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NASA NTRS1997

(abstract) Mars Global Surveyor Mission

The Mars Global Surveyor (MGS) spacecraft will be launched in November of 1996 to the planet Mars for an extended study of the planet's surface, atmosphere, gravitational field and magnetic field. In order to achieve the scientific objectives of the mission, the spacecraft will be inserted into a low-altitude, near-polar, Sun-synchronous orbit. Data will be collected and returned from six prime experiments on the spacecraft for over one Martian year (687 Earth days) and will provide for a better understanding of the geology, geophysics, and climatology of Mars. Five of these six experiments will utilize scientific instruments mounted on the spacecraft. The sixth investigation will collect data about Mars by analyzing the spacecraft's radio signal.

Mars↗

NASA NTRS2020

Flood Mapping Using UAVSAR and Convolutional Neural Networks

We have mapped flooded areas in data collected by the NASA/JPL Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) using two convolutional neural network (CNN) image classifier architectures: U-Net and SegNet. Our study area was a region around Houston, TX, USA affected by widespread flooding in 2017 due to Hurricane Harvey. To train and test the classifiers, we manually labelled over 10000 image segments in two flight lines. Both U-Net and SegNet yielded higher accuracy than a previous non-machine learning classifier we used as a baseline. U-Net had slightly higher accuracy than SegNet. The classifiers performed better in areas with more homogeneous land cover. To independently validate the classifier accuracy we used NOAA aerial imagery, with overall accuracy around 80%. Future work includes assessing the classifier robustness in other study areas, assessing the classifier dependence on UAVSAR incidence angle, particularly for open water and bare ground, and collecting more training data, particularly in urban areas. This study demonstrates the potential of CNN image classifiers for mapping flooded areas in airborne polarimetric SAR imagery, and for land cover classification of polarimetric SAR imagery more generally.

Denbina, Michael W↗

NASA NTRSDate not supplied

How To Train Your Dragon (and Vice Versa) – Human Spaceflight Research and The First Commercial Crews

The International Space Station has been an orbiting laboratory for human spaceflight research for over 20 years. NASA’s human research implementation teams have worked to develop, refine, and execute pre-, in-, and post-flight sessions to collect critical research data that will enable future spaceflight missions. The teams have worked closely with the spaceflight vehicle teams, including those for Soyuz and the now retired Space Shuttle vehicles, to successfully conduct this research. As NASA has transitioned to commercial vehicles for transport of crews to the ISS, the implementation teams have expanded their scope to include the SpaceX and upcoming Boeing vehicles. This session will focus on the unique implementation needs for the first available commercial platform, SpaceX. We will identify implementation adjustments made to accommodate the SpaceX Dragon system, including crew training and preflight baseline data collection, inflight operations tied to landing, and postflight planning and crew testing, as well as offer lessons learned from the past three SpaceX long-duration crew missions. Representatives from the Flight Operations Directorate, including the Astronaut Office and the vehicle recovery team, will also provide their perspectives on this new system, and how it affects their work with the human research community. A panel discussion with dedicated time for Q&A will follow.

Pasha Morshedi↗

NASA NTRS2022

Colorado Eastern Plains Agriculture: Rangeland Monitoring to Inform Grazing Management in Eastern Colorado

Adaptive management on cattle ranches requires rangeland managers to decide the location and duration of the cattle grazing activity across different pastures. Biodiversity, forage availability, and cattle health are all affected by rangeland management. Virtual fencing is a tool that rangeland managers can use to potentially increase biodiversity and improve ranching operations. NASA DEVELOP and Colorado State University (CSU) collaborated with the Nature Conservancy (TNC), and Red Top Ranch to demonstrate the efficacy of virtual fencing. We sought to identify annual and monthly biomass patterns on the ranch through the creation of monthly max biomass productivity maps. We utilized a dataset from the Agricultural Research Service (ARS) to calculate biomass on the ranch. To validate our remotely-sensed results, we compared model-predicted biomass values to field-collected biomass clipping data and an additional biomass dataset from the Rangeland Analysis Platform (RAP). We used satellite imagery from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 –OLI-2, and Sentinel-2 MultiSpectral Instrument (MSI) for 2021 and 2022. We found that there was heterogeneity in biomass across the ranch, with higher biomass on the western side. The highest peak of biomass was in the summer months, with a smaller peak in mid-September. The ARS biomass dataset had a significant relationship with RAP for 2021. ARS biomass did not have a significant relationship with the biomass field data collected in 2022. The results of our study are aimed to support rotation management, ranch production, biodiversity, and conservation management.

