Results for “cover complexity” — Page 20

NASA NTRS2018

Serving NASA GES DISC Multi-Spatiotemporal Earth Science Data to the GIS community

NASA Earth Science (ES) data is essential to a wide range of GIS research and applications. However, for many GIS users, searching, accessing, using and analyzing NASA ES data can be of a great challenge- ranging from the sheer data volumes, types of science parameters, and to the complexity of data encoding formats. As one of the twelve NASA Science Mission Directorate (SMD) Data Centers, Goddard Earth Sciences (GES) Data and Information Services Center (DISC) archives and distributes petabytes of ES parameters covering atmosphere, land, and ocean fields. Most data are multidimensional and multi-spatiotemporal in nature and are encoded in different science data formats (e.g, HDF, HDF-EOS, netCDF, GRIB, binary), which usually contain multiple variables and different metadata information. By far, GES DISC has been developing a number of services and online tools to help GIS users to easily explore our data products. In this presentation, we will describe our ArcGIS-based data accessing and visualization services and portals, which allow users directly exploring the multi-spatiotemporal ES data in ArcGIS clients without having to pre-download/import the data. The ArcGIS services are also compliant with the Open Geospatial Consortium (OGC) Web Coverage Service (WCS) and Web Map Service (WMS) protocols and can be accessed by any other WCS/WMS clients to get customized GES DISC EO data on-the-fly from such services.

Wei, Jennifer↗

NASA NTRS2022

Launch Complex 39A, SWMU 008 and Launch Complex 39B, SWMU 009 Performance Monitoring and Air Sparge Expansion Construction Completion Report Kennedy Space Center, Florida

This Performance Monitoring and Construction Completion Report (PM-CCR) presents the findings, observations, and results for air sparging (AS) operations and sitewide groundwater monitoring for Launch Complex 39A (LC39A), Solid Waste Management Unit (SWMU) 008, and Launch Complex 39B (LC39B), SWMU 009, at Kennedy Space Center (KSC), Florida. Results from direct push technology (DPT) sampling and AS system expansion activities at LC39A are also included in this report. The reporting period covered under this PM-CCR is from January 1, 2021, to December 31, 2021.

Andrew M Walters↗

NASA NTRS1979

Evolution of the Shuttle extravehicular mobility unit

This paper deals briefly with the emergence of space suits as an important factor in supporting space missions but focuses mainly on the conceptual design of the Shuttle EMU (extravehicular mobility unit). Factors covering the criteria for the design approach are discussed. Several of the more specific subjects concerning the configuration selected are stressed; the EMU operating pressure, simplicity in don/doff, male/female sizing, components' useful life and the complexity surrounding the support of multi-year missions throughout the Shuttle program duration. In addition, comparisons with past EMU programs are made including a detailed discussion of how the Shuttle application and requirements drove and made this configuration a significant departure from previous EMU systems.

Correale, J. V.↗

NASA NTRS1980

Unsupervised classification of MSS Landsat data for mapping spatially complex vegetation

The various stages in carrying out a monocluster block unsupervised classification using Landsat MSS data are described. Procedures for carrying out these various stages were found to be far from well-established for the type of terrain being investigated, which is rugged and contains many small land cover units. Two particular difficulties were encountered: first, that of precise ground location of pixels; and, secondly, that of objectively evaluating the results. Ways in which these can be surmounted are suggested.

Townshend, J. R. G.↗

NASA NTRS2005

On Structural Design of a Mobile Lunar Habitat With Multi- Layered Environmental Shielding

This report presents an overview of a Mobile Lunar Habitat (MLH) structural design consisting of advanced composite materials. The habitat design is derived from the cylindrical-shaped U.S. Lab module aboard the International Space Station (ISS) and includes two lateral ports and a hatch at each end that geometrically match those of the ISS Nodes. Thus, several MLH units can be connected together to form a larger lunar outpost of various architectures. For enhanced mobility over the lunar terrain, the MLH uses six articulated insect-like robotic, retractable legs enabling the habitat to .t aboard a launch vehicle. The carbon-composite shell is sandwiched between two layers of hydrogen-rich polyethylene for enhanced radiation shielding. The pressure vessel is covered by modular double-wall panels for meteoroid impact shielding supported by externally mounted stiffeners. The habitat s structure is an assembly of multiple parts manufactured separately and bonded together. Based on the geometric complexity of a part and its material system, an appropriate fabrication process is proposed.

