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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Non-Spherical Aerosol Phase Functions Derived from MODIS and AERONET Observations

We compare MODIS (Moderate Resolution Imaging Spectroradiometer) satellite aerosol retrievals of spectral optical thickness and size parameters over ocean with the same quantities derived from AERONET (Aerosol Robotic Network) observations made at island and coastal sites. Over much of the globe, the satellite-derived quantities agree well with the AERONET quantities. However, in regimes dominated by desert dust aerosol, the agreement is less robust. In the dust regimes, the MODIS retrievals show greater spectral dependence and report smaller particle sizes than do the AERONET derivations. We suggest that the reason for this discrepancy is the nonspherical nature of desert dust particles, which the initial MODIS algorithm is not able to handle. Using the discrepancy between MODIS and AERONET derived spectral optical thickness as an asset, instead of a detriment, we reconstruct the aerosol phase functions that the MODIS algorithm would have needed in order to match the AERONET retrievals. No assumptions of particle shape are used in the derivation of these functions and the results are empirical total column, ambient phase functions. We compare the empirically derived phase functions with phase functions calculated from spheres and spheroids, both situations in which assumptions about particle shape must be made. The resulting empirical nonspherical phase functions will be included in future updates of the MODIS algorithm.

Remer, L. A.↗
NASA NTRS2001

A Rapid Aerodynamic Design Procedure Based on Artificial Neural Networks

An aerodynamic design procedure that uses neural networks to model the functional behavior of the objective function in design space has been developed. This method incorporates several improvements to an earlier method that employed a strategy called parameter-based partitioning of the design space in order to reduce the computational costs associated with design optimization. As with the earlier method, the current method uses a sequence of response surfaces to traverse the design space in search of the optimal solution. The new method yields significant reductions in computational costs by using composite response surfaces with better generalization capabilities and by exploiting synergies between the optimization method and the simulation codes used to generate the training data. These reductions in design optimization costs are demonstrated for a turbine airfoil design study where a generic shape is evolved into an optimal airfoil.

Rai, Man Mohan↗
NASA NTRS2012

Are the Basins of Tui Regio and Hotei Arcus Sites of Former Titanian Seas?

Features observed in the basins of Tui Regio and Hotei Arcus on Titan have attracted the attention of the Cassini-era investigators. At both locations, VIMS observed discrete 5-micron bright approx.500-km wide features described as lobate in shape. Several studies have proposed that these materials are cryo-volcanic flows; in the case of the Hotei Arcus feature this inference was buttressed with SAR RADAR images showing bright and dark patches with lobate margins. We propose an alternative explanation. First we note that all landforms on Titan that are unambiguously identifiable can be explained by exogenic processes (aeolian, fluvial, impact cratering, and mass wasting). Suggestions of endogenically produced cryovolcanic constructs and flows have, without exception, lacked conclusive diagnostic evidence. Recently published topographic profiles across Tui Regio and the lobate feature region north of Hotei Arcus indicate these features appear to occur in large regional basins, at least along the direction of the profiles. SAR images show that the terrains surrounding both 5-micron bright features exhibit fluvial networks that appear to converge and debauch into the probable basins. The 5-micron bright features themselves correspond to fields of discrete radar-bright depressions whose bounding edges are commonly rounded and cumulate in planform in SAR images. These fields of discrete radar-bright depressions strongly resemble fields of features seen at Titan s high latitudes usually attributed to be dry lakes. Thus the combination of (1) the resemblance to high-latitude dry lakes, (2) location in the centers of probable regional depressions, and (3) convergence of fluvial networks are inferred by us to best explain the 5-micron bright regions at Tui Regio and Hotei Arcus as sites of dry seas or at least paleolake clusters. Such equatorial seas, if real, may be evidence of substantially larger inventories of liquid alkanes in Titan s past.

