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A New Direction for NASA Materials Science Research Using the International Space Station

NASA recently created a fifth Strategic Enterprise, the Office of Biological and Physical Research (OBPR), to bring together physics, chemistry, biology, and engineering to foster interdisciplinary research. The Materials Science Program is one of five Microgravity Research disciplines within this new enterprise's Division of Physical Sciences Research. The Materials Science Program will participate within this new enterprise structure in order to facilitate effective use of ISS facilities, target scientific and technology questions and transfer scientific and technology results for Earth benefits. The Materials Science research will use a low gravity environment for flight and ground-based research in crystallization, fundamental processing, properties characterization, and biomaterials in order to obtain fundamental understanding of various phenomena effects and relationships to the structures, processing, and properties of materials. Completion of the International Space Station's (ISS) first major assembly, during the past year, provides new opportunities for on-orbit research and scientific utilization. Accommodations will support a variety of Materials Science payload hardware both in the US and international partner modules with emphasis on early use of Express Rack and Glovebox facilities. This paper addresses the current scope of the flight investigator program. These investigators will use the various capabilities of the ISS to achieve their research objectives. The type of research and classification of materials being studied will be addressed. This includes the recent emphasis being placed on nanomaterials and biomaterials type research. Materials Science Program will pursue a new, interdisciplinary approach, which contributes, to Human Space Flight Exploration research. The Materials Science Research Facility (MSRF) and other related American and International experiment modules will serve as the foundation for this research. Discussion will be included to explain the changing concept for materials science research processing capabilities aboard the ISS along with the various ground facilities necessary to support the program. Finally, the paper will address the initial utilization schedule and strategy for the various materials science payloads including their corresponding hardware.

Schlagheck, Ronald

A New Direction for the NASA Materials Science Research Using the International Space Station

In 2001 NASA created a fifth Strategic Enterprise, the Office of Biological and Physical Research (OBPR), to bring together physics, chemistry, biology, and engineering to foster interdisciplinary research. The Materials Science Program is one of five Microgravity Research disciplines within this new Enterprise's Division of Physical Sciences Research. The Materials Science Program will participate within this new enterprise structure in order to facilitate effective use of ISS facilities, target scientific and technology questions and transfer results for Earth benefits. The Materials Science research will use a low gravity environment for flight and ground-based research in crystallization, fundamental processing, properties characterization, and biomaterials in order to obtain fundamental understanding of various phenomena effects and relationships to the structures, processing, and properties of materials. Completion of the International Space Station's (ISS) first major assembly, during the past year, provides new opportunities for on-orbit research and scientific utilization. The Enterprise has recently completed an assessment of the science prioritization from which the future materials science ISS type payloads will be implemented. Science accommodations will support a variety of Materials Science payload hardware both in the US and international partner modules with emphasis on early use of Express Rack and Glovebox facilities. This paper addresses the current scope of the flight and ground investigator program. These investigators will use the various capabilities of the ISS lab facilities to achieve their research objectives. The type of research and classification of materials being studied will be addressed. This includes the recent emphasis being placed on radiation shielding, nanomaterials, propulsion materials, and biomaterials type research. The Materials Science Program will pursue a new, interdisciplinary approach, which contributes, to Human Space Flight Exploration research. The Materials Science Research Facility (MSRF) and other related American and International experiment modules will serve as the foundation for the flight research environment. A summary will explain the concept for materials science research processing capabilities aboard the ISS along with the various ground facilities necessary to support the program.

Schlagheck, Ronald A.

Test and evaluation of Fern Engineering Company, Incorporated, solar heating and hot water system

Tests, test results, examination and evaluation by Underwriters Laboratory, Inc., of a single family solar heating and hot water system consisting of collector, storage, control, transport, and data acquisition are presented. The structural characteristics of the solar flat plate collectors were evaluated according to snow and wind loads indicated in various building codes to determine their suitability for use both Michigan and Pennsylvania where prototype systems were installed. The flame spread classification of the thermal insulation is discussed and the fire tests conducted on components are described. The operation and dielectrics withstand tests of the energy transport module indicate the module is capable of rated air delivery. Tests of the control panel indicate the relay coil temperatures exceed the temperature limits allowed for the insulating materials involved.