cattle↗

NASA NTRS2023

NASA Researcher Demographics

NASA is committed to supporting a research environment that is fair and equitable. In order to promote opportunity for everyone, NASA is collecting data on the demographic makeup of its research community with the aim of using this data to support decision making in future programs and projects. This report summarizes the demographic data we have collected for the Science Mission Directorate since 2016.

demographics↗

NASA NTRS2018

Evaluation of Crew-Centric Onboard Mission Operations Planning and Execution Tool: Year 2

Currently, mission planning for the International Space Station (ISS) is largely affected by ground operators in mission control. The task of creating a week-long mission plan for ISS crew takes dozens of people multiple days to complete, and is often created far in advance of its execution. As such, re-planning or adapting to changing real-time constraints or emergent issues is similarly taxing. As we design for future mission operations concepts to other planets or areas with limited connectivity to Earth, more of these ground-based tasks will need to be handled autonomously by the crew onboard.There is a need for a highly usable (including low training time) tool that enables efficient self-scheduling and execution within a single package. The ISS Program has identified Playbook as a potential option. It already has high crew acceptance as a plan viewer from previous analogs and can now support a crew self-scheduling assessment on ISS or on another mission. The goals of this work, a collaboration between the Human Research Program and the ISS Program, are to inform the design of systems for more autonomous crew operations and provide a platform for research on crew autonomy for future deep space missions. Our second year of the research effort have included new insights on the crew self-scheduling sessions performed by the crew through use on the HERA (Human Exploration Research Analog) and NEEMO (NASA Extreme Environment Mission Operations) analogs. Use on the NEEMO analog involved two self-scheduling strategies where the crew planned and executed two days of EVAs (Extra-Vehicular Activities). On HERA year two represented the first HERA campaign where we were able to perform research tasks. This involved selected flexible activities that the crew could schedule, mock timelines where the crew completed more complex planning exercises, usability evaluation of the crew self-scheduling features, and more insights into the limit of plan complexity that the crew could effectively self-schedule. In parallel we have added in new features and functionality in the Playbook tool based off of our insights from crew self-scheduling in the NASA analogs. In particular this year we have added in the ability for the crew to add, edit, and remove their own activities in the Playbook tool, expanding the type of planning and re-planning possible in the tool and opening up the ability for more free form plan creation. The ability to group and manipulate groups of activities from the plan task list was also added, allowing crew members to add predefined sets of activities onto their mission timeline. In addition we also added a way for crew members to roll back changes in their plan, in order to allow an undo like capability. These features expand and complement the initial self-scheduling features added in year one with the goal of making crew autonomous planning more efficient. As part of this work we have also finished developing the first version of our Playbook Data Analysis Tool, a research tool built to interpret and analyze the unobtrusively collected data obtained during the NASA analog missions through Playbook. This data which includes user click interaction as well as plan change information, through the Playbook Data Analysis Tool, allows us to playback this information as if a video camera was mounted over the crewmember's tablet. While the primary purpose of this tool is to allow usability analysis of crew self-scheduling sessions used on the NASA analog, since the data collected is structured, the tool can automatically derive metrics that would be traditionally tedious to achieve without manual analysis of video playback. We will demonstrate and discuss the ability for future derived metrics to be added to the tool. In addition to the current data and results gathered in year two we will also discuss the preparation and goals of our International Space Station (ISS) onboard technology demonstration with Playbook. This technology demonstration will be preformed as part of the CAST payload starting in late 2016.

