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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Platform for Postprocessing Waveform-Based NDE

Taking advantage of the similarities that exist among all waveform-based non-destructive evaluation (NDE) methods, a common software platform has been developed containing multiple- signal and image-processing techniques for waveforms and images. The NASA NDE Signal and Image Processing software has been developed using the latest versions of LabVIEW, and its associated Advanced Signal Processing and Vision Toolkits. The software is useable on a PC with Windows XP and Windows Vista. The software has been designed with a commercial grade interface in which two main windows, Waveform Window and Image Window, are displayed if the user chooses a waveform file to display. Within these two main windows, most actions are chosen through logically conceived run-time menus. The Waveform Window has plots for both the raw time-domain waves and their frequency- domain transformations (fast Fourier transform and power spectral density). The Image Window shows the C-scan image formed from information of the time-domain waveform (such as peak amplitude) or its frequency-domain transformation at each scan location. The user also has the ability to open an image, or series of images, or a simple set of X-Y paired data set in text format. Each of the Waveform and Image Windows contains menus from which to perform many user actions. An option exists to use raw waves obtained directly from scan, or waves after deconvolution if system wave response is provided. Two types of deconvolution, time-based subtraction or inverse-filter, can be performed to arrive at a deconvolved wave set. Additionally, the menu on the Waveform Window allows preprocessing of waveforms prior to image formation, scaling and display of waveforms, formation of different types of images (including non-standard types such as velocity), gating of portions of waves prior to image formation, and several other miscellaneous and specialized operations. The menu available on the Image Window allows many further image processing and analysis operations, some of which are found in commercially-available image-processing software programs (such as Adobe Photoshop), and some that are not (removing outliers, Bscan information, region-of-interest analysis, line profiles, and precision feature measurements).

Roth, Don↗
NASA NTRS2012

Fiber-Optic Sensor for Aircraft Lightning Current Measurement

An electric current sensor based on Faraday rotation effect in optical fiber was developed for measuring aircraft lightning current. Compared to traditional sensors, the design has many advantages including the ability to measure total current and to conform to structure geometries. The sensor is also small, light weight, non-conducting, safe from interference, and free of hysteresis and saturation. Potential applications include characterization of lightning current waveforms, parameters and paths, and providing environmental data for aircraft certifications. In an optical fiber as the sensing medium, light polarization rotates when exposed to a magnetic field in the direction of light propagation. By forming closed fiber loops around a conductor and applying Ampere s law, measuring the total light rotation yields the enclosed current. A reflective polarimetric scheme is used, where polarization change is measured after the polarized light travels round-trip through the sensing fiber. The sensor system was evaluated measuring rocket-triggered lightning over the 2011 summer. Early results compared very well against a reference current shunt resistor, demonstrating the sensor's accuracy and feasibility in a lightning environment. While later comparisons show gradually increasing amplitude deviations for an undetermined cause, the overall waveforms still compared very well.

Nguyen, Truong X.↗
NASA NTRS2012

Fiber-Optic Sensor for Aircraft Lightning Current Measurement

An electric current sensor based on Faraday rotation effect in optical fiber was developed for measuring aircraft lightning current. Compared to traditional sensors, the design has many advantages including the ability to measure total current and to conform to structure geometries. The sensor is also small, light weight, non-conducting, safe from interference, and free of hysteresis and saturation. Potential applications include characterization of lightning current waveforms, parameters and paths, and providing environmental data for aircraft certifications. In an optical fiber as the sensing medium, light polarization rotates when exposed to a magnetic field in the direction of light propagation. By forming closed fiber loops around a conductor and applying Ampere s law, measuring the total light rotation yields the enclosed current. A reflective polarimetric scheme is used, where polarization change is measured after the polarized light travels round-trip through the sensing fiber. The sensor system was evaluated measuring rocket-triggered lightning over the 2011 summer. Early results compared very well against a reference current shunt resistor, demonstrating the sensor s accuracy and feasibility in a lightning environment. While later comparisons show gradually increasing amplitude deviations for an undetermined cause, the overall waveforms still compared very well.

