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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 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 NTRS2000

TRMM Surface Backscatter Measurements - Temporal and Spatial Analysis: Inter-Comparison with NSCAT

Global rainfall is the primary redistributor of earth's energy by the process of latent heat release. This forms the main driving force for the tropical circulation, which in turn impacts the global circulation .through transient events-such as El Nino. Hence, more precise and long-term time series of the rainfall and its variability is crucial to the understanding and prediction of the global climate and climate change. The Precipitation Radar (PR) abroad the US/Japan Tropical Rainfall Measuring Mission (TRMM) is the first radar ever launched into space that measures detailed vertical profiles of rain intensity over the tropics. One of the challenges in estimating rainfall from spaceborne radars is the presence of attenuation at frequencies, such as 14 GHz of the TRMM PR and future planned systems at this and higher frequencies. A common approach in current rainfall retrieval algorithms is to employed the path integrated attenuation (PIA) as a constraint to the retrieval, and hence overcome errors in the radar calibration or in the assumed rainfall parameters. PIA can either be derived from a radiometer or from the surface reference technique, in which a clear air radar measurement is compared with the measurement in the raining area. The current TRMM 2A21 PIA data product makes use of both a temporal and spatial clear air database for comparison to rainy measurements. In this paper we present results from analysis of TRMM surface backscatter cross-section (sigmaO) measurements from Nov 97-Feb99, and a comparison with sigmaO measurements obtained by the NASA Scatterometer (NSCAT) between Sept96-June97. Measurements for a given month from both instruments are compiled on a 1 deg. (lat.) x 1 deg. (lon.) x 1 hr. grid. This enables TRMM--NSCAT comparison and the investigation of seasonal and diurnal trends in both data sets. From preliminary analysis of TRMM sigmaO's we have decided not to treat the ocean as a single homogeneous region but to select a number of ocean sub-regions and individually analyze their trends. Likewise, and in a similar approach to previous studies of Seasat over-land data, we have selected a number of over-land regions for study. From said sigmaO maps and regional trend analysis we investigate possible sources of trends and variability. In addition, we study the effects of TRMM PR sensitivity through the PR "possible rain" class. Given NSCAT's inability to flag rain contaminated measurements we are able to gauge the impact of rain contamination on NSCAT monthly sigmaO maps, using TRMM measurements. The research described in this paper was carried out by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (NASA), U.S.A.

Im, Eastwood↗
NASA NTRS2000

Lidar Technology at the Goddard Laser and Electro-Optics Branch

The Laser and Electro-Optics Branch at Goddard Space flight Center was established about three years ago to provide a focused center of engineering support and technology development in these disciplines with an emphasis on spaced based instruments for Earth and Space Science. The Branch has approximately 15 engineers and technicians with backgrounds in physics, optics, and electrical engineering. Members of the Branch are currently supporting a number of space based lidar efforts as well as several technology efforts aimed at enabling future missions. The largest effort within the Branch is support of the Ice, Cloud, and land Elevation Satellite (ICESAT) carrying the Geoscience Laser Altimeter System (GLAS) instrument. The ICESAT/GLAS primary science objectives are: 1) To determine the mass balance of the polar ice sheets and their contributions to global sea level change; and 2) To obtain essential data for prediction of future changes in ice volume and sea-level. The secondary science objectives are: 1) To measure cloud heights and the vertical structure of clouds and aerosols in the atmosphere; 2) To map the topography of land surfaces; and 3) To measure roughness, reflectivity, vegetation heights, snow-cover, and sea-ice surface characteristics. Our efforts have concentrated on the GLAS receiver component development, the Laser Reference Sensor for the Stellar Reference System, the GLAS fiber optics subsystems, and the prelaunch calibration facilities. We will report on our efforts in the development of the space qualified interference filter [Allan], etalon filter, photon counting detectors, etalor/laser tracking system, and instrument fiber optics, as well as specification and selection of the star tracker and development of the calibration test bed. We are also engaged in development work on lidar sounders for chemical species. We are developing new lidar technology to enable a new class of miniature lidar instruments that are compatible with small Discovery-class orbiters now in the NASA planetary program. The purpose of the lidar is to continuously profile the water vapor and dust in the Mars atmosphere from orbit in order to quantify its dynamics, their relationship in the diurnal cycles, and to infer water vapor exchange with the Mars surface. To remotely measure the water-vapor height profiles, we will use the differential absorption lidar (DIAL) technique. We are also developing a laser sensor for measuring the total column content of CO2 in the atmosphere of the earth. CO2 is the principal greenhouse gas and has increased by roughly 80 ppm in the last century and a half. We will report our efforts in the development of the laser transmitter and photon counting detector components for a Mars Orbiting DIAL system and for the CO2 sounder.

Heaps, William S.↗
NASA NTRS2022

A Unifying View of Estimation and Control Using Belief Propagation With Application to Path Planning

The use of estimation techniques on stochastic models to solve control problems is an emerging paradigm that falls under the rubric of Active Inference (AI) and Control as Inference (CAI). In this work, we use probability propagation on factor graphs to show that various algorithms proposed in the literature can be seen as specific composition rules in a factor graph. We show how this unified approach, presented both in probability space and in log of the probability space, provides a very general framework that includes the Sum-product, the Max-product, Dynamic programming and mixed Reward/Entropy criteria-based algorithms. The framework also expands algorithmic design options that lead to new smoother or sharper policy distributions. We propose original recursions such as: a generalized Sum/Max-product algorithm, a Smooth Dynamic programming algorithm and a modified versions of the Reward/Entropy algorithm. The discussion is carried over with reference to a path planning problem where the recursions that arise from various cost functions, although they may appear similar in scope, bear noticeable differences. We provide a comprehensive table of composition rules and a comparison through simulations, first on a synthetic small grid with a single goal with obstacles, and then on a grid extrapolated from a real-world scene with multiple goals and a semantic map.

