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At least 469 records · Page 26

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NASA NTRS1976

Analysis of LEAM experiment response to charged particles

The objectives of the Lunar Ejecta and Meteorites Experiment (LEAM) were to measure the long-term variations in cosmic dust influx rates and the extent and nature of the lunar ejecta. While analyzing these characteristics in the data, it was discovered that a majority of the events could not be associated with hypervelocity particle impacts of the type usually identified with cosmic dust, but could only be correlated with the lunar surface and local sun angle. The possibility that charged particles could be incident on the sensors led to an analysis of the electronics to determine if such signals could cause the large pulse height analysis (PHA) signals. A qualitative analysis of the PHA circuit showed that an alternative mode of operation existed if the input signal were composed of pulses with pulse durations very long compared to the durations for which it was designed. This alternative mode would give large PHA outputs even though the actual input amplitudes were small. This revelation led to the examination of the sensor and its response to charged particles to determine the type of signals that could be expected.

Perkins, D.↗

DOE OSTI2021

Evaluation of nature and intensity of fire concrete spalling by frequency analysis of sound records

Highlights: • Original sound-based NDT method to assess the spalling form and intensity within the time of the test is proposed. • Frequency analysis of recorded sound provides a quantitative and qualitative assessment of concrete propensity to spalling. • Nature of fire concrete spalling can be categorized by a well-defined frequency value. • Waveform and spectrogram analysis delivers information on the exact number of spalling events within the performed test. The paper presents a new method for identifying the form and intensity of spalling using an analysis of the acoustic signal emitted by concrete. To assess the intensity and monitor the course of concrete spalling during fire exposure, the analysis of the recorded sound from the furnace chamber is used. The spalling intensity was determined based on signal amplitude analysis. Investigation of sound records showed that the character of spalling can be categorized by a well-defined frequency value. Based on the analysis of the Fast Fourier Transform (FFT) spectrum, the authors have distinguished the following phenomena that are the source of the signal by assigning the corresponding frequency of the sound wave vibration: explosive spalling, aggregate spalling and destructive spalling.

36 MATERIALS SCIENCE↗

NASA NTRS1985

Turbomachinery incipient failure dynamic detection indicators and analysis

Tape recorded signals from case-mounted accelerometers are examined to determine the feasibility of detecting spalls on bearing balls in the liquid oxygen (LOX) pump in the Space Shuttle Main Engine (SSME). The nonperiodic nature of the spall impact on inner and outer bearing races caused traditional techniques to be unsuccessful. A technique involving statistical techniques and spectra ratios was used to review available pump test tapes.

Faby, D. R.↗

NASA NTRS1986

Analytical Ultrasonics in Materials Research and Testing

Research results in analytical ultrasonics for characterizing structural materials from metals and ceramics to composites are presented. General topics covered by the conference included: status and advances in analytical ultrasonics for characterizing material microstructures and mechanical properties; status and prospects for ultrasonic measurements of microdamage, degradation, and underlying morphological factors; status and problems in precision measurements of frequency-dependent velocity and attenuation for materials analysis; procedures and requirements for automated, digital signal acquisition, processing, analysis, and interpretation; incentives for analytical ultrasonics in materials research and materials processing, testing, and inspection; and examples of progress in ultrasonics for interrelating microstructure, mechanical properites, and dynamic response.

Vary, A.↗

NASA NTRS1987

Materials analysis by ultrasonics: Metals, ceramics, composites

Vary, Alex↗

NASA NTRS1980

Application of small-signal modeling and measurement techniques to the stability analysis of an integrated switching-mode power system

Small-signal modeling techniques are used in a system stability analysis of a breadboard version of a complete functional electrical power system. The system consists of a regulated switching dc-to-dc converter, a solar-cell-array simulator, a solar-array EMI filter, battery chargers and linear shunt regulators. Loss mechanisms in the converter power stage, including switching-time effects in the semiconductor elements, are incorporated into the modeling procedure to provide an accurate representation of the system without requiring frequency-domain measurements to determine the damping factor. The small-signal system model is validated by the use of special measurement techniques which are adapted to the poor signal-to-noise ratio encountered in switching-mode systems. The complete electrical power system with the solar-array EMI filter is shown to be stable over the intended range of operation.

Wong, R. C.↗

NASA NTRS1971

A real-time statistical time-series analyzer

Device extracts average frequency of human speech and produces second, third, and fourth moments of instantaneous frequency about this average. It operates on electrical time representation of input signal, performs statistical analysis on zero-crossing of almost any signal, and does not require specialized personnel to operate it.

