America.

Glacial varves↗
NASA NTRSDate not supplied

VIPER Lunar Surface Simulator

Overview of synthetic lunar terrain generation methods used for the Resource Prospector and Volatiles Investigating Polar Exploration Rover projects.

simulation↗
NASA NTRS2021

AI4MARS: A Dataset for Terrain-Aware Autonomy on Mars

Deep learning has quickly become a necessity for selfdriving vehicles on Earth. In contrast, the self-driving vehicles on Mars, including NASA’s latest rover, Perseverance, which is planned to land on Mars in February 2021, are still driven by classical machine vision systems. Deep learning capabilities, such as semantic segmentation and object recognition, would substantially benefit the safety and productivity of ongoing and future missions to the red planet. To this end, we created the first large-scale dataset, AI4Mars, for training and validating terrain classification models for Mars, consisting of ~326K semantic segmentation full image labels on 35K images from Curiosity, Opportunity, and Spirit rovers, collected through crowdsourcing. Each image was labeled by ~10 people to ensure greater quality and agreement of the crowdsourced labels. It also includes ~1.5K validation labels annotated by the rover planners and scientists from NASA’s MSL (Mars Science Laboratory) mission, which operates the Curiosity rover, and MER (Mars Exploration Rovers) mission, which operated the Spirit and Opportunity rovers. We trained a DeepLabv3 model on the AI4Mars training dataset and achieved over 96% overall classification accuracy on the test set. The dataset is made publicly available.1

Ono, Hiro↗
NASA NTRSDate not supplied

Digital Lunar Exploration Sites Unreal Simulation Tool (DUST)

NASA’s future Artemis missions to the Moon seek to explore areas around the Lunar South Pole. Though humans have previously set foot on the lunar surface, the proposed region provides unique and challenging environments that require insight and investigation prior to arrival. Several teams throughout the agency are performing this site and mission planning, design, and analysis to support areas like the Human Landing System (HLS), surface mobility, habitation elements, and scientific exploration.

Lunar↗
NASA NTRS2023

Neural Radiance Fields for Shadow Removal and Relighting of Satellite Imagery

Multi-view stereo photogrammetric techniques have been conventionally utilized to generate Global Digital Elevation Models (GDEM) of planetary and lunar surfaces. However, these methods, relying on conventional feature detectors, are often subject to inaccuracies caused by changes in lighting conditions, including diffuse reflection and harsh shading. This has limited the ability of these methods to accurately reconstruct shadowed regions in orbital imagery, such as highly shaded urban areas and the permanently shadowed regions (PSRs) located in the lunar surface, which are critical targets for NASA's Artemis program. Neural Radiance Fields (NeRFs) offer a novel solution to these limitations by breaking away from traditional photogrammetric assumptions of ridged, opaque surfaces. NeRFs are capable of reconstructing 3D objects with variably transmissive properties, such as fluids, PSRs, and reflective surfaces. In this work, we demonstrate the robustness of NeRFs in generating high-fidelity 3D models of terrain from highly shaded orbital imagery acquired from small satellites in low earth orbit (LEO). Our results showcase the ability of NeRF to overcome the limitations of traditional photogrammetric methods and provide a promising solution for reconstructing complex scenes in challenging lighting conditions.

Caleb Ashmore Adams↗