Moore, Jeffrey Morgan↗
NASA NTRS2021

Geological Factors Impacted Cadmium Availability and use as an Alternative Cofactor for Zinc in the Carbon Fixation Pathways of Marine Diatoms

Transition metal cofactors are crucial for many biological processes. Despite being primarily considered to be toxic, the transition metal cadmium (Cd) was discovered to be a substitute cofactor for zinc (Zn) in photosynthetic carbon fixation pathways of marine diatoms. However, it is not known how conditions in the geosphere impacted Cd availability and its incorporation as an alternative metal cofactor for phytoplankton. We employed mineral chemistry network analysis to investigate which geochemical factors may have influenced the availability of Cd and Zn during the putative time period that the alternative Cd-based pathway evolved. Our results show that Zn minerals are more chemically diverse than are Cd minerals, but Zn- and Cd-containing minerals have similar network centrality values when specifically considering sulfur (S)-containing species. Cadmium and Zn sulfides are the most common Cd- and Zn-containing mineral species over the past 500 million years. In particular, the Cd and Zn sulfides, respectively greenockite and sphalerite, were highly abundant during this time period. Furthermore, S-containing Cd and Zn minerals are commonly co-located in geologic time, allowing them to be weathered and transported to the ocean in tandem, rather than from separate sources. We suggest that the simultaneous weathering of Cd and Zn sulfides allowed for Cd to be a bioavailable direct substitute for Zn in protein complexes during periods of Zn depletion. The biogeochemical cycles of Zn and Cd exemplify the importance of the coevolution of the geosphere and biosphere in shaping primary production in the modern ocean.

Naman Srivastava↗
NASA NTRS1990

Optical neural network system for pose determination of spinning satellites

An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

Lee, Andrew↗
NASA NTRS1999

Tracker: Image-Processing and Object-Tracking System Developed

Tracker is an object-tracking and image-processing program designed and developed at the NASA Lewis Research Center to help with the analysis of images generated by microgravity combustion and fluid physics experiments. Experiments are often recorded on film or videotape for analysis later. Tracker automates the process of examining each frame of the recorded experiment, performing image-processing operations to bring out the desired detail, and recording the positions of the objects of interest. It can load sequences of images from disk files or acquire images (via a frame grabber) from film transports, videotape, laser disks, or a live camera. Tracker controls the image source to automatically advance to the next frame. It can employ a large array of image-processing operations to enhance the detail of the acquired images and can analyze an arbitrarily large number of objects simultaneously. Several different tracking algorithms are available, including conventional threshold and correlation-based techniques, and more esoteric procedures such as "snake" tracking and automated recognition of character data in the image. The Tracker software was written to be operated by researchers, thus every attempt was made to make the software as user friendly and self-explanatory as possible. Tracker is used by most of the microgravity combustion and fluid physics experiments performed by Lewis, and by visiting researchers. This includes experiments performed on the space shuttles, Mir, sounding rockets, zero-g research airplanes, drop towers, and ground-based laboratories. This software automates the analysis of the flame or liquid s physical parameters such as position, velocity, acceleration, size, shape, intensity characteristics, color, and centroid, as well as a number of other measurements. It can perform these operations on multiple objects simultaneously. Another key feature of Tracker is that it performs optical character recognition (OCR). This feature is useful in extracting numerical instrumentation data that are embedded in images. All the results are saved in files for further data reduction and graphing. There are currently three Tracking Systems (workstations) operating near the laboratories and offices of Lewis Microgravity Science Division researchers. These systems are used independently by students, scientists, and university-based principal investigators. The researchers bring their tapes or films to the workstation and perform the tracking analysis. The resultant data files generated by the tracking process can then be analyzed on the spot, although most of the time researchers prefer to transfer them via the network to their offices for further analysis or plotting. In addition, many researchers have installed Tracker on computers in their office for desktop analysis of digital image sequences, which can be digitized by the Tracking System or some other means. Tracker has not only provided a capability to efficiently and automatically analyze large volumes of data, saving many hours of tedious work, but has also provided new capabilities to extract valuable information and phenomena that was heretofore undetected and unexploited.

Klimek, Robert B.↗
NASA NTRS2008

Evolution and Reengineering of NASA's Flight Dynamics Facility (FDF)