onboard planning↗

NASA NTRS2010

Spatial Statistical Data Fusion for Remote Sensing Applications

Data fusion is the process of combining information from heterogeneous sources into a single composite picture of the relevant process, such that the composite picture is generally more accurate and complete than that derived from any single source alone. Data collection is often incomplete, sparse, and yields incompatible information. Fusion techniques can make optimal use of such data. When investment in data collection is high, fusion gives the best return. Our study uses data from two satellites: (1) Multiangle Imaging SpectroRadiometer (MISR), (2) Moderate Resolution Imaging Spectroradiometer (MODIS).

fusion techniques↗

NASA NTRSDate not supplied

Addressing Critical Knowledge Gaps on Wildland Fires with UAS Technology

To better predict and respond to extreme fire behavior, wind shear, and superheated gases, there is a need for enhanced tactical microclimate wind forecasting. Collecting real-time or near-real-time three-dimensional atmospheric data during wildland fire suppression is vital for both ground firefighters and aviation safety. The use of balloons for soundings is not allowed due to aircraft operations, so new technology must be used. To address this need, the NASA FireSense Project has invested in co-developing and transitioning advanced technologies for atmospheric data collection to operational platforms to support decisions for wildland fire management. One of these technology investments has been with Uninhabited Aerial Systems (UAS) for atmospheric soundings. In collaboration with MITRE Corporation, a technology demonstration of Uninhabited Aerial Systems (UAS) for atmospheric soundings was held in Missoula, MT. This demonstration featured a NASA-designed payload on a Freefly Alta-X UAS, consistent with USFS UAS operations, balloon-borne soundings for data validation, and microscale modeling efforts. Results of this effort will be presented including comparison of forecasted conditions to data collection values as well as the impact on forecasts given real-time mixing heights and dispersion levels.

Jennifer Fowler↗

NASA NTRS2015

RUMS - Realtime Visualization and Evaluation of Live, Virtual, Constructive Simulation Data

This paper describes the tools and display capabilities being developed to visualize aircraft flight and trajectory information that is produced during a distributed Live, Virtual, Constructive (LVC) simulation events involving a mix of manned and unmanned aircraft. This paper discusses the design approach and general software architecture of the Remote User Monitor Service (RUMS) application. The simulations and flight tests are conducted over a nationwide network with components communicating via software gateways that translate the messages and provide a location to access and collect data. The data collected is not only archived for post-processing and analysis, but also processed in real-time by RUMS, which allows dynamic viewing of the information via a web browser. This real-time dynamic viewing of the data allows test conductors and researchers to monitor the health of the distributed system and of the data being collected not only in situ where tests are conducted but also at remote locations.

distributed simulation↗

NASA NTRS1979

Accuracy assessment in the Large Area Crop Inventory Experiment

The Accuracy Assessment System (AAS) of the Large Area Crop Inventory Experiment (LACIE) was responsible for determining the accuracy and reliability of LACIE estimates of wheat production, area, and yield, made at regular intervals throughout the crop season, and for investigating the various LACIE error sources, quantifying these errors, and relating them to their causes. Some results of using the AAS during the three years of LACIE are reviewed. As the program culminated, AAS was able not only to meet the goal of obtaining accurate statistical estimates of sampling and classification accuracy, but also the goal of evaluating component labeling errors. Furthermore, the ground-truth data processing matured from collecting data for one crop (small grains) to collecting, quality-checking, and archiving data for all crops in a LACIE small segment.

Houston, A. G.↗

NASA NTRSDate not supplied

An Agile-Like Approach to Hardware Development: The Ejectable Data Recorder (EDR) for Orion's Ascent Abort 2 (AA-2) Test Flight