Nguyen, Truong X.↗
DOE OSTI2022

Assessing the Effectiveness of Generalized Likelihood Ratio Test Detector Schemes in Seismic Event Detection and the Avoidance of Nontarget Signals

Cross-correlation techniques have played a long-standing and pivotal role in seismic event monitoring. However, the performance of correlation-based detectors is challenged by nuisance seismicity, or nontarget signals. Such detections are a problem when the mission is to automatically map events to the correct source region. Using aftershocks of the 2014 $M_w$ 6.0 South Napa, California, earthquake, we demonstrate the effectiveness of utilizing a dynamic correlation processor framework in a generalized likelihood ratio test (GLRT) detector configuration to minimize nontarget detections. A GLRT maximizes a detection statistic with respect to one or more unknown parameters. In this case, the detection statistic is a template signal match against the waveform in a window sliding over a data stream, and the unknown parameter is an index variable indicating group membership of the template event or events. Detected events are assigned to the event group that yields the largest detection statistic. In this work, our results show that a GLRT detector will outperform a suite of independently operating correlation and subspace detectors in terms of having a lower nontarget detection rate at a given missed detection rate. We also show that a GLRT detector composed of a few high-rank subspace detectors has a slightly higher nontarget detection rate, but a significantly lower missed detection rate, than a GLRT detector composed of many low-rank subspace detectors. The high-rank GLRT configuration produced impressive results even with marginal data (single channel, single station, and very low time bandwidth product), which bodes well for the utility of building efficient aftershock classification systems and global monitoring systems at larger scales. However, future work is required to assess performance at the regional scale and to assess the performance of the system at detecting target events not used in the detector template creation.

58 GEOSCIENCES↗
DOE OSTI2020

Improved Parametric Models for Explosion Pressure Signals Derived From Large Datasets

Accurate recording and characterization of explosion-induced pressure signals are key components of the forensic analysis of explosion events in the atmosphere. Parametric overpressure models based on several key waveform features (peak overpressure, positive pulse duration, and impulse) are widely used to estimate explosion energy in terms of trinitrotoluene equivalent yield. However, those models are often developed by a limited dataset, including only a few events or recordings at relatively short propagation distances. Here, we develop empirical waveform-parameter models based on a regression analysis of a large set of data curated from four chemical explosion experiments including 16 detonations. We measured peak overpressure and impulse for positive and negative phases from 1000 pressure signals recorded at local ranges (<20 km) with scaled distance up to 8000 m/kg 1/3 . Additionally, the measured waveform parameters showed large variation with respect to observing distances indicating the effects of atmospheric propagation. In this study, a second-order polynomial model was used in a least-squares regression to account for those propagation effects and to improve data fitting. In addition to model parameters for waveform features, we also determined range-dependent model uncertainties based on data variance. The model uncertainty represents the prediction error of our models and can be critical to evaluating the uncertainty of yield estimate.

58 GEOSCIENCES↗
DOE OSTI2025

Filtered Multi-Tone Spread Spectrum With Overlapping Subbands

A new form of the filter bank multi-carrier spread spectrum (FBMC-SS) waveform is presented. This new waveform modifies the filtered multi-tone spread spectrum (FMT-SS) system, and is intended to whiten the power spectral density (PSD) of the transmit signal. In the conventional FMT-SS, subcarrier bands are non-overlapping, leaving a spectral null between the adjacent subcarrier bands. To make FMT-SS more appealing for a broader set of applications than those studied in the past, we propose adding additional subcarriers centered at these nulls and thoroughly explore the impact of the added subcarriers on the system performance. This modified form of FMT-SS is referred to as overlapped FMT-SS (OFMT-SS). We explore the conditions required for maximally flattening the PSD of the synthesized OFMT-SS signal and for cancelling the interference caused by overlapping subbands. We also explore the choices of spreading gains that result in a low peak-to-average power ratio (PAPR) for a number of different scenarios. Further reduction of the PAPR of the synthesized signal through clipping methods is also explored. Additionally, we propose methods of multi-coding for increasing the data rate of the OFMT-SS waveform, while minimally impacting its PAPR.

