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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Exploration of Planetary Terrains with a Legged Robot as a Scout Adjunct to a Rover

The Scorpion robot is an innovative, biologically inspired 8-legged walking robot. It currently runs a novel approach to control which utilizes a central pattern generator (CPG) and local reflex action for each leg. From this starting point we are proposing to both extend the system's individual capabilities and its capacity to function as a "scout", cooperating with a larger wheeled rover. For this purpose we propose to develop a distributed system architecture that extends the system's capabilities both in the direction of high level planning and execution in collaboration with a rover, and in the direction of force-feedback based low level behaviors that will greatly enhance its ability to walk and climb in rough varied terrains. The final test of this improved ability will be a rappelling experiment where the Scorpion explores a steep cliff side in cooperation with a rover that serves as both anchor and planner/executive.

Colombano, Silvano↗
NASA NTRS2005

Aircraft Fault Detection and Classification Using Multi-Level Immune Learning Detection

This work is an extension of a recently developed software tool called MILD (Multi-level Immune Learning Detection), which implements a negative selection algorithm for anomaly and fault detection that is inspired by the human immune system. The immunity-based approach can detect a broad spectrum of known and unforeseen faults. We extend MILD by applying a neural network classifier to identify the pattern of fault detectors that are activated during fault detection. Consequently, MILD now performs fault detection and identification of the system under investigation. This paper describes the application of MILD to detect and classify faults of a generic transport aircraft augmented with an intelligent flight controller. The intelligent control architecture is designed to accommodate faults without the need to explicitly identify them. Adding knowledge about the existence and type of a fault will improve the handling qualities of a degraded aircraft and impact tactical and strategic maneuvering decisions. In addition, providing fault information to the pilot is important for maintaining situational awareness so that he can avoid performing an action that might lead to unexpected behavior - e.g., an action that exceeds the remaining control authority of the damaged aircraft. We discuss the detection and classification results of simulated failures of the aircraft's control system and show that MILD is effective at determining the problem with low false alarm and misclassification rates.

Wong, Derek↗
NASA NTRS2018

Observations from Exploration of VTOL Urban Air Mobility Designs

NASA is exploring rotorcraft designs for VTOL air taxi operations, also known as urban air mobility (UAM) or on-demand mobility (ODM) applications. Several concept vehicles have been developed, intended to focus and guide NASA research activities in support of aircraft development for this emerging market. This paper summarizes the work conducted to date. To initially explore the broad design trade-space, three concept vehicles were designed: a quadrotor with electric propulsion; a side-by-side helicopter with hybrid propulsion; and a tiltwing with turbo-electric propulsion. Next a specific UAM mission was developed, accounting for the existing geography, population patterns, infrastructure, and weather in twenty-eight markets across the United States of America. Then in order to quantify the tradeoffs and performance targets necessary for practical implementation of the UAM vision, aircraft were designed to perform this mission, considering a range of aircraft types and propulsion system architectures: quadrotor aircraft, with turboshaft and all-electric propulsion; side-by-side aircraft, with turboshaft and all-electric propulsion; and lift+cruise aircraft with all-electric and turbo-electric propulsion. In examining these vehicles, performance targets and recurring technology themes emerged, which can guide investments in research and development within NASA, other government agencies, academia, and industry. In addition, results from the designs support observations about the trade-offs and key design decisions.

Observations from Exploration↗
NASA NTRS1999

Portable Parallel Programming for the Dynamic Load Balancing of Unstructured Grid Applications

The ability to dynamically adapt an unstructured -rid (or mesh) is a powerful tool for solving computational problems with evolving physical features; however, an efficient parallel implementation is rather difficult, particularly from the view point of portability on various multiprocessor platforms We address this problem by developing PLUM, tin automatic anti architecture-independent framework for adaptive numerical computations in a message-passing environment. Portability is demonstrated by comparing performance on an SP2, an Origin2000, and a T3E, without any code modifications. We also present a general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication pattern, with a goal to providing a global view of system loads across processors. Experiments on, an SP2 and an Origin2000 demonstrate the portability of our approach which achieves superb load balance at the cost of minimal extra overhead.