On July 2, 2019, the Ascent Abort 2 (AA-2) Flight Test Vehicle was launched from Cape Canaveral, with the goal of demonstrating the performance of Orion’s Launch Abort System (LAS) and collecting data from hundreds of sensors throughout the vehicle. The data collected during this test flight is of paramount importance, as it will be used to certify the Orion vehicle for human spaceflight. Originally, the data was to be downlinked via a single string network of antennas on the LAS, with the associated risk of potential data dropouts, as well as loss of data once the LAS was jettisoned. Thus, additional antennas were added onto the crew module (CM) to support data downlink post-LAS jettison, a buffer rebroadcast capability was added to fill in any gaps in data downlink transmissions, and an ejectable data recorder (EDR) subsystem was added to the CM as a redundant measure to collect all the instrumentation data. The EDR subsystem was added to the project about one year after the project commenced, which significantly reduced the available development time when compared with the other subsystems of the AA-2 Test Flight. The project was further accelerated by six months, around the critical design review gate. Due to the schedule compression challenge and the fact that the EDR subsystem was a backup system and not flight critical, the EDR subsystem was further challenged to find a new and more efficient way to develop hardware. Thus, the EDR subsystem experimented with different management and systems engineering processes, team sizes, communication methods, and tools. Some examples are novel uses of SharePoint as a Data-centric Project Management & Systems Engineering environment, a continuous testing approach through the lifecycle, and a Skunkworks approach to managing the team. The EDR subsystem blended Commercial Off The Shelf (COTS) hardware with in-house developed hardware and software to create a novel data retrieval capability. The capability evolved rapidly through a hardware in the loop simulation environment that enabled incremental component updates for not only the EDR subsystem but across the entire Crew Module. This paper will present an overview of how the EDR subsystem was managed and compare it to an Agile approach to managing projects. The paper will further provide a recommended approach to future Agile-like hardware development that incorporates lessons learned from the EDR experience.

Agile↗

NASA NTRS1988

A facility for precise temperature control applications in microgravity

The general design, main components, and operation of the isothermal dendritic growth apparatus (IDGA) designed for microgravity experimentation are described. The four major subsystems of the IDGA are a temperature controlled thermostatic bath capable of milli-kelvin stability, a photographic data collection system, a crystal growth chamber, and a growth detection system to initiate data collection. Some of the specific experiments that could utilize the capabilities of the IDGA are dendritic growth in alloys, monotectic systems, life science experiments, and technological applications.

Glicksman, M. E.↗

NASA NTRS1993

Backscatter Characteristics of the Winter Sea Ice Cover in the Beaufort

The microwave backscatter statistics of the sea ice cover in the winter Beaufort Sea were characterized using C-band Synthetic Aperture Radar (SAR) data collected by ERS-1. Sea ice backscatter signatures were sampled from SAR image data collected during the winter of 1991/92 and winter of 1992/93. The spatial and temporal variabilities of the backscatter signatures of different ice types are discussed. The results show considerable seasonal stability of the backscatter signature of multi-year ice as well as first-year ice. Small amplitude regional variations of the multi-year ice backscatter can be observed. Consistent contrast between multiyear ice and first-year ice is maintained throughout the season.

Kwok, R.↗

NASA NTRSDate not supplied

Methodology for Validation of Unsteady Pressure-Sensitive Paint Measurements using Pressure Transducers

Unsteady Pressure-Sensitive Paint (uPSP) technology provides simultaneously high-frequency and high-spatial resolution surface pressure fluctuation measurements. It has demonstrated value in wind tunnel test facilities to evaluate aerospace vehicle unsteady aerodynamics. The calibration of measurements from digital pixel counts into corresponding physical units relies on both lab-based and in-situ calibration steps, and its validation is both challenging and critical to adoption of the technology. We present a rigorous methodology for direct comparison of uPSP-derived surface pressure measurements to reference pressure transducer data based on a model of the camera-based measurement error, a model of the flow field pressure signal, and their propagation through the uPSP data reduction algorithm. The methodology is demonstrated on data collected in a small-scale, subsonic wind tunnel test as well as data collected from a Space Launch System unsteady aerodynamics characterization test at the NASA Ames Research Center Unitary Plan Wind Tunnel Complex.

Pressure-Sensitive Paint↗

NASA NTRSDate not supplied

Validating uPSP with Transducers

Pressure-Sensitive Paint↗

NASA NTRS1987

Measurement-based reliability/performability models

Measurement-based models based on real error-data collected on a multiprocessor system are described. Model development from the raw error-data to the estimation of cumulative reward is also described. A workload/reliability model is developed based on low-level error and resource usage data collected on an IBM 3081 system during its normal operation in order to evaluate the resource usage/error/recovery process in a large mainframe system. Thus, both normal and erroneous behavior of the system are modeled. The results provide an understanding of the different types of errors and recovery processes. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A sensitivity analysis is performed to investigate the significance of using a semi-Markov process, as opposed to a Markov process, to model the measured system.

