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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 109 records · Page 6

Nuclear Science Symposium, 26th and Symposium on Nuclear Power Systems, 11th, San Francisco, Calif., October 17-19, 1979, Proceedings

The paper covers the studies presented on nuclear science and nuclear power systems symposiums. The studies deal with nuclear radiation detectors, nuclear circuits and systems, space and medical instrumentation, as well as with environmental and reactor instrumentation. Data preprocessing and acquisition are discussed. Emphasis is placed on the engineered safety features of nuclear systems.

Kerns, C. R.↗

Data Projection of the High Temperature Electrolysis System in the Dynamic Energy Transport and Integration Laboratory using Dynamic System Scaling

For nuclear power to be flexible in a functioning Integrated Energy System (IES), excess produced heat must be stored or utilized during times of low power demand to ensure a load factor of 1 while load balancing. The Dynamic Energy Transport and Integration Laboratory (DETAIL) is one facility that is under development to emulate IES conditions on the engineering-scale, planned to conduct virtual real time operations with industry-scale facilities, and is currently testing thermal storage and high temperature electrolysis. As part of the study to develop a method to preprocess input signals or postprocess output signals between systems of different scales via Dynamical System Scaling (DSS), the current research is one of the continued efforts branching from the data projection activity conducted for the Thermal Energy Distribution System and currently engages the High Temperature Electrolysis (HTE) System in DETAIL. The HTE SOEC electrical, fluid, and thermal dynamics Figure of Merits (FOM) were identified, governing equations and closure relations were successfully scaled, and relations between FOM scaling ratios were determined. Setting the scaling objectives to reform existing data to project a data set that doubly accelerated the electrolysis process while preserving the produced amount of hydrogen was generated for the full transient. The calculated boundary conditions were inlet temperature, stack current, and inlet steam mass flow rate at 1470 K, 121.1 A, and 1.886 g/s, respectively. The research outcomes demonstrated an output signal postprocessing case accelerating the hydrogen production without changing geometry, number of cells, and partial pressures.

08 HYDROGEN↗

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

Fayyad, Usama M.↗

Multichannel Phase and Power Detector

An electronic signal-processing system determines the phases of input signals arriving in multiple channels, relative to the phase of a reference signal with which the input signals are known to be coherent in both phase and frequency. The system also gives an estimate of the power levels of the input signals. A prototype of the system has four input channels that handle signals at a frequency of 9.5 MHz, but the basic principles of design and operation are extensible to other signal frequencies and greater numbers of channels. The prototype system consists mostly of three parts: An analog-to-digital-converter (ADC) board, which coherently digitizes the input signals in synchronism with the reference signal and performs some simple processing; A digital signal processor (DSP) in the form of a field-programmable gate array (FPGA) board, which performs most of the phase- and power-measurement computations on the digital samples generated by the ADC board; and A carrier board, which allows a personal computer to retrieve the phase and power data. The DSP contains four independent phase-only tracking loops, each of which tracks the phase of one of the preprocessed input signals relative to that of the reference signal (see figure). The phase values computed by these loops are averaged over intervals, the length of which is chosen to obtain output from the DSP at a desired rate. In addition, a simple sum of squares is computed for each channel as an estimate of the power of the signal in that channel. The relative phases and the power level estimates computed by the DSP could be used for diverse purposes in different settings. For example, if the input signals come from different elements of a phased-array antenna, the phases could be used as indications of the direction of arrival of a received signal and/or as feedback for electronic or mechanical beam steering. The power levels could be used as feedback for automatic gain control in preprocessing of incoming signals. For another example, the system could be used to measure the phases and power levels of outputs of multiple power amplifiers to enable adjustment of the amplifiers for optimal power combining.

