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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Processing and Prolonged 500 C Testing of 4H-SiC JFET Integrated Circuits with Two Levels of Metal Interconnect

Complex integrated circuit (IC) chips rely on more than one level of interconnect metallization for routing of electrical power and signals. This work reports the processing and testing of 4H-SiC junction field effect transistor (JFET) prototype ICs with two levels of metal interconnect capable of prolonged operation at 500 C. Packaged functional circuits including 3-and 11-stage ring oscillators, a 4-bit digital to analog converter, and a 4-bit address decoder and random access memory cell have been demonstrated at 500 C. A 3-stage oscillator functioned for over 3000 hours at 500 C in air ambient.

Silicon Carbide↗
NASA NTRS2015

Processing and Prolonged 500 C Testing of 4H-SiC JFET Integrated Circuits with Two Levels of Metal Interconnect

Complex integrated circuit (IC) chips rely on more than one level of interconnect metallization for routing of electrical power and signals. This work reports the processing and testing of 4H-SiC junction field effect transistor (JFET) prototype IC's with two levels of metal interconnect capable of prolonged operation at 500 C. Packaged functional circuits including 3- and 11-stage ring oscillators, a 4-bit digital to analog converter, and a 4-bit address decoder and random access memory cell have been demonstrated at 500 C. A 3-stage oscillator functioned for over 3000 hours at 500 C in air ambient. Improved reproducibility remains to be accomplished.

JFET↗
NASA NTRS1989

Advanced power system protection and incipient fault detection and protection of spaceborne power systems

This research concentrated on the application of advanced signal processing, expert system, and digital technologies for the detection and control of low grade, incipient faults on spaceborne power systems. The researchers have considerable experience in the application of advanced digital technologies and the protection of terrestrial power systems. This experience was used in the current contracts to develop new approaches for protecting the electrical distribution system in spaceborne applications. The project was divided into three distinct areas: (1) investigate the applicability of fault detection algorithms developed for terrestrial power systems to the detection of faults in spaceborne systems; (2) investigate the digital hardware and architectures required to monitor and control spaceborne power systems with full capability to implement new detection and diagnostic algorithms; and (3) develop a real-time expert operating system for implementing diagnostic and protection algorithms. Significant progress has been made in each of the above areas. Several terrestrial fault detection algorithms were modified to better adapt to spaceborne power system environments. Several digital architectures were developed and evaluated in light of the fault detection algorithms.

Russell, B. Don↗
DOE OSTI2021

In Situ Transmission Electron Microscopy: Signal processing challenges and examples

Transmission electron microscopy (TEM) is a powerful tool for imaging material structure and characterizing material chemistry. Recent advances in data collection technology for TEM have enabled high-volume and high-resolution data collection at a microsecond frame rate. Here, taking advantage of these advances in data collection rates requires the development and application of data processing tools, including image analysis, feature extraction, and streaming data processing techniques. In this article, we highlight a few areas in materials science that have benefited from combining signal processing and statistical analysis with data collection capabilities in TEM and present a future outlook on opportunities of integrating signal processing with automated TEM data analysis.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Cramer-Rao Bound for Gaussian Random Processes and Applications to Radar Processing of Atmospheric Signals

Calculations of the exact Cramer-Rao Bound (CRB) for unbiased estimates of the mean frequency, signal power, and spectral width of Doppler radar/lidar signals (a Gaussian random process) are presented. Approximate CRB's are derived using the Discrete Fourier Transform (DFT). These approximate results are equal to the exact CRB when the DFT coefficients are mutually uncorrelated. Previous high SNR limits for CRB's are shown to be inaccurate because the discrete summations cannot be approximated with integration. The performance of an approximate maximum likelihood estimator for mean frequency approaches the exact CRB for moderate signal to noise ratio and moderate spectral width.

