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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

A computer controlled signal preprocessor for laser fringe anemometer applications

The operation of most commercially available laser fringe anemometer (LFA) counter-processors assumes that adjustments are made to the signal processing independent of the computer used for reducing the data acquired. Not only does the researcher desire a record of these parameters attached to the data acquired, but changes in flow conditions generally require that these settings be changed to improve data quality. Because of this limitation, on-line modification of the data acquisition parameters can be difficult and time consuming. A computer-controlled signal preprocessor has been developed which makes possible this optimization of the photomultiplier signal as a normal part of the data acquisition process. It allows computer control of the filter selection, signal gain, and photo-multiplier voltage. The raw signal from the photomultiplier tube is input to the preprocessor which, under the control of a digital computer, filters the signal and amplifies it to an acceptable level. The counter-processor used at Lewis Research Center generates the particle interarrival times, as well as the time-of-flight of the particle through the probe volume. The signal preprocessor allows computer control of the acquisition of these data.Through the preprocessor, the computer also can control the hand shaking signals for the interface between itself and the counter-processor. Finally, the signal preprocessor splits the pedestal from the signal before filtering, and monitors the photo-multiplier dc current, sends a signal proportional to this current to the computer through an analog to digital converter, and provides an alarm if the current exceeds a predefined maximum. Complete drawings and explanations are provided in the text as well as a sample interface program for use with the data acquisition software.

Oberle, Lawrence G.↗
DOE OSTI2015

Towards intelligent diagnostic system employing integration of mathematical and engineering model

The development of medical diagnostic system has been one of the main research fields during years. The goal of the medical diagnostic system is to place a nosological system that could ease the diagnostic evaluation normally performed by scientists and doctors. Efficient diagnostic evaluation is essentials and requires broad knowledge in order to improve conventional diagnostic system. Several approaches on developing the medical diagnostic system have been designed and tested since the earliest 60s. Attempts on improving their performance have been made which utilizes the fields of artificial intelligence, statistical analyses, mathematical model and engineering theories. With the availability of the microcomputer and software development as well as the promising aforementioned fields, medical diagnostic prototypes could be developed. In general, the medical diagnostic system consists of several stages, namely the 1) data acquisition, 2) feature extraction, 3) feature selection, and 4) classifications stages. Data acquisition stage plays an important role in converting the inputs measured from the real world physical conditions to the digital numeric values that can be manipulated by the computer system. One of the common medical inputs could be medical microscopic images, radiographic images, magnetic resonance image (MRI) as well as medical signals such as electrocardiogram (ECG) and electroencephalogram (EEG). Normally, the scientist or doctors have to deal with myriad of data and redundant to be processed. In order to reduce the complexity of the diagnosis process, only the significant features of the raw data such as peak value of the ECG signal or size of lesion in the mammogram images will be extracted and considered in the subsequent stages. Mathematical models and statistical analyses will be performed to select the most significant features to be classified. The statistical analyses such as principal component analysis and discriminant analysis as well as mathematical model of clustering technique have been widely used in developing the medical diagnostic systems. The selected features will be classified using mathematical models that embedded engineering theory such as artificial intelligence, support vector machine, neural network and fuzzy-neuro system. These classifiers will provide the diagnostic results without human intervention. Among many publishable researches, several prototypes have been developed namely NeuralPap, Neural Mammo, and Cervix Kit. The former system (NeuralPap) is an automatic intelligent diagnostic system for classifying and distinguishing between the normal and cervical cancerous cells. Meanwhile, the Cervix Kit is a portable Field-programmable gate array (FPGA)-based cervical diagnostic kit that could automatically diagnose the cancerous cell based on the images obtained during sampling test. Besides the cervical diagnostic system, the Neural Mammo system is developed to specifically aid the diagnosis of breast cancer using a fine needle aspiration image.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