Francesco A. N. Palmieri↗
NASA NTRS1995

A simple method for verifying the deployment of the TOMS-EP solar arrays

The Total Ozone Mapping Spectrometer-Earth Probe (TOMS-EP) mission relies upon a successful deployment of the spacecraft's solar arrays. Several methods of verification are being employed to ascertain the solar array deployment status, with each requiring differing amounts of data. This paper describes a robust attitude-independent verification method that utilizes telemetry from the coarse Sun sensors (CSS's) and the three-axis magnetometers (TAM's) to determine the solar array deployment status - and it can do so with only a few, not necessarily contiguous, points of data. The method developed assumes that the solar arrays are deployed. Telemetry data from the CSS and TAM are converted to the Sun and magnetic field vectors in spacecraft body coordinates, and the angle between them is calculated. Deployment is indicated if this angle is within a certain error tolerance of the angle between the reference Sun and magnetic field vectors. Although several other methods can indicate a non-deployed state, with this method there is a 70% confidence level in confirming deployment as well as a nearly 100% certainty in confirming a non-deployed state. In addition, the spacecraft attitude (which is not known during the first orbit after launch) is not needed for this algorithm because the angle between the Sun and magnetic field vectors is independent of the spacecraft attitude. This technique can be applied to any spacecraft with a TAM and with CSS's mounted on the solar array(s).

Koppersmith, James R.↗
NASA NTRS2005

Simultaneous Conoscopic Holography and Raman Spectroscopy

A new instrument was developed for chemical characterization of surfaces that combines the analytical power of Raman spectroscopy with the three-dimensional topographic information provided by conoscopic holography. The figure schematically depicts the proposed hybrid instrument. The output of the conoscopic holographic portion of the instrument is a topographical map of the surface; the output of the Raman portion of the instrument is hyperspectral Raman data, from which the chemical and/or biological composition of the surface would be deduced. By virtue of the basic principles of design and operation of the instrument, the hyperspectral image data would be inherently spatially registered with the topographical data. In conoscopic holography, the object and reference beams of classical holography are replaced by the ordinary and extraordinary components generated by a single beam traveling through a birefringent, uniaxial crystal. In the basic conoscopic configuration, a laser light is projected onto a specimen and the resulting illuminated spot becomes a point source of diffuse light that propagates in every direction. The laser beam is rasterscanned in two dimensions (x and y) perpendicular to the beam axis (z), and at each x,y location, the pattern of interference between the ordinary and extraordinary rays is recorded. The recorded interferogram constitutes the conoscopic hologram. Of particular significance for the proposed instrument is that the conoscopic hologram contains information on the z coordinate (height) of the illuminated surface spot. Hence, a topographical map of the specimen is constructed point-by-point by rastering the laser beam in the x and y directions and correlating the x and y coordinates with the z information obtained from the interferograms. Conoscopic imaging is an established method, and conoscopic laboratory instruments for surface metrology are commercially available. In Raman spectroscopy of a surface, one measures the spectrum of laser light scattered inelastically from a laser-illuminated spot on the surface. The wavelengths of the inelastically scattered light differ from that of the incident laser beam by amounts that correspond to the energies of molecular vibrations. The resulting vibrational spectrum can be used to identify the molecules. Raman spectroscopy is a standard laboratory technique for identifying mineralogical, biological, and other specific chemical compositions.

Schramm, Harry F.↗
NASA NTRS1994

A simple suboptimal least-squares algorithm for attitude determination with multiple sensors

Three-axis attitude determination is equivalent to finding a coordinate transformation matrix which transforms a set of reference vectors fixed in inertial space to a set of measurement vectors fixed in the spacecraft. The attitude determination problem can be expressed as a constrained optimization problem. The constraint is that a coordinate transformation matrix must be proper, real, and orthogonal. A transformation matrix can be thought of as optimal in the least-squares sense if it maps the measurement vectors to the reference vectors with minimal 2-norm errors and meets the above constraint. This constrained optimization problem is known as Wahba's problem. Several algorithms which solve Wahba's problem exactly have been developed and used. These algorithms, while steadily improving, are all rather complicated. Furthermore, they involve such numerically unstable or sensitive operations as matrix determinant, matrix adjoint, and Newton-Raphson iterations. This paper describes an algorithm which minimizes Wahba's loss function, but without the constraint. When the constraint is ignored, the problem can be solved by a straightforward, numerically stable least-squares algorithm such as QR decomposition. Even though the algorithm does not explicitly take the constraint into account, it still yields a nearly orthogonal matrix for most practical cases; orthogonality only becomes corrupted when the sensor measurements are very noisy, on the same order of magnitude as the attitude rotations. The algorithm can be simplified if the attitude rotations are small enough so that the approximation sin(theta) approximately equals theta holds. We then compare the computational requirements for several well-known algorithms. For the general large-angle case, the QR least-squares algorithm is competitive with all other know algorithms and faster than most. If attitude rotations are small, the least-squares algorithm can be modified to run faster, and this modified algorithm is faster than all but a similarly specialized version of the QUEST algorithm. We also introduce a novel measurement averaging technique which reduces the n-measurement case to the two measurement case for our particular application, a star tracker and earth sensor mounted on an earth-pointed geosynchronous communications satellite. Using this technique, many n-measurement problems reduce to less than or equal to 3 measurements; this reduces the amount of required calculation without significant degradation in accuracy. Finally, we present the results of some tests which compare the least-squares algorithm with the QUEST and FOAM algorithms in the two-measurement case. For our example case, all three algorithms performed with similar accuracy.

