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Lunar and Planetary Science XXXV: Lunar Remote Sensing: Fire, Ice, and Regolith

The session "Lunar Remote Sensing: Fire, Ice, and Regolith" included the following:Compositional and Structural Study of the Aristarchus Plateau from Integrated UV-VIS-NIR Spectral Data; Clementine 2.7-?m Data: Mapping the Mare and Searching for Water; On the Search for Water at the Lunar Poles: Results of Forward Modeling of Permanently Shaded Areas and Lunar Prospector Measurements; Searching the Moon for Aluminous Mare Basalts Using Compositional Remote-Sensing Constraints I: Finding the Regions of Interest; Semi-automated Extraction of Contours from Lunar Topographic Maps; Basalts in Mare Humorum and S.E. Procellarum; The Hansteen and Helmet Volcanic Dome Regions on the Moon: Stratigraphy and Ages; Derivation of Elemental Abundance Maps at 15-km Spatial Resolution from the Merging of Clementine Optical and Lunar Prospector Geochemical Data; Remote Sensing and Geologic Studies of the Balmer Region of the Moon; Lava Flows in Mare Nubium and Mare Cognitum: A Geological History Based on Analysis of Multispectral Data; Development of Ground-based Lunar VIS/NEAR IR Spectral Imager; A BRDF Measurement Apparatus for Lab-based Samples; A New Source of High Resolution Lunar Images: Amateur Astronomers! ; Leakage of Gamma Rays and Neutrons from Thick Targets Bombarded by Energetic Protons; Progress on Reviving Lunar Orbiter: Scanning, Archiving, and Cartographic Processing at USGS; Modeling Lateral and Vertical Mixing by Impact Cratering with Applications for the Moon; Optical Maturity Study of Stuart#s Crater Candidate Impact; Evidence for Three Basins Beneath Oceanus Procellarum; and Ellipses of the South Pole-Aitken Basin: Implications for Basin Formation.

Source record↗

In-Space Inspection Needs: Opportunities for advanced NDE tools such as x-ray CT for additively manufactured parts, in-situ resource utilization, geological applications, and more

It is now 50 years since the first human presence on the surface of the Moon and as we strive to return with women and men in the next few years, we embrace new technical challenges, goals, and innovative solutions to address 21st century objectives. These new ambitions carry fresh challenges and risks, with the field of NDE playing an increasingly more relevant role towards meeting these essential goals. In recent years, more advanced NDE tools have triggered a rapid expansion of applications for the space industry. In particular, x-ray Computed Tomography (CT) has proven to be a trusted and powerful asset for spaceflight hardware inspection, as well as applied geotechnical analysis for natural materials (e.g., rocks, soils) for NASA and across industry. However, such methods have yet to be extended to “deep space” applications such as those that are now part of the US National Space Policy Directive (SPD-1) and the accelerated push to return humans to the Moon (i.e., Artemis). For this reason, advancing these powerful Earth-based laboratory methods via new technologies, integrated computational solutions, and creative engineering approaches is directly aligned with national space policies, as well as with multiple NASA Strategic Plan priorities. The use of x-ray CT at scales as fine as a few microns or smaller can identify spacecraft part failure modes relevant to quality assurance for flight hardware and AM parts such as those recently developed for ISS. This technology could also identify valuable metallic phases within geological materials (i.e., rocks or drill cores), enabling resource-relevant triage of samples for In-Situ Resource Utilization (ISRU) and high science value sample return to Earth laboratories. There is also significant application for 3D imaging tools for medical use such as inspecting protective gear as well as bone density degradation studies which are critical in establishing a sustained presence in space. Timing for development of these tools for space use is advantageous as we prepare for new opportunities in the next few years and recognize recent commercial technology advancements which make it feasible. Moreover, as NASA strives to take full advantage of developments in AM technologies, including In-Space Manufacturing (ISM), it is widely recognized that NDE tools such as CT will play an essential role in acceptance of these parts for widespread use. New in-space 3D inspection tools with complimentary technology such as AI-based automated feature recognition (accelerated by machine learning), rapid compositional analysis, and advanced sample manipulation, would be a game-changing step toward a new class of crew-based laboratory sensors once human outposts on the Moon are established.