Frehlich, Rod↗
DOE OSTI2022

GaN HEMT Fabrication for Radiation-Hardened Sensing and Communications Electronics

Gallium nitride (GaN), a wide bandgap semiconductor, has vast potential to address two environment conditions associated with the application of electronics to nuclear power: elevated temperatures, and high levels of radiation. A process was developed at The Ohio State University (OSU) to enable fabrication of complex digital and analog electronics circuits for application to nuclear power environments such as locations near or in the reactor core or in spent nuclear fuel casks. Radio frequency (RF)-grade GaN high electron mobility transistor (HEMT) devices were fabricated as part of this process. These were fabricated as depletion mode and enhancement mode devices. They have been electrically characterized and have demonstrated the expected performance. Behavioral models (Verilog-A) were developed from these device measurements to enable electrical simulation of GaN HEMT devices and circuits using common electronics simulation tools based on Simulation Program with Integrated Circuit Emphasis (SPICE). A similar set of GaN HEMT devices is being developed to provide lower speed devices for logic and analog functions. These accomplishments position this technology for effective application to sensor interfacing, signal processing, and data communications in nuclear power plants, including operation in or near the reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2009

Estimating Transmitted-Signal Phase Variations for Uplink Array Antennas

A method of estimating phase drifts of microwave signals distributed to, and transmitted by, antennas in an array involves the use of the signals themselves as phase references. The method was conceived as part of the solution of the problem of maintaining precise phase calibration required for proper operation of an array of Deep Space Network (DSN) antennas on Earth used for communicating with distant spacecraft at frequencies between 7 and 8 GHz. The method could also be applied to purely terrestrial phased-array radar and other radio antenna array systems. In the DSN application, the electrical lengths (effective signal-propagation path lengths) of the various branches of the system for distributing the transmitted signals to the antennas are not precisely known, and they vary with time. The variations are attributable mostly to thermal expansion and contraction of fiber-optic and electrical signal cables and to a variety of causes associated with aging of signal-handling components. The variations are large enough to introduce large phase drifts at the signal frequency. It is necessary to measure and correct for these phase drifts in order to maintain phase calibration of the antennas. A prior method of measuring phase drifts involves the use of reference-frequency signals separate from the transmitted signals. A major impediment to accurate measurement of phase drifts over time by the prior method is the fact that although DSN reference-frequency sources separate from the transmitting signal sources are stable and accurate enough for most DSN purposes, they are not stable enough for use in maintaining phase calibrations, as required, to within a few degrees over times as long as days or possibly even weeks. By eliminating reliance on the reference-frequency subsystem, the present method overcomes this impediment. In a DSN array to which the present method applies (see figure), the microwave signals to be transmitted are generated by exciters in a signal-processing center, then distributed to the antennas via optical fibers. At each antenna, the signals are used to drive a microwave power-amplifier train, the output of which is coupled to the antenna for transmission. A small fraction of the power-amplifier-train output is sent back to the signal-processing center along another optical fiber that is part of the same fiber-optic cable used to distribute the transmitted signal to the antenna. In the signal-processing center, the signal thus returned from each antenna is detected and its phase is compared with the phase of the signal sampled directly from the corresponding exciter. It is known, from other measurements, that the signal-propagation path length from the power-amplifier-train output port to the phase center of each antenna is sufficiently stable and, hence, that sampling the signal at the power-amplifier-train output port suffices for the purpose of characterizing the phase drift of the transmitted signal at the phase center of the antenna

Paal, Leslie↗
DOE OSTI2022

Generalizability analysis of tool condition monitoring ensemble machine learning models