Stewart, C. H.↗

DOE OSTI2022

Effect of the pump beam profile and wavefront on the amplified signal wavefront in optical parametric amplifiers

We present a theoretical and experimental analysis of the signal phase introduced by the pump-beam wavefront and spatial profile during optical parametric amplification (OPA) process. The theory predicts the appearance of an additional wavefront in the amplified signal beam that is proportional to the spatial derivative of the pump-beam wavefront. The effect of the pump-beam profile on the signal-beam wavefront is also investigated. Our experiments tested these theoretical predictions by comparing the wavefront of the signal beam before and after amplification in a multi-joule broadband OPA. The measured signal wavefront was shown to have the expected dependence on the pump-beam profile and wavefront. These results can be considered when designing petawatt-scale ultrabroadband optical parametric chirped-pulse–amplification systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1976

Fourier analysis computer-aided design of CCD signal processing analog multiplier arrays

The design of MOS multipliers with CAD was studied. In particular the Fourier analysis capability of the CAD program was used to analyze the harmonic distortion rejection, DR, of the multiplier.

Lin, H. C.↗

NASA NTRS1992

Signal Quality Influence on Averaging Procedure for DIAL Pollution Monitoring

Presented here is an analysis of the relative effect of each stochastic phenomenon on the accuracy of LIDAR measurements. The preferred averaging procedure to be applied is noted. The analysis takes into account the temporal correlation of the transmitted power variations which are associated with laser modal noise, short term temporal correlation of atmospheric turbulence, and 'white' additive noise. A distinction is made between two types of systems, one that transmits a sequence of pulses tuned into two wavelengths, but with a relatively large time separation, and another that transmits pulses in two wavelengths almost coincidentally. This distinction is important because the effect of speckle noise can be minimized when the pulses at two wavelengths are sent within the correlation time of the atmospheric turbulence. The presented analysis compares the signal to noise ratio in the calculation of the ratio beta (sub 1)/beta (sub 2), as achieved by using two methods of calculations: first averaging the data related to each wavelength and then taking the ratio, and first taking the ratio and then averaging. For both methods, normalization with respect to the transmitted power is considered, either prior to or after the averaging of the signals in each wavelength.

Egert, S.↗

NASA NTRS1990

Acousto-ultrasonics

The theoretical development, methodology, and potential applications of acousto-ultrasonic nondestructive testing are set forth in an overview to assess the effectiveness of the technique. Stochastic wave propagation is utilized to isolate and describe defects in fiber-reinforced composites, particularly emphasizing the integrated effects of diffuse populations of subcritical flaws. The generation and nature of acousto-ultrasonic signals are described in detail, and stress-wave factor analysis of the signals is discussed. Applications of acousto-ultrasonics are listed including the prediction of failure sites, assessing fatique and impact damage, calculating ultimate tensile strength, and determining interlaminar bond strength. The method can identify subtle but important variations in fiber-reinforced composites, and development of the related instrumentation technology is emphasized.

Vary, Alex↗

DOE OSTI2024

A comparison of smartphone and infrasound microphone data from a fuel air explosive and a high explosive

For prompt detection of large (>1 kt) above-ground explosions, infrasound microphone networks and arrays are deployed at surveyed locations across the world. Denser regional and local networks are deployed for smaller explosions, however, they are limited in number and are often deployed temporarily for experiments. With the expanded interest in smaller yield explosions targeted at vulnerable areas such as population centers and key infrastructures, the need for more dense microphone networks has increased. An “attritable” (affordable, reusable, and replaceable) and flexible alternative can be provided by smartphone networks. Explosion signals from a fuel air explosive (thermobaric bomb) and a high explosive with trinitrotoluene equivalent yields of 6.35 and 3.63 kg, respectively, were captured on both an infrasound microphone and a network of smartphones. The resulting waveforms were compared in time, frequency, and time-frequency domains. The acoustic waveforms collected on smartphones produced a filtered explosion pulse due to the smartphone's diminishing frequency response at infrasound frequencies (<20 Hz) and was found difficult to be used with explosion characterization methods utilizing waveform features (peak overpressure, impulse, etc.). However, the similarities in time frequency representations and additional sensor inputs are promising for other explosion signal identification and analysis. As an example, a method utilizing the relative acoustic amplitudes for source localization using the smartphone sensor network is presented.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Analysis of the ghost and mirror fields in the Nernst signal induced by superconducting fluctuations

In this work, we present a complete analysis of the Nernst signal due to superconducting fluctuations in a large variety of superconductors from conventional to unconventional ones. A closed analytical expression of the fluctuation contribution to the Nernst signal is obtained in a large range of temperature and magnetic field. We apply this expression directly to experimental measurements of the Nernst signal in Nb x Si 1-x thin films and URu 2 Si 2 superconductors. Both magnetic field and temperature dependence of the available data are fitted with very good accuracy using only two fitting parameters, the superconducting temperature T c0 and the upper critical field H c2 (0). The obtained values agree very well with experimentally obtained values. We also extract the ghost lines (the maximum of the Nernst signal for constant temperature or magnetic field) from the complete expression and also compare it to several experimentally obtained curves. Our approach predicts a linear temperature dependence for the ghost critical field well above T c0 . Within the errors of the experimental data, this linearity is indeed observed in many superconductors far from T c0 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRSDate not supplied

Design and Analysis of Convolutional Neural Network for RF Signal Modulation Classification for In-Orbit Deployment