Pruitt, J. R.↗

NASA NTRS2012

Automating Mid- and Long-Range Scheduling for the NASA Deep Space Network

NASA has recently deployed a new mid-range scheduling system for the antennas of the Deep Space Network (DSN), called Service Scheduling Software, or S(sup 3). This system was designed and deployed as a modern web application containing a central scheduling database integrated with a collaborative environment, exploiting the same technologies as social web applications but applied to a space operations context. This is highly relevant to the DSN domain since the network schedule of operations is developed in a peer-to-peer negotiation process among all users of the DSN. These users represent not only NASA's deep space missions, but also international partners and ground-based science and calibration users. The initial implementation of S(sup 3) is complete and the system has been operational since July 2011. This paper describes some key aspects of the S(sup 3) system and on the challenges of modeling complex scheduling requirements and the ongoing extension of S(sup 3) to encompass long-range planning, downtime analysis, and forecasting, as the next step in developing a single integrated DSN scheduling tool suite to cover all time ranges.

Deep Space Network↗

NASA NTRS2015

Landsat-Swath Imaging Spectrometer Design

We describe the design of a high-throughput pushbroom imaging spectrometer and telescope system that is capable of Landsat swath and resolution while providing better than 10 nm per pixel spectral resolution. The design is based on a 3200 x 480 element x 18 μm pixel size focal plane array, two of which are utilized to cover the full swath. At an optical speed of F/1.8, the system is the fastest proposed to date to our knowledge. The utilization of only two spectrometer modules fed from the same telescope reduces system complexity while providing a solution within achievable detector technology. Predictions of complete system response are shown. Also, it is shown that detailed ghost analysis is a requirement for this type of spectrometer and forms an essential part of a complete design.

Dyson spectrometer↗

NASA NTRS2022

A Study of Photoionized Gas in Two H װ Regions of the N44 Complex in the LMC Using MUSE Observations

We use the optical integral field observations with Multi-Unit Spectroscopic Explorer (MUSE) on the Very Large Telescope, together with CLOUDY photoionization models, to study ionization structure and physical conditions of two luminous H װ regions in the N44 star-forming complex of the Large Magellanic Cloud. The spectral maps of various emission lines reveal a stratified ionization geometry in N44 D1. The spatial distribution of [O ו] λ6300 emission in N44 D1 indicates a partially covered ionization front at the outer boundary of the H װ region. These observations reveal that N44 D1 is a blister H װ region. The [O ו] λ6300 emission in N44 C does not provide a well-defined ionization front at the boundary, while patches of [S װ] λ6717 and [O ו] λ6300 emission bars are found in the interior. The results of spatially resolved MUSE spectra are tested with the photoionization models for the first time in these H װ regions. A spherically symmetric ionization-bounded model with a partial covering factor, which is appropriate for a blister H װ region, can well reproduce the observed geometry and most of the diagnostic line ratios in N44 D1. Similarly, in N44 C we apply a low-density and optically thin model based on the observational signatures. Our modeling results show that the ionization structure and physical conditions of N44 D1 are mainly determined by the radiation from an O5 V star. However, local X-rays, possibly from supernovae or stellar wind, play a key role. In N44 C, the main contribution is from three ionizing stars.

