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NASA NTRS2005

The Fluids and Combustion Facility: Enabling the Exploration of Space

The Fluids and Combustion Facility (FCF) is an International Space Station facility designed to support physical and biological research as well as technology experiments in space. The FCF consists of two racks called the Combustion Integrated Rack (CIR) and the Fluids Integrated Rack (FIR). The capabilities of the CIR and the FIR and plans for their utilization will support the President's vision for space exploration. The CIR will accommodate physical research and technology experiments that address needs in the areas of spacecraft fire prevention, detection and suppression, incineration of solid wastes, and power generation. Initial experiments will provide data to support design decisions for exploration spacecraft. The CIR provides a large sealed chamber in a near-weightless environment. The chamber supports many simulated atmospheres including lunar or Martian environments. The FIR will accommodate experiments that address needs for advanced life support, power, propulsion, and spacecraft thermal control systems. The FIR can also serve as a platform for experiments that address human health and performance, medical technologies, and biological sciences. The FIR provides a large volume for payload hardware, reconfigurable diagnostics, customizable software, active rack-level vibration isolation, and data acquisition and management in a nearly uniform temperature environment.

Weiland, Karen J.↗

NASA NTRS2005

THE FLUIDS AND COMBUSTION FACILITY: ENABLING THE EXPLORATION OF SPACE

The Fluids and Combustion Facility (FCF) is an International Space Station facility designed to support physical and biological research as well as technology experiments in space. The FCF consists of two racks called the Combustion Integrated Rack (CIR) and the Fluids Integrated Rack (FIR). The capabilities of the CIR and the FIR and plans for their utilization will support the President s vision for space exploration. The CIR will accommodate physical research and technology experiments that address needs in the areas of spacecraft fire prevention, detection and suppression, incineration of solid wastes, and power generation. Initial experiments will provide data to support design decisions for exploration spacecraft. The CIR provides a large sealed chamber in a near-weightless environment. The chamber supports many simulated atmospheres including lunar or Martian environments. The FIR will accommodate experiments that address needs for advanced life support, power, propulsion, and spacecraft thermal control systems. The FIR can also serve as a platform for experiments that address human health and performance, medical technologies, and biological sciences. The FIR provides a large volume for payload hardware, reconfigurable diagnostics, customizable software, active rack-level vibration isolation, and data acquisition and management in a nearly uniform temperature environment.

Weiland, Karen J.↗

NASA NTRS2015

Orion Launch Abort System Performance During Exploration Flight Test 1

The Orion Launch Abort System Office is taking part in flight testing to enable certification that the system is capable of delivering the astronauts aboard the Orion Crew Module to a safe environment during both nominal and abort conditions. Orion is a NASA program, Exploration Flight Test 1 is managed and led by the Orion prime contractor, Lockheed Martin, and launched on a United Launch Alliance Delta IV Heavy rocket. Although the Launch Abort System Office has tested the critical systems to the Launch Abort System jettison event on the ground, the launch environment cannot be replicated completely on Earth. During Exploration Flight Test 1, the Launch Abort System was to verify the function of the jettison motor to separate the Launch Abort System from the crew module so it can continue on with the mission. Exploration Flight Test 1 was successfully flown on December 5, 2014 from Cape Canaveral Air Force Station's Space Launch Complex 37. This was the first flight test of the Launch Abort System preforming Orion nominal flight mission critical objectives. The abort motor and attitude control motors were inert for Exploration Flight Test 1, since the mission did not require abort capabilities. Exploration Flight Test 1 provides critical data that enable engineering to improve Orion's design and reduce risk for the astronauts it will protect as NASA continues to move forward on its human journey to Mars. The Exploration Flight Test 1 separation event occurred at six minutes and twenty seconds after liftoff. The separation of the Launch Abort System jettison occurs once Orion is safely through the most dynamic portion of the launch. This paper will present a brief overview of the objectives of the Launch Abort System during a nominal Orion flight. Secondly, the paper will present the performance of the Launch Abort System at it fulfilled those objectives. The lessons learned from Exploration Flight Test 1 and the other Flight Test Vehicles will certainly contribute to the vehicle architecture of a human-rated space launch vehicle.