Brozenec, Thomas F.↗
NASA NTRS2022

Lunar Rover Localization Using Craters as Landmarks

Onboard localization capabilities for planetary rovers to date have used relative navigation, by integrating combinations of wheel odometry, visual odometry, and inertial measurements during each drive to track position relative to the start of each drive. At the end of each drive, a “ground-in-the-loop” (GITL) interaction is used to get a position update from human operators in a more global reference frame, such as a map frame defined by orbital reconnaissance imaging of a large region around the rover’s current position. For Mars rovers, this typically has involved downlinking imagery from the rover mast cameras and using interactive visualization tools on Earth to register such images to the orbital reconnaissance images. For safety purposes, rover mission operations typically specify “keep out zones”, which human operators recognize as being unsafe in the orbital images. Autonomous rover drives are limited in distance so that accumulated relative navigation error does not risk the possibility of the rover driving into a keep out zone. The allowable autonomous drive distance in this mode of operation depends on the distribution of keep out zones and the accuracy of relative navigation; in practice, drive limits of a few hundred meters between GITL cycles are to be expected. Several rover mission concepts have recently been studied that require much longer drives between GITL cycles, particularly for the Moon. This includes lunar rover mission concepts that involve (1) driving mostly in sunlight at low latitudes, (2) driving in permanently shadowed regions near the south pole, and (3) a mixture of day and night driving in mid-latitudes. These concepts include total traverse distance requirements of up to 1,800 km in 4 Earth years, with individual drives of several kilometers between stops for downlink. These concepts require greater autonomy to minimize GITL cycles to enable such large range; onboard global localization is a key element of such autonomy. Multiple techniques have been studied in the past for onboard rover global localization, including radio navigation aiding from an orbiter, recognizing horizon landmarks that are known in a regional elevation map, and correlating a local elevation map created onboard the rover with a regional elevation map. These techniques all have drawbacks, including requiring an expensive extra mission element (navigation orbiter), unavailability of sufficient regional elevation map data, or limited accuracy in resulting position estimates (e.g. a few hundred meters with horizon landmarks). For the Moon, the ubiquitous craters offer another possibility, which involves mapping craters from orbit, then recognizing crater landmarks with cameras and/or a lidar onboard the rover. This approach is applicable everywhere on the Moon, does not require high resolution stereo imaging from orbit as some other approaches do, and has potential to enable position knowledge with order of 10 m accuracy at all times. This paper will provide more detail on our technical approach to crater-based lunar rover localization and will present initial results on crater detection using 3-D point cloud data from onboard lidar or stereo cameras and using shading cues in monocular onboard imagery.

Ono, M.↗
NASA NTRS1996

Soot Imaging and Measurement

Soot, sometimes referred to as smoke, is made up primarily of the carbon particles generated by most combustion processes. For example, large quantities of soot can be seen issuing from the exhaust pipes of diesel-powered vehicles. Heated soot also is responsible for the warm orange color of candle flames, though that soot is generally consumed before it can exit the flame. Research has suggested that heavy atmospheric soot concentrations aggravate conditions such as pneumonia and asthma, causing many deaths each year. To understand the formation and oxidation of soot, NASA Lewis Research Center scientists, together with several university investigators, are investigating the properties of soot generated in reduced gravity, where the absence of buoyancy allows more time for the particles to grow. The increased time allows researchers to better study the life cycle of these particles, with the hope that increased understanding will lead to better control strategies. To quantify the amount of soot present in a flame, Lewis scientists developed a unique imaging technique that provides quantitative and qualitative soot data over a large field of view. There is significant improvement over the single-point methods normally used. The technique is shown in the sketch, where light from a laser is expanded with a microscope objective, rendered parallel, and passed through a flame where soot particles reduce the amount of light transmitted to the camera. A filter only allows light at the wavelength of the laser to pass to the camera, preventing any extraneous signals. When images of the laser light with and without the flame are compared, a quantitative map of the soot concentration is produced. In addition to that data, a qualitative image of the soot in the flame is also generated, an example of which is displayed in the photo. This technique has the potential to be adapted to real-time process control in industrial powerplants.

Source record↗
NASA NTRS2017

Measuring Shock Stage of ltokawa Regolith Grains by Electron Back-Scattered Diffraction and Synchrotron X-Ray Diffraction

We have been analyzing Itokawa samples in order to definitively establish the degree of shock experienced by the regolith of asteroid Itokawa, and to devise a bridge between shock determinations by standard light optical petrography, crystal structures as determined by electron and X-ray diffraction techniques. We are making measurements of olivine crystal structures and using these to elucidate critical regolith impact processes. We use electron back-scattered diffraction (EBSD) and synchrotron X-ray diffraction (SXRD). We are comparing the Itokawa samples to L and LL chondrite meteorites chosen to span the shock scale experienced by Itokawa, specifically Chainpur (LL3.4, Shock Stage 1), Semarkona (LL3.00, S2), Kilabo (LL6, S3), NWA100 (L6, S4) and Chelyabinsk (LL5, S4). In SXRD we measure the line broadening of olivine reflections as a measure of shock stage. In this presentation we concentrate on the EBSD work. We employed JSC's Supra 55 variable pressure FEG-SEM and Bruker EBSD system. We are not seeking actual strain values, but rather indirect strain-related measurements such as extent of intra-grain lattice rotation, and determining whether shock state "standards" (meteorite samples of accepted shock state, and appropriate small grain size) show strain measurements that may be statistically differentiated, using a sampling of particles (number and size range) typical of asteroid regoliths. Using our system we determined that a column pressure of 9 Pa and no C-coating on the sample was optimal. We varied camera exposure time and gain to optimize mapping performance, concluding that 320x240 pattern pixilation, frame averaging of 3, 15 kV, and low extractor voltage yielded an acceptable balance of hit rate (>90%), speed (11 fps) and map quality using an exposure time of 30 ms (gain 650). We found that there was no strong effect of step size on Grain Orientation Spread (GOS) and Grain Reference Orientation Deviation angle (GROD-a) distribution; there was some effect on grain average Kernel Average Misorientation (KAM) (reduced with smaller step size for the same grain), as expected. We monitored GOS, Maximum Orientation Spread (MOS) and GROD-a differences between whole olivine grains and sub-sampled areas, and found that there were significant differences between the whole grain dataset and subsets, as well as between subsets, likely due to sampling-related "noise". Also, in general (and logically) whole grains exhibit greater degrees of cumulative lattice rotation. Sampling size affects the apparent strain character of the grain, at least as measured by GOS, MOS and GROD-a. There were differences in the distribution frequencies of GOS and MOS between shock stages, and in plots of MOS and GOS vs. grain diameter. These results are generally consistent with those reported this year. However, it is unknown whether the differences between samples of different shock states exceeds the clustering of these values to the extent that shock stage determinations can still be made with confidence. We are investigating this by examination of meteorites with higher shock stage 4 to 5. Our research will improve our understanding of how small, primitive solar system bodies formed and evolved, and improve understanding of the processes that determine the history and future of habitability of environments on other solar system bodies. The results will directly enrich the ongoing asteroid and comet exploration missions by NASA and JAXA, and broaden our understanding of the origin and evolution of small bodies in the early solar system, and elucidate the nature of asteroid and comet regolith.