Biswas, Rupak↗
NASA NTRS1993

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

Lure, Y. M. Fleming↗
NASA NTRS1992

Automatic target recognition using a feature-based optical neural network

An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

Chao, Tien-Hsin↗
NASA NTRS1998

Future human bone research in space

Skylab crewmembers demonstrated negative calcium (Ca) balance reaching about -300 mg/day by flight day 84. Limited bone density (BMD) measurements documented that bone was not lost equally from all parts of the skeleton. Subsequent BMD studies during long duration Russian flights documented the regional extent of bone loss. These studies demonstrated mean losses in the spine, femur neck, trochanter, and pelvis of about 1%-1.6% with large differences between individuals as well as between bone sites in a given individual. Limited available data indicate postflight bone recovery occurred in some individuals, but may require several years for complete restoration. Long duration bedrest studies showed a similar pattern of bone loss and calcium balance (-180 mg/day) as spaceflight. During long duration bedrest, resorption markers were elevated, formation markers were unchanged, 1,25 vitamin D (VitD) and calcium absorption were decreased, and serum ionized Ca was increased. Although this information is a good beginning, additional spaceflight research is needed to assess architectural and subregional bone changes, elucidate mechanisms, and develop efficient as well as effective countermeasures. Space research poses a number of unique problems not encountered in ground-based laboratory research. Therefore, researchers contemplating human spaceflight research need to consider a number of unique problems related to spaceflight in their experimental design.

NASA Center JSC↗
NASA NTRS2007

Advances in Scanning Reflectarray Antennas Based on Ferroelectric Thin Film Phase Shifters for Deep Space Communications

Though there are a few examples of scanning phased array antennas that have flown successfully in space, the quest for low-cost, high-efficiency, large aperture microwave phased arrays continues. Fixed and mobile applications that may be part of a heterogeneous exploration communication architecture will benefit from the agile (rapid) beam steering and graceful degradation afforded by phased array antennas. The reflectarray promises greater efficiency and economy compared to directly-radiating varieties. Implementing a practical scanning version has proven elusive. The ferroelectric reflectarray, under development and described herein, involves phase shifters based on coupled microstrip patterned on Ba(x)Sr(1-x)TiO3 films, that were laser ablated onto LaAlO3 substrates. These devices outperform their semiconductor counterparts from X- through and K-band frequencies. There are special issues associated with the implementation of a scanning reflectarray antenna, especially one realized with thin film ferroelectric phase shifters. This paper will discuss these issues which include: relevance of phase shifter loss; modulo 2(pi) effects and phase shifter transient effects on bit error rate; scattering from the ground plane; presentation of a novel hybrid ferroelectric-semiconductor phase shifter; and the effect of mild radiation exposure on phase shifter performance.

Romanofsky, Robert R.↗
NASA NTRS1993

Optical implementation of a feature-based neural network with application to automatic target recognition

An optical neural network based on the neocognitron paradigm is introduced. A novel aspect of the architecture design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by feeding back the ouput of the feature correlator interatively to the input spatial light modulator and by updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved. A detailed system description is provided. Experimental demonstrations of a two-layer neural network for space-object discrimination is also presented.

Chao, Tien-Hsin↗
NASA NTRS1996

A Note on Interfacing Object Warehouses and Mass Storage Systems for Data Mining Applications

Data mining is the automatic discovery of patterns, associations, and anomalies in data sets. Data mining requires numerically and statistically intensive queries. Our assumption is that data mining requires a specialized data management infrastructure to support the aforementioned intensive queries, but because of the sizes of data involved, this infrastructure is layered over a hierarchical storage system. In this paper, we discuss the architecture of a system which is layered for modularity, but exploits specialized lightweight services to maintain efficiency. Rather than use a full functioned database for example, we use light weight object services specialized for data mining. We propose using information repositories between layers so that components on either side of the layer can access information in the repositories to assist in making decisions about data layout, the caching and migration of data, the scheduling of queries, and related matters.

