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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

The Effects of Gravity on the Circadian Timing System

All vertebrates have a physiological control system that regulates the timing of the rhythms of their daily life. Dysfunction of this system, the circadian timing system (CTS), adversely affects an organism's ability to respond to environmental challenges and has been linked to physiological and psychological disorders. Exposure to altered gravitational environments (the microgravity of space and hyperdynamic environments produced via centrifugation) produces changes in both the functioning of the CTS and the rhythmic variables it controls. The earliest record of primate rhythms in a spaceflight environment come from Biosatellite III. The subject, a pig-tailed macaque, showed a loss of synchronization of the body temperature rhythm and a fragmented sleep-wake cycle. Alterations in the rhythm of body temperature were also seen in rhesus macaques flown on COSMOS 1514. Squirrel monkeys exposed to chronic centrifugation showed an initial decrease in the amplitude and mean of their body temperature and activity rhythms. In a microgravity environment, Squirrel monkeys on Spacelab-3 showed a reduction in the mean and amplitude of their feeding rhythms. Since 1992 we have had the opportunity to participate on three US/Russian sponsored biosatellite missions on which a total of six juvenile male rhesus macaques were flown. These animals uniformly exhibited delays in the phasing of their temperature rhythms, but not their heart rate or activity rhythms during spaceflight. There was also a tendency for changes in waveform mean and amplitude. These data suggest that the spaceflight environment may have a differential effect on the different oscillators controlling different rhythmic variables. Ongoing studies are examining the effects of +G on the CTS. The long-term presence of humans in space highlights the need for effective countermeasures to gravitational effects on the CTS.

Fuller, Charles A.↗
NASA NTRS1989

Digital first order hold circuit

There is provided a digitally controlled first order hold circuit and waveform synthesizer for digitally controlling the representation of a function over an approximation interval. In accordance with the operation of the invention, the first order hold circuit and waveform generator receives a digital data input signal which contains initial condition data, up/down data, and slope data for the approximation interval. The initial condition data is loaded into an up/down counter which is incremented using counting data at a rate depending on the value of the slope data and in a direction depending on the value of the up-down data. In order to minimize delays arising from data acquistion, two frequency synthesizer circuits are provided such that one frequency synthesizer provides counting data while the other frequency synthesizer receives slope data. During alternating intervals, the other frequency synthesizer circuit provides counting data while the other circuit receives slope data. In addition, long length data input signals covering a plurality of approximation intervals are provided to reduce the demands on a main system central processing unit.

Chan, Fred N.↗
NASA NTRS2012

Low-power triggered data acquisition system and method

A low-power triggered data acquisition system and method utilizes low-powered circuitry, comparators, and digital logic incorporated into a miniaturized device interfaced with self-generating transducer sensor inputs to detect, identify and assess impact and damage to surfaces and structures wherein, upon the occurrence of a triggering event that produces a signal greater than a set threshold changes the comparator output and causes the system to acquire and store digital data representative of the incoming waveform on at least one triggered channel. The sensors may be disposed in an array to provide triangulation and location of the impact.

Champaigne, Kevin↗
DOE OSTI2024

Convolution Neural Network for Fault Identification in Distribution Feeder with High Penetration Solar PV

Identification and zonal classification of the faults is a decisive factor in the relay’s decision to trip or not. Different types of fault like three-phase, line-to-line-to-ground and single-line-to-ground can occur at various locations in the feeder. These faults are seen as the variation in the instantaneous values of three-phase voltages and currents, i.e., waveforms, that are measured at the relay location. The objective of this work is to develop a machine learning model that can identify a fault and classify it to various protection zones based on measured waveforms. In this work, a data-driven relay based on Convolutional Neural Network (CNN) is proposed for fault identification in distribution feeders with high penetration solar PV. The proposed CNN model takes local current and voltage waveforms as input and classify it into fault, no-fault or a capacitor switching. Further, the CNN also attempts to identify fault zones based on the images of waveforms. The overall testing accuracy of the trained model exceeds 95%.