42 - ENGINEERING↗
NASA NTRS1995

Shuttle Laser Altimeter (SLA): A pathfinder for space-based laser altimetry and lidar

The Shuttle Laser Altimeter (SLA) is a Hitchhiker experiment now being integrated for first flight on STS-72 in November 1995. Four Shuttle flights of the SLA are planned at a rate of about a flight every 18 months. They are aimed at the transition of the Goddard Space Flight Center airborne laser altimeter and lidar technology to low Earth orbit as a pathfinder for operational space-based laser remote sensing devices. Future alser altimeter sensors such as the Geoscience Laser Altimeter System (GLAS), an Earth Observing System facility instrument, and the Multi-Beam Laser Altimeter (MBLA), the land and vegetation laser altimeter for the NASA TOPSAT (Topography Satellite) Mission, will utilize systems and approaches being tested with SLA. The SLA Instrument measures the distance from the Space Shuttle to the Earth's surface by timing the two-way propagation of short (approximately 10 na noseconds) laser pulses. laser pulses at 1064 nm wavelength are generated in a laser transmitter and are detected by a telescope equipped with a silicon avalanche photodiode detector. The SLA data system makes the pulse time interval measurement to a precision of about 10 nsec and also records the temporal shape of the laser echo from the Earth's surface for interpretation of surface height distribution within the 100 m diam. sensor footprint. For example, tree height can be determined by measuring the characteristic double-pulse signature that results from a separation in time of laser backscatter from tree canopies and the underlying ground. This is accomplished with a pulse waveform digitizer that samples the detector output with an adjustable resolution of 2 nanoseconds or wider intervals in a 100 sample window centered on the return pulse echo. The digitizer makes the SLA into a high resolution surface lidar sensor. It can also be used for cloud and atmospheric aerosol lidar measurements by lengthening the sampling window and degrading the waveform resolution. Detailed test objectives for the STS-72 mission center on the acquisition of sample data sets for land topography and vegetation height, waveform digitizer performance, and verification of data acquisition algorithms. The operational concept of SLA is illustrated in Fig. 1 where a series of 100 m footprints stretch in a profile of Earth surface topography along the nadir track of the Space Shuttle. The location of SLA as a dual canister payload on the Hitchhiker Bridge Assembly in Bay 12 of the Space Shuttle Endeavor can also be noted in this figure. Full interpretation of the SLA range measurement data set requires a 1 m knowledge of the Orbiter trajectory and better than 0.1 deg knowledge of Orbiter pointing angle. These ancillary data sets will be acquired during the STS-72 mission with an on-board Global Positioning System (GPS) receiver, K-band range and range-rate tracking of the Orbiter through TDRSS, and use of on-board inertial measurement units and star trackers. Integration and interpretation of all these different data sets as a pathfinder investigation for accurate determination of Earth surface elevation is the overall science of the SLA investigation.

Bufton, Jack↗
DOE OSTI2012

Embedded calibration system for the DIII-D Langmuir probe analog fiber optic links

This paper describes a generally applicable technique for simultaneously measuring offset and gain of 64 analog fiber optic data links used for the DIII-D fixed Langmuir probes by embedding a reference voltage waveform in the optical transmitted signal before every tokamak shot. The calibrated data channels allow calibration of the power supply control fiber optic links as well. The array of fiber optic links and the embedded calibration system described here makes possible the use of superior modern data acquisition electronics in the control room.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

