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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Systems and Methods for RFID-Enabled Dispenser

Methods, apparatuses and systems for radio frequency identification (RFID)-enabled information collection are disclosed, including an enclosure, a collector coupled to the enclosure, an interrogator, a processor, and one or more RFID field sensors, each having an individual identification, disposed within the enclosure. In operation, the interrogator transmits an incident signal to the collector, causing the collector to generate an electromagnetic field within the enclosure. The electromagnetic field is affected by one or more influences. RFID sensors respond to the electromagnetic field by transmitting reflected signals containing the individual identifications of the responding RFID sensors to the interrogator. The interrogator receives the reflected signals, measures one or more returned signal strength indications ("RSSI") of the reflected signals and sends the RSSI measurements and identification of the responding RFID sensors to the processor to determine one or more facts about the influences. Other embodiments are also described.

Fink, Patrick W.↗
NASA NTRS2016

Systems and Methods for RFID-Enabled Pressure Sensing Apparatus

Methods, apparatuses and systems for radio frequency identification (RFID)-enabled information collection are disclosed, including an enclosure, a collector coupled to the enclosure, an interrogator, a processor, and one or more RFID field sensors, each having an individual identification, disposed within the enclosure. In operation, the interrogator transmits an incident signal to the collector, causing the collector to generate an electromagnetic field within the enclosure. The electromagnetic field is affected by one or more influences. RFID sensors respond to the electromagnetic field by transmitting reflected signals containing the individual identifications of the responding RFID sensors to the interrogator. The interrogator receives the reflected signals, measures one or more returned signal strength indications ("RSSI") of the reflected signals and sends the RSSI measurements and identification of the responding RFID sensors to the processor to determine one or more facts about the influences. Other embodiments are also described.

Fink, Patrick W.↗
NASA NTRS2016

System and Method for RFID-Enabled Information Collection

Methods, apparatuses and systems for radio frequency identification (RFID)-enabled information collection are disclosed, including an enclosure, a collector coupled to the enclosure, an interrogator, a processor, and one or more RFID field sensors, each having an individual identification, disposed within the enclosure. In operation, the interrogator transmits an incident signal to the collector, causing the collector to generate an electromagnetic field within the enclosure. The electromagnetic field is affected by one or more influences. RFID sensors respond to the electromagnetic field by transmitting reflected signals containing the individual identifications of the responding RFID sensors to the interrogator. The interrogator receives the reflected signals, measures one or more returned signal strength indications ("RSSI") of the reflected signals and sends the RSSI measurements and identification of the responding RFID sensors to the processor to determine one or more facts about the influences. Other embodiments are also described.

Fink, Patrick W.↗
NASA NTRS2017

Systems and Methods for RFID-Enabled Pressure Sensing Apparatus

Methods, apparatuses and systems for radio frequency identification (RFID)-enabled information collection are disclosed, including an enclosure, a collector coupled to the enclosure, an interrogator, a processor, and one or more RFID field sensors, each having an individual identification, disposed within the enclosure. In operation, the interrogator transmits an incident signal to the collector, causing the collector to generate an electromagnetic field within the enclosure. The electromagnetic field is affected by one or more influences. RFID sensors respond to the electromagnetic field by transmitting reflected signals containing the individual identifications of the responding RFID sensors to the interrogator. The interrogator receives the reflected signals, measures one or more returned signal strength indications ("RSSI") of the reflected signals and sends the RSSI measurements and identification of the responding RFID sensors to the processor to determine one or more facts about the influences. Other embodiments are also described.

Fink, Patrick W.↗
NASA NTRS2016

Dynamic Range Enhancement of High-Speed Electrical Signal Data via Non-Linear Compression

Systems and methods for high-speed compression of dynamic electrical signal waveforms to extend the measuring capabilities of conventional measuring devices such as oscilloscopes and high-speed data acquisition systems are discussed. Transfer function components and algorithmic transfer functions can be used to accurately measure signals that are within the frequency bandwidth but beyond the voltage range and voltage resolution capabilities of the measuring device.