The data acquisition system of the LZ dark matter detector: FADR

The Data Acquisition System (DAQ) for the LUX-ZEPLIN (LZ) dark matter detector is described. The signals from 745 PMTs, distributed across three subsystems, are sampled with 100-MHz 32-channel digitizers (DDC-32s). A basic waveform analysis is carried out on the on-board Field Programmable Gate Arrays (FPGAs) to extract information about the observed scintillation and electroluminescence signals. This information is used to determine if the digitized waveforms should be preserved for offline analysis. The system is designed around the Kintex-7 FPGA. In addition to digitizing the PMT signals and providing basic event selection in real time, the flexibility provided by the use of FPGAs allows us to monitor the performance of the detector and the DAQ in parallel to normal data acquisition. Furthermore, the hardware and software/firmware of this FPGA-based Architecture for Data acquisition and Realtime monitoring (FADR) are discussed and performance measurements are described.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1975

The COMSAT 13 and 18 GHz Propagation Experiment

The ATS-6 COMSAT Propagation Experiment was designed to gather statistical data on attenuation caused by rain and snow at 13 and 18 GHz. These data will be used to determine system design parameters for future communications satellite systems operating at frequencies above 10 GHz. The experiment used 25, 18 GHz, and 15, 13 GHz unattended ground transmitters at 25 locations in the eastern U.S. to transmit to the ATS-6. The ATS-6 transponder converts these carriers to frequencies around 4150 MHz and transmits these signals to the COMSAT large horn antenna/data acquisition and receiving facility at Andover, Me. This facility calibrates and digitally records each carrier once per second. These data have been processed and analyzed for the period from July to Nov. 2, 1972. Plans are being made to conduct the experiment in Europe and India during the 35 deg E longitude site phase of ATS-6 operations.

King, J. L.↗
DOE OSTI2024

Miniaturized Magnetoelastic Sensor System

This article describes the design, assembly, and implementation of a hand-held, magnetic-field-based sensor system that can be adapted for a variety of sensing applications. The miniaturized system is based on Chemical Identification by Magneto-Elastic Sensing (ChIMES) technology, which uses three concentric solenoid coils to wirelessly interrogate a sensor body comprised of a response material coupled to a magnetoelastic wire. The response material expands when it encounters a target, imposing mechanical stress on the wire and altering its magnetic permeability. The sensor bodies are passive, requiring no external power source, and they are small, measuring about 15 mm in length and 3.0 mm in diameter. Up to four sensor bodies can be configured as an evenly-spaced linear array. The sensor system operates by applying a low-frequency, current-stabilized, filtered triangle wave to a uniform-density excitation coil to switch the magnetic domains within the wire. Further, the responses from the sensors are picked up by a detection coil as stress-induced changes in the Faraday voltage, and the strong magnetic field induced by the excitation coil in the detection coil is nullified by a cancellation coil reverse-wound in series with the detection coil. The responses of the sensors in an array are separated in time by a linear gradient dc biasing coil. The sensors can be interrogated through metallic and nonmetallic barriers. The signals from the detection coil and the excitation coil are digitized by a pair of bipolar analog-to-digital converters (ADCs). A Raspberry Pi single-board computer (SBC) and associated software perform data acquisition and control all aspects of the sensor system hardware. The program allows the user to select the number of sensors in the array, the type of signal that is being collected, and the number of samples to take. The program also allows for signal processing of the sensor data, such as baseline correction. The program can differentiate sensor peaks from each other and calculate the magnitude of each sensor response with less than 1% error. The data are then displayed along with a graph of the signal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Neurogenesis Deep Learning: Extending deep networks to accommodate new classes