The NASA Goddard Space Flight Center's Flight Dynamics Facility (FDF) is a multimission support facility that performs ground navigation and spacecraft trajectory design services for a wide range of scientific satellites. The FDF also supports the NASA Space Network by providing orbit determination and tracking data evaluation services for the Tracking Data Relay Satellite System (TDRSS). The FDF traces its history to early NASA missions in the 1960's, including navigation support to the Apollo lunar missions. Over its 40 year history, the FDF has undergone many changes in its architecture, services offered, missions supported, management approach, and business operation. As a fully reimbursable facility (users now pay 100% of all costs for FDF operations and sustaining engineering activities), the FDF has faced significant challenges in recent years in providing mission critical products and services at minimal cost while defining and implementing upgrades necessary to meet future mission demands. This paper traces the history of the FDF and discusses significant events in the past that impacted the FDF infrastructure and/or business model, and the events today that are shaping the plans for the FDF in the next decade. Today's drivers for change include new mission requirements, the availability of new technology for spacecraft navigation, and continued pressures for cost reduction from FDF users. Recently, the FDF completed an architecture study based on these drivers that defines significant changes planned for the facility. This paper discusses the results of this study and a proposed implementation plan. As a case study in how flight dynamics operations have evolved and will continue to evolve, this paper focuses on two periods of time (1992 and the present) in order to contrast the dramatic changes that have taken place in the FDF. This paper offers observations and plans for the evolution of the FDF over the next ten years. Finally, this paper defines the mission model of the future for the FDF based on NASA's current mission list and planning for the Constellation Program. As part of this discussion the following are addressed: the relevance and benefits of a multi-mission facility for NASA's navigation operations in the future; anticipated technologies affecting ground orbit determination; continued incorporation of Commercial Off-the-shelf (COTS) software into the FDF; challenges of a business model that relies entirely on user fees to fund facility upgrades; anticipated changes in flight dynamics services required; and considerations for defining architecture upgrades given a set of cost drivers.

Stengle, Thomas↗
NASA NTRS2003

Extraction of Qualitative Features from Sensor Data Using Windowed Fourier Transform

In this paper, we use Matlab to model the health monitoring of a system through the information gathered from sensors. This implies assessment of the condition of the system components. Once a normal mode of operation is established any deviation from the normal behavior indicates a change. This change may be due to a malfunction of an element, a qualitative change, or a change due to a problem with another element in the network. For example, if one sensor indicates that the temperature in the tank has experienced a step change then a pressure sensor associated with the process in the tank should also experience a step change. The step up and step down as well as sensor disturbances are assumed to be exponential. An RC network is used to model the main process, which is step-up (charging), drift, and step-down (discharging). The sensor disturbances and spike are added while the system is in drift. The system is allowed to run for a period equal to three time constant of the main process before changes occur. Then each point of the signal is selected with a trailing data collected previously. Two trailing lengths of data are selected, one equal to two time constants of the main process and the other equal to two time constants of the sensor disturbance. Next, the DC is removed from each set of data and then the data are passed through a window followed by calculation of spectra for each set. In order to extract features the signal power, peak, and spectrum are plotted vs time. The results indicate distinct shapes corresponding to each process. The study is also carried out for a number of Gaussian distributed noisy cases.

Amini, Abolfazl M.↗
NASA NTRS2018

Towards Explainability of UAV-Based Convolutional Neural Networks for Object Classification

f autonomous systems using trust and trustworthiness is the focus of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR), a new NASA Convergent Aeronautical Solutions (CAS) Project. One critical research element of ATTRACTOR is explainability of the decision-making across relevant subsystems of an autonomous system. The ability to explain why an autonomous system makes a decision is needed to establish a basis of trustworthiness to safely complete a mission. Convolutional Neural Networks (CNNs) are popular visual object classifiers that have achieved high levels of classification performances without clear insight into the mechanisms of the internal layers and features. To explore the explainability of the internal components of CNNs, we reviewed three feature visualization methods in a layer-by-layer approach using aviation related images as inputs. Our approach to this is to analyze the key components of a classification event in order to generate component labels for features of the classified image at different layers of depths. For example, an airplane has wings, engines, and landing gear. These could possibly be identified somewhere in the hidden layers from the classification and these descriptive labels could be provided to a human or machine teammate while conducting a shared mission and to engender trust. Each descriptive feature may also be decomposed to a combination of primitives such as shapes and lines. We expect that knowing the combination of shapes and parts that create a classification will enable trust in the system and insight into creating better structures for the CNN.