McCauley, Rachel↗

NASA NTRS2019

Evolving HPC and Application Design Toward a Coupled Data Assimilation System at NASA Suitable for Emerging Exascale Platforms

The prediction capabilities of global models have continuously evolved from the traditional medium-range global weather prediction application to span scales in support of hourly prediction of convective scale storms to seasonal Earth system prediction. This evolution has increased the demands on the system infrastructure design and workflow to achieve the required performance on modern high-performance computing (HPC) platforms. The planned evolution of the Goddard Earth Observing System (GEOS) modeling and assimilation system will stress the capabilities of conventional HPC overwhelming the available compute cycles at the NASA Center for Climate Simulation (NCCS) at the NASA Goddard Space Flight Center in the coming 5-10 years. This has led to the re-design of key elements of the assimilation and modeling systems to achieve significant gains in performance on anticipated Exacale platforms. The transition of the assimilation system to the Joint Effort for Data assimilation Integration (JEDI) framework has positioned GEOS to exploit new efficient algorithms for data assimilation (DA) in a fully-coupled Earth system context. The suitability of the GEOS model to leverage a domain specific language (DSL) approach and artificial intelligence (AI) is being explored to accelerate computational performance and data exchange efficiency of the coupled Earth system model. The storage and processing of large data volumes produced by these advance systems is being redesigned with a data-centric cloud-based approach. We will highlight the recent efforts in these areas and emphasize the demand for further development and re-design to achieve the science objectives in support of NASA's Earth system modeling and assimilation missions.

Putman, Bill↗

NASA NTRS1990

Vehicle processing operations database

The Vehicle Processing Operations Data base (VPOD) has been designed and constructed to enable the collection and preliminary analysis of data relative to the processing of planetary exploration vehicles in low Earth orbit. VPOD has the capability to hierarchically store the events, assemblies, and equipment data needed for performing vehicle processing analysis, to whatever level of detail available. This permits some analysis to be performed even during the very early phases of vehicle and mission design. As more data about the events, assemblies, or equipment become available, the analysis can then be refined using the increased level of detail. VPOD output is based on a mission defined by selecting from the VPOD Events data base the events that are required to perform the desired tasks. The outputs available include total crew time, crew skill requirements, equipment needed, assemblies worked per event, to any available level of detail. The VPOD design is structured to interface with an operations simulation capability which is currently in the requirements definition phase. The simulator will use information from the VPOD to perform operations analysis for missions being conducted in low Earth orbit. VPOD information, along with information from the science missions operations data base and a Space Station configuration data base, will be used by the simulator to provide a capability to study total system operations and resources requirements.

Ganoe, George G.↗

NASA NTRS2002

Laboratory Astrophysics White Paper: Summary of Laboratory Astrophysics Needs

The NASA Laboratory Astrophysics Workshop (NASA LAW) met at NASA Ames Research Center from 1-3 May 2002 to assess the role that laboratory astrophysics plays in the optimization of NASA missions, both at the science conception level and at the science return level. Space missions provide understanding of fundamental questions regarding the origin and evolution of galaxies, stars, and planetary systems. In all of these areas the interpretation of results from NASA's space missions relies crucially upon data obtained from the laboratory. We stress that Laboratory Astrophysics is important not only in the interpretation of data, but also in the design and planning of future missions. We recognize a symbiosis between missions to explore the universe and the underlying basic data needed to interpret the data from those missions. In the following we provide a summary of the consensus results from our Workshop, starting with general programmatic findings and followed by a list of more specific scientific areas that need attention. We stress that this is a 'living document' and that these lists are subject to change as new missions or new areas of research rise to the fore.

Source record↗

NASA NTRS2011

Provenance Challenges for Earth Science Dataset Publication

Modern science is increasingly dependent on computational analysis of very large data sets. Organizing, referencing, publishing those data has become a complex problem. Published research that depends on such data often fails to cite the data in sufficient detail to allow an independent scientist to reproduce the original experiments and analyses. This paper explores some of the challenges related to data identification, equivalence and reproducibility in the domain of data intensive scientific processing. It will use the example of Earth Science satellite data, but the challenges also apply to other domains.

Tilmes, Curt↗

NASA NTRS1987

Coadsorption of H2O and CO2 on the Martian surface

The adsorption of both CO2 and H2O was measured, under conditions of temperature and partial pressure similar to Mars, for a variety of absorbents. Both adsorb at coverages that exceed a monolayer at their respective Martian abundances. Clearly, their simultaneous presence in the Martian atmosphere will result in coadsorption of both at concentrations that may differ greatly from those measured during separate measurements. To the best of our knowledge, no data exists on the coadsorption of both gases. Co-adsorption experiments were begun and pertinent results will be reported. In the meantime the predicted behavior of such a system was mathematically explored as a compliment to the data, and to aid in its eventual interpretation.