Neural machine learning methods, such as deep neural networks (DNN), have achieved remarkable success in a number of complex data processing tasks. These methods have arguably had their strongest impact on tasks such as image and audio processing – data processing domains in which humans have long held clear advantages over conventional algorithms. In contrast to biological neural systems, which are capable of learning continuously, deep artificial networks have a limited ability for incorporating new information in an already trained network. As a result, methods for continuous learning are potentially highly impactful in enabling the application of deep networks to dynamic data sets. Here, inspired by the process of adult neurogenesis in the hippocampus, we explore the potential for adding new neurons to deep layers of artificial neural networks in order to facilitate their acquisition of novel information while preserving previously trained data representations. Our results on the MNIST handwritten digit dataset and the NIST SD 19 dataset, which includes lower and upper case letters and digits, demonstrate that neurogenesis is well suited for addressing the stability-plasticity dilemma that has long challenged adaptive machine learning algorithms.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1982

Vibration damping characteristics of graphite/epoxy composites for large space structures

Limited data on extensional and flexural damping of small specimens of graphite/epoxy and unreinforced epoxy resin were obtained. Flexural damping was measured using a forced vibration technique based on resonant flexural vibration of shaker excited double cantilever specimens. Extensional damping was measured by subjecting similar specimens to low frequency sinusoidal oscillation in a servohydraulic tensile testing machine while plotting load versus extensional strain. Damping was found to vary slowly and continuously over the frequency range 0.01 - 1000 Hz, and no drastic transitions were observed. Composite damping was found to be less than neat resin damping. Comparison of small specimen damping values with assembled column damping values seems to indicate that, for those materials, material damping is more important than joint damping. The data reported was limited not by the test apparatus, but by signal conditioning and data acquisition. It is believed that filtering of the strain gage signals and the use of digital storage with slow playback will make it possible to extend the frequency and amplitude ranges significantly.

Gibson, R. F.↗
NASA NTRS1990

Feasibility study for the advanced one-dimensional high temperature optical strain measurement system, phase 3

The Instrumentation and Control Technology Division is developing optical strain measurement systems for applications using high temperature wire and fiber specimens. This feasibility study has determined that stable optical signals can be obtained from specimens at temperatures beyond 2,400 C. A system using an area array sensor is proposed to alleviate off-axis decorrelation arising from rigid body motions. A digital signal processor (DSP) is recommended to perform speckle correlations at a rate near the data acquisition rate. Design parameters are discussed, and fundamental limits on the speckle shift strain measurement technique are defined.

Lant, Christian T.↗
NASA NTRS1993

Instrumentation and data acquisition for full-scale aircraft crash testing

The Landing and Impact Dynamics Branch of the NASA Langley Research Center has been conducting full-scale aircraft crash tests since the 1970s. Using a pendulum method, aircraft are suspended by cables from a 240-ft high gantry and swung into the impact surface at various attitudes and velocities. Instrumentation for these tests include on-board high-speed cameras, strain gages, load cells, displacement transducers, and accelerometers. Transducers in the aircraft are hard-wired through a long umbilical cable to the data acquisition room. Up to 96 channels of data can be collected at a typical rate of 4000 samples per second. Data acquisition using an FM multiplexed analog system and a high-speed personal computer based digital system is described.

Jones, Lisa E.↗
NASA NTRS1998

Simultaneous in situ Optical Monitoring Techniques during Crystal Growth of ZnSe by Physical Vapor Transport

ZnSe crystals grown in sealed ampoules by the physical vapor transport method were monitored in situ using three techniques, simultaneously. A Michelson interferometer was set-up to observe the growth rate and surface morphological evolution. An interference pattern (interferogram) is formed by the interaction between the reflection of a HeNe laser (632.8 nm wavelength) off the crystal-vapor interface and a reference beam from the same laser. Preliminary results indicate that the rate of growth/thermal-etching can be calculated using analog data acquisition and simple fringe counting techniques. Gross surface features may also be observed using a digital frame grabber and fringe analysis software. The second in situ technique uses optical absorption to determine the partial pressures of the vapor species. The Se2 and Zn vapor species present in the sealed ampoule absorb light at characteristic wavelengths. The optical absorption is determined by monitoring the light intensity difference between the sample and reference beams. The Se2 Partial pressure profile along the length of the ampoule was estimated from the vibronic absorption peaks at 340.5, 350.8, 361.3 and 379.2 nm using the Beer's law constants established in the calibration runs of pure Se. Finally, because the high temperature crystal growth furnace contains windows, in situ visual observation of the growing crystal is also possible. The use of these techniques not only permits in situ investigation of high temperature vapor growth of semiconductors, but also offers the potential for real time feed back on the growing crystal and allows the possibility of actively controlling the growth process.