Hsueh, Mei-Chen↗

NASA NTRS2006

Results from the Gas Chromatograph Mass Spectrometer (GCMS) Experiment on the Cassini-Huygens Probe

The GCMS was part of the instrument complement on the Cassini-Huygens Probe to measure in situ the chemical composition of the atmosphere during the probe descent and coupled with the Aerosol Collector Pyrolyser (ACP) experiment by serving as detector for the pyrolization products to determine the composition of the aerosol particles. The GCMS employed a quadrupole mass filter with a secondary electron multiplier detection system and a gas sampling system providing continuous direct atmospheric composition measurements and batch sampling through three gas chromatographic (GC) columns, a chemical scrubber and a hydrocarbon enrichment cell. The GCMS gas inlet was heated to prevent condensation, and to evaporate volatiles from the surface after impact. The GCMS collected data from an altitude of 146 km to ground impact. The Probe and the GCMS survived impact and collected data for 1 hour and 9 minutes on the surface. Mass spectra were collected during descent and on the ground over a range of m/z from 2 to 141. The major constituents of the lower atmosphere were confirmed to be NP and CH4. The methane mole fraction was uniform in the stratosphere. It increased below the tropopause, at about 32 km altitude, monotonically toward the surface, reaching a plateau at about 8 km at a level near saturation. After surface impact a steep increase of the methane signal was observed, suggesting evaporation of surface condensed methane due to heating by the GCMS sample inlet heater. The measured mole fraction of Ar-40 is 4.3 x 10(exp-5) and of Ar-36 is 2.8 x 10(exp -7). The other primordial noble gases were below mole fraction. The isotope ratios of C-12/C-13 determined from methane measurements are 82.3 and of N-14/N-15 determined from molecular nitrogen are 183. The D/H isotope ratio determined from the H2 and HD measurements is 2.3 x l0(exp -4). Carbon dioxide, ethane, acetylene and cyanogen were detected evaporating from the surface in addition to methane.

Niemann, Hasso B.↗

NASA NTRS2006

Results from the Gas Chromatograph Mass Spectrometer (GCMS) Experiment on the Cassini-Huygens Probe

The Gas Chromatograph Mass Spectrometer was one of six instruments on the Cassini-Huygens Probe mission to Titan. The GCMS measured in situ the chemical composition of the atmosphere during the probe descent and served as the detector for the pyrolization products for the Aerosol Collector Pyrolyser (ACP) experiment to determine the composition of the aerosol particles. The GCMS collected data from an altitude of 146 km to ground impact. The Probe and the GCMS survived impact and collected data for 1 hour and 9 minutes on the surface. Mass spectra were collected during descent and on the ground over a range of m/z from 2 to 141. The major constituents of the lower atmosphere were confirmed to be N2 and CH4. The methane mole fraction was uniform in the stratosphere. It increased below the tropopause, at about 32 km altitude, monotonically toward the surface, reaching a plateau at about 8 km at a level near saturation. After surface impact a steep increase of the methane signal was observed, suggesting evaporation of surface condensed methane due to heating by the GCMS sample inlet heater. The measured mole fraction of Ar-40 is 4.3x10(exp -5) and of Ar-36 is 2.8x10(exp -7). The other primordial noble gases were below 10(exp -8) mole fraction. The isotope ratios of C-12/C-13 determined from methane measurements are 82.3 and of N-14/N-15 determined from molecular nitrogen are 183. The D/H isotope ratio determined from the H2 and HD measurements is 2.3x10(exp -4). Carbon dioxide, methane, acetylene and cyanogen were detected evaporating from the surface in addition to methane. The GCMS employed a quadrupole mass filter with a secondary electron multiplier detection system and a gas sampling system providing continuous direct atmospheric composition measurements and batch sampling through three gas chromatographic (GC) columns, a chemical scrubber and a hydrocarbon enrichment cell. The GCMS gas inlet was heated to prevent condensation, and to evaporate volatiles from the surface after impact.

Niemann, H.↗