Zolensky, Michael↗
NASA NTRSDate not supplied

Wildfire Segmentation From Remotely Sensed Data Using Quantum-Compatible Conditional Vector Quantized-Variational Autoencoders

Wildfires represent a critical environmental hazard with multifaceted implications for ecosystems, communities, and public health [1]. The escalating frequency and intensity of wildfires globally have intensified the urgency for robust segmentation methodologies to facilitate effective mitigation, response, and recovery strategies [2]. Accurate wildfire segmentation is pivotal for delineating fire boundaries, assessing progression patterns, and prioritizing resource allocation during emergency scenarios. Furthermore, precise segmentation enables stakeholders, including policymakers, environmental scientists, and emergency responders, to formulate evidence-based strategies, thereby minimizing socio-economic disruptions and ecological degradation. Consequently, advancing wildfire segmentation techniques through innovative technological interventions remains a paramount research imperative. Although foundational in wildfire segmentation, traditional deterministic models exhibit inherent limitations that compromise their efficacy in dynamic and uncertain environments. These models often operate on rigid algorithms prioritizing deterministic classifications, thereby overlooking the inherent complexities and uncertainties associated with wildfire behavior and satellite data variability. Such deterministic frameworks tend to produce oversimplified representations that fail to capture the intricate nuances of evolving fire dynamics, spatial heterogeneity, and environmental interactions [1]. Consequently, the deterministic approach’s propensity for uncertainty collapsing [1, 3] hampers the accuracy, reliability, and applicability of segmentation outcomes in real-world scenarios. Contrastingly, stochastic models offer a more nuanced and adaptable framework for wildfire segmentation. By integrating probabilistic elements into the modeling paradigm, stochastic approaches, particularly probabilistic approaches such as variational auto encoders (VAEs) [4], facilitate comprehensive uncertainty assessment, enabling researchers to quantify and incorporate uncertainties into segmentation outcomes effectively. This probabilistic nature empowers stochastic models to encapsulate variability, account for data inconsistencies, and adapt to evolving environmental conditions, enhancing segmentation accuracy, reliability, and robustness. Embracing stochastic methodologies thus catalyzes advancements in wildfire science by fostering a more holistic, adaptive, and resilient segmentation framework. Despite VAEs demonstrating significant promise in various applications, they come with inherent limitations that have garnered attention within the machine learning community. One of the primary drawbacks lies in their reliance on static priors, which essentially assume a fixed distribution for latent variables, thereby limiting the model’s flexibility to capture complex data structures effectively [5]. This static nature leads to suboptimal representations, especially when dealing with complex and high-dimensional data. Additionally, VAEs often struggle with generating sharp and realistic samples, a phenomenon commonly referred to as mode collapse [5, 7, 6]. Furthermore, the optimization process in VAEs, which involves balancing the reconstruction loss and the regularization term, can sometimes be challenging to fine-tune [7]. In recent efforts to address these shortcomings, alternative approaches like Vector Quantized Variational Auto encoders(VQ-VAEs) [7], address the challenges by incorporating discrete latent variables and leveraging techniques that enhance the quality and diversity of generated samples while maintaining efficient training dynamics. VQ-VAEs propose a dynamic prior distribution generation mechanism that diverges from the static priors commonly associated with traditional VAEs. This dynamic approach allows for more adaptive and context-aware latent variable representations, thereby potentially capturing complex data structures more effectively. Unlike autoregressive prior models such as PixelCNN, which, despite their ability to model dependencies across data dimensions, suffer from significant computational inefficiencies and lack flexibility in handling diverse datasets. In our work, we propose to use a generative quantum-compatible approach to help alleviate the shortcomings of autoregressive prior model in VQ-VAEs. Restricted Boltzmann Machines (RBMs) are a viable alternative prior model that can learn prior distributions in a faster and more flexible manner. In this research endeavor, we meticulously curate a state-of-the-art dataset leveraging satellite MODIS data in conjunction with VIIRS fire masks, derived from Fire Radiative Power (FRP), thereby encapsulating diverse wildfire scenarios and environmental contexts. We developed a conditional VQ-VAE architecture with the RBM prior model that is trained in a supervised manner for segmenting wildfire masks. This innovative approach synergistically harnesses deep learning capabilities, enabling the generation of segmentation maps characterized by heightened precision, granularity, and contextual relevance. Furthermore, replacing the autoregressive prior learning method proposed by the original VQ-VAE with a prior density approximation via quantum-compatible RBM facilitates expedited inference processes, augments flexibility in prior sampling, optimizes computational efficiency and establishes a groundbreaking benchmark in wildfire segmentation methodologies.