In-Space Non-Destructive Evaluation↗

NASA Tech Briefs, December 2007

Topics include: Ka-Band TWT High-Efficiency Power Combiner for High-Rate Data Transmission; Reusable, Extensible High-Level Data-Distribution Concept; Processing Satellite Imagery To Detect Waste Tire Piles; Monitoring by Use of Clusters of Sensor-Data Vectors; Circuit and Method for Communication Over DC Power Line; Switched Band-Pass Filters for Adaptive Transceivers; Noncoherent DTTLs for Symbol Synchronization; High-Voltage Power Supply With Fast Rise and Fall Times; Waveguide Calibrator for Multi-Element Probe Calibration; Four-Way Ka-Band Power Combiner; Loss-of-Control-Inhibitor Systems for Aircraft; Improved Underwater Excitation-Emission Matrix Fluorometer; Metrology Camera System Using Two-Color Interferometry; Design and Fabrication of High-Efficiency CMOS/CCD Imagers; Foam Core Shielding for Spacecraft CHEM-Based Self-Deploying Planetary Storage Tanks Sequestration of Single-Walled Carbon Nanotubes in a Polymer PPC750 Performance Monitor Application-Program-Installer Builder Using Visual Odometry to Estimate Position and Attitude Design and Data Management System Simple, Script-Based Science Processing Archive Automated Rocket Propulsion Test Management Online Remote Sensing Interface Fusing Image Data for Calculating Position of an Object Implementation of a Point Algorithm for Real-Time Convex Optimization Handling Input and Output for COAMPS Modeling and Grid Generation of Iced Airfoils Automated Identification of Nucleotide Sequences Balloon Design Software Rocket Science 101 Interactive Educational Program Creep Forming of Carbon-Reinforced Ceramic-Matrix Composites Dog-Bone Horns for Piezoelectric Ultrasonic/Sonic Actuators Benchtop Detection of Proteins Recombinant Collagenlike Proteins Remote Sensing of Parasitic Nematodes in Plants Direct Coupling From WGM Resonator Disks to Photodetectors Using Digital Radiography To Image Liquid Nitrogen in Voids Multiple-Parameter, Low-False-Alarm Fire-Detection Systems Mosaic-Detector-Based Fluorescence Spectral Imager Plasmoid Thruster for High Specific-Impulse Propulsion Analysis Method for Quantifying Vehicle Design Goals Improved Tracking of Targets by Cameras on a Mars Rover Sample Caching Subsystem Multistage Passive Cooler for Spaceborne Instruments GVIPS Models and Software Stowable Energy-Absorbing Rocker-Bogie Suspensions

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Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003.2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS) ]derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top ]down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗

Cloud properties inferred from 8-12 micron data

A trispectral combination of observations at 8-, 11-, and 12-micron bands is suggested for detecting cloud and cloud properties in the infrared. Atmospheric ice and water vapor absorption peak in opposite halves of the window region so that positive 8-minus-11-micron brightness temperature differences indicate cloud, while near-zero or negative differences indicate clear regions. The absorption coefficient for water increases more between 11 and 12 microns than between 8 and 11 microns, while for ice, the reverse is true. Cloud phases is determined by a scatter diagram of 8-minus-11-micron versus 11-minus-12-micron brightness temperature differences; ice cloud shows a slope greater than 1 and water cloud less than 1. The trispectral brightness temperature method was tested upon high-resolution interferometer data resulting in clear-cloud and cloud-phase delineation. Simulations using differing 8-micron bandwidths revealed no significant degradation of cloud property detection. Thus, the 8-micron bandwidth for future satellites can be selected based on the requirements of other applications, such as surface characterization studies. Application of the technique to current polar-orbiting High-Resolution Infrared Sounder (HIRS)-Advanced Very High Resolution Radiometer (AVHRR) datasets is constrained by the nonuniformity of the cloud scenes sensed within the large HIRS field of view. Analysis of MAS (MODIS Airborne Simulator) high-spatial resolution (500 m) data with all three 8-, 11-, and 12-micron bands revealed sharp delineation of differing cloud and background scenes, from which a simple automated threshold technique was developed. Cloud phase, clear-sky, and qualitative differences in cloud emissivity and cloud height were identified on a case study segment from 24 November 1991, consistent with the scene. More rigorous techniques would allow further cloud parameter clarification. The opportunities for global cloud delineation with the Moderate-Resolution Imaging Spectrometer (MODIS) appear excellent. The spectral selection, the spatial resolution, and the global coverage are all well suited for significant advances.