Grossman, Robert L.↗
NASA NTRS2008

NASA Tech Briefs, June 2008

Topics covered include: Charge-Control Unit for Testing Lithium-Ion Cells; Measuring Positions of Objects Using Two or More Cameras; Lidar System for Airborne Measurement of Clouds and Aerosols; Radiation-Insensitive Inverse Majority Gates; Reduced-Order Kalman Filtering for Processing Relative Measurements; Spaceborne Processor Array; Instrumentation System Diagnoses a Thermocouple; Chromatic Modulator for a High-Resolution CCD or APS; Commercial Product Activation Using RFID; Cup Cylindrical Waveguide Antenna; Aerobraking Maneuver (ABM) Report Generator; ABM Drag_Pass Report Generator; Transformation of OODT CAS to Perform Larger Tasks; Visualization Component of Vehicle Health Decision Support System; Mars Reconnaissance Orbiter Uplink Analysis Tool; Problem Reporting System; G-Guidance Interface Design for Small Body Mission Simulation; DSN Scheduling Engine; Replacement Sequence of Events Generator; Force-Control Algorithm for Surface Sampling; Tool for Merging Proposals Into DSN Schedules; Micromachined Slits for Imaging Spectrometers; Fabricating Nanodots Using Lift-Off of a Nanopore Template; Making Complex Electrically Conductive Patterns on Cloth; Special Polymer/Carbon Composite Films for Detecting SO2; Nickel-Based Superalloy Resists Embrittlement by Hydrogen; Chemical Passivation of Li+-Conducting Solid Electrolytes; Organic/Inorganic Polymeric Composites for Heat-Transfer Reduction; Composite Cathodes for Dual-Rate Li-Ion Batteries; Improved Descent-Rate Limiting Mechanism; Alignment-Insensitive Lower-Cost Telescope Architecture; Micro-Resistojet for Small Satellites; Using Piezoelectric Devices to Transmit Power through Walls; Miniature Latching Valve; Apparatus for Sampling Surface Contamination; Novel Species of Non-Spore-Forming Bacteria; Chamber for Aerosol Deposition of Bioparticles; Hyperspectral Sun Photometer for Atmospheric Characterization and Vicarious Calibrations; Dynamic Stability and Gravitational Balancing of Multiple Extended Bodies; Simulation of Stochastic Processes by Coupled ODE-PDE; Cluster Inter-Spacecraft Communications; Genetic Algorithm Optimizes Q-LAW Control Parameters; Low-Impact Mating System for Docking Spacecraft; Non-Destructive Evaluation of Materials via Ultraviolet Spectroscopy; Gold-on-Polymer-Based Sensing Films for Detection of Organic and Inorganic Analytes in the Air; and Quantum-Inspired Maximizer.

Source record↗
NASA NTRS1988

Distributed cooperating processes in a mobile robot control system

A mobile inspection robot has been proposed for the NASA Space Station. It will be a free flying autonomous vehicle that will leave a berthing unit to accomplish a variety of inspection tasks around the Space Station, and then return to its berth to recharge, refuel, and transfer information. The Flying Eye robot will receive voice communication to change its attitude, move at a constant velocity, and move to a predefined location along a self generated path. This mobile robot control system requires integration of traditional command and control techniques with a number of AI technologies. Speech recognition, natural language understanding, task and path planning, sensory abstraction and pattern recognition are all required for successful implementation. The interface between the traditional numeric control techniques and the symbolic processing to the AI technologies must be developed, and a distributed computing approach will be needed to meet the real time computing requirements. To study the integration of the elements of this project, a novel mobile robot control architecture and simulation based on the blackboard architecture was developed. The control system operation and structure is discussed.

Skillman, Thomas L., Jr.↗
NASA NTRS1997

Composition of the carbohydrate granules of the cyanobacterium, Cyanothece sp. strain ATCC 51142

Cyanothece sp. strain ATCC 51142 is an aerobic, unicellular, diazotrophic cyanobacterium that temporally separates O2-sensitive N2 fixation from oxygenic photosynthesis. The energy and reducing power needed for N2 fixation appears to be generated by an active respiratory apparatus that utilizes the contents of large interthylakoidal carbohydrate granules. We report here on the carbohydrate and protein composition of the granules of Cyanothece sp. strain ATCC 51142. The carbohydrate component is a glucose homopolymer with branches every nine residues and is chemically identical to glycogen. Granule-associated protein fractions showed temporal changes in the number of proteins and their abundance during the metabolic oscillations observed under diazotrophic conditions. There also were temporal changes in the protein pattern of the granule-depleted supernatant fractions from diazotrophic cultures. None of the granule-associated proteins crossreacted with antisera directed against several glycogen-metabolizing enzymes or nitrogenase, although these proteins were tentatively identified in supernatant fractions. It is suggested that the granule-associated proteins are structural proteins required to maintain a complex granule architecture.