quantum machine learning↗
NASA NTRS2016

Optical Modeling and Polarization Calibration for CMB Measurements with Actpol and Advanced Actpol

The Atacama Cosmology Telescope Polarimeter (ACTPol) is a polarization sensitive upgrade to the Atacama Cosmology Telescope, located at an elevation of 5190 m on Cerro Toco in Chile. ACTPol uses transition edge sensor bolometers coupled to orthomode transducers to measure both the temperature and polarization of the Cosmic Microwave Background (CMB). Calibration of the detector angles is a critical step in producing polarization maps of the CMB. Polarization angle offsets in the detector calibration can cause leakage in polarization from E to B modes and induce a spurious signal in the EB and TB cross correlations, which eliminates our ability to measure potential cosmological sources of EB and TB signals, such as cosmic birefringence. We calibrate the ACTPol detector angles by ray tracing the designed detector angle through the entire optical chain to determine the projection of each detector angle on the sky. The distribution of calibrated detector polarization angles are consistent with a global offset angle from zero when compared to the EB-nulling offset angle, the angle required to null the EB cross-correlation power spectrum. We present the optical modeling process. The detector angles can be cross checked through observations of known polarized sources, whether this be a galactic source or a laboratory reference standard. To cross check the ACTPol detector angles, we use a thin film polarization grid placed in front of the receiver of the telescope, between the receiver and the secondary reflector. Making use of a rapidly rotating half-wave plate (HWP) mount we spin the polarizing grid at a constant speed, polarizing and rotating the incoming atmospheric signal. The resulting sinusoidal signal is used to determine the detector angles. The optical modeling calibration was shown to be consistent with a global offset angle of zero when compared to EB nulling in the first ACTPol results and will continue to be a part of our calibration implementation. The first array of detectors for Advanced ACTPol, the next generation upgrade to ACTPol, will be deployed in 2016.We plan to continue using both techniques and compare them to astrophysical source measurements for the Advanced ACTPol polarization calibration.

Koopman, Brian↗
NASA NTRS2007

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

This report details one of three experiments performed during FY 2007 for the NASA RPC (Rapid Prototyping Capability) at Stennis Space Center. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria dispar). The intent of the RPC experiment was to assess the degree to which VIIRS data can provide forest disturbance monitoring information as an input to a forest threat EWS (Early Warning System) as compared to the level of information that can be obtained from MODIS data. The USDA Forest Service (USFS) plans to use MODIS products for generating broad-scaled, regional monitoring products as input to an EWS for forest health threat assessment. NASA SSC is helping the USFS to evaluate and integrate currently available satellite remote sensing technologies and data products for the EWS, including the use of MODIS products for regional monitoring of forest disturbance. Gypsy moth defoliation of the mid-Appalachian highland region was selected as a case study. Gypsy moth is one of eight major forest insect threats listed in the Healthy Forest Restoration Act (HFRA) of 2003; the gypsy moth threatens eastern U.S. hardwood forests, which are also a concern highlighted in the HFRA of 2003. This region was selected for the project because extensive gypsy moth defoliation occurred there over multiple years during the MODIS operational period. This RPC experiment is relevant to several nationally important mapping applications, including agricultural efficiency, coastal management, ecological forecasting, disaster management, and carbon management. In this experiment, MODIS data and VIIRS data simulated from MODIS were assessed for their ability to contribute broad, regional geospatial information on gypsy moth defoliation. Landsat and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data were used to assess the quality of gypsy moth defoliation mapping products derived from MODIS data and from simulated VIIRS data. The project focused on use of data from MODIS Terra as opposed to MODIS Aqua mainly because only MODIS Terra data was collected during 2000 and 2001-years with comparatively high amounts of gypsy moth defoliation within the study area. The project assessed the quality of VIIRS data simulation products. Hyperion data was employed to assess the quality of MODIS-based VIIRS simulation datasets using image correlation analysis techniques. The ART (Application Research Toolbox) software was used for data simulation. Correlation analysis between MODIS-simulated VIIRS data and Hyperion-simulated VIIRS data for red, NIR (near-infrared), and NDVI (Normalized Difference Vegetation Index) image data products collectively indicate that useful, effective VIIRS simulations can be produced using Hyperion and MODIS data sources. The r(exp 2) for red, NIR, and NDVI products were 0.56, 0.63, and 0.62, respectively, indicating a moderately high correlation between the 2 data sources. Temporal decorrelation from different data acquisition times and image misregistration may have lowered correlation results. The RPC experiment also generated MODIS-based time series data products using the TSPT (Time Series Product Tool) software. Time series of simulated VIIRS NDVI products were produced at approximately 400-meter resolution GSD (Ground Sampling Distance) at nadir for comparison to MODIS NDVI products at either 250- or 500-meter GSD. The project also computed MODIS (MOD02) NDMI (Normalized Difference Moisture Index) products at 500-meter GSD for comparison to NDVI-based products. For each year during 2000-2006, MODIS and VIIRS (simulated from MOD02) time series were computed during the peak gypsy moth defoliation time frame in the study area (approximately June 10 through July 27). Gypsy moth defoliation mapping products from simated VIIRS and MOD02 time series were produced using multiple methods, including image classification and change detection via image differencing. The latter enabled an automated defoliation detection product computed using percent change in maximum NDVI for a peak defoliation period during 2001 compared to maximum NDVI across the entire 2000-2006 time frame. Final gypsy moth defoliation mapping products were assessed for accuracy using randomly sampled locations found on available geospatial reference data (Landsat and ASTER data in conjunction with defoliation map data from the USFS). Extensive gypsy moth defoliation patches were evident on screen displays of multitemporal color composites derived from MODIS data and from simulated VIIRS vegetation index data. Such defoliation was particularly evident for 2001, although widespread denuded forests were also seen for 2000 and 2003. These visualizations were validated using aforementioned reference data. Defoliation patches were visible on displays of MODIS-based NDVI and NDMI data. The viewing of apparent defoliation patches on all of these products necessitated adoption of a specialized temporal data processing method (e.g., maximum NDVI during the peak defoliation time frame). The frequency of cloud cover necessitated this approach. Multitemporal simulated VIIRS and MODIS Terra data both produced effective general classifications of defoliated forest versus other land cover. For 2001, the MOD02-simulated VIIRS 400-meter NDVI classification produced a similar yet slightly lower overall accuracy (87.28 percent with 0.72 Kappa) than the MOD02 250-meter NDVI classification (88.44 percent with 0.75 Kappa). The MOD13 250-meter NDVI classification had a lower overall accuracy (79.13 percent) and a much lower Kappa (0.46). The report discusses accuracy assessment results in much more detail, comparing overall classification and individual class accuracy statistics for simulated VIIRS 400-meter NDVI, MOD02 250-meter NDVI, MOD02-500 meter NDVI, MOD13 250-meter NDVI, and MOD02 500-meter NDMI classifications. Automated defoliation detection products from simulated VIIRS and MOD02 data for 2001 also yielded similar, relatively high overall classification accuracy (85.55 percent for the VIIRS 400-meter NDVI versus 87.28 percent for the MOD02 250-meter NDVI). In contrast, the USFS aerial sketch map of gypsy moth defoliation showed a lower overall classification accuracy at 73.64 percent. The overall classification Kappa values were also similar for the VIIRS (approximately 0.67 Kappa) versus the MOD02 (approximately 0.72 Kappa) automated defoliation detection product, which were much higher than the values exhibited by the USFS sketch map product (overall Kappa of approximately 0.47). The report provides additional details on the accuracy of automated gypsy moth defoliation detection products compared with USFS sketch maps. The results suggest that VIIRS data can be effectively simulated from MODIS data and that VIIRS data will produce gypsy moth defoliation mapping products that are similar to MODIS-based products. The results of the RPC experiment indicate that VIIRS and MODIS data products have good potential for integration into the forest threat EWS. The accuracy assessment was performed only for 2001 because of time constraints and a relative scarcity of cloud-free Landsat and ASTER data for the peak defoliation period of the other years in the 2000-2006 time series. Additional work should be performed to assess the accuracy of gypsy moth defoliation detection products for additional years.The study area (mid-Appalachian highlands) and application (gypsy moth forest defoliation) are not necessarily representative of all forested regions and of all forest threat disturbance agents. Additional work should be performed on other inland and coastal regions as well as for other major forest threats.