Su, C.- H.↗
NASA NTRS1983

Creep testing of foil-gage metals at elevated temperature using an automated data acquisition system

A method is being developed to obtain creep data on foil gage metals at elevated temperatures using an automated data acquisition system in conjunction with a mechanically counter balanced extensometer. The automated system components include the Hewlett-Packard (HP) 9845A desktop computer, the HP 3455A digital voltmeter and the HP 3495A scanner. Software for test monitoring and data collection was developed; data manipulation, including curve plotting was done with a HP regression analysis software package. Initial creep tests were conducted on .003 in. thick foil specimens of Ti-6A1-4V at temperatures of 800 F and 1000 F and at stress levels of 25 ksi and 45 ksi. For comparison, duplicate tests were run on .049 in. thick specimens sheet of the same alloy. During testing, the furnace and specimen temperature, bridge voltage, strain and load output were automatically monitored and recorded at predetermined intervals. Using the HP regression analysis program, recorded strain output was plotted as a function of time. These resultant creep curves indicate that, under similar conditions of temperature and stress, foil gage specimens exhibit a higher creep rate than sheet specimens.

Blackburn, L. B.↗
NASA NTRS1988

Image processing in optical astronomy

Successful efforts to enhance optical-astronomy images through digital processing often exploit such 'weaknesses' of the image as the objects' near-symmetry, their preferred directionality, or a differentiation in spatial frequency between the object or objects and superimposed clutter. Attention is presently given to the calibration of a camera prior to astronomical data-acquisition, methods for the enhancement of faint surface brightness features, automated target detection and extraction techniques, the importance of the geometric transformations of digital imagery, the preparation of two-dimensional histograms, and the application of polarization.

Lorre, Jean J.↗
NASA NTRS2011

Apollo Lunar Sample Integration into Google Moon: A New Approach to Digitization

The Google Moon Apollo Lunar Sample Data Integration project is part of a larger, LASER-funded 4-year lunar rock photo restoration project by NASA s Acquisition and Curation Office [1]. The objective of this project is to enhance the Apollo mission data already available on Google Moon with information about the lunar samples collected during the Apollo missions. To this end, we have combined rock sample data from various sources, including Curation databases, mission documentation and lunar sample catalogs, with newly available digital photography of rock samples to create a user-friendly, interactive tool for learning about the Apollo Moon samples

Dawson, Melissa D.↗
NASA NTRS2012

Innovative Video Diagnostic Equipment for Material Science

Materials science experiments under microgravity increasingly rely on advanced optical systems to determine the physical properties of the samples under investigation. This includes video systems with high spatial and temporal resolution. The acquisition, handling, storage and transmission to ground of the resulting video data are very challenging. Since the available downlink data rate is limited, the capability to compress the video data significantly without compromising the data quality is essential. We report on the development of a Digital Video System (DVS) for EML (Electro Magnetic Levitator) which provides real-time video acquisition, high compression using advanced Wavelet algorithms, storage and transmission of a continuous flow of video with different characteristics in terms of image dimensions and frame rates. The DVS is able to operate with the latest generation of high-performance cameras acquiring high resolution video images up to 4Mpixels@60 fps or high frame rate video images up to about 1000 fps@512x512pixels.

Capuano, G.↗
NASA NTRS1971

Precision calibration and reference voltage source for data acquisition systems

Hybrid integrated circuit operational amplifiers, which have inherent characteristics of low quiescent power dissipation and extended operational lifetime with high reliability, are source for digital systems. Amplifiers are coupled to Zener reference diode in current control and buffer configuration.