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NASA Tech Briefs, December 2008

Topics covered include: Crew Activity Analyzer; Distributing Data to Hand-Held Devices in a Wireless Network; Reducing Surface Clutter in Cloud Profiling Radar Data; MODIS Atmospheric Data Handler; Multibeam Altimeter Navigation Update Using Faceted Shape Model; Spaceborne Hybrid-FPGA System for Processing FTIR Data; FPGA Coprocessor for Accelerated Classification of Images; SiC JFET Transistor Circuit Model for Extreme Temperature Range; TDR Using Autocorrelation and Varying-Duration Pulses; Update on Development of SiC Multi-Chip Power Modules; Radio Ranging System for Guidance of Approaching Spacecraft; Electromagnetically Clean Solar Arrays; Improved Short-Circuit Protection for Power Cells in Series; Electromagnetically Clean Solar Arrays; Logic Gates Made of N-Channel JFETs and Epitaxial Resistors; Improved Short-Circuit Protection for Power Cells in Series; Communication Limits Due to Photon-Detector Jitter; System for Removing Pollutants from Incinerator Exhaust; Sealing and External Sterilization of a Sample Container; Converting EOS Data from HDF-EOS to netCDF; HDF-EOS 2 and HDF-EOS 5 Compatibility Library; HDF-EOS Web Server; HDF-EOS 5 Validator; XML DTD and Schemas for HDF-EOS; Converting from XML to HDF-EOS; Simulating Attitudes and Trajectories of Multiple Spacecraft; Specialized Color Function for Display of Signed Data; Delivering Alert Messages to Members of a Work Force; Delivering Images for Mars Rover Science Planning; Oxide Fiber Cathode Materials for Rechargeable Lithium Cells; Electrocatalytic Reduction of Carbon Dioxide to Methane; Heterogeneous Superconducting Low-Noise Sensing Coils; Progress toward Making Epoxy/Carbon-Nanotube Composites; Predicting Properties of Unidirectional-Nanofiber Composites; Deployable Crew Quarters; Nonventing, Regenerable, Lightweight Heat Absorber; Miniature High-Force, Long-Stroke SMA Linear Actuators; "Bootstrap" Configuration for Multistage Pulse-Tube Coolers; Reducing Liquid Loss during Ullage Venting in Microgravity; Ka-Band Transponder for Deep-Space Radio Science; Replication of Space-Shuttle Computers in FPGAs and ASICs; Demisable Reaction-Wheel Assembly; Spatial and Temporal Low-Dimensional Models for Fluid Flow; Advanced Land Imager Assessment System; Range Imaging without Moving Parts.

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The X-ray selected cataclysmic variables H0459 + 246 and H0857 - 242

We report the discovery of two cataclysmic variables located with the assistance of X-ray positions from the HEAO 1 Modulation Collimator and the Large-Area Sky Survey. Each case is distinguished by evidence of two periodic modulations that appear to represent the orbital period and the spin period of the white dwarf, respectively. The first case, H0459 + 246, has been observed optically during faint states (V approximately 16), in which there are spectral features of both an accretion disk and a K star. The light curves in the V and I bands are consistent with ellipsoidal variations in the secondary stars with a binary period of 9.952 hr. X-ray observations with EXOSAT reveal a strong pulsation with a period approximately 62 minutes. This result confirms an 'intermediate polar' classification for H0459 + 246. The pulsation is observed at 63.2 minutes in the optical I band. The long orbital period opens the possibility that H0459 + 246 is a relatively young intermediate polar that might evolve into a polar. The second case, H0857--242, shows radial velocity modulations at 1.78 hr along with photometric variations at a period approximately 49 minutes. The latter are observed only during the decay phase of dwarf nova outbursts (13 less than V less than 17), which apparently recur frequently. Given the lack of X-ray monitoring observations and the absence of proof that the 49 minute periodicity is coherent over long time-scales, we regard H0857--242 as a candidate intermediate polar. Photographic records from th e Harvard Observatory Plate Library further reveal superoutbursts for H0857--242 (V approximately 11). A bright X-ray source that is both an intermediate polar and a continually cycling dwarf nova may provide an effective means of measuring the time delay for the arrival of accreting matter at the white dwarf surface, relative to the onset of optical brightening.

Remillard, R. A.