Measurement Of The Neutron Spectrum Of A DD Electronic Neutron Generator

A Cuttler-Shalev (C-S){sup 3}He proportional counter has been used to measure the energy spectrum of neutrons from a portable deuterium-deuterium electronic neutron generator. To improve the analysis of results from the C-S detector digital pulse shape analysis techniques have been used to eliminate neutron recoil artifacts in the recorded data. Data was collected using a 8-GHz, 10-bit waveform digitizer with its full scale corresponding to approximately 6-MeV neutrons. The measurements were made with the detector axis perpendicular to the direction of ions in the ENG in a plane 0.5-m to the side of the ENG, measuring neutrons emitted at an angle from 87.3 deg. to 92.7 deg. with respect to the path of ions in the ENG. The system demonstrated an energy resolution of approximately 0.040 MeV for the thermal peak and approximately 0.13 MeV at the DD neutron energy. In order to achieve the ultimate resolution capable with this type of detector it is clear that a higher-precision digitizer will be needed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2012

Systematic Biases in Parameter Estimation of Binary Black-Hole Mergers

Parameter estimation of binary-black-hole merger events in gravitational-wave data relies on matched filtering techniques, which, in turn, depend on accurate model waveforms. Here we characterize the systematic biases introduced in measuring astrophysical parameters of binary black holes by applying the currently most accurate effective-one-body templates to simulated data containing non-spinning numerical-relativity waveforms. For advanced ground-based detectors, we find that the systematic biases are well within the statistical error for realistic signal-to-noise ratios (SNR). These biases grow to be comparable to the statistical errors at high signal-to-noise ratios for ground-based instruments (SNR approximately 50) but never dominate the error budget. At the much larger signal-to-noise ratios expected for space-based detectors, these biases will become large compared to the statistical errors but are small enough (at most a few percent in the black-hole masses) that we expect they should not affect broad astrophysical conclusions that may be drawn from the data.

Littenberg, Tyson B.↗
DOE OSTI2011

Quantitative Monitoring for Enhanced Geothermal Systems Using Double-Difference Waveform Inversion with Spatially-Variant Total-Variation Regularization

Double-difference waveform inversion is a promising tool for quantitative monitoring for enhanced geothermal systems (EGS). The method uses time-lapse seismic data to jointly inverts for reservoir changes. Due to the ill-posedness of waveform inversion, it is a great challenge to obtain reservoir changes accurately and efficiently, particularly when using timelapse seismic reflection data. To improve reconstruction, we develop a spatially-variant total-variation regularization scheme into double-difference waveform inversion to improve the inversion accuracy and robustness. The new regularization scheme employs different regularization parameters in different regions of the model to obtain an optimal regularization in each area. We compare the results obtained using a spatially-variant parameter with those obtained using a constant regularization parameter. Utilizing a spatially-variant regularization scheme, the target monitoring regions are well reconstructed and the image noise is significantly reduced outside the monitoring regions. Our numerical examples demonstrate that the spatially-variant total-variation regularization scheme provides the flexibility to regularize local regions based on the a priori spatial information without increasing computational costs and the computer memory requirement.

ACCURACY↗
DOE OSTI2015

Capture Cross Section Measurements in {sup nat}Fe and {sup 181}Ta from 1 to 2000 keV Using a New C6D6 Detector Array

A new array of four C6D6 detectors has been developed at the Rensselaer Polytechnic Institute Gaerttner LINAC center for the purposes of measuring neutron capture cross sections in the keV resonance region with low sensitivity to scattered neutrons. The new detection apparatus incorporates low-mass, low cross-section materials to reduce neutron sensitivity, and uses digital data acquisition equipment to enable saving of the full waveform output of each detector module for offline analysis. Capture yields are determined by applying the total energy method and pulse height weighting technique during the analysis of the saved data. Measurements have been performed on samples of iron and tantalum using the new system, with results consistent with existing data libraries. (authors)

42 ENGINEERING↗
DOE OSTI2015

A new method to reduce the statistical and systematic uncertainty of chance coincidence backgrounds measured with waveform digitizers