Laun, Matthew C.↗
NASA NTRS2011

Calibrated Noise Measurements with Induced Receiver Gain Fluctuations

The lack of well-developed techniques for modeling changing statistical moments in our observations has stymied the application of stochastic process theory in science and engineering. These limitations were encountered when modeling the performance of radiometer calibration architectures and algorithms in the presence of non stationary receiver fluctuations. Analyses of measured signals have traditionally been limited to a single measurement series. Whereas in a radiometer that samples a set of noise references, the data collection can be treated as an ensemble set of measurements of the receiver state. Noise Assisted Data Analysis is a growing field of study with significant potential for aiding the understanding and modeling of non stationary processes. Typically, NADA entails adding noise to a signal to produce an ensemble set on which statistical analysis is performed. Alternatively as in radiometric measurements, mixing a signal with calibrated noise provides, through the calibration process, the means to detect deviations from the stationary assumption and thereby a measurement tool to characterize the signal's non stationary properties. Data sets comprised of calibrated noise measurements have been limited to those collected with naturally occurring fluctuations in the radiometer receiver. To examine the application of NADA using calibrated noise, a Receiver Gain Modulation Circuit (RGMC) was designed and built to modulate the gain of a radiometer receiver using an external signal. In 2010, an RGMC was installed and operated at the National Institute of Standards and Techniques (NIST) using their Noise Figure Radiometer (NFRad) and national standard noise references. The data collected is the first known set of calibrated noise measurements from a receiver with an externally modulated gain. As an initial step, sinusoidal and step-function signals were used to modulate the receiver gain, to evaluate the circuit characteristics and to study the performance of a variety of calibration algorithms. The receiver noise temperature and time-bandwidth product of the NFRad are calculated from the data. Statistical analysis using temporal-dependent calibration algorithms reveals that the natural occurring fluctuations in the receiver are stationary over long intervals (100s of seconds); however the receiver exhibits local non stationarity over the interval over which one set of reference measurements are collected. A variety of calibration algorithms have been applied to the data to assess algorithms' performance with the gain fluctuation signals. This presentation will describe the RGMC, experiment design and a comparative analysis of calibration algorithms.

Racette, Paul↗
NASA NTRS2016

Multiparameter Flowfield Measurements in High-Pressure, Cryogenic Environments Using Femtosecond Lasers

Femtosecond laser electronic excitation tagging (FLEET) and Rayleigh scattering (RS) from a femtosecond laser are demonstrated in the NASA Langley 0.3-m Transonic Cryogenic Tunnel (TCT). The measured signals from these techniques are examined for their thermodynamic dependencies in pure nitrogen. The FLEET signal intensity and signal lifetimes are found to scale primarily with the gas density, as does the RS signal. Several models are developed, which capture these physical behaviors. Notably, the FLEET and Rayleigh scattering intensities scale linearly with the flow density, while the FLEET signal decay rates are a more complex function of the thermodynamic state of the gas. The measurement of various flow properties are demonstrated using these techniques. While density was directly measured from the signal intensities and FLEET signal lifetime, temperature and pressure were measured using the simultaneous FLEET velocity measurements while assuming the flow had a constant total enthalpy. Measurements of density, temperature, and pressure from the FLEET signal are made with accuracies as high as 5.3 percent, 0.62 percent, and 6.2 percent, respectively, while precisions were approximately 10 percent, 0.26 percent, and 11 percent for these same quantities. Similar measurements of density from Rayleigh scattering showed an overall accuracy of 3.5 percent and a precision of 10.2 percent over a limited temperature range (T greater than 195 K). These measurements suggest a high degree of utility at using the femtosecond-laser based diagnostics for making multiparameter measurements in high-pressure, cryogenic environments such as large-scale TCT facilities.

Burns, Ross A.↗
NASA NTRS1993

System Measures Errors Between Time-Code Signals

System measures timing errors between signals produced by three asynchronous time-code generators. Errors between 1-second clock pulses resolved to 2 microseconds. Basic principle of computation of timing errors as follows: central processing unit in microcontroller constantly monitors time data received from time-code generators for changes in 1-second time-code intervals. In response to any such change, microprocessor buffers count of 16-bit internal timer.

Cree, David↗
NASA NTRS1990

Real-time failure control (SAFD)

The Real Time Failure Control program involves development of a failure detection algorithm, referred as System for Failure and Anomaly Detection (SAFD), for the Space Shuttle Main Engine (SSME). This failure detection approach is signal-based and it entails monitoring SSME measurement signals based on predetermined and computed mean values and standard deviations. Twenty four engine measurements are included in the algorithm and provisions are made to add more parameters if needed. Six major sections of research are presented: (1) SAFD algorithm development; (2) SAFD simulations; (3) Digital Transient Model failure simulation; (4) closed-loop simulation; (5) SAFD current limitations; and (6) enhancements planned for.

Panossian, Hagop V.↗
NASA NTRS1997

Earth-Based Radio Tracking of the Galileo Probe for Jupiter Wind Estimation

Although the Galileo probe was designed to communicate only to the orbiter, the probe radio signal was detected at two Earth-based radio observatories where the signal was a billion times weaker. The measured signal frequency was used to derive a vertical profile of the jovian zonal wind speed. Due to the mission geometry, the Earth-based wind estimates are less sensitive to descent trajectory errors than estimates based on probe-orbiter Doppler measurements. The two estimates of wind profiles agree qualitatively; both show high wind speeds at all depths sampled.