Li, Samuel↗

Herbaceous Feedstock 2020 (State of Technology Report)

The Energy Independence and Security Act (EISA) of 2007 required a minimum supply of 36 million gallons of renewable fuels per year by 2022. In order to achieve these goals, the Bioenergy Technologies Office (BETO) has set cost and technology targets for producing advanced and cellulosic biofuels. One of the targets is to validate feedstock supply infrastructures and systems with 90% overall operating effectiveness and field-to-reactor throat delivered cost less than $85.51/dry ton (2016). As stated by the 2017 Multi-Year Program Plan (DOE 2017), the research and development focus of the Feedstock Technologies (FT) platform is reducing the cost, improving the supply chain logistic efficiency, improving biomass quality, and increasing the supply volume. In addition, BETO oversees annual State of Technology (SOT) report that assesses current technologies that are relevant to BETO’s targets based on actual data and experimental results. Feedstocks are essential to achieving BETO goals because the cost, quality, and quantity of feedstock available and accessible at any given time limit the maximum volume of biofuels that can be produced. In accordance with the 2016 Multi-Year Program Plan (DOE 2016a), FT focuses on (1) reducing the delivered cost of sustainably produced biomass, (2) preserving and improving the physical and chemical quality parameters of harvested biomass to meet the individual needs of biorefineries and other biomass users, and (3) expanding the quantity of feedstock materials accessible to the bioenergy industry. This is done by identifying, developing, demonstrating, and validating efficient and economical integrated systems for harvest and collection, storage, handling, transport, and preprocessing raw biomass from a variety of crops to reliably deliver the required supplies of high-quality, affordable feedstocks to biorefineries as the industry expands. The elements of cost, quality, and quantity are key considerations when developing advanced feedstock supply concepts and systems (DOE 2016a).

09 BIOMASS FUELS↗

Development of a quantitative basis for selection of spectral features in a vegetation monitoring system

The development of an objective methodology for evaluation of alternative Landsat data preprocessing options, spectral transform features for monitoring vegetation, and feature summarization algorithms is presented. Based on estimates of spectral separability between a target class and its confusion classes, analysis of variance techniques are used to evaluate potential design options for large scale vegetation monitoring systems. Case studies are presented for early season and through the season spring small grains separation and for barley/other spring small grains separation. It is concluded that a basis for efficient, objective selection among alternative feature extraction approaches has been established for the large scale vegetation mapping/inventory problem. Although the approach has been demonstrated for the unitemporal class separability case, extensions to the multitemporal case are under development.

Phinney, D. E.↗

Future interactive data systems

The information and control requirements of the investigator-users of future free-flying, platform-based, or Space Station-based scientific experiments are assessed, and the implications of these requirements for the design of the information systems are discussed. The principal requirements include near-real-time interaction with the payload, distributed or remote payload command and control, rapid access to quick-look data, flexibility of payload command sequences, on-demand uplink-downlink availability, system transparency, and modular design to facilitate replacement of system components. Current developments in systems architecture such as increased use of onboard microprocessors to select and preprocess data and transmit autonomous streams directly to the user, standardization of interfaces, and the NASA Tracking and Data Relay Satellite System are characterized, and block diagrams of present and future systems are provided.

Bracken, P. A.↗

Morphological evidence for local microcircuits in rat vestibular maculae

Previous studies suggested that intramacular, unmyelinated segments of vestibular afferent nerve fibers and their large afferent endings (calyces) on type I hair cells branch. Many of the branches (processes) contain vesicles and are presynaptic to type II hair cells, other processes, intramacular nerve fibers, and calyces. This study used serial section transmission electron microscopy and three-dimensional reconstruction methods to document the origins and distributions of presynaptic processes of afferents in the medial part of the adult rat utricular macula. The ultrastructural research focused on presynaptic processes whose origin and termination could be observed in a single micrograph. Results showed that calyces had 1) vesiculated, spine-like processes that invaginated type I cells and 2) other, elongate processes that ended on type II cells pre- as well as postsynaptically. Intramacular, unmyelinated segments of afferent nerve fibers gave origin to branches that were presynaptic to type II cells, calyces, calyceal processes, and other nerve fibers in the macula. Synapses with type II cells occurred opposite subsynaptic cisternae (C synapses); all other synapses were asymmetric. Vesicles were pleomorphic but were differentially distributed according to process origin. Small, clear-centered vesicles, approximately 40-60 nm in diameter, predominated in processes originating from afferent nerve fibers and basal parts of calyces. Larger vesicles approximately 70-120 nm in diameter having approximately 40-80 nm electron-opaque cores were dominant in processes originating from the necks of calyces. Results are interpreted to indicate the existence of a complex system of intrinsic feedforward (postsynaptic)-feedback (presynaptic) connections in a network of direct and local microcircuits. The morphological findings support the concept that maculae dynamically preprocess linear acceleratory information before its transmission to the central nervous system.