Spruce, Joseph P.↗
NASA NTRSDate not supplied

Applicability of Micro X-Ray Fluorescence Spectroscopy to Astromaterials Curation and Research

Introduction: The Astromaterials Acquisition and Curation Office at NASA’s Johnson Space Center (JSC) curates NASA’s astromaterial sample collections which includes: Apollo samples, Luna samples, Ant-arctic meteorites, cosmic dust particles, microparticle impacts into space-flown materials, Genesis solar wind atoms, Stardust comet Wild-2 particles, Stardust inter-stellar particles, Hayabusa asteroid Itokawa particles, Hayabusa 2 asteroid Ryugu particles, and future OSIRIS-Rex asteroid Bennu particles (landing in Sep-tember, 2023) [1–3]. To enhance JSC’s advanced cu-ration capabilities, we have recently installed a high-performance micro-X-ray fluorescence (µXRF) spec-trometer to assist in sample characterization through rapid, non-destructive, in-situ elemental analyses that do not require the sample preparation protocols (i.e., polishing and carbon-coating) commonly needed for electron beam analyses. With this new instrument, we are capable of detecting all elements down to carbon in a variable-pressure or He-purged chamber for anal-ysis of a wide range of sample types. Here we describe the instrumental set-up, capabilities, and applicability of µXRF analysis to astromaterials curation and re-search. Instrumentation and Methodology: The X-ray fluorescence and computed tomography lab (X-FaCT) lab at JSC is now equipped with a Bruker M4 Tornado Plus µXRF (Fig. 1). This system is an energy-dispersive x-ray spectrometer equipped with two 60 mm2 silicon drift detectors (SDD) that are able to be used simulta-neously for output count rates ~500,000 cps. New light element windows allow detecting and analyzing the entire elemental range from carbon to americium. Two x-ray tubes (micro-focus Rh with polycapillary lenses and W with collimators of 0.5, 1.0, 2.0, and 4.5 mm) with max excitation parameters of 50 kV, 30 W and 50 kV, 40 W, respectively, allow for more flexibility of the analysis of high energy lines. The motorized X-Y-Z stage has a mapping range of 190 x 160 mm and can support samples up to 7 kg (~15.5 lbs) and a height of 120 mm [4]. Analytical modes include elemental analysis (down to ~20 µm spot size) via point, line, or area of bulk materials (rock surfaces, thin sections, thick sections, etc.) as well as coating analysis (determination of thickness and composition) of samples. This system has a variable vacuum chamber (1 mbar to 1 atm) that is also equipped with a He-purge system which accommodates vacuum sensitive samples while still allowing detection of light elements at atmospheric pressure. Utility and Applicability of µXRF in Astro-materials research and exploration science (ARES): Elemental analysis using µXRF is commonly em-ployed for both terrestrial and planetary geological science disciplines [5]. It is especially useful for analy-sis of astromaterials given the limited sample prepara-tion required, which is not feasible for certain materi-als. Here we show select applications of µXRF anal-yses of astromaterials that can, have, and will be done at JSC’s X-FaCT lab. Point analysis: In-situ spot analyses (~20 µm spot size) on a cut slab of Martian meteorite NWA 10922 allowed for the discovery, qualitative elemental analy-sis and determination of different feldspar minerals [6]. These point analyses served as an effective prelim-inary step for subsequent quantitative analyses. Ana-lytical standards can be employed for more accurate quantification of µXRF spot analyses. Area analysis: This analytical mode measures all detectable elements (from C to Am) at each pixel (>5 µm pixel size) in a user-defined area. The results are shown as elemental maps which can be extracted as 16-bit TIFF’s for further data processing. In Fig. 2. we show elemental distribution maps of the high-Ti basalt 73001,531 that have been processed using ImageJ software. From these maps you can accurately and quickly (this map took ~50 mins.) identify mineral components, such as pyroxene, plagioclase, oxides, and phosphates, compositional zoning, and mineral textures. Detection of high-Z phases: µXRF techniques are es-pecially effective at analyzing trace minerals with high-atomic-number (high-Z) elements because the high-energy characteristic X-rays used (relative to SEM EDS) allow for mapping of K lines in elements up to La (typically SEM maps use L X-ray lines for elements >Zn, and these can often have interferences). Thus, µXRF is especially suited for identifying minerals like zircon, baddeleyite, REE-rich phosphates, Fe-rich met-als, oxides, sulfides, and phosphides [4]. In Fig. 3 we show elemental distribution maps for 73001,530 where we are able to correlate the original video image with, Zr, Si, Y and Hf elemental maps together identi-fying the location of a zircon. In this location you would expect lower Si compared to surrounding mate-rial, as well as higher Zr, Y, and Hf content compared to surrounding material, all of which is confirmed by our XRF ele-mental distribution maps (Figure 2.) Conclusions: The new M4 Tornado Plus µXRF within the Astromaterials Acquisition and Curation office at NASA JSC allows for rapid and non-destructive elemental analysis of astromaterials with limited or no sample preparation. µXRF analyses pro-vide crucial compositional knowledge for the prelimi-nary examination and curation of astromaterials. This instrument enhances the advanced curation capabili-ties in the X-FaCT laboratory at JSC by allowing pro-ductive, cohesive, and non-destructive multi-modal x-ray analyses on astromaterial samples, which is neces-sary for the comprehensive curation and study of our current and future astromaterial collections. Addition-ally, µXRF can provide complimentary information to researchers for studies on astromaterials. References: [1] Allen, C. et al., (2011). Chemie De Erde Geochemistry, 71, 1-20. [2] McCubbin, F. M. et al., (2016) 47th LPSC, abstract #2668 [3] Zeigler, R. A. et al., (2017) 48th LPSC, abstract #2772 [4] Bruker User Manual [5] Young et al., (2016) Appl. Geochemistry, 72, 77-87 [6] Mor-ris, R. V. et al., (2023) 54th LPSC.