To effectively transmit data to and from satellites requires a complex and robust RF communication system. Commonly, several different types of signal modulations may be required to maximize satellite efficiency depending on a variety of unexpected channel impairments. We propose a neural network algorithm capable of learning these RF signal modulations using a supervised learning technique designed for low power, high-efficiency in-orbit deployment. The work presented demonstrates a convolutional neural network (CNN) capable of learning and recognizing a set of modulation schemes commonly used to transmit RF information. We are capable of recognizing the modulation scheme from the I and Q data channels directly, with no preprocessing or data conversion required other than breaking the incoming signal into a set of uniform normalized samples. We perform a network design and size analysis, showing that reasonably high accuracy can be obtained using networks with a relatively low number of trainable parameters. Given that a user of a system such as this may wish to receive a signal using a modulation scheme that the network has not previously learned, we demonstrate that transfer learning can learn new modulation schemes by retraining only the fully connected layers in the CNN. Thus, this type of network would excel in outer space deployment using high-efficiency transfer learning hardware. Modulation recognition can be performed through rapid feedforward computation, and the CNN training process is significantly simplified when learning new modulations is required.

CNN↗

DOE OSTI2025

FNCL Enhancements Implementation (FY25 Annual Report)

The FNCL investigations team at Lawrence Livermore National Laboratory (LLNL) has completed research and development of hardware, signal processing, and analysis tools to enhance the measurement capabilities of both the current CAEN SyS VeryFuel Fast Neutron Collar (FNCL) instrument and a next-generation FNCL prototype. The team successfully built and commissioned the LLNL Demonstrator System: a fully integrated, three-panel detector system featuring higher segmentation, plastic scintillators (EJ-276D), Silicon Photomultipliers (SiPMs), no high-voltage requirement, a reduced electronic footprint, and the LLNL-developed Gaussian Mixture Model Pulse Shape Discrimination (GMM-PSD) signal processing. An extensive experimental campaign was conducted at LLNL’s Inherently Safe Subcritical Assembly (ISSA) facility using both the baseline FNCL and the LLNL Demonstrator. The campaign results validated system performance, calibration stability, and the effectiveness of advanced signal processing and analysis algorithms in a relevant environment.

and physical protection↗

DOE OSTI2025

Signal-preserving CMB component separation with machine learning

Analysis of microwave sky signals, such as the cosmic microwave background, often requires component separation using multifrequency methods, whereby different signals are isolated according to their different frequency behaviors. Many so-called blind methods, such as the internal linear combination (ILC), make minimal assumptions about the spatial distribution of the signal or contaminants, and only assume knowledge of the frequency dependence of the signal. The ILC produces a minimum-variance linear combination of the measured frequency maps. In the case of Gaussian, statistically isotropic fields, this is the optimal linear combination, as the variance is the only statistic of interest. However, in many cases the signal we wish to isolate, or the foregrounds we wish to remove, are non-Gaussian and/or statistically anisotropic (in particular for the case of Galactic foregrounds). In such cases, it is possible that machine learning (ML) techniques can be used to exploit the non-Gaussian features of the foregrounds and thereby improve component separation. However, many ML techniques require the use of complex, difficult-to-interpret operations on the data. We propose a hybrid method whereby we train an ML model using only combinations of the data that , and combine the resulting ML-predicted foreground estimate with the ILC solution to reduce the error from the ILC. We demonstrate our methods on simulations of extragalactic temperature and Galactic polarization foregrounds and show that our ML model can exploit non-Gaussian features, such as point sources and spatially varying spectral indices, to produce lower-variance maps than ILC—e.g., reducing the variance of the B-mode residual by factors of up to 5—while preserving the signal of interest in an unbiased manner. Moreover, we often find improved performance even when applying our ML technique to foreground models on which it was not trained. Published by the American Physical Society 2025

McCarthy, Fiona (ORCID:0000000253893565)↗

NASA NTRS1983

An improvement in SAR image interpretability provided by post-correlation signal processing

A presentation on the basis of subjective analysis of computer-generated SAR imagery depicts the improvement in interpretability obtained by post-correlation signal processing. A parametric study was conducted to determine the improvement in interpretability obtained by the application of signal weighting functions on the post-processed returns. The results suggest that a marked improvement in interpretability results from symmetrizing the exponential distribution of the fading signal. Preliminary analysis indicates that signal weighting improves the contrast ratio between the mean value of adjacent homogeneous regions in a SAR scene.

Matthews, N. D.↗

NASA NTRS1991

Superfine resolution acoustooptic spectrum analysis

High resolution spectrum analysis of RF signals is required in applications such as the search for extraterrestrial intelligence, RF interference monitoring, or general purpose decomposition of signals. Sub-Hertz resolution in three-dimensional acoustooptic spectrum analysis is theoretically and experimentally demonstrated. The operation of a two-dimensional acoustooptic spectrum analyzer is extended to include time integration over a sequence of CCD frames.

Ansari, Homayoon↗