NASA Center ARC↗

Significant techniques in the processing and interpretation of ERTS-1 data

The discipline oriented investigations underway at the Johnson Space Center (JSC) using ERTS-1 data provide an appropriate framework for the systematic evaluation of the various elements comprising a prototype multispectral data processing and analysis system. In particular such a system may be thought of as the integration of: (1) a preprocessing subsystem; (2) a spectral clustering subsystem, (3) a correlation and classification subsystem; (4) mensuration subsystem; and (5) an information management subsystem. Specific elements of this system are already operational at JSC. It is in the context of this system that technique development and application is being pursued at JSC. Aircraft, ERTS and EREP data will be utilized to refine the subsystem elements for each of the data acquisition systems or system combinations that are optimally suited for a specific Earth Resources application. The techniques reported are those that have been developed to date during the utilization of ERTS-1 data in this processing and analysis system.

Cousin, S. B.↗

Constrained optimization of image restoration filters.

A preprocessing method to correct for image degradation is proposed which can be thought of as a generalization and extension of previous work by Smith (1966) and Stuller (1972). This method accomodates the problem of noncircularly symmetric imaging system point-spread functions, provides for controlled extent of the preprocessing filter to minimize distortion due to transients resulting from truncation errors and edge effects, can be used with various kinds of system noise, and can be readily extended to provide constraint of other system parameters. The analysis relates to a line-scanner system, although it is applicable in principle to many other system configurations.

Riemer, T. E.↗

Appendix B: Principles of computer processing of LANDSAT data

Computer processing facilitates extraction of information from every pixel by executing a variety of functional operations, called processed algorithms, in general or specialized routines. The best results are obtained when data from more than one multispectral band are used together. Multivariate tatistical analysis, computer tape characteristics, processing modes, and a choice of systems (batch or interactive) are discussed. The major operations in computer processing elaborated include: preprocessing, enhancement, effects of rationing, and classification. Techniques for multisource data correlation are considered with emphasis on geobased systems.

Source record↗

Satellite laser ranging work at the Goddard Space Flight Center

The paper describes the satellite laser ranging system at the Goddard Space Flight Center, its range and accuracy capabilities, and planned improvements for future systems. Major subsystems are described, including the laser, optical/mechanical, receiver, computer/software, timing, and laser data preprocessing subsystems. Operational considerations are examined, with attention given the mobile station layout, manpower requirements, and transportability. System performance is considered, with emphasis on system accuracy (calibration, stability, clock synchronization, atmospheric propagation correction) and range capability.

Mcgunigal, T. E.↗

Super resolution for root imaging

Premise High‐resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above‐ground plant attributes. However, the acquisition of high‐resolution images of plant roots is more challenging than above‐ground data collection. An effective super‐resolution (SR) algorithm is therefore needed for overcoming the resolution limitations of sensors, reducing storage space requirements, and boosting the performance of subsequent analyses. Methods We propose an SR framework for enhancing images of plant roots using convolutional neural networks. We compare three alternatives for training the SR model: (i) training with non‐plant‐root images, (ii) training with plant‐root images, and (iii) pretraining the model with non‐plant‐root images and fine‐tuning with plant‐root images. The architectures of the SR models were based on two state‐of‐the‐art deep learning approaches: a fast SR convolutional neural network and an SR generative adversarial network. Results In our experiments, we observed that the SR models improved the quality of low‐resolution images of plant roots in an unseen data set in terms of the signal‐to‐noise ratio. We used a collection of publicly available data sets to demonstrate that the SR models outperform the basic bicubic interpolation, even when trained with non‐root data sets. Discussion The incorporation of a deep learning–based SR model in the imaging process enhances the quality of low‐resolution images of plant roots. We demonstrate that SR preprocessing boosts the performance of a machine learning system trained to separate plant roots from their background. Our segmentation experiments also show that high performance on this task can be achieved independently of the signal‐to‐noise ratio. We therefore conclude that the quality of the image enhancement depends on the desired application.

Ruiz‐Munoz, Jose F.↗

Forecasting of in situ electron energy loss spectroscopy

Abstract Forecasting models are a central part of many control systems, where high-consequence decisions must be made on long latency control variables. These models are particularly relevant for emerging artificial intelligence (AI)-guided instrumentation, in which prescriptive knowledge is needed to guide autonomous decision-making. Here we describe the implementation of a long short-term memory model (LSTM) for forecasting in situ electron energy loss spectroscopy (EELS) data, one of the richest analytical probes of materials and chemical systems. We describe key considerations for data collection, preprocessing, training, validation, and benchmarking, showing how this approach can yield powerful predictive insight into order-disorder phase transitions. Finally, we comment on how such a model may integrate with emerging AI-guided instrumentation for powerful high-speed experimentation.