Zent, A. P.↗

NASA NTRS2011

Onboard Radar Processing Development for Rapid Response Applications

We are developing onboard processor (OBP) technology to streamline data acquisition on-demand and explore the potential of the L-band SAR instrument onboard the proposed DESDynI mission and UAVSAR for rapid response applications. The technology would enable the observation and use of surface change data over rapidly evolving natural hazards, both as an aid to scientific understanding and to provide timely data to agencies responsible for the management and mitigation of natural disasters. We are adapting complex science algorithms for surface water extent to detect flooding, snow/water/ice classification to assist in transportation/ shipping forecasts, and repeat-pass change detection to detect disturbances. We are near completion of the development of a custom FPGA board to meet the specific memory and processing needs of L-band SAR processor algorithms and high speed interfaces to reformat and route raw radar data to/from the FPGA processor board. We have also developed a high fidelity Matlab model of the SAR processor that is modularized and parameterized for ease to prototype various SAR processor algorithms targeted for the FPGA. We will be testing the OBP and rapid response algorithms with UAVSAR data to determine the fidelity of the products.

dual polarized data↗

NASA NTRS1999

Strategies and Technologies for In Situ Mineralogical Investigations on Mars

Surface landers on Mars (Viking and Pathfinder) have not revealed satisfying answers to the mineralogy and lithology of the planet's surface. In part, this results from their prime directives: Viking focused on exobiology, Pathfinder focused on technology demonstration. The analytical instruments on board the landers made admirable attempts to extract the mineralogy and geology of Mars, as did countless modeling efforts after the missions. Here we suggest a framework for elucidating martian, or any other planetary geology, through an approach that defines (a) type of information required, (b) explorational strategy harmonious with acquisition of these data, (c) interpretation approach to the data, (d) compatible mission architecture, (e) instrumentation for interrogating rocks and soil. (a) Data required: The composition of a planet is ordered at scales ranging from molecules to minerals to rocks, and from geological units to provinces to planetary-scale systems. The largest ordering that in situ compositional instruments can attempt to interrogate is rock type "aggregate" information. This is what the geologist attempts to identify first. From this, mineralogy can be either directly seen or inferred. From mineralogy can be determined elemental abundances and perhaps the state of the compounds as being crystalline or amorphous. Knowledge of rock type and mineralogy is critical for elucidating geologic process. Mars landers acquired extremely valuable elemental data, but attempted to move from elements to aggregates, but this can only be done by making many assumptions and sometimes giant leaps of faith. Data we believe essential are elements, minerals, degree of ordering of compounds, and the aggregate or rock type that these materials compose. (b) Explorational strategy: A lander should function as a surrogate geologist. Of the total landscape, a geologist sees much, but gives detailed attention to an infinitesimally small amount of what is seen. To acquire samples worth detailed scrutiny, as many samples as possible need examining at a cursory or reconnaissance level. A representative, statistically-meaningful sample number cannot be overemphasized. This maxim still applies to geological exploration of our own planet of which we have abundant knowledge. Analysis of many samples mandates low-power consumption per sample. (c) Data interpretation: No single instrument can analyze the full spectrum of the x-axis. An instrument is optimized for detecting certain material characteristics and must therefore affix itself to some point on the x-axis. Any conclusions drawn about data to the left or right of the instrument's position on this axis must necessarily be derived by inference. Hence, it seems logical to include on a mission, instruments that are not closely spaced in their x-axis-position, and if only two analytical methods are used, as shown, they should start at opposite ends of the axis and work towards the center. As examples, we depict a high-resolution camera to evaluate rock type ("aggregate" state) and mineralogy, and an x-ray diffractometer-fluorescence spectrometer (XRD-XRF) to determine elements, minerals, and the degree of order of materials. (d) Mission architecture: No instrument or suite of instruments can be relied upon to always give truly unequivocal analyses. The suite of instruments should therefore permit conclusions of one instrument to be checked against those of another through closed analytical loops. These "loops" can be structured by a combination of orbital imagery, descent imagery, broad-band site viewing/analysis, and data that cover both x and y axes. For example, the detection of a basaltic-looking rock with a microscope should be checked against the elements detected, the appearance of the rock as a lava flow from descent imagery, and so forth. (e) Instrumentation: To satisfy the above criteria, it is necessary to: (i) See the rock or soil with high resolution + magnification, (ii) Examine many samples, (iii) Consume little power per analysis, (iv) Determine elemental species, (v) Determine mineralogy directly (not inferentially) and the degree of ordering of compounds, (vi) Start analyzing from both ends of the x-axis. Every geologist wants to see the hand sample first, and apply a hand lens to its surface. This has not been the starting point for missions to Mars. Thus, our technology satisfies all these criteria . This XRD-XRF-Optical instrument currently being developed, analyses rock or soil surfaces without the need for sample acquisition or preparation; this satisfies the power criterion, and enables many analyses. The device acquires direct mineralogy and determines elemental species. The embedded endoscopic camera satisfies the critical criterion of close inspection of samples; the fiber optic cable can also be used for IR, LTV, or laser sample analysis. Additional information is contained in the original (Figures).