Source record↗
NASA NTRS1978

Information extraction from digital images of the earth and the planets

An overview is presented of recent developments at the JPL Image Processing Laboratory which emphasize the utilization of a digital computer to automate the process of information extraction from digital imagery. Consideration is given to: (1) the analysis of Viking Orbiter stereo imagery to determine elevation profiles of the Mars surface, (2) the use of Viking Lander stereo imagery to determine nonhazardous surface sample acquisition strategies, (3) the correlation of Landsat imagery with geographically referenced cultural data to determine land use trends, and (4) the generation of mosaics using digital computer techniques.

Green, W. B.↗
DOE OSTI2024

Digital Analytics, Causal Knowledge Acquisition and Reasoning for Technical Language Processing

Complex engineering systems such as nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) data elements that contain information on the status of components, assets, and systems. Some of this information is textual in form and can be found in documents such as incident reports (IRs) and work orders (WOs). Analyses of textual data in current NPPs-using natural language processing (NLP) methods-have been expanded over the last decade, and it is only recently that the true potential of such analyses has emerged. So far, applications of NLP methods have mostly been limited to classification and prediction, the goal being to identify the nature of the textual element (e.g., safety or non-safety related). Here, we target a more complex problem: automatically extracting knowledge from a textual element in order to assist system engineers in conducting system health assessments. Knowledge extraction is a very broad concept, and its definition may vary depending on the application context. Our methods are a blend of both rule-based and machine learning (ML) algorithms. For our purposes, knowledge extraction means identifying the systems or assets mentioned in a given textual element, as well as the type of event described (e.g., component failure or maintenance activity). In addition, we want to capture details such as measured quantities and the temporal/cause-effect relations between events. In this tool, we also demonstrate how textual data elements are preprocessed in order to handle typos, acronyms, and abbreviations. One main feature of these methods is that they are not based solely on data, but are in fact model-based. In other words, they also rely on MBSE models that are designed to capture-from a functional point of view-the architecture of the systems/assets under consideration. The main purpose of such models is to digitally emulate system engineers' knowledge of system and asset architecture and to identify dependencies among systems, assets, and components. Provided these models, analyses of textual and numeric ER data can be performed by first identifying the OPM model elements to which the ER data elements are referring. The relationships between ER data elements are then identified by checking for any temporal or logical dependencies.

Mandelli, Diego [Idaho National Laboratory (INL), ↗
NASA NTRS1991

Description of real-time Ada software implementation of a power system monitor for the Space Station Freedom PMAD DC testbed

The Ada language software development to perform the electrical system monitoring functions for the NASA Lewis Research Center's Power Management and Distribution (PMAD) DC testbed is described. The results of the effort to implement this monitor are presented. The PMAD DC testbed is a reduced-scale prototype of the electrical power system to be used in the Space Station Freedom. The power is controlled by smart switches known as power control components (or switchgear). The power control components are currently coordinated by five Compaq 382/20e computers connected through an 802.4 local area network. One of these computers is designated as the control node with the other four acting as subsidiary controllers. The subsidiary controllers are connected to the power control components with a Mil-Std-1553 network. An operator interface is supplied by adding a sixth computer. The power system monitor algorithm is comprised of several functions including: periodic data acquisition, data smoothing, system performance analysis, and status reporting. Data is collected from the switchgear sensors every 100 milliseconds, then passed through a 2 Hz digital filter. System performance analysis includes power interruption and overcurrent detection. The reporting mechanism notifies an operator of any abnormalities in the system. Once per second, the system monitor provides data to the control node for further processing, such as state estimation. The system monitor required a hardware time interrupt to activate the data acquisition function. The execution time of the code was optimized using an assembly language routine. The routine allows direct vectoring of the processor to Ada language procedures that perform periodic control activities. A summary of the advantages and side effects of this technique are discussed.

Ludwig, Kimberly↗