Tool condition monitoring (TCM) is an essential research area for the optimization and automation of metal machining processes, and could help manufacturers reduce costs, production time, machine downtime, energy use, and part scrappage. However, TCM systems developed in prior studies have struggled to reach the high level of generalizability which is necessary for industrial applications. This study addresses TCM system generalizability to new machining conditions, how variations in machining and environmental conditions may be used to improve model generalizability, and ensemble machine learning techniques for TCM. Further, milling tool life experiments were conducted using various machining conditions, and the processes' sound, spindle power, and axial load signals were collected. Different machine learning models were evaluated for the prediction of tool wear levels, including four individual models and five ensemble models. Changes in cutting speed were found to display a large effect on model performance, while the chip load showed some effect, and the feed rate had little effect. A simulated noise data augmentation technique for model improvement is applied within TCM for the first time, and resulted in increased model generalizability and reduced overfitting. Across several performance metrics the extremely randomized trees ensemble machine learning model generally performed the best for this application, achieving a leave-one-group-out cross validation accuracy score of 92.4 %, a 10-fold cross validation score of 98.9 %, and an averaged accuracy across 11 generalizability tests of 87.3 %.

42 ENGINEERING↗
DOE OSTI2022

Indirect Tool Condition Monitoring Using Ensemble Machine Learning Techniques

Abstract Tool condition monitoring (TCM) has become a research area of interest due to its potential to significantly reduce manufacturing costs while increasing process visibility and efficiency. Machine learning (ML) is one analysis technique which has demonstrated advantages for TCM applications. However, the commonly studied individual ML models lack generalizability to new machining and environmental conditions, as well as robustness to the unbalanced datasets which are common in TCM. Ensemble ML models have demonstrated superior performance in other fields, but have only begun to be evaluated for TCM. As a result, it is not well understood how their TCM performance compares to that of individual models, or how homogeneous and heterogeneous ensemble models’ performances compare to one another. To fill in these research gaps, milling experiments were conducted using various cutting conditions, and the model groups were compared across several performance metrics. Statistical t-tests were also used to evaluate the significance of model performance differences. Through the analysis of four individual ML models and five ensemble models, all based on the processes’ sound, spindle power, and axial load signals, it was found that on average, the ensemble models performed better than the individual models, and that the homogeneous ensembles outperformed the heterogeneous ensembles.

Engineering↗
NASA NTRS1977

Non-parametric PCM to ADM conversion

An all-digital technique to convert pulse code modulated (PCM) signals into adaptive delta modulation (ADM) format is presented. The converter developed is shown to be independent of the statistical parameters of the encoded signal and can be constructed with only standard digital hardware. The structure of the converter is simple enough to be fabricated on a large scale integrated circuit where the advantages of reliability and cost can be optimized. A concise evaluation of this PCM to ADM translation technique is presented and several converters are simulated on a digital computer. A family of performance curves is given which displays the signal-to-noise ratio for sinusoidal test signals subjected to the conversion process, as a function of input signal power for several ratios of ADM rate to Nyquist rate.

Locicero, J. L.↗
NASA NTRS1995

Improved Noise-Power Estimators Based On Order Statistics

Technique based on order statistics enables design of improved noise-power estimators. In original intended application, noise-power estimators part of microwave-signal-processing system of Search for Extraterrestrial Intelligence project. Involves limiting dynamic range of value to be estimated; making it possible to achieve performance of order-statistical estimator with simple algorithms and equipment and with only one pass over input data. Technique also applicable to other signal-detection systems and to image-detection systems required to exhibit constant false-alarm rates.

Zimmerman, George A.↗
NASA NTRS1999

Design of Advanced Atmospheric Water Vapor Differential Absorption Lidar (DIAL) Detection System

The measurement of atmospheric water vapor is very important for understanding the Earth's climate and water cycle. The lidar atmospheric sensing experiment (LASE) is an instrument designed and operated by the Langley Research Center for high precision water vapor measurements. The design details of a new water vapor lidar detection system that improves the measurement sensitivity of the LASE instrument by a factor of 10 are discussed. The new system consists of an advanced, very low noise, avalanche photodiode (APD) and a state-of-the-art signal processing circuit. The new low-power system is also compact and lightweight so that it would be suitable for space flight and unpiloted atmospheric vehicles (UAV) applications. The whole system is contained on one small printed circuit board (9 x 15 sq cm). The detection system is mounted at the focal plane of a lidar receiver telescope, and the digital output is read by a personal computer with a digital data acquisition card.