Marshall, J. R.↗

NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform with Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera, Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗

NASA NTRS1986

Magnetospheric particle injection and the upstream ion event of September 5, 1984

Energetic particle data from the AMPTE Charge Composition Explorer (CCE) spacecraft in the outer dayside magnetosphere are examined during the period of an upstream ion event observed by the AMPTE Ion Release Module (IRM) spacecraft on September 5, 1984. The CCE data reveal the following: (1) an ion enhancement was observed at about 0040 UT in near coincidence with a substorm onset at about 0035 UT, approximately 15 minutes prior to the onset of the event upstream of the shock; (b) ions of both solar-wind - H(2+) Fe-group - and ionospheric O(+) - origin over a broad energy range (about 20 keV to greater than 1350 keV) were injected at substorm onset; (3) the time evolution of the H(+), He(2+), and O(+) pitch angle distributions markedly differed, with O(+) exhibiting mostly enhancements at off-90-deg angles for the first hour after injection; (4) an enhancement in the Fe-group ions inside the magnetosphere at L = about 6.4 occurred simultaneously with the appearance of an O(+) burst upstream of the shock. The CCE observations, taken together with the simultaneously observed IRM ion event, suggest that a plausible explanation for the appearance of upstream ions is leakage from the magnetosphere into the upstream region, rather than the alternative explanation which requires in situ acceleration of solar wind ions via the Fermi Mechanims.

Krimigis, S. M.↗

NASA NTRS2002

Monitoring Global Precipitation Using Satellite Observations: Status and Future

The current status of monitoring global precipitation amounts and patterns is described using data sets from the Global Precipitation Climatology Project (GPCP) of the World Climate Research Program (WCRP) and from recent research satellites, especially the Tropical Rainfall Measuring Mission (TRMM). The GPCP monthly (and pentad) data set is a 23-year, globally complete precipitation analysis that is used to explore global and regional variations and trends. The data set is a blend of data mainly from low-orbit microwave satellites and geosynchronous infrared satellites, with additional input from satellite sounder data, Outgoing Longwave Radiation (OLR) data and raingauges. The monthly GPCP data set shows no significant global trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the 23-year data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the 23-year period. This apparent trend may be a short-term variation, but also might be related to the increase with time of extreme precipitation events reported elsewhere. Patterns of precipitation variation related to ENSO and other phenomena are shown with clear signals extending from the Tropics into middle and high latitudes of both hemispheres. Also shown, as an example of higher time resolution data is the GPCP daily analysis, which is available for the last six years. A second focus of the talk is on TRMM precipitation data and how these newer data sets incorporating information from the first space-borne meteorological radar compare with the established GPCP data sets.

Adler, Robert F.↗

NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform With Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks [1]. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration [2]. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera [3], Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) [5] is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools [5, 7]. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool [8]. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers [5,6]. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗

NASA NTRS1991

Thermal design, testing, and analysis of the Cosmic Background Explorer's external calibrator

The thermal design of a calibrator used to correlate the collected data with an absolute reference onboard of the Cosmic Background Explorer is considered. Since flight conditions could not be simulated in ground testing, the design was qualified by analysis and testing. The requirements imposed on the calibrator are outlined, along with spacecraft hardware modifications aimed at reducing the thermal load on the calibrator. A geometric mathematical model created in order to obtain view factors from the cryogenic instruments to the spacecraft and dewar is discussed. It is shown that the calibrator met or exceeded all of its performance requirements, and that the modifications to such energy sources as the thermal shield and differential microwave radiometers proved effective in reducing the radiative energy the calibrator received from the spacecraft to acceptable levels.