We present a new method for measuring chance-coincidence backgrounds during the collection of coincidence data. The method relies on acquiring data with near-zero dead time, which is now realistic due to the increasing deployment of flash electronic-digitizer (waveform digitizer) techniques. An experiment designed to use this new method is capable of acquiring more coincidence data, and a much reduced statistical fluctuation of the measured background. A statistical analysis is presented, and us ed to derive a figure of merit for the new method. Factors of four improvement over other analyses are realistic. The technique is illustrated with preliminary data taken as part of a program to make new measurements of the prompt fission neutron spectra at Los Alamo s Neutron Science Center. In conclusion, it is expected that the these measurements will occur in a regime where the maximum figure of merit will be exploited

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Investigation of acoustic waves under subsurface conditions to improve the predictions of rock mechanical properties and natural fracture characteristics

Mechanical properties and natural fracture characteristics are critical to investigate for subsurface engineering applications, including carbon storage, well drilling, and stimulation, as they govern rock stability, fluid flow, and mechanical behavior under stress. This dissertation integrates experimental and machine learning approaches to enhance the prediction and understanding of these properties by analyzing acoustic wave behavior under varied subsurface conditions. First, the influence of temperature, pore pressure, and supercritical CO2 (scCO2) saturation on poroelastic properties is examined using Gray Berea sandstone samples. The results show that temperature and pore pressure significantly affect the bulk modulus and Biot’s coefficient, while scCO2 saturation impacts rock compressibility, informing strategies for effective geological carbon storage. The study extends this understanding by experimentally evaluating the impact of reservoir depletion on the dynamic mechanical properties of the emerging Caney shale in South Oklahoma with the employment of unsupervised machine learning to predict static mechanical properties across the Caney shale. Integrating petrophysical data and chemostratigraphy, the workflow—featuring K-means clustering, principal component analysis (PCA), and inverse distance weighting (IDW)—improves stratigraphic characterization and the estimation of static-to-dynamic modulus ratios, which is vital for optimizing drilling and stimulation strategies. Finally, the work explores how natural fracture characteristics in shale influence acoustic waveforms and shear wave splitting (SWS) analysis. Experimental data on fractured samples under different stress and temperature conditions, combined with machine learning models such as K-nearest neighbors (KNN) and extreme gradient boosting (XGBoost), reveal key fracture properties impacting SWS and wave propagation. Together, these studies provide a comprehensive framework for linking acoustic wave behavior with rock properties, advancing the methods for monitoring and predicting geomechanical changes. The insights offered valuable implications for safer, more efficient CO2 injection, hydrocarbon extraction, and subsurface management.

Elkholy, Sherif↗
DOE OSTI2024

Seismic Signal Detection on International Monitoring System 3-Component Stations using PhaseNet

In this report we discuss training a deep learning seismic signal detection model on 3-component stations from the International Monitoring System (IMS) using the PhaseNet architecture. Using 14 years of associated signals from the International Data Centre’s (IDC) Late Event Bulletin (LEB), we auto-curated training data consisting of signal windows containing associated arrivals, and noise windows that contain no LEB-associated signals. We trained several models using different waveform window durations (30 seconds and 100 seconds), with and without bandpass filtering. We evaluated the effectiveness of our models using associated signals from the Unconstrained Global Event Bulletin (UGEB) and found that several of our models outperformed the signal detections from the IDC’s Selected Event List 3 (SEL3) arrival table. The SEL3 bulletin evaluated on the UGEB dataset with 100-second waveform windows registered a precision and recall of .15 and .48, respectively, versus .19 and .59 for our filtered-data model. For the 30-second waveform window dataset, the SEL3 bulletin achieved a precision and recall of .31 and .47, respectively, versus .32 and .60 for our filtered-data model. Finally, our models detected signals from all source-to-receiver distances, suggesting it is feasible to use a single PhaseNet model for the IMS network.