Ramesh, Meghana↗
NASA NTRS2019

Retrieval of Snow Freeboard of Antarctic Sea Ice Using Waveform Fitting of CryoSat-2 Returns

In this paper we develop a CryoSat-2 algorithm to retrieve the surface elevation of the air–snow interface over Antarctic sea ice. This algorithm utilizes a two-layer physical model that accounts for scattering from a snow layer atop sea ice as well as scattering from below the snow surface. The model produces waveforms that are fit to CryoSat-2 level 1B data through a bounded trust region least-squares fitting process. These fit waveforms are then used to track the air–snow interface and retrieve the surface elevation at each point along the CryoSat-2 ground track, from which the snow freeboard is computed. To validate this algorithm, we compare retrieved surface elevation measurements and snow surface radar return power levels with those from Operation IceBridge, which flew along a contemporaneous CryoSat-2 orbit in October 2011 and November 2012. Average elevation differences (standard deviations) along the flight lines (IceBridge Airborne Topographic Mapper, ATM – CryoSat-2) are found to be 0.016 cm (29.24 cm) in 2011 and 2.58 cm (26.65 cm) in 2012. The spatial distribution of monthly average pan-Antarctic snow freeboard found using this method is similar to what was observed from NASA's Ice, Cloud, and land Elevation Satellite (ICESat), where the difference (standard deviation) between October 2011–2017 CryoSat-2 mean snow freeboard and spring 2003–2007 mean freeboard from ICESat is 1.92 cm (9.23 cm). While our results suggest that this physical model and waveform fitting method can be used to retrieve snow freeboard from CryoSat-2, allowing for the potential to join laser and radar altimetry data records in the Antarctic, larger (∼30 cm) regional differences from ICESat and along-track differences from ATM do exist, suggesting the need for future improvements to the method. Snow–ice interface elevation retrieval is also explored as a potential to obtain snow depth measurements. However, it is found that this retrieval method often tracks a strong scattering layer within the snow layer instead of the actual snow–ice interface, leading to an overestimation of ice freeboard and an underestimation of snow depth in much of the Southern Ocean but with promising results in areas such as the East Antarctic sector.

Fons, Steven W.↗
DOE OSTI2018

Continuous Fluorescence Depletion Anisotropy Measurement of Protein Rotation

Protein rotation in viscous environments can be measured by fluorescence depletion anisotropy (FDA) which combines long lifetimes of chromophore triplet states with the sensitivity of fluorescence excitation and detection. FDA achieves sensitivity well beyond that attainable by the more common technique of time-resolved phosphorescence anisotropy (TPA). We have now combined benefits of both time-domain and frequency-domain FDA into a single continuous technique (CFDA). Intensity and polarization of a single laser beam are modulated continuously according to a complex, repeating waveform. Fluorescence signals excited from triplet-forming fluorescent probes are digitized over recurring waveform periods by a high-speed signal averager. CFDA experiments typically involve substantial ground state depletion. Thus signals, unlike those of TPA, are not linear in the exciting light intensity and simple data analysis based on such linearity is not appropriate. An exact solution of the coupled diffusion and triplet production/decay equation describing CFDA within individual data points has been combined with simulated annealing optimization to extract triplet and anisotropy decay kinetics from experimental data. Related calculations compare possible excitation waveforms with respect to rotational information provided per fluorescence photon. We present CFDA results for the model system of eosin conjugates of carbonic anhydrase, BSA and immunoglobulin G in 90% glycerol at various temperatures and initial cellular results on eosin-IgE bound to 2H3 cell Type I Fcε receptors. We explore how CFDA reflects rotational parameters of heterogeneous systems and discuss challenges of extending this method to single cell microscopic measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1999

GPS Ocean Reflection Experiment on Spartan 251

It has recently been demonstrated that the GPS signal which has reflected from the ocean surface contains useful geophysical data from which the sea surface wind speed and other parameters can be extracted. This can be used for remote sensing, similar to present day use of radar altimeters or scatterometers, but with significantly smaller instrumentation because of the utilization of the existing GPS broadcast signal for illumination. Several campaigns of aircraft experimentation have been completed demonstrating this technique and reflected GPS data has been reliably collected from 25 km altitude on a balloon. However, there has not yet been a demonstration that the reflected GPS signal can be detected from orbit with sufficient signal to noise ratio (SNR) to make useful remote sensing measurements. A technology demonstration experiment is planned for a Space Shuttle flight in the late 2000 using the Spartan 251 recoverable carrier. This experiment will be also be the first flight validation of the PiVoT GPS receiver developed in house at the Goddard Space Flight Center. The open-architecture, design of this receiver allows the software modifications to be made which control code-correlator spacing to map out the shape of the reflected signal waveform, which is the most basic data product generated by this instrumentation. A moderate gain left-hand circularly polarized antenna, constructed from an array of off-the-shelf hemispherical antennas will be used to give approximately 6dB of additional gain. Preliminary SNR predictions have been done indicating that this antenna will offer sufficient gain to record waveform measurements. A system level description of the experiment instrumentation, including the receiver, antenna and data storage and retrieval will be given. The visibility of GPS reflections over the mission duration of several hours will be studied, including the effects of the limited beamwidth of the antenna. Additionally, because of the small size of this instrumentation, several other space flight opportunities are being considered in the near term. If these missions materialize, they will be described in the paper as well.