H II regions↗

NASA NTRS1979

An evaluation of Landsat 3 RBV imagery for an area of complex terrain in Southern Italy

Return Beam Videcon imagery from Landsat 3 was obtained in August, 1978 for part of Southern Italy in the regions of Basilicata and Apulia. The resolution of this imagery for medium contrast objects is approximately 40 meters and is shown to provide significant information concerning land cover and fluvial morphometry. Because of the wide spectral band width which is sensed (0.505-0.750 microns) by the RBV cameras, discrimination is only possible for spectrally distinct cover types, especially oak woodland. Fluvial morphometry can be readily described using the imagery. Because of the intense dissection of the area, the lowest order streams cannot be consistently mapped, but the rank order of the measured values of properties such as drainage density and link frequency for different lithologies corresponds closely to the actual ranking.

Townshend, J. R. G.↗

NASA NTRS1982

Transmission of sound across a vortex layer enclosing a cylindrical column of jet

An approximate solution to the problem of transmission of sound across a cylindrical vortex was obtained. Results are considerably different from the plane vortex sheet case because of the added role played by the curvature of the jet. In comparison with the plane case, the specularly transmitted waves are more complex and require some numerical integration. Resonance waves are identically predicted for M 2, but there is also a wave field whose modified effect appears to extend the region of resonance just as the instability waves cover a region in space and time. The instability waves are predicted to exist for all Mach numbers but vanish for wavelengths that are large compared to the jet radius. The region of propagation is similarly wavelength dependent.

Luh, R.↗

NASA NTRS2000

Cooperative Robotics and the Search for Extraterrestrial Life

If we think tenuous abodes of life may be hiding in remote extraterrestrial environmental niches, and if we want to assess the biological status of a given locale or entire planet before sending humans (perhaps because of contamination concerns or other motivations) then we face the challenge of robotically exploring a large space efficiently and in enough detail to have confidence in our assessment of the biological status of the environment in question. On our present schedule of perhaps two or so missions per opportunity, we will likely need a different exploratory approach than singular stationary landers or singular rover missions or sample return, because there appear to be fundamental limitations in these mission profiles to-obtain the many samples we will likely need if we want to have confidence in assessing the biological status of an environment in which life could be hiding in remote environmental niches. Singular rover missions can potentially accommodate sampling over a fairly large area, but are still limited by range and can be a single point of failure. More importantly, such mission profiles have limited payload capabilities which are unlikely to meet the demanding requirements of life-detection. Sample return has the advantage of allowing sophisticated analysis of the sample, but also has the severe limitations associated with only being able to bring back a few samples. This presentation will suggest two cooperative robotic approaches for exploration that have the potential to overcome these difficulties and facilitate efficient and thorough life-detecting exploration of a large space. Given the two premises state above, it appears at least two fundamental challenges have to be met simultaneously: coverage of a large space and bringing to bear a sophisticated suite of detection and experimental payloads on any specific location in order to address a major challenge in looking for extraterrestrial life: namely, executing a wide variety of detection scenarios and in situ experiments in order to gather the required data for a confident assessment that life has been detected and to, more generally, cover a wide range of extraterrestrial life possibilities. Cooperative robotics ]ends itself to this kind of problem because cooperation among the combined capabilities of a variety of simple single function agents can give rise to fairly complex task execution such as the search for and detection of extraterrestrial life.