Dolph, Chester V.↗
NASA NTRS2004

Lunar and Planetary Science XXXV: Mars: Hydrology, Drainage, and Valley Systems

The titles in this section include: 1) Analysis of Orientation Dependence of Martian Gullies; 2) A Preliminary Relationship between the Depth of Martian Gullies and the Abundance of Hydrogen on Near-Surface Mars; 3) Water Indicators in Sirenum Terra and around the Argyre Impact Basin, Mars; 4) The Distribution of Gullies and Tounge-shaped Ridges and Their Role in the Degradation of Martian Craters; 5) A Critical Evaluation of Crater Lake Systems in Memnonia Quadrangle, Mars; 6) Impact-generated Hydrothermal Activity at Gusev Crater: Implications for the Spirit Mission; 7) Characterization of the Distributary Fan in Holden NE Crater using Stereo Analysis; 8) Computational Analysis of Drainage Basins on Mars: Appraising the Drainage Density; 9) Hypsometric Analyses of Martian Basins: A Comparison to Terrestrial, Lunar, and Venusian Hypsometry; 10) Morphologic Development of Harmakhis Vallis, Mars; 11) Mangala Valles, Mars: Investigations of the source of Flood Water and Early Stages of Flooding; 12) The Formation of Aromatum Chaos and the Water Discharge Rate at Ravi Vallis; 13) Inferring Hydraulics from Geomorphology for Athabasca Valles, Mars; 14) The Origin and Evolution of Dao Vallis: Formation and Modification of Martian Channels by Structural Collapse and Glaciation; 15) Snowmelt and the Formation of Valley Networks on Martian Volcanoes; 16) Extent of Floating Ice in an Ancient Echus Chasma/Kasei Valley System, Mars.

Source record↗
NASA NTRS2013

NASA Tech Briefs, April 2013

Topics covered include: Fully Integrated, Miniature, High-Frequency Flow Probe Utilizing MEMS Leadless SOI Technology; Nanoscale Surface Plasmonics Sensor With Nanofluidic Control; Advanced Dispersed Fringe Sensing Algorithm for Coarse Phasing Segmented Mirror Telescopes; Neural Network Back-Propagation Algorithm for Sensing Hypergols; Bulk Moisture and Salinity Sensor; Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing; Circularly Polarized Microwave Antenna Element with Very Low Off-Axis Cross-Polarization; Ultra-Low Heat-Leak, High-Temperature Superconducting Current Leads for Space Applications; Flash Cracking Reactor for Waste Plastic Processing; An Automated Safe-to-Mate (ASTM) Tester; Wireless Chalcogenide Nanoionic-Based Radio-Frequency Switch; Compute Element and Interface Box for the Hazard Detection System; DOT Transmit Module; Composite Aerogel Multifoil Protective Shielding; Li-Ion Electrolytes with Improved Safety and Tolerance to High-Voltage Systems; Polymer-Reinforced, Non-Brittle, Lightweight Cryogenic Insulation; Controlled, Site-Specific Functionalization of Carbon Nanotubes with Diazonium Salts; Regenerable Sorbent for CO2 Removal; Sprayable Aerogel Bead Compositions With High Shear Flow Resistance and High Thermal Insulation Value; Lexan Linear Shaped Charge Holder with Magnets and Backing Plate; Robotic Ankle for Omnidirectional Rock Anchors; Wind, Wave, and Tidal Energy Without Power Conditioning; An Active Heater Control Concept to Meet IXO Type Mirror Module Thermal-Structural Distortion Requirement; Waterless Clothes-Cleaning Machine; Integrated Electrical Wire Insulation Repair System; LVGEMS Time-of-Flight Mass Spectrometry on Satellites; Surface Inspection Tool for Optical Detection of Surface Defects; Per-Pixel, Dual-Counter Scheme for Optical Communications; Certification-Based Process Analysis; Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization; Smart-Divert Powered Descent Guidance to Avoid the Backshell Landing Dispersion Ellipse; Estimating Foreign-Object-Debris Density from Photogrammetry Data; Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria; Building a 2.5D Digital Elevation Model From 2D Imagery; Eyes on the Earth 3D; Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles; Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS; ISTP CDF Skeleton Editor; Uplink Summary Generator (ULSGEN) Version 1.0; Robotics On-Board Trainer (ROBoT); Software Engineering Tools for Scientific Models; Automatic Data Filter Customization Using a Genetic Algorithm; Tracker Toolkit; Towards Efficient Scientific Data Management Using Cloud Storage; On a Formal Tool for Reasoning About Flight Software Cost Analysis; A Nanostructured Composites Thermal Switch Controls Internal and External Short Circuit in Lithium Ion Batteries; Spacecraft Crew Cabin Condensation Control; and Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex.