E W O'Neal↗
NASA NTRS2011

NASA Tech Briefs, May 2011

Topics covered include: 1) Method to Estimate the Dissolved Air Content in Hydraulic Fluid; 2) Method for Measuring Collimator-Pointing Sensitivity to Temperature Changes; 3) High-Temperature Thermometer Using Cr-Doped GdAlO3 Broadband Luminescence; 4)Metrology Arrangement for Measuring the Positions of Mirrors of a Submillimeter Telescope; 5) On-Wafer S-Parameter Measurements in the 325-508-GHz Band; 6) Reconfigurable Microwave Phase Delay Element for Frequency Reference and Phase-Shifter Applications; 7) High-Speed Isolation Board for Flight Hardware Testing; 8) High-Throughput, Adaptive FFT Architecture for FPGA-Based Spaceborne Data Processors; 9) 3D Orbit Visualization for Earth-Observing Missions; 10) MaROS: Web Visualization of Mars Orbiting and Landed Assets; 11) RAPID: Collaborative Commanding and Monitoring of Lunar Assets; 12) Image Segmentation, Registration, Compression, and Matching; 13) Image Calibration; 14) Rapid ISS Power Availability Simulator; 15) A Method of Strengthening Composite/Metal Joints; 16) Pre-Finishing of SiC for Optical Applications; 17) Optimization of Indium Bump Morphology for Improved Flip Chip Devices; 18) Measuring Moisture Levels in Graphite Epoxy Composite Sandwich Structures; 19) Marshall Convergent Spray Formulation Improvement for High Temperatures; 20) Real-Time Deposition Monitor for Ultrathin Conductive Films; 21) Optimized Li-Ion Electrolytes Containing Triphenyl Phosphate as a Flame-Retardant Additive; 22) Radiation-Resistant Hybrid Lotus Effect for Achieving Photoelectrocatalytic Self-Cleaning Anticontamination Coatings; 23) Improved, Low-Stress Economical Submerged Pipeline; 24) Optical Fiber Array Assemblies for Space Flight on the Lunar Reconnaissance Orbiter; 25) Local Leak Detection and Health Monitoring of Pressurized Tanks; 26) Dielectric Covered Planar Antennas at Submillimeter Wavelengths for Terahertz Imaging; 27) Automated Cryocooler Monitor and Control System; 28) Broadband Achromatic Phase Shifter for a Nulling Interferometer; 29) Super Dwarf Wheat for Growth in Confined Spaces; 30) Fine Guidance Sensing for Coronagraphic Observatories; 31) Single-Antenna Temperature- and Humidity-Sounding Microwave Receiver; 32) Multi-Wavelength, Multi-Beam, and Polarization-Sensitive Laser Transmitter for Surface Mapping; 33) Optical Communications Link to Airborne Transceiver; 34) Ascent Heating Thermal Analysis on Spacecraft Adaptor Fairings; 35) Entanglement in Self-Supervised Dynamics; 36) Prioritized LT Codes; 37) Fast Image Texture Classification Using Decision Trees; 38) Constraint Embedding Technique for Multibody System Dynamics; 39) Improved Systematic Pointing Error Model for the DSN Antennas; 40) Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks; 41) More-Accurate Model of Flows in Rocket Injectors; 42) In-Orbit Instrument-Pointing Calibration Using the Moon as a Target; 43) Reliability of Ceramic Column Grid Array Interconnect Packages Under Extreme Temperatures; 44) Six Degrees-of-Freedom Ascent Control for Small-Body Touch and Go; and 45) Optical-Path-Difference Linear Mechanism for the Panchromatic Fourier Transform Spectrometer.