Lupisella, Mark L.↗

NASA NTRS2000

Cooperative Robotics and the Search for Extraterrestrial Life

If we think tenuous abodes of life may be hiding in remote extraterrestrial environmental niches, and if we want to assess the biological status of a given locale or entire planet before sending humans (perhaps because of contamination concerns or other motivations) then we face the challenge of robotically exploring a large space efficiently and in enough detail to have confidence in our assessment of the biological status of the environment in question. On our present schedule of perhaps two or so missions per opportunity, we will likely need a different exploratory approach than singular stationary landers or singular rover missions or sample return, because there appear to be fundamental limitations in these mission profiles to obtain the many samples we will likely need if we want to have confidence in assessing the biological status of an environment in which life could be hiding in remote environmental niches. Singular rover missions can potentially accommodate sampling over a fairly large area, but are still limited by range and can be a single point of failure. More importantly, such mission profiles have limited payload capabilities which are unlikely to meet the demanding requirements of life-detection. Sample return has the advantage of allowing sophisticated analysis of the sample, but also has the severe limitations associated with only being able to bring back a few samples. This presentation will suggest two cooperative robotic approaches for exploration that have the potential to overcome these difficulties and facilitate efficient and thorough life-detecting exploration of a large space. Given the two premises stated above, it appears at least two fundamental challenges have to be met simultaneously: (1) coverage of a large space and (2) bringing to bear a sophisticated suite of detection and experimental payloads on any specific location in order to address a major challenge in looking for extraterrestrial life: namely, executing a wide variety of detection scenarios and in situ experiments in order to gather the required data for a confident assessment that life has been detected and to, more generally, cover a wide range of extraterrestrial life possibilities. Cooperative robotics lends itself to this kind of problem because cooperation among the combined capabilities of a variety of simple single function agents can give rise to fairly complex task execution such as the search for and detection of extraterrestrial life.

Lupisella, M. L.↗

NASA NTRS2008

A View of Earth's Aerosol System from Space to Your Office Chair

Aerosols are tiny particles and droplets suspended in the air. Each day you breathe in about 10 billion of them, about a half a million per breath. They are formed in nature by volcanoes, dust storms, sea spray, and emissions from vegetation. Humans create aerosols and alter their natural sources by burning fossil fuels and modifying land cover. Fires are another important source of aerosols; some are natural, such as wildfires started by lightning strikes, while others are from human-caused burning of vegetation for cooking, heating, and land clearing. Aerosols have complex effects on Earth's climate. In general, they cool the surface by reflecting (scattering) radiation from the sun back into space. Dust and smoke absorb solar radiation and heat the atmosphere where they are concentrated. Aerosols change the properties of clouds. Indeed, it would be very difficult to form clouds in the atmosphere without aerosols to act as 'seeds' for water to condense on. In aerosol polluted environments clouds tend to have smaller droplets than clouds formed in cleaner environments; these polluted clouds appear brighter from space because they reflect more sunlight, and they may persist longer and not rain as intensely. Aerosols also affect local air quality and visibility. Data collected by NASA satellites over the past decade have provided an unprecedented view of Earth's aerosol distribution and dramatically increased our understanding of where aerosols come from and just how far they travel in the atmosphere. In this talk I will discuss observations of aerosols from space and how they inform numerical transport models attempting to simulate the global aerosol system.

Colarco, Peter↗

NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

reinforcement learning↗

NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

Validation↗

NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

Validation↗

NASA NTRS2024

Launch Complex 39A Operations Support Building Area SWMU 111 Year 3 Air Sparge System Performance Monitoring Report

This Air Sparge (AS) System Performance Monitoring Report (PMR) presents the findings, observations, and results for Year 3 of operation, maintenance, and monitoring activities for the AS Interim Measure (IM) at the Launch Complex 39A Operations Support Building Area (AOSB) at Kennedy Space Center (KSC), Florida. This report was presented as an Advance Data Package during the October 2024 KSC Remediation Team (KSCRT) meeting. The reporting period for activities covered under this PMR is from August 2023 through October 2024.

Mark P Speranza↗

NASA NTRS1988

The Mariner Mark II high precision scan actuator - Results of an options trade study covering pointing performance and system-wide impacts

Four actuators considered as candidates to meet the requirements of the Mariner Mark II high-precision scan platform are evaluated with respect to such criteria as the net effect on spacecraft mass, required power, cost, expected pointing performance, operational considerations, and necessary control complexity. A direct drive actuator is found to be the most suitable candidate. It is noted that for missions where reactionless actuation results in a lower spacecraft mass due to propellant savings, the option of using a platform mounted or spacecraft mounted reaction wheel for platform momentum compensation and spacecraft attitude control is attractive.

Schier, J. Alan↗