Strabala, Kathleen I.↗

Spinoff 2010

Topics covered include: Burnishing Techniques Strengthen Hip Implants; Signal Processing Methods Monitor Cranial Pressure; Ultraviolet-Blocking Lenses Protect, Enhance Vision; Hyperspectral Systems Increase Imaging Capabilities; Programs Model the Future of Air Traffic Management; Tail Rotor Airfoils Stabilize Helicopters, Reduce Noise; Personal Aircraft Point to the Future of Transportation; Ducted Fan Designs Lead to Potential New Vehicles; Winglets Save Billions of Dollars in Fuel Costs; Sensor Systems Collect Critical Aerodynamics Data; Coatings Extend Life of Engines and Infrastructure; Radiometers Optimize Local Weather Prediction; Energy-Efficient Systems Eliminate Icing Danger for UAVs; Rocket-Powered Parachutes Rescue Entire Planes; Technologies Advance UAVs for Science, Military; Inflatable Antennas Support Emergency Communication; Smart Sensors Assess Structural Health; Hand-Held Devices Detect Explosives and Chemical Agents; Terahertz Tools Advance Imaging for Security, Industry; LED Systems Target Plant Growth; Aerogels Insulate Against Extreme Temperatures; Image Sensors Enhance Camera Technologies; Lightweight Material Patches Allow for Quick Repairs; Nanomaterials Transform Hairstyling Tools; Do-It-Yourself Additives Recharge Auto Air Conditioning; Systems Analyze Water Quality in Real Time; Compact Radiometers Expand Climate Knowledge; Energy Servers Deliver Clean, Affordable Power; Solutions Remediate Contaminated Groundwater; Bacteria Provide Cleanup of Oil Spills, Wastewater; Reflective Coatings Protect People and Animals; Innovative Techniques Simplify Vibration Analysis; Modeling Tools Predict Flow in Fluid Dynamics; Verification Tools Secure Online Shopping, Banking; Toolsets Maintain Health of Complex Systems; Framework Resources Multiply Computing Power; Tools Automate Spacecraft Testing, Operation; GPS Software Packages Deliver Positioning Solutions; Solid-State Recorders Enhance Scientific Data Collection; Computer Models Simulate Fine Particle Dispersion; Composite Sandwich Technologies Lighten Components; Cameras Reveal Elements in the Short Wave Infrared; Deformable Mirrors Correct Optical Distortions; Stitching Techniques Advance Optics Manufacturing; Compact, Robust Chips Integrate Optical Functions; Fuel Cell Stations Automate Processes, Catalyst Testing; Onboard Systems Record Unique Videos of Space Missions; Space Research Results Purify Semiconductor Materials; and Toolkits Control Motion of Complex Robotics.

Source record↗

Two Years Onboard the MER Opportunity Rover

The Autonomous Exploration for Gathering Increased Science (AEGIS) system provides automated data collection for planetary rovers. AEGIS is currently being used onboard the Mars Exploration Rover (MER) mission's Opportunity to provide autonomous targeting of the MER Panoramic camera. Prior to AEGIS, targeted data was collected in a manual fashion where targets were manually identified in images transmitted to Earth and the rover had to remain in the same location for one to several communication cycles. AEGIS enables targeted data to be rapidly acquired with no delays for ground communication. Targets are selected by AEGIS through the use of onboard data analysis techniques that are guided by scientist-specified objectives. This paper provides an overview of the how AEGIS has been used on the Opportunity rover, focusing on usage that occurred during a 21 kilometer historic trek to the Mars Endeavour crater.