The composite classification problem in optical information processing

Optical pattern recognition allows objects to be recognized from their images and permits their positional parameters to be estimated accurately in real time. The guiding principle behind optical pattern recognition is that a lens focusing a beam of coherent light modulated with an image produces the two-dimensinal Fourier transform of that image. When the resulting output is further transformed by the matched filter corresponding to the original image, one obtains the autocorrelation function of the original image, which has a peak at the origin. Such a device is called an optical correlator and may be used to recognize the locate the image for which it is designed. (From a practical perspective, an approximation to the matched filter must be used since the spatial light modulator (SLM) on which the filter is implemented usually does not allow one to independently control both the magnitude and phase of the filter.) Generally, one is not just concerned with recognizing a single image but is interested in recognizing a variety of rotated and scaled views of a particular image. In order to recognize these different views using an optical correlator, one may select a subset of these views (whose elements are called training images) and then use a composite filter that is designed to produce a correlation peak for each training image. Presumably, these peaks should be sharp and easily distinguishable from the surrounding correlation plane values. In this report we consider two areas of research regarding composite optical correlators. First, we consider the question of how best to choose the training images that are used to design the composite filter. With regard to quantity, the number of training images should be large enough to adequately represent all possible views of the targeted object yet small enough to ensure that the resolution of the filter is not exhausted. As for the images themselves, they should be distinct enough to avoid numerical difficulties yet similar enough to avoid gaps in which certain views of the target will be unrecognized. One method that we introduce to study this problem is called probing and involves the creation of the artificial imagery. The second problem we consider involves the clasification of the composite filter's correlation plane data. In particular, we would like to determine not only whether or not we are viewing a training image, but, in the former case, we would like to determine which training image is being viewed. This second problem is investigated using traditional M-ary hypothesis testing techniques.

Hall, Eric B.

Learning from examples - Generation and evaluation of decision trees for software resource analysis

A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

Selby, Richard W.

Studies of optical and biological properties of terrestrial land cover using multispectral linear array technology

A series of experiments to study the optical and biological properties of terrestrial land cover are planned for late 1987 using a six-channel imaging spectroradiometer based on newly developed multispectral linear array (MLA) detector technology. Data from selected portions of the Sahel and rain forests of Africa and South America will be used to delineate biomass classes and estimate spherical albedos. A spatial resolution of 15 meters in the four visible-near IR channels and 30 meters in two shortwave IR channels, including a 'new' channel centered at 1.24 micrometers when combined with a spectral width of 20 nm for all channels, will be used to investigate possible improvements in land cover classification. Technology demonstrations include a test of data compression on data quality, the first spaceborne utilization of short wave infrared Schottky barrier Pd2Si detector arrays, and the use of close-butted, multi-array modules with attached spectral filters.

Barnes, W. L.

Real-valued composite filters for correlation-based optical pattern recognition

Advances in the technology of optical devices such as spatial light modulators (SLMs) have influenced the research and growth of optical pattern recognition. In the research leading to this report, the design of real-valued composite filters that can be implemented using currently available SLMs for optical pattern recognition and classification was investigated. The design of real-valued minimum average correlation energy (RMACE) filter was investigated. Proper selection of the phase of the output response was shown to reduce the correlation energy. The performance of the filter was evaluated using computer simulations and compared with the complex filters. It was found that the performance degraded only slightly. Continuing the above investigation, the design of a real filter that minimizes the output correlation energy and the output variance due to noise was developed. Simulation studies showed that this filter had better tolerance to distortion and noise compared to that of the RMACE filter. Finally, the space domain design of RMACE filter was developed and implemented on the computer. It was found that the sharpness of the correlation peak was slightly reduced but the filter design was more computationally efficient than the complex filter.

Rajan, P. K.

Long-Term Evaluation of Landsat 9 Oli Data Product Uniformity at Focal Plane Module-Boundaries Using Earth Scenes

The uniformity performance characteristic in remote sensing data products is a metric that helps evaluate how an image accurately represents radiometric responses to geophysical variability at the Earth’s surface or within the atmosphere. These uniformity attributes are used in Earth remote sensing science applications such as investigating water quality, land-cover/land-use classifications, and crop health assessments. To ensure these applications perform effectively, it is crucial to maintain and regularly assess the uniformity of calibrated remote sensing data products. In the Landsat missions, data from the onboard radiometric reference Solar diffuser device are used as the standard approach to derive the calibration parameters, ensuring the maintenance of both absolute radiance and radiometric uniformity through quarterly updates. This publication presents an alternative approach that leverages Earth scene data to assess the on-orbit uniformity performance of the Landsat 9 (L9) mission. The analysis characterizes uniformity at a specific set of spatial positions (the focal-plane boundary zones) that are intrinsic to the Operational Land Imager (OLI) focal plane design. By employing these Earth data statistics, the article further explores the temporal trends in the radiometric uniformity results. The results shown in this article demonstrate that for pushbroom imaging design systems with staggered sensor chip focal plane architectures, the co-registered pixels, i.e., overlapping measurements of the same ground target viewed by different detectors, offer a self-contained mechanism for assessing product uniformity. Remarkably, this alternative approach achieves a level of radiometric quality comparable to that delivered by a stable, well-characterized onboard Solar diffuser calibration device. The findings demonstrate the potential and capability of such Earth scene statistics in maintaining radiometric uniformity in calibrated data products to better than 1% (1-sigma) throughout the mission’s operational lifetime.