Mosier, Carol L.↗

NASA NTRSDate not supplied

Kinematic Sensors Evaluation for Spaceflight Exercise Data Collections

INTRODUCTION: On the International Space Station (ISS), exercise feedback from astronauts is very important to diagnose and mitigate any form-related injuries and ensure efficacious exercise prescriptions and systems. Going forward, exploration exercise efforts seek to gain further quantitative data of human and system performance. Currently, methods of collecting in-flight exercise data on the ISS are limited to marker-based motion capture (MoCap) where astronauts must wear reflective markers over their clothes and specialized cameras are used. The main objective of this work was to investigate the following alternative tracking options: markerless video-based MoCap and inertial measurement units (IMUs). These were compared against traditional marker-based MoCap to evaluate kinematic accuracy and inform feasible methods for future exercise data collections on the ISS, especially in support of future Vibration Isolation and Stabilization (VIS) system development. METHODS: Three test subjects performed a variety of flight-like resistance and aerobic exercises using the Miniature Exercise Device (MED-2), Concept-2 rowing ergometer, barbell mockup, bench (e.g., for bench press, hip thruster, and cycling), and a custom structure for dips. These were intended also to represent exercises which could be performed on the multi-modality European Enhanced Exploration Exercise Device (E4D) [1]. The marker-based MoCap data, collected through a 16-camera OptiTrack MoCap system, was regarded as the gold standard to compare the data against. Passive markers were affixed to each subject according to a modified full body Plug-in Gait marker set [2] with 46 total markers. The markerless MoCap data was collected using two GoPro Hero7 cameras and one GoPro Hero11 camera. For the IMU data, a full body set of 17 Xsens DOTs were placed on the subject: 10 upper body and 7 lower body IMUs. Biomechanical modeling and evaluation was conducted through OpenSim [3] (MoCap), OpenSense [4] (IMU), OpenCap [5] (markerless), ENABLE [6] (markerless), and other modeling software. Secondary objectives included comparing the volume of equipment, reducing mass and crew set-up time. RESULTS AND DISCUSSION: While there were issues with initial processing for the IMUs and markerless MoCap, the results aided in the understanding of each sensor, developing end-to-end processes, and identifying future needs. Some observed concerns with the markerless MoCap approaches included being cognizant of a cluttered background, number of people in field of view, camera number and placement. Some challenges with the IMUs included possible sliding, early deactivation possibly due to exercise pose, and large quantity sensor synchronization. Overall, the markerless MoCap option may be the preferred method of data collection and processing as it provides a solution for certain IMU shortcomings and may be least in equipment volume, upmass, and crew setup time. CONCLUSIONS: While this work was mainly focused on ISS data collection, these sensor data along with continued evaluation and development efforts will help to establish best methods for exercise data collection on Gateway, for other Artemis missions, and beyond. Details on the latest end-to-end processing of the data and results will be presented, along with lessons learned and recommended sensor selection and methods.

S. Faragalla↗

NASA NTRS2024

Kinematic Sensors Evaluation for Spaceflight Exercise Data Collections

S Faragalla↗

NASA NTRSDate not supplied

Digital Lunar Exploration Sites (DLES)

After an almost 50-year absence, NASA along with a group of international and commercial partners will return humans to the surface of the Moon as part of the Artemis program. As with the preceding Apollo program, modeling and simulation (M&S) will be an enabling technology for achieving the Artemis mission objectives. Fortunately, M&S has advanced considerably in the past half century, permitting much more detailed and encompassing integrated representations of the Artemis systems. One modeling area of critical importance to simulating the Artemis elements and mission activities is the accurate and efficient modeling of the operational lunar environment. This is particularly challenging since the Artemis program is considering exploration sites in the area of the Lunar South Pole (LSP), far away from any previous surface exploration sites. Fortunately, we now have considerably more and better data from recent lunar sensing missions. A planetary science team and a human exploration simulation team at NASA’s Johnson Space Center are developing a suite of products called the Digital Lunar Exploration Sites (DLES). DLES is intended to provide some of the necessary lunar environmental data products. This paper describes the fundamental need for DLES, the science data sets that are going into DLES, some of the processes used to integrate this data into DLES products, the basic products that constitute DLES, and some examples of DLES in use.

DLES↗