Mars Exploration Rover (MER)↗

NASA Tech Briefs, June 2004

Topics covered include: COTS MEMS Flow-Measurement Probes; Measurement of an Evaporating Drop on a Reflective Substrate; Airplane Ice Detector Based on a Microwave Transmission Line; Microwave/Sonic Apparatus Measures Flow and Density in Pipe; Reducing Errors by Use of Redundancy in Gravity Measurements; Membrane-Based Water Evaporator for a Space Suit; Compact Microscope Imaging System with Intelligent Controls; Chirped-Superlattice, Blocked-Intersubband QWIP; Charge-Dissipative Electrical Cables; Deep-Sea Video Cameras Without Pressure Housings; RFID and Memory Devices Fabricated Integrally on Substrates; Analyzing Dynamics of Cooperating Spacecraft; Spacecraft Attitude Maneuver Planning Using Genetic Algorithms; Forensic Analysis of Compromised Computers; Document Concurrence System; Managing an Archive of Images; MPT Prediction of Aircraft-Engine Fan Noise; Improving Control of Two Motor Controllers; Electro-deionization Using Micro-separated Bipolar Membranes; Safer Electrolytes for Lithium-Ion Cells; Rotating Reverse-Osmosis for Water Purification; Making Precise Resonators for Mesoscale Vibratory Gyroscopes; Robotic End Effectors for Hard-Rock Climbing; Improved Nutation Damper for a Spin-Stabilized Spacecraft; Exhaust Nozzle for a Multitube Detonative Combustion Engine; Arc-Second Pointer for Balloon-Borne Astronomical Instrument; Compact, Automated Centrifugal Slide-Staining System; Two-Armed, Mobile, Sensate Research Robot; Compensating for Effects of Humidity on Electronic Noses; Brush/Fin Thermal Interfaces; Multispectral Scanner for Monitoring Plants; Coding for Communication Channels with Dead-Time Constraints; System for Better Spacing of Airplanes En Route; Algorithm for Training a Recurrent Multilayer Perceptron; Orbiter Interface Unit and Early Communication System; White-Light Nulling Interferometers for Detecting Planets; and Development of Methodology for Programming Autonomous Agents.

Source record↗

FTIR Spectroscopic Characterization Of II-VI Semiconductors

Combination of commercial Fourier-transform infrared (FTIR) spectrometer with computer and special-purpose software constitutes highly automated facility for acquisition and processing of infrared transmission or reflection spectral image data. Intended principally to acquire transmission spectra of some compounds of elements in groups II and VI of periodic table. System used to characterize specimens of II/VI alloy semiconductors grown by directional solidification and quenching. Transmission-edge maps helpful in studies of flows, gradients of temperature, and coefficients of diffusion in solidifying melts. Data acquired by system include optical characteristics, and they both verify and complement data obtained by such other techniques as measurements of density and x-ray-dispersion analysis.

Perry, G. L. E.↗

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗

ARCTRON: A Rapid Experimental Proving Ground for TPS Experiments and Arcjet Technology Development

Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.

experimental diagnostics↗

Automated Guided-Wave Scanning Developed to Characterize Materials and Detect Defects