Source record↗
NASA NTRS2000

Surface Change Detection Using Large Footprint Laser Altimetry

Laser altimeters provide a precise and accurate method for mapping topography at fine horizontal and vertical scales. A laser altimeter provides range by measuring the roundtrip flight time of a short pulse of laser light from the laser altimeter instrument to the target surface. The range is then combined with laser beam pointing knowledge and absolute position knowledge to provide an absolute measurement of the surface topography. Newer generations of laser altimeters measure the range by recording the shape and time of the outgoing and received laser pulses. The shape of the return pulse can also provide unique information about the vertical structure of material such as vegetation within each laser footprint. Distortion of the return pulse is caused by the time-distributed reflections adding together and representing the vertical distribution of surfaces within the footprint. Larger footprints (10 - 100m in diameter) can support numerous target surfaces and thus provide the potential for producing complex return pulses. Interpreting the return pulse from laser altimeters has evolved from simple timing between thresholds, range-walk corrections, constant-fraction discriminators, and multi-stop time interval units to actual recording of the time varying return pulse intensity - the return waveform. Interpreting the waveform can be as simple as digitally thresholding the return pulse, calculating a centroid, to fitting one or more gaussian pulse-shapes to the signal. What we present here is a new technique for using the raw recorded return pulse as a raw observation to detect centimeter-level vertical topographic change using large footprint airborne and spaceborne laser altimetry. We use the correlation of waveforms from coincident footprints as an indication of the similarity in structure of the waveforms from epoch to epoch, and assume that low correlation is an indicator of vertical structure or elevation change. Thus, using vertically and horizontally geolocated waveforms as raw observables (i.e., waveforms tied to a common reference ellipsoid), we assess whether epoch-to-epoch vertical ground motion results in a decrease in the correlation of coincident waveforms over time, and whether this can be used to quantify the magnitude of the deformation. Results of computer models and an example over an area of eroded beachfront will be presented.

Blair, J. Bryan↗
NASA NTRS2007

Sulfur and Moisture Effects on Alumina Scale and TBC Spallation

It has been well established that a few ppmw sulfur impurity may segregate to the interface of thermally grown alumina scales and the underlying substrate, resulting in bond degradation and premature spallation. This has been shown for NiAl and NiCrAl-based alloys, bare single crystal superalloys, or coated superalloys. The role of reactive elements (especially Y) has been to getter the sulfur in the bulk and preclude interfacial segregation. Pt additions are also very beneficial, however a similar thermodynamic explanation does not apply. The purpose of the present discussion is to highlight some observations of these effects on Rene'142, Rene'N5, PWA1480, and PWA1484. For PWA1480, we have mapped cyclic oxidation and spallation in terms of potential sulfur interfacial layers and found that a cumulative amount of about one monolayer is sufficient to degrade long term adhesion. Depending on substrate thickness, optimum performance occurs if sulfur is reduced below about 0.2-0.5 ppmw. This is accomplished in the laboratory by hydrogen annealing or commercially by melt-fluxing. Excellent 1150 C cyclic oxidation is thus demonstrated for desulfurized Rene'142, Rene'N5, and PWA1484. Alternatively, a series of N5 alloys provided by GE-AE have shown that as little as 15 ppmw of Y dopant was effective in providing remarkable scale adhesion. In support of a Y-S gettering mechanism, hydrogen annealing was unable to desulfurize these alloys from their initial level of 5 ppmw S. This impurity and critical doping level corresponds closely to YS or Y2S3 stoichiometry. In many cases, Y-doped alloys or alloys with marginal sulfur levels exhibit an oxidative sensitivity to the ambient humidity called Moisture-Induced Delayed Spallation (MIDS). After substantial scale growth, coupled with damage from repeated cycling, cold samples may spall after a period of time, breathing on them, or immersing them in water. While stress corrosion arguments may apply, we propose that the underlying cause is related to a hydrogen embrittlement reaction: Al alloy + 3 H2O = Al(OH)3 + 3H(+) + 3e(-). This mechanism is derived from an analogous moisture-induced hydrogen embrittlement mechanism originally shown for Ni3Al and FeAl intermetallics. Consequently, a cathodic hydrogen charging technique was used to demonstrate that electrolytic de-scaling occurs for these otherwise adherent alumina scales formed on Y-doped Rene'N5, in support of hydrogen effects. Finally, some TBC observations are discussed in light of all of the above. Plasma sprayed 8YSZ coatings, produced on PWA1484 without a bond coat, were found to survive more than 1000 1-hr cycles at 1100 C when desulfurized to below 0.1 ppmw. At higher sulfur (1.2 ppmw) levels, moisture sensitivity and delayed TBC failure, referred to as Desk Top Spallation, occurred at just 200 hr. Despite a large degree of scatter, a factor of 5 in life improvement is indicated for desulfurized samples in cyclic furnace tests, confirming the beneficial effect of low sulfur alloys on model TBC systems. (DTS and moisture effects are also observed on commercially applied PVD 7YSZ coatings on Rene'N5+Y with Pt-aluminide bond coats). These types of catastrophic failure were subverted on the model system by segmenting the substrate into a network of 0.010 high ribs, spaced in. apart, prior to plasma spraying. No failures occurred after 1000 cycles at 1150 C or after 2000 cycles at 1100 C, even after water immersion. The benefit is described in terms of elasticity models and a critical buckling stress.

Smialek, James L.↗