58 GEOSCIENCES↗
DOE OSTI2025

Mathematical Morphological Filtering with a Self-Adaptive Reconstruction Technique and Application to Local Seismic Data

Recorded seismic data are generally contaminated by noise from different sources, which masks the signals of interest. In the seismology community, frequency filtering (FF) is the standard method for noise suppression. However, when the signal of interest and noise share the same frequency band, the latter cannot be filtered out without infringing on the former. We implemented a noise suppression approach based on the mathematical morphology theorem. The method involves compound operations of dilation and erosion using structuring elements of varying lengths and decomposes an input noisy waveform into several time functions with differing characteristics. Further, the filtered waveform is constructed from the time functions using a self-adaptive reconstruction technique. Application to a data set of >4700 local waveforms suggests that the implemented mathematical morphological filtering (MMF) approach is efficient for data with low signal-to-noise ratio (SNR) and significantly outperforms FF in that SNR range. For most of the dataset, FF, machine learning (ML) denoising, and continuous wavelet transform (CWT) thresholding result in higher SNR values compared with the MMF method. However, for ~42% of the waveforms, MMF outperforms FF, and the SNR gain achieved with MMF is as large as ~23 dB. Compared to ML denoising and CWT thresholding, this proportion drops to only ~10%–14%. Our results suggests that in an operational setting, MMF cannot replace the other noise suppression methods; however, signal detection can be improved if MMF is used to supplement them in some scenarios. MMF could help detect signals in problematic low-SNR data, which are currently being missed particularly when using FF alone.

58 GEOSCIENCES↗
DOE OSTI2017

Digital pile-up rejection for plutonium experiments with solution-grown stilbene

A solution-grown stilbene detector was used in several experiments with plutonium samples including plutonium oxide, mixed oxide, and plutonium metal samples. Neutrons from different reactions and plutonium isotopes are accompanied by numerous gamma rays especially by the 59-keV gamma ray of 241Am. Identifying neutrons correctly is important for nuclear nonproliferation applications and makes neutron/gamma discrimination and pile-up rejection necessary. Each experimental dataset is presented with and without pile-up filtering using a previously developed algorithm. The experiments were simulated using MCNPX-PoliMi, a Monte Carlo code designed to accurately model scintillation detector response. Collision output from MCNPX-PoliMi was processed using the specialized MPPost post-processing code to convert neutron energy depositions event-by-event into light pulses. The model was compared to experimental data after pulse-shape discrimination identified waveforms as gamma ray or neutron interactions. We show that the use of the digital pile-up rejection algorithm allows for accurate neutron counting with stilbene to within 2% even when not using lead shielding

Bourne, M. M.↗
DOE OSTI2018

Properties of Intense Field-Aligned Lower-Band Chorus Waves: Implications for Nonlinear Wave-Particle Interactions: INTENSE FIELD-ALIGNED CHORUS WAVE-PACKETS

Resonant interactions between electrons and chorus waves are responsible for a wide range of phenomena in near-Earth space (e.g., diffuse aurora and acceleration of > 1 MeV electrons). Although quasi-linear diffusion is believed to be the primary paradigm for describing such interactions, an increasing number of investigations suggest that nonlinear effects are also important in controlling the rapid dynamics of electrons. However, present models of nonlinear wave-particle interactions, which have been successfully used to describe individual short-term events, are not directly applicable for a statistical evaluation of nonlinear effects and the long-term dynamics of the outer radiation belt, because they lack information on the properties of intense (nonlinearly resonating with electrons) chorus waves. In this paper, we use the Time History of Events and Macroscale Interactions during Substorms and Van Allen Probes data sets of field-aligned chorus waveforms to study two key characteristics of these waves: effective amplitude Β w (nonlinear interaction can occur when Β w >2) and wave packet length β (the number of wave periods within it). While as many as 10–15% of chorus wave packets are sufficiently intense (Β w >2–3) to interact nonlinearly with relativistic electrons, most of them are short (β < 10) reducing the efficacy of such interactions. Revised models of nonlinear interactions are thus needed to account for the long-term effects of these common, intense but short chorus wave packets. We also discuss the dependence of Β w , β on location (MLT and L-shell) and on the properties of the suprathermal electron population.

79 ASTRONOMY AND ASTROPHYSICS↗