The Nondestructive Evaluation (NDE) Group of the Optical Instrumentation Technology Branch at the NASA Glenn Research Center has developed a scanning system that uses guided waves to characterize materials and detect defects. The technique uses two ultrasonic transducers to interrogate the condition of a material. The sending transducer introduces an ultrasonic pulse at a point on the surface of the specimen, and the receiving transducer detects the signal after it has passed through the material. The aim of the method is to correlate certain parameters in both the time and frequency domains of the detected waveform to characteristics of the material between the two transducers. The scanning system is shown. The waveform parameters of interest include the attenuation due to internal damping, waveform shape parameters, and frequency shifts due to material changes. For the most part, guided waves are used to gauge the damage state and defect growth of materials subjected to various mechanical or environmental loads. The technique has been applied to polymer matrix composites, ceramic matrix composites, and metal matrix composites as well as metallic alloys. Historically, guided wave analysis has been a point-by-point, manual technique with waveforms collected at discrete locations and postprocessed. Data collection and analysis of this type limits the amount of detail that can be obtained. Also, the manual movement of the sensors is prone to user error and is time consuming. The development of an automated guided-wave scanning system has allowed the method to be applied to a wide variety of materials in a consistent, repeatable manner. Experimental studies have been conducted to determine the repeatability of the system as well as compare the results obtained using more traditional NDE methods. The following screen capture shows guided-wave scan results for a ceramic matrix composite plate, including images for each of nine calculated parameters. The system can display up to 18 different wave parameters. Multiple scans of the test specimen demonstrated excellent repeatability in the measurement of all the guided-wave parameters, far exceeding the traditional point-by-point technique. In addition, the scan was able to detect a subsurface defect that was confirmed using flash thermography This technology is being further refined to provide a more robust and efficient software environment. Future hardware upgrades will allow for multiple receiving transducers and the ability to scan more complex surfaces. This work supports composite materials development and testing under the Ultra-Efficient Engine Technology (UEET) Project, but it also will be applied to other material systems under development for a wide range of applications.

Martin, Richard E.↗

Large Area Scene Selection Interface (LASSI). Methodology of Selecting Landsat Imagery for the Global Land Survey 2005

The Global Land Survey (GLS) 2005 is a cloud-free, orthorectified collection of Landsat imagery acquired during the 2004-2007 epoch intended to support global land-cover and ecological monitoring. Due to the numerous complexities in selecting imagery for the GLS2005, NASA and the U.S. Geological Survey (USGS) sponsored the development of an automated scene selection tool, the Large Area Scene Selection Interface (LASSI), to aid in the selection of imagery for this data set. This innovative approach to scene selection applied a user-defined weighting system to various scene parameters: image cloud cover, image vegetation greenness, choice of sensor, and the ability of the Landsat 7 Scan Line Corrector (SLC)-off pair to completely fill image gaps, among others. The parameters considered in scene selection were weighted according to their relative importance to the data set, along with the algorithm's sensitivity to that weight. This paper describes the methodology and analysis that established the parameter weighting strategy, as well as the post-screening processes used in selecting the optimal data set for GLS2005.

Franks, Shannon↗

Automatic Generation of Overlays and Offset Values Based on Visiting Vehicle Telemetry and RWS Visuals

The development of computer software as a tool to generate visual displays has led to an overall expansion of automated computer generated images in the aerospace industry. These visual overlays are generated by combining raw data with pre-existing data on the object or objects being analyzed on the screen. The National Aeronautics and Space Administration (NASA) uses this computer software to generate on-screen overlays when a Visiting Vehicle (VV) is berthing with the International Space Station (ISS). In order for Mission Control Center personnel to be a contributing factor in the VV berthing process, computer software similar to that on the ISS must be readily available on the ground to be used for analysis. In addition, this software must perform engineering calculations and save data for further analysis.

Dunne, Matthew J.↗

Machine vision for real time orbital operations

Machine vision for automation and robotic operation of Space Station era systems has the potential for increasing the efficiency of orbital servicing, repair, assembly and docking tasks. A machine vision research project is described in which a TV camera is used for inputing visual data to a computer so that image processing may be achieved for real time control of these orbital operations. A technique has resulted from this research which reduces computer memory requirements and greatly increases typical computational speed such that it has the potential for development into a real time orbital machine vision system. This technique is called AI BOSS (Analysis of Images by Box Scan and Syntax).