Folkner, W. M.↗
NASA NTRS2010

Methods and apparatus for determining cardiac output

The present invention provides methods and apparatus for determining a dynamical property of the systemic or pulmonary arterial tree using long time scale information, i.e., information obtained from measurements over time scales greater than a single cardiac cycle. In one aspect, the invention provides a method and apparatus for monitoring cardiac output (CO) from a single blood pressure signal measurement obtained at any site in the systemic or pulmonary arterial tree or from any related measurement including, for example, fingertip photoplethysmography.According to the method the time constant of the arterial tree, defined to be the product of the total peripheral resistance (TPR) and the nearly constant arterial compliance, is determined by analyzing the long time scale variations (greater than a single cardiac cycle) in any of these blood pressure signals. Then, according to Ohm's law, a value proportional to CO may be determined from the ratio of the blood pressure signal to the estimated time constant. The proportional CO values derived from this method may be calibrated to absolute CO, if desired, with a single, absolute measure of CO (e.g., thermodilution). The present invention may be applied to invasive radial arterial blood pressure or pulmonary arterial blood pressure signals which are routinely measured in intensive care units and surgical suites or to noninvasively measured peripheral arterial blood pressure signals or related noninvasively measured signals in order to facilitate the clinical monitoring of CO as well as TPR.

Cohen, Richard J.↗
NASA NTRS1991

Frequency domain laser velocimeter signal processor

A new scheme for processing signals from laser velocimeter systems is described. The technique utilizes the capabilities of advanced digital electronics to yield a signal processor capable of operating in the frequency domain maximizing the information obtainable from each signal burst. This allows a sophisticated approach to signal detection and processing, with a more accurate measurement of the chirp frequency resulting in an eight-fold increase in measurable signals over the present high-speed burst counter technology. Further, the required signal-to-noise ratio is reduced by a factor of 32, allowing measurements within boundary layers of wind tunnel models. Measurement accuracy is also increased up to a factor of five.

Meyers, James F.↗
NASA NTRS2010

Application of Ensemble Detection and Analysis to Modeling Uncertainty in Non Stationary Process

Characterization of non stationary and nonlinear processes is a challenge in many engineering and scientific disciplines. Climate change modeling and projection, retrieving information from Doppler measurements of hydrometeors, and modeling calibration architectures and algorithms in microwave radiometers are example applications that can benefit from improvements in the modeling and analysis of non stationary processes. Analyses of measured signals have traditionally been limited to a single measurement series. Ensemble Detection is a technique whereby mixing calibrated noise produces an ensemble measurement set. The collection of ensemble data sets enables new methods for analyzing random signals and offers powerful new approaches to studying and analyzing non stationary processes. Derived information contained in the dynamic stochastic moments of a process will enable many novel applications.

Racette, Paul↗
NASA NTRS1981

Data enhancement and analysis through mathematical deconvolution of signals from scientific measuring instruments

Mathematical deconvolution of digitized analog signals from scientific measuring instruments is shown to be a means of extracting important information which is otherwise hidden due to time-constant and other broadening or distortion effects caused by the experiment. Three different approaches to deconvolution and their subsequent application to recorded data from three analytical instruments are considered. To demonstrate the efficacy of deconvolution, the use of these approaches to solve the convolution integral for the gas chromatograph, magnetic mass spectrometer, and the time-of-flight mass spectrometer are described. Other possible applications of these types of numerical treatment of data to yield superior results from analog signals of the physical parameters normally measured in aerospace simulation facilities are suggested and briefly discussed.

Wood, G. M.↗
DOE OSTI2025

PickerXL, A Large Deep Learning Model to Measure Arrival Times from Noisy Seismic Signals

Precisely measuring seismic arrival times is a labor-intensive task but is critical for both earthquake monitoring and subsurface imaging. Recently published deep learning models have demonstrated superior performance compared to traditional automatic approaches for picking arrival times. Although existing deep learning models have shown promising results, further advancements are necessary as their performance is not yet satisfactory especially when applied to new regions and station networks. Increasing model size has led to improved performance in other machine learning applications. Here, we aimed to investigate whether enlarging deep learning models can increase performance on accepted benchmarks. We trained three models of varying sizes, small (1X), medium (4X), and large (16X), using globally distributed local and regional earthquake signals and background noise waveforms from a benchmark dataset, Stanford Earthquake Dataset. Our results indicate that the largest model (PickerXL) outperforms both the smaller models and Seisbench implementation of the PhaseNet model, which has the same number of parameters as our small model. The PickerXL model’s enhanced capacity to extract complex patterns from seismograms contributes to its superior arrival picking abilities compared to the smaller model.

Chai, Chengping [Oak Ridge National Laboratory (OR↗
NASA NTRS2003

A new relative referencing method for crop monitoring using chlorophyll fluorescence

The measurement of plant chlorophyll fluorescence has been used for many years as a method to monitor a plant's health status. These types of methods have been mostly relegated to the laboratory. The newly developed Relative Referencing Method allows for the measurement of chlorophyll fluorescence under artificial lighting conditions. The fluorescence signal can be determined by first taking a reference signal measurement, then a second measurement with an additional fluorescence excitation source. The first signal can then be subtracted from the second and the plant's chlorophyll fluorescence due to the second lighting source can be determined. With this simple approach, a photosynthesizing plant can be monitored to detect signs of water stress. Using this approach experiments on tomato plants have shown that it was possible to detect water stress, while the plants were continuously illuminated by fluorescent lamps. This method is a promising tool for the remote monitoring of crops grown in a CELSS-type application. Published by Elsevier Science Ltd on behalf of COSPAR.

Plant Physiology↗