Refaat, Tamer F.↗
NASA NTRS2003

Flight Test Results from the Low Power Transceiver Communications and Navigation Demonstration on Shuttle (CANDOS)

The Low Power Transceiver (LPT) is an advanced signal processing platform that offers a configurable and reprogrammable capability for supporting communications, navigation and sensor functions for mission applications ranging from spacecraft TT&C and autonomous orbit determination to sophisticated networks that use crosslinks to support communications and real-time relative navigation for formation flying. The LPT is the result of extensive collaborative research under NASNGSFC s Advanced Technology Program and ITT Industries internal research and development efforts. Its modular, multi-channel design currently enables transmitting and receiving communication signals on L- or S-band frequencies and processing GPS L-band signals for precision navigation. The LPT flew as a part of the GSFC Hitchhiker payload named Fast Reaction Experiments Enabling Science Technology And Research (FREESTAR) on-board Space Shuttle Columbia s final mission. The experiment demonstrated functionality in GPS-based navigation and orbit determination, NASA STDN Ground Network communications, space relay communications via the NASA TDRSS, on-orbit reconfiguration of the software radio, the use of the Internet Protocol (IP) for TT&C, and communication concepts for space based range safety. All data from the experiment was recovered and, as a result, all primary and secondary objectives of the experiment were successful. This paper presents the results of the LPTs maiden space flight as a part of STS- 107.

Rush, John↗
NASA NTRS2017

System and Method for Multi-Wavelength Optical Signal Detection

The system and method for multi-wavelength optical signal detection enables the detection of optical signal levels significantly below those processed at the discrete circuit level by the use of mixed-signal processing methods implemented with integrated circuit technologies. The present invention is configured to detect and process small signals, which enables the reduction of the optical power required to stimulate detection networks, and lowers the required laser power to make specific measurements. The present invention provides an adaptation of active pixel networks combined with mixed-signal processing methods to provide an integer representation of the received signal as an output. The present invention also provides multi-wavelength laser detection circuits for use in various systems, such as a differential absorption light detection and ranging system.

McGlone, Thomas D.↗
NASA NTRS1979

On the design of a postprocessor for a search for extraterrestrial intelligence /SETI/ system

The design of an on-line postprocessor for a search for extraterrestrial intelligence (SETI) system is described. Signal processing tasks of the postprocessor include: (1) analysis of power level, phase coherence, and state of polarization of single-channel signals in a search for significant signals; (2) grouping or aggregation of adjacent channel data, time averaging of data; and (3) the detection of drifting and modulated signals. Control functions include multichannel spectrum analyzer frequency and clock control, system calibration and selfdiagnostic, control of data flow to and from short-term and long-term (archival) memories, and operation of detection subsystems, such as a visual display and a tunable receiver.

Healy, T. J.↗
NASA NTRS1984

Two-dimensional optical processing using one-dimensional input devices

Two-dimensional optical processing architectures that are implemented with one-dimensional input spatial light modulators are reviewed. The advanced state of the art of available one-dimensional devices and the flexibility that exists in the design of two-dimensional architectures with one-dimensional transducers leads to the implementation of the most powerful and versatile optical processors. Signal and image processing architectures of this type are discussed.

Psaltis, D.↗
NASA NTRS2006

Optical Profilometers Using Adaptive Signal Processing

A method of adaptive signal processing has been proposed as the basis of a new generation of interferometric optical profilometers for measuring surfaces. The proposed profilometers would be portable, hand-held units. Sizes could be thus reduced because the adaptive-signal-processing method would make it possible to substitute lower-power coherent light sources (e.g., laser diodes) for white light sources and would eliminate the need for most of the optical components of current white-light profilometers. The adaptive-signal-processing method would make it possible to attain scanning ranges of the order of decimeters in the proposed profilometers.

Hall, Gregory A.↗