trend

Critical Software for Human Spaceflight

The NASA Orion vehicle that will fly to the moon in the next years is propelled along its mission by the European Service Module (ESM), developed by ESA and its prime contractor Airbus Defense and Space. This paper describes the development of the Propulsion Drive Electronics (PDE) Software that provides the interface between the propulsion hardware of the European Service Module with the Orion flight computers, and highlights the challenges that have been faced during the development. Particularly, the specific aspects relevant to Human Spaceflight in an international cooperation are presented, as the compliance to both European and US standards and the software criticality classification to the highest category A. An innovative aspect of the PDE SW is its Time- Triggered Ethernet interface with the Orion Flight Computers, which has never been flown so far on any European spacecraft. Finally the verification aspects are presented, applying the most exigent quality requirements defined in the European Cooperation for Space Standardization (ECSS) standards such as the structural coverage analysis of the object code and the recourse to an independent software verification and validation activity carried on in parallel by a different team.

Preden, Antonio

Product Assurance for Spaceflight Hardware

This report contains information about the tasks I have completed and the valuable experience I have gained at NASA. The report is divided into two different sections followed by a program summary sheet. The first section describes the two reports I have completed for the Office of Mission Assurance (OMA). I describe the approach and the resources and facilities used to complete each report. The second section describes my experience working in the Receipt Inspection/Quality Assurance Lab (RI/QA). The first report described is a Product Assurance Plan for the Gas Permeable Polymer Materials (GPPM) mission. The purpose of the Product Assurance Plan is to define the various requirements which are to be met through completion of the GPPM mission. The GPPM experiment is a space payload which will be flown in the shuttle's SPACEHAB module. The experiment will use microgravity to enable production of complex polymeric gas permeable materials. The second report described in the first section is a Fracture Analysis for the Mir Environmental Effects Payload (MEEP). The Fracture Analysis report is a summary of the fracture control classifications for all structural elements of the MEEP. The MEEP hardware consists of four experiment carriers, each of which contains an experiment container holding a passive experiment. The MEEP hardware will be attached to the cargo bay of the space shuttle. It will be transferred by Extravehicular Activity and mounted on the Mir space station. The second section of this report describes my experiences in the RVQA lab. I listed the different equipment I used at the lab and their functions. I described the extensive inspection process that must be completed for spaceflight hardware. Included, at the end of this section, are pictures of most of the equipment used in the lab. There is a summary sheet located at the end of this report. It briefly describes the valuable experience I have gained at NASA this summer and what I will be able to take with me as I return to college. I briefly discuss the experiences I mentioned in the previous three paragraphs along with training classes I attended and courses I completed at the Learning Lab.

Monroe, Mike

Developing Coastal Surface Roughness Maps Using ASTER and QuickBird Data Sources

This viewgraph presentation regards one element of a larger project on the integration of NASA science models and data into the Hazards U.S. Multi-Hazard (HAZUS-MH) Hurricane module for hurricane damage and loss risk assessment. HAZUS-MH is a decision support tool being developed by the National Institute of Building Sciences for the Federal Emergency Management Agency (FEMA). It includes the Hurricane Module, which employs surface roughness maps made from National Land Cover Data (NLCD) maps to estimate coastal hurricane wind damage and loss. NLCD maps are produced and distributed by the U.S. Geological Survey. This presentation discusses an effort to improve upon current HAZUS surface roughness maps by employing ASTER multispectral classifications with QuickBird "ground reference" imagery.

Spruce, Joe

S-154 in the Large Magellanic Cloud - Spectral evolution from a luminous Fe II variable to a symbiotic-like star

The evolution of the emission-line Star S-154, between February and December 1988, from a low-excitation 'Fe II star' into a high-excitation state that resembles symbiotic stars, is traced. It is inferred that the spectral type of central stars do not always dominate the physical conditions in the circumstellar material and thereby determine the nebular classification. The membership of S-154 in the LMC was confirmed with a radial velocity measurement of +274 km/s. The historical light curve (1880-1990) obtained from 346 photograph plates of the Harvard Plate Library exhibits about 4 mag of variations, with an MB range of -6 to -2. No evidence was found for coherent modulations that would represent the orbital period of a symbiotic binary.

Remillard, R. A.