36 MATERIALS SCIENCE↗

ATS-6 - Preliminary results from the 13/18-GHz COMSAT Propagation Experiment

The 13/18-GHz COMSAT Propagation Experiment (CPE) is reviewed, the data acquisition and processing are discussed, and samples of preliminary results are presented. The need for measurements of both hydrometeor-induced attenuation statistics and diversity effectiveness is brought out. The facilitation of the experiment - CPE dual frequency and diversity site location, the CPE ground transmit terminals, the CPE transponder on Applications Technology Satellite-6 (ATS-6), and the CPE receive and data acquisition system - is briefly examined. The on-line preprocessing of the received signal is reviewed, followed by a discussion of the off-line processing of this database to remove signal fluctuations not due to hydrometeors. Finally, samples of the results of first-level analysis of the resultant data for the 18-GHz diversity site near Boston, Mass., and for the dual frequency 13/18-GHz site near Detroit, Mich., are presented and discussed.

Hyde, G.↗

An investigation for the development of an integrated optical data preprocessor

The successful fabrication and demonstration of an integrated optical circuit designed to perform a parallel processing operation by utilizing holographic subtraction to simultaneously compare N analog signal voltages with N predetermined reference voltages is summarized. The device alleviates transmission, storage and processing loads of satellite data systems by performing, at the sensor site, some preprocessing of data taken by remote sensors. Major accomplishments in the fabrication of integrated optics components include: (1) fabrication of the first LiNbO3 waveguide geodesic lens; (2) development of techniques for polishing TIR mirrors on LiNbO3 waveguides; (3) fabrication of high efficiency metal-over-photoresist gratings for waveguide beam splitters; (4) demonstration of high S/N holographic subtraction using waveguide holograms; and (5) development of alignment techniques for fabrication of integrated optics circuits. Important developments made in integrated optics are the discovery and suggested use of holographic self-subtraction in LiNbO3, development of a mathematical description of the operating modes of the preprocessor, and the development of theories for diffraction efficiency and beam quality of two dimensional beam defined gratings.

Verber, C. M.↗

Using Hyperspectral Imagery to Identify Turfgrass Stresses

The use of a form of remote sensing to aid in the management of large turfgrass fields (e.g. golf courses) has been proposed. A turfgrass field of interest would be surveyed in sunlight by use of an airborne hyperspectral imaging system, then the raw observational data would be preprocessed into hyperspectral reflectance image data. These data would be further processed to identify turfgrass stresses, to determine the spatial distributions of those stresses, and to generate maps showing the spatial distributions. Until now, chemicals and water have often been applied, variously, (1) indiscriminately to an entire turfgrass field without regard to localization of specific stresses or (2) to visible and possibly localized signs of stress for example, browning, damage from traffic, or conspicuous growth of weeds. Indiscriminate application is uneconomical and environmentally unsound; the amounts of water and chemicals consumed could be insufficient in some areas and excessive in most areas, and excess chemicals can leak into the environment. In cases in which developing stresses do not show visible signs at first, it could be more economical and effective to take corrective action before visible signs appear. By enabling early identification of specific stresses and their locations, the proposed method would provide guidance for planning more effective, more economical, and more environmentally sound turfgrass-management practices, including application of chemicals and water, aeration, and mowing. The underlying concept of using hyperspectral imagery to generate stress maps as guides to efficient management of vegetation in large fields is not new; it has been applied in the growth of crops to be harvested. What is new here is the effort to develop an algorithm that processes hyperspectral reflectance data into spectral indices specific to stresses in turfgrass. The development effort has included a study in which small turfgrass plots that were, variously, healthy or subjected to a variety of controlled stresses were observed by use of a hand-held spectroradiometer. The spectroradiometer readings in the wavelength range from 350 to 1,000 nm were processed to extract hyperspectral reflectance data, which, in turn, were analyzed to find correlations with the controlled stresses. Several indices were found to be correlated with drought stress and to be potentially useful for identifying drought stress before visible symptoms appear.

Hutto, Kendall↗