NASA Discipline Cell Biology↗
NASA NTRSDate not supplied

Bi-axial Strain Measurement of Woven-Webbing Inflatable Structures Using Digital Image Correlation with RGB Filtering

Crewed inflatable softgoods structures can significantly reduce launch volume for habitable pressure vessels. To ensure the operational safety of these structures, NASA has developed an extensive testing program to evaluate the structural capability on ground test articles. This paper will discuss a current challenge faced by test engineers evaluating the strain of large-scale inflatable space structures during ground testing. Namely, the difficulty that arises using monochrome digital image correlation (DIC) to evaluate bi-axial strain for woven-webbing restraint layers. This report provides insight into a novel method of photogrammetry using red-green-blue (RGB) filtering in conjunction with DIC to evaluate the strain in each direction on a test article experiencing bi-directional strain. To evaluate this concept, a uniaxial tensile test was performed that represented a biaxial woven architecture using orthogonally interfaced straps. The resulting analysis demonstrates promise for this novel approach for isolating a specific region and direction of strain, reducing the effects of straps not in the area of interest, while allowing for a larger region of analysis. Moreover, it was shown that the application of a white basecoat prior to applying photogrammetry patterns significantly reduced data loss while performing RGB filtered DIC.

inflatable↗
NASA NTRS1996

The NIST Real-Time Control System (RCS): A Reference Model Architecture for Computational Intelligence

The Real-time Control System (RCS) developed at NIST and elsewhere over the past two decades defines a reference model architecture for design and analysis of complex intelligent control systems. The RCS architecture consists of a hierarchically layered set of functional processing modules connected by a network of communication pathways. The primary distinguishing feature of the layers is the bandwidth of the control loops. The characteristic bandwidth of each level is determined by the spatial and temporal integration window of filters, the temporal frequency of signals and events, the spatial frequency of patterns, and the planning horizon and granularity of the planners that operate at each level. At each level, tasks are decomposed into sequential subtasks, to be performed by cooperating sets of subordinate agents. At each level, signals from sensors are filtered and correlated with spatial and temporal features that are relevant to the control function being implemented at that level.

Albus, James S.↗
NASA NTRS2001

Processing bottlenecks in dual-task performance: structural limitation or strategic postponement?

Recent evidence indicates that a central bottleneck causes much of the slowing that occurs when two tasks are performed at the same time. This bottleneck might reflect a structural limitation inherent in the cognitive architecture. Alternatively, the bottleneck might reflect strategic (i.e., voluntary) postponement, induced by instructions to emphasize one task over the other. To distinguish structural limitations from strategic postponement, we examine a new paradigm in which subjects are told to place equal emphasis on both tasks and to emit both responses at about the same time. An experiment using this paradigm demonstrated patterns of interference that cannot easily be attributed to strategic postponement, preparation effects, or conflicts in response production. The data conform closely to the predictions of structural central bottleneck models.

Attention↗
NASA NTRS1986

Optical processing and Space Station automation

Optical information processing research aimed at Space Station automation applications is reviewed. The emphasis of the NASA Ames Research Center program is on intelligent optical pattern recognition and optical control processing. Attention is given to the primary functions of an overall scene understanding system: distortion-invariant optical feature generation, dimensionality reduction, object classification, and contextual information processing. A method of using synthetic discriminant functions to facilitate learning in a high-speed optical correlator is described. A discussion is presented of candidate analog and digital architectures for the optical implementation of state-estimation algorithms needed for the control of high-dimension dynamic systems. The multivariate system chosen for the optical control technology demonstration - a segmented, adaptive mirror and interferometrically based wavefront sensor - is also described.

Ennis, D. J.↗