Evolution of EF-hand calcium-modulated proteins. II. Domains of several subfamilies have diverse evolutionary histories

In the first report in this series we described the relationships and evolution of 152 individual proteins of the EF-hand subfamilies. Here we add 66 additional proteins and define eight (CDC, TPNV, CLNB, LPS, DGK, 1F8, VIS, TCBP) new subfamilies and seven (CAL, SQUD, CDPK, EFH5, TPP, LAV, CRGP) new unique proteins, which we assume represent new subfamilies. The main focus of this study is the classification of individual EF-hand domains. Five subfamilies--calmodulin, troponin C, essential light chain, regulatory light chain, CDC31/caltractin--and three uniques--call, squidulin, and calcium-dependent protein kinase--are congruent in that all evolved from a common four-domain precursor. In contrast calpain and sarcoplasmic calcium-binding protein (SARC) each evolved from its own one-domain precursor. The remaining 19 subfamilies and uniques appear to have evolved by translocation and splicing of genes encoding the EF-hand domains that were precursors to the congruent eight and to calpain and to SARC. The rates of evolution of the EF-hand domains are slower following formation of the subfamilies and establishment of their functions. Subfamilies are not readily classified by patterns of calcium coordination, interdomain linker stability, and glycine and proline distribution. There are many homoplasies indicating that similar variants of the EF-hand evolved by independent pathways.

Non-NASA Center

Comparison of Signals from Gravitational Wave Detectors with Instantaneous Time-Frequency Maps

Gravitational wave astronomy relies on the use of multiple detectors, so that coincident detections may distinguish real signals from instrumental artifacts, and also so that relative timing of signals can provide the sky position of sources. We show that the comparison of instantaneous time-frequency and time-amplitude maps provided by the Hilbert-Huang Transform (HHT) can be used effectively for relative signal timing of common signals, to discriminate between the case of identical coincident signals and random noise coincidences and to provide a classification of signals based on their time-frequency trajectories. The comparison is done with a X(sup 2) goodness-of~fit method which includes contributions from both the instantaneous amplitude and frequency components of the HHT to match two signals in the time domain. This approach naturally allows the analysis of waveforms with strong frequency modulation.

Stroeer, A.

State Predictor of Classification Cognitive Engine Applied to Channel Fading

This study presents the application of machine learning (ML) to a space-to-ground communication link, showing how ML can be used to detect the presence of detrimental channel fading. Using this channel state information, the communication link can be used more efficiently by reducing the amount of lost data during fading. The motivation for this work is based on channel fading observed during on-orbit operations with NASA's Space Communication and Navigation (SCaN) testbed on the International Space Station (ISS). This paper presents the process to extract a target concept (fading and not-fading) from the raw data. The pre-processing and data exploration effort is explained in detail, with a list of assumptions made for parsing and labelling the dataset. The model selection process is explained, specifically emphasizing the benefits of using an ensemble of algorithms with majority voting for binary classification of the channel state. Experimental results are shown, highlighting how an end-to-end communication system can utilize knowledge of the channel fading status to identity fading and take appropriate action. With a laboratory testbed to emulate channel fading, the overall performance is compared to standard adaptive methods without fading knowledge, such as adaptive coding and modulation.

Fading

Neurosymbolic Hybrid Approach to Driver Collision Warning

There are two main algorithmic approaches to autonomous driving systems: (1) An end-to-end system in which a single deep neural network learns to map sensory input directly into appropriate warning and driving responses. (2) A mediated hybrid recognition system in which a system is created by combining independent modules that detect each semantic feature. While some researchers believe that deep learning can solve any problem, others believe that a more engineered and symbolic approach is needed to cope with complex environments with less data. Deep learning alone has achieved state-of-the-art results in many areas, from complex gameplay to predicting protein structures. In particular, in image classification and recognition, deep learning models have achieved accuracies as high as humans. But sometimes it can be very difficult to debug if the deep learning model doesn't work. Deep learning models can be vulnerable and are very sensitive to changes in data distribution. Generalization can be problematic. It's usually hard to prove why it works or doesn't. Deep learning models can also be vulnerable to adversarial attacks. Here, we combine deep learning-based object recognition and tracking with an adaptive neurosymbolic network agent, called the Non-Axiomatic Reasoning System (NARS), that can adapt to its environment by building concepts based on perceptual sequences. We achieved an improved intersection-over-union (IOU) object recognition performance of 0.65 in the adaptive retraining model compared to IOU 0.31 in the COCO data pre-trained model. We improved the object detection limits using RADAR sensors in a simulated environment, and demonstrated the weaving car detection capability by combining deep learning-based object detection and tracking with a neurosymbolic model.

Wang, Pei