Source record↗
NASA NTRS2021

Scheduling the NASA Deep Space Network with Deep Reinforcement Learning

With three complexes spread evenly across the Earth, NASA’s Deep Space Network (DSN) is the primary means of communications as well as a significant scientific instrument for dozens of active missions around the world. A rapidly rising number of spacecraft and increasingly complex scientific instruments with higher bandwidth requirements have resulted in demand that exceeds the network’s capacity across its 12 antennae. The existing DSN scheduling process operates on a rolling weekly basis and is time-consuming; for a given week, generation of the final baseline schedule of spacecraft tracking passes takes roughly 5 months from the initial requirements submission deadline, with several weeks of peer-to-peer negotiations in between. This paper proposes a deep reinforcement learning (RL) approach to generate candidate DSN schedules from mission requests and spacecraft ephemeris data with demonstrated capability to address real-world operational constraints. A deep RL agent is developed that takes mission requests for a given week as input, and interacts with a DSN scheduling environment to allocate tracks such that its reward signal is maximized. A comparison is made between an agent trained using Proximal Policy Optimization and its random, untrained counterpart. The results represent a proof-of-concept that, given a well-shaped reward signal, a deep RL agent can learn the complex heuristics used by experts to schedule the DSN. A trained agent can potentially be used to generate candidate schedules to bootstrap the scheduling process and thus reduce the turnaround cycle for DSN scheduling.

Wilson, Brian↗
NASA NTRS2006

A Microstrip Patch-Fed Short Backfire Antenna for the Tracking and Data Relay Satellite System-Continuation (TDRSS-C) Multiple Access (MA) Array

Short Backfire Antennas (SBAs) are widely utilized for mobile satellite communications, tracking, telemetry, and wireless local area network (WLAN) applications due to their compact structure and excellent radiation characteristics [1-3]. Typically, these SBA s consist of an excitation element (i.e., a half-wavelength dipole), a reflective bottom plane, a planar sub-reflector located above the "exciter", and an outer circular rim. This configuration is capable of achieving gains on the order of 13-15 dBi, but with relatively narrow bandwidths (approx.3%-5%), making it incompatible with the requirements of the next generation enhanced Tracking and Data Relay Satellite System-Continuation (TDRSS-C) Multiple Access (MA) array [1]. Several attempts have been made to enhance the bandwidth performance of the common dipole-fed SBA by employing various other feeding mechanisms (e.g., waveguide, slot) with moderate success [4-5]. In this paper, a novel method of using a microstrip patch is employed for the first time to excite an SBA. The patch element is fed via two H-shaped slots electromagnetically coupled to a broadband hybrid coupler to maintain a wide bandwidth, as well as provide for dual circular polarization capabilities.

Nessel, James A.↗
NASA NTRS2018

Conceptual Ideas for Radio Telescope on the Far Side of the Moon

A radio telescope on the far-side of the Moon has tremendous advantages compared to Earth-based telescopes because it could observe the universe at wavelengths that are hitherto poorly explored by humans so far and the Moon acts as a physical shield that isolates the telescope from the radio interference and noises from Earth. This paper presents a novel concept for building a radio telescope on the far-side of the Moon. The main idea is to shape a suitable existing lunar crater (1 − 50km in diameter) on the far-side of the Moon into a spherical reflecting dish. The proposed Lunar Crater Radio Telescope (LCRT) would be able to observe the universe in the 5 − 100m wavelength band (i.e., 3 − 60MHz radio frequency band). The key innovations of this concept are: (1) LCRT would be the largest filled-aperture radio telescope in the Solar System. (2) LCRT could potentially make tremendous scientific discoveries in fields of cosmology and extrasolar planets by observing the universe in the 5−100m λ band(i.e., 3−60MHz ν band) that has been hitherto poorly explored. (3) It would require only a few robots from Earth and autonomously modify an existing lunar crater to build the LCRT; thereby significantly reducing launch weight and cost compared to all previous lunar surface telescope mission concepts. (4) Furthermore, the Earth based robots are not consumed during construction of LCRT. Therefore, they could create a network of LCRTs to (i) observe different regions of the universe, and (ii) enable lunar Very-Long-Baseline Interferometry (VLBI) astronomy. We envisage that this concept would unlock the potential for groundbreaking scientific discoveries in radio astronomy.

Rahmani, Amir↗
NASA NTRSDate not supplied

Tin-Essako 001: A Metal-Rich Ureilite?