Garrison, James L.↗
NASA NTRS1977

Capacitively-coupled data receiver clipper stage

Circuit technique compensates for dc offset and asymmetry in dc clipping levels, negates unbalance in input waveform that causes voltage offset at end of data word, blocks any dc component that is generated by asymmetrical operation of clipper, and improves data threshold detection.

Saunders, F. W.↗
NASA NTRS1999

GPS Ocean Reflection Experiment on Spartan 251

It has recently been demonstrated that the GPS signal which has reflected from the ocean surface contains useful geophysical data from which the sea surface wind speed and other parameters can be extracted. This can be used for remote sensing, similar to present day use of radar altimeters or scatterometers, but with significantly smaller instrumentation because of the utilization of the existing GPS broadcast signal for illumination. Several campaigns of aircraft experimentation have been completed demonstrating this technique and reflected GPS data has been reliably collected from 25 km altitude on a balloon. However, there has not yet been a demonstration that the reflected GPS signal can be detected from orbit with sufficient signal to noise ratio (SNR) to make useful remote sensing measurements. A technology demonstration experiment was planned for a Space Shuttle flight in the late 2000 using the Spartan 251 recoverable carrier. This experiment would also have been the first flight validation of the PiVoT GPS receiver developed in house at the Goddard Space Flight Center. The "open-architecture" design of this receiver would allow the software modifications to be made which control code-correlator spacing to map out the shape of the reflected signal waveform, which is the most basic data product generated by this instrumentation. A moderate gain left-hand circularly polarized antenna, constructed from an array of off-the-shelf hemispherical antennas was to be used to give approximately 3 to 6 dB of additional gain. Preliminary SNR predictions have been done indicating that this antenna would offer sufficient gain to record waveform measurements. A system level description of the experiment instrumentation, including the receiver, antenna and data storage and retrieval will be given. The visibility of GPS reflections over the mission duration of several hours will be studied, including the effects of the limited beamwidth of the antenna. Spartan 251 has now been postponed with the earliest opportunity in the year 2002. The results of this study however, have been 2 used to further the define the requirements and expected performance of reflected GPS receivers in orbit. Several other space flight opportunities are being considered based upon this new information.

Garrison, James L↗
NASA NTRS1995

A seismic data compression system using subband coding

This article presents a study of seismic data compression techniques and a compression algorithm based on subband coding. The algorithm includes three stages: a decorrelation stage, a quantization stage that introduces a controlled amount of distortion to allow for high compression ratios, and a lossless entropy coding stage based on a simple but efficient arithmetic coding method. Subband coding methods are particularly suited to the decorrelation of nonstationary processes such as seismic events. Adaptivity to the nonstationary behavior of the waveform is achieved by dividing the data into separate blocks that are encoded separately with an adaptive arithmetic encoder. This is done with high efficiency due to the low overhead introduced by the arithmetic encoder in specifying its parameters. The technique could be used as a progressive transmission system, where successive refinements of the data can be requested by the user. This allows seismologists to first examine a coarse version of waveforms with minimal usage of the channel and then decide where refinements are required. Rate-distortion performance results are presented and comparisons are made with two block transform methods.

Kiely, A. B.↗
DOE OSTI2011

Full-waveform inversion in the time domain with an energy-weighted gradient

When applying full-waveform inversion to surface seismic reflection data, one difficulty is that the deep region of the model is usually not reconstructed as well as the shallow region. We develop an energy-weighted gradient method for the time-domain full-waveform inversion to accelerate the convergence rate and improve reconstruction of the entire model without increasing the computational cost. Three different methods can alleviate the problem of poor reconstruction in the deep region of the model: the layer stripping, depth-weighting and pseudo-Hessian schemes. The first two approaches need to subjectively choose stripping depths and weighting functions. The third one scales the gradient with only the forward propagation wavefields from sources. However, the Hessian depends on wavefields from both sources and receivers. Our new energy-weighted method makes use of the energies of both forward and backward propagated wavefields from sources and receivers as weights to compute the gradient. We compare the reconstruction of our new method with those of the conjugate gradient and pseudo-Hessian methods, and demonstrate that our new method significantly improves the reconstruction of both the shallow and deep regions of the model.