Vinz, Frank L.↗

Automating sky object classification in astronomical survey images

We describe the application of machine classification techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Palomer Observatory Sky Survey is nearly completed. This survey provides comprehensive coverage of the northern celestial hemisphere in the form of photographic plates. The plates are being transformed into digitized images whose quality will probably not be surpassed in the next ten to twenty years. The images are expected to contain on the order of 10(exp 7) galaxies and 10(exp 8) stars. Astronomers wish to determine which of these sky objects belong to various classes of galaxies and stars. The size of this data set precludes manual analysis. Our approach is to develop a software system which integrates the functions of independently developed techniques for image processing and data classification. Digitized sky images are passed through image processing routines to identify sky objects and to extract a set of features for each object. These routines are used to help select a useful set of attributes for classifying sky objects. Then GID3* and O-BTree, two inductive learning techniques, learn classification decision trees from examples. These classifiers will be used to process the rest of the data. This paper gives an overview of the machine learning techniques used, describes the details of our specific application, and reports the initial encouraging results. The results indicate that our approach is well-suited to the problem. The primary benefits of the approach are increased data reduction throughput and consistency of classification. The classification rules which are the product of the inductive learning techniques will form an object, examinable basis for classifying sky objects. A final, not to be underestimated benefit is that astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems based on automatically cataloged data.

Fayyad, Usama M.↗

Spitzer Telemetry Processing System

The Spitzer Telemetry Processing System (SirtfTlmProc) was designed to address objectives of JPL's Multi-mission Image Processing Lab (MIPL) in processing spacecraft telemetry and distributing the resulting data to the science community. To minimize costs and maximize operability, the software design focused on automated error recovery, performance, and information management. The system processes telemetry from the Spitzer spacecraft and delivers Level 0 products to the Spitzer Science Center. SirtfTlmProc is a unique system with automated error notification and recovery, with a real-time continuous service that can go quiescent after periods of inactivity. The software can process 2 GB of telemetry and deliver Level 0 science products to the end user in four hours. It provides analysis tools so the operator can manage the system and troubleshoot problems. It automates telemetry processing in order to reduce staffing costs.

Stanboli, Alice↗

An Automated Approach to Map the History of Forest Disturbance from Insect Mortality and Harvest with Landsat Time-Series Data

Forests contain a majority of the aboveground carbon (C) found in ecosystems, and understanding biomass lost from disturbance is essential to improve our C-cycle knowledge. Our study region in the Wisconsin and Minnesota Laurentian Forest had a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 2007, observed with the National Ocean and Atmospheric Administration's (NOAA) series of Advanced Very High Resolution Radiometer (AVHRR). To understand the potential role of disturbances in the terrestrial C-cycle, we developed an algorithm to map forest disturbances from either harvest or insect outbreak for Landsat time-series stacks. We merged two image analysis approaches into one algorithm to monitor forest change that included: (1) multiple disturbance index thresholds to capture clear-cut harvest; and (2) a spectral trajectory-based image analysis with multiple confidence interval thresholds to map insect outbreak. We produced 20 maps and evaluated classification accuracy with air-photos and insect air-survey data to understand the performance of our algorithm. We achieved overall accuracies ranging from 65% to 75%, with an average accuracy of 72%. The producer's and user's accuracy ranged from a maximum of 32% to 70% for insect disturbance, 60% to 76% for insect mortality and 82% to 88% for harvested forest, which was the dominant disturbance agent. Forest disturbances accounted for 22% of total forested area (7349 km2). Our algorithm provides a basic approach to map disturbance history where large impacts to forest stands have occurred and highlights the limited spectral sensitivity of Landsat time-series to outbreaks of defoliating insects. We found that only harvest and insect mortality events can be mapped with adequate accuracy with a non-annual Landsat time-series. This limited our land cover understanding of NDVI decline drivers. We demonstrate that to capture more subtle disturbances with spectral trajectories, future observations must be temporally dense to distinguish between type and frequency in heterogeneous landscapes.

Forest↗