Introduction: Metal-rich achondrites include a variety of types, and likely have a variety of origins. Models range from gravitational mixing at the core-mantle boundaries of differentatiated asteroids, to complex impact mixing scenarios. We describe a new type of metal-rich achondrite that might be the first metal-rich ureilite. Sample: Tin-Essako (TE) 001 (~4.3 g) was found in Mali in 2020 and purchased by Jay Piatek in 2021. It was classified as a metal-rich ungrouped achondrite, with olivine and oxygen isotope (d18O=8.2810‰, d17O=3.718‰, avg. 3) compositions suggesting affinity to ureilites [1]. We studied one polished section (~187.7 mm2) of TE 001. Petrography: TE 001 consists of ~60% metal and 40% silicates, heterogeneously distributed. The metal is largely fresh, but iron oxides (presumably terrestrial) occur along one edge and in some patches and veins in the interior. The silicates are dominantly olivine (≥90%), with melt-textured areas of plagioclase + Si-rich glass. Minor phases include chromite and carbon. Olivine occurs as rounded grains (up to ~2.5 mm) in metal, commonly with rims of melt-textured plagioclase + glass. Olivine also occurs in more massive areas having a “honeycomb” texture, with rounded olivine “cells” surrounded by an interstitial network of reduced olivine riddled with tiny metal grains, plus melt-textured plagioclase + Si-rich glass. Chromite occurs as subhedral to rounded grains; smaller grains (30-250 mm) are included in olivine and a few larger grains (400-500 mm) are isolated within metal. A carbon phase occurs as lacy-textured rims around olivine grains in metal, or small patches within metal. Mineral Compositions: The olivine (excluding interstitial areas) is Fo 73.9±0.5, with 0.25±0.02 wt.% CaO, 0.31±0.01 wt% Cr2O3, 0.01 wt.% NiO, and molar Fe/Mn=49.8±2.2 (53 analyses). Olivine in interstitial areas has Fo up to at least 91. Smaller chromite grains have Fe# (molar Fe/[Fe+Mg]) = 0.54±0.01, Cr# (molar Cr/[Cr+Al]) = 0.52±0.01, 0.52±0.02 wt.% V2O3 and 0.21±0.04 wt% ZnO (28 analyses). One larger grain is zoned from Fe# = 0.45, Cr# =0.52 to Fe# = 0.40, Cr# =0.57, and contains thin Al-rich lamellae not resolved by EMPA. One irregularly shaped patch of chromite included in olivine has Fe# =0.26 and contains no ZnO. Plagioclase laths are An ~53-60, with ≤0.01 wt.% K2O. Glass contains 75-76 wt% SiO2 and ~16 wt% Al2O3. The metal contains 5.2±0.2 wt% Ni, 0.46±0.02 wt.% Co, and 0.01±0.01 wt.% Cr, with Si and P below detection (168 analyses). Discussion: The olivine + chromite assemblage in TE 001 is similar to the most ferroan ureilites (Fo ~75-79 [2]), as are the oxygen isotopes [1]. The presence of a carbon phase supports this, although the identity of this phase (graphite as in ureilites?) remains to be determined. The “honeycomb” textured areas, in particular, the presence of olivine “reduction rims,” resemble shock-smelted olivine areas in ureilites [3], but interstitial melt-textured plagioclase laths + glass like those in TE 001 have not been reported in such (or any) ureilites. Olivine in TE 001 is marginally more ferroan than in the most FeO-rich ureilite, with Fe-Mg-Mn composition offset from the trend of olivine + low-Ca pyroxene ureilites similar to augite-bearing ureilites [4]. CaO and Cr2O3 contents are in the range of those in ureilite olivine [ ] , though Cr2O3 is at the extreme low end of the range [5]. Chromites (except the unusual one) have similar Fe# to the most ferroan primary chromites in ureilites [2], but distinctly lower Cr# (0.52 vs. 0.71). Metal compositions are with the range for metal in ureilites [7]. The absence of pyroxene and sulfide, and the high abundance of metal in TE 001, are unlike ureilites. One possibility is that a ferroan, chromite-bearing, pyroxene-poor ureilite was invaded (possibly due to impact) by a metallic liquid (low S content suggests very high temperature), resulting in complete melting of pyroxene and smelting of olivine, with rapid recrystallization of melted silicate as plagioclase + glass. Alternatively, a pre-existing metal-rich ureilite assemblage may have been impact melted. Additional types of data will be obtained to evaluate these hypotheses (i.e., is the metal indigenous?) and assess affinity to ureilites.