CONVERGENCE↗
DOE OSTI2026

Rolling Root Mean Square Based Multimodal Anomaly Detection for Real Time Monitoring of Smart Grid

Reliable real-time monitoring is valuable for maintaining the operational integrity of modern electrical smart grids. Deployment of heterogeneous sensing technologies in substations has enabled high-resolution, multichannel waveform monitoring, but also introduces challenges for anomaly detection due to noise, baseline drift, and modality-dependent signal characteristics. In this work, we present a computationally efficient unsupervised method for multimodal event detection based on Rolling Root Mean Square based Event Detection (RRMSED). The method is developed using in-house, field deployed sensors collecting data at a utility substation. The sensing system comprises voltage and current sensors, triaxial accelerometers, and magnetometers, collectively capturing electrical, vibrational, and magnetic waveform measurements at high temporal resolution. RRMSED operates by extracting rolling RMS energy features and their first-order temporal differences from consecutive waveform segments for each channel and then applying channel-specific statistical thresholds learned from historical data. A persistence-based exceedance logic is employed to robustly identify transient events while suppressing impulsive noise, and to provide precise temporal localization with high resolution. The framework is designed for continuous server-side operation and can be deployed in real time without requiring complex models. Experiments on simulated waveform data with known ground truth demonstrate low false positive (FP) and false negative (FN) rates. Application to real substation data shows RRMSED to identify events that are not captured by conventional monitoring indicators including fast transient detection algorithm currently deployed in the system. These results indicate that rolling RMS based features provide an effective and practical basis for real-time multimodal event detection in smart-grid substations.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2020

Full waveform analysis for high pressure ultrasonic measurement

In this paper we report a data analysis protocol for ultrasonic velocity measurements carried out in a synchrotron x-ray facility based multi-anvil high-pressure apparatus. Synthetic ultrasonic signals for the time period between echoes from the two ends of the sample assembly are created with a few simple parameters as the echo waveform is modeled by the first echo from the anvil-assembly boundary. Each echo is modeled as a delta function with an amplitude and arrival time and convolved with this waveform. The final waveform, fit to the data, enables analysis of signals with overlapped echoes as they are common in small cell assemblies and high pressure.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Automatic Waveform Quality Control for Surface Waves Using Machine Learning

Surface-wave seismograms are widely used by researchers to study Earth’s interior and earthquakes. To extract information reliably and robustly from a suite of surface waveforms, the signals require quality control screening to reduce artifacts from signal complexity and noise. This process has usually been completed by human experts labeling each waveform visually, which is time consuming and tedious for large data sets. We explore automated approaches to improve the efficiency of waveform quality control processing by investigating logistic regression, support vector machines, K-nearest neighbors, random forests (RF), and artificial neural networks (ANN) algorithms. To speed up signal quality assessment, we trained these five machine learning (ML) methods using nearly 400,000 human-labeled waveforms. The ANN and RF models outperformed other algorithms and achieved a test accuracy of 92%. We evaluated these two best-performing models using seismic events from geographic regions not used for training. The results show that the two trained models agree with labels from human analysts but required only 0.4% of the time. Although the original (human) quality assignments assessed general waveform signal-to-noise, the ANN or RF labels can help facilitate detailed waveform analysis. Our investigations demonstrate the capability of the automated processing using these two ML models to reduce outliers in surface-wave-related measurements without human quality control screening.

58 GEOSCIENCES↗
DOE OSTI2022

Probing D-region globally using lightning waveforms detected by ENTLN [Slides]

This report includes research and data that the author's state demonstrates "the technique from [Shao et al., Nature Geoscience, 2012] can be used with ENTLN waveforms. Furthermore, an "automated processing has been developed to produce averaged waveforms and associated measurements." Ideas for future work is also presented.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

Gastellu-Etchegorry, Jean-Philippe↗
NASA NTRS2010

Observing Mergers of Non-Spinning Black-Hole Binaries

Advances in the field of numerical relativity now make it possible to calculate the final, most powerful merger phase of binary black-hole coalescence for generic binaries. The state of the art has advanced well beyond the equal-mass case into the unequal-mass and spinning regions of parameter space. We present a study of the nonspinning portion of parameter space, primarily using an analytic waveform model tuned to available numerical data, with an emphasis on observational implications. We investigate the impact of varied m8BS ratio on merger signal-to-noise ratios (SNR~) for several detectors, and compare our results with expectations from the test-mass limit. We note a striking similarity of the waveform phasing of the merger waveform across the available mass ratios. Motivated by this, we calculate the match between our equal-mass and 4:1 mass-ratio waveforms during the merger as a function of location on the source sky, using a new formalism for the match that accounts for higher harmonics. This is an indicator of the amount of degeneracy in mass ratio for mergers of moderate mass ratio systems.

McWilliams, Sean T.↗