olivine↗
NASA NTRS1994

Human factors involvement in bringing the power of AI to a heterogeneous user population

The Human Factors involvement in developing COMPAQ QuickSolve, an electronic problem-solving and information system for Compaq's line of networked printers, is described. Empowering customers with expert system technology so they could solve advanced networked printer problems on their own was a major goal in designing this system. This process would minimize customer down-time, reduce the number of phone calls to the Compaq Customer Support Center, improve customer satisfaction, and, most importantly, differentiate Compaq printers in the marketplace by providing the best, and most technologically advanced, customer support. This represents a re-engineering of Compaq's customer support strategy and implementation. In its first generation system, SMART, the objective was to provide expert knowledge to Compaq's help desk operation to more quickly and correctly answer customer questions and problems. QuickSolve is a second generation system in that customer support is put directly in the hands of the consumers. As a result, the design of QuickSolve presented a number of challenging issues. Because the produce would be used by a diverse and heterogeneous set of users, a significant amount of human factors research and analysis was required while designing and implementing the system. Research that shaped the organization and design of the expert system component as well.

Czerwinski, Mary↗
NASA NTRS1998

Analyzing Space-Based Interferometric Measurements of Stars and Network Measurements of Gamma-Ray Bursts

Since the announcement of the discovery of sources of bursts of gamma-ray radiation in 1973, hundreds more reports of such bursts have now been published. Numerous artificial satellites have been equipped with gamma-ray detectors including the very successful Compton Gamma Ray Observatory BATSE instrument. Unfortunately, we have made no progress in identifying the source(s) of this high energy radiation. We suspected that this was a consequence of the method used to define gamma-ray burst source "error boxes." An alternative procedure to compute gamma-ray burst source positions, with a purely physical underpinning, was proposed in 1988 by Taff. Since then we have also made significant progress in understanding the analytical nature of the triangulation problem and in computing actual gamma-ray burst positions and their corresponding error boxes. For the former, we can now mathematically illustrate the crucial role of the area occupied by the detectors, while for the latter, the Atteia et al. (1987) catalog has been completely re-reduced. There are very few discrepancies in locations between our results and those of the customary "time difference of arrival" procedure. Thus, we have numerically demonstrated that the end result, for the positions, of these two very different-looking procedures is the same. Finally, for the first time, we provide a sample of realistic "error boxes" whose non-simple shapes vividly portray the difficulty of burst source localization.

Taff, L. G.↗
NASA NTRS2008

Jet Propulsion Laboratory: Annual Report 2007

Many milestones are celebrated in the business of space exploration, but one of them that arrived this year has particular meaning for us. Half a century ago, on January 31, 1958, the Jet Propulsion Laboratory was responsible for creating America's first satellite, Explorer 1, and joined with the Army to launch it into orbit. That makes 2007 the 50th year we have been sending robotic craft from Earth to explore space. No other event before or since has had such a profound effect on JPL's basic identity, setting it on the path to become the world's leader in robotic solar system exploration. It is not lost on historians that Explorer 1, besides being America's first satellite, was also the first spacecraft from any country to deliver scientific results in its case, the discovery of the Van Allen Radiation Belts that surround Earth. Science, of course, has been the prime motivator for all the dozens of missions that we have lofted into space in the half-century since then. JPL has sent spacecraft to every planet in the solar system from Mercury to Neptune, some of them very sophisticated machines. But in one way or another, they all owe their heritage to the 31-pound bullet-shaped probe JPL shot into space in 1958. Although we have ranged far and wide across the solar system, we have a very strong contingent of satellites and instruments dedicated, like Explorer, to the environment of our home planet. JPL missions have been providing much of the data to establish the facts of global warming - most especially, the melting of ice sheets in Greenland and Antarctica. During the past year, JPL and our parent organization, the California Institute of Technology, have created a task force to focus the special capabilities of the Laboratory and campus on ways to better understand the physics of global change. While Earth is a chaotic and dynamic system capable of large natural variations, evidence is mounting that human activities are playing an increasingly important role. A central piece of this effort is a search for novel energy sources to replace fossil fuels, the combustion of which adds carbon dioxide to our atmosphere. All of this is supported by our worldwide Deep Space Network, which provides the communication link between spacecraft and the ground. In addition, missions are infused with technologies developed by researchers working on projects for non-NASA sponsors as well as on pure research.

Jet Propulsion Laboratory (JPL)↗