Wave Speed Propagation Measurements on Highly Attenuative Heated Materials.
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Mechanical wave transmission through a material is influenced by the mechanical discontinuity in the material. The propagation of embedded discontinuities can be monitored by analyzing the wave-transmission measurements recorded by a multipoint sensor system placed on the surface of the material. The proposed workflow monitors the propagation of mechanical discontinuity through three stages, namely initial, intermediate, and final stages, by using supervised learning followed by data-driven causal discovery. To the end, the workflow processes the multipoint waveform measurements resulting from a single impulse source, while considering the effects of wave attenuation, dispersion and multiple wave-propagation modes due to the discontinuity and material boundaries. Among various feature reduction techniques ranging from decomposition methods to manifold approximation methods, the features derived based on statistical parameterizations of the measured waveforms lead to reliable monitoring that is robust to changes in precision, resolution, and signal-to-noise ratio of the multipoint sensor measurements. The numbers of zero-crossing, negative-turning, and positive turning in the waveforms are the strongest causal signatures of the propagation of mechanical discontinuity. Higher order moments of the waveforms, such as variance, skewness and kurtosis, are also strong causal signatures of the propagation. Finally, the newly discovered causal signatures confirm that the statistical correlations and conventional feature rankings are not always statistically significant indicators of causality.
The National Aeronautics and Space Administration (NASA) at Goddard Space Flight Center (GSFC) has developed a laser ranging device (LIDAR) which provides accurate and timely data of earth features. NASA/GSFC recently modified the sensor to include a scanning capability to produce LIDAR swaths. They have also integrated a Global Positioning System (GPS) and an Inertial Navigation System (INS) to accurately determine the absolute aircraft location and aircraft attitude (pitch, yaw, and roll), respectively. The sensor has been flown in research mode by NASA for many years. The LIDAR has been used in different configurations or modes to acquire such data as altimetry (topography), bathymetry (water depth), laser-induced fluorosensing (tracer dye movements, oil spills and oil thickness, chlorophyll and plant stress identification), forestry, and wetland discrimination studies. NASA and HARC are developing a commercial version of the instrument for topographic mapping applications. The next phase of the commercialization project will be to investigate other applications such as wetlands mapping and coastal bathymetry. In this paper we report on preliminary laboratory measurements to determine the feasibility of making accurate depth measurements in relatively shallow water (approximately 2 to 6 feet deep) using a LIDAR system. The LIDAR bathymetry measurements are relatively simple in theory. The water depth is determined by measuring the time interval between the water surface reflection and the bottom surface reflection signals. Depth is then calculated by dividing by the index of refraction of water. However, the measurements are somewhat complicated due to the convolution of the water surface return signal with the bottom surface return signal. Therefore in addition to the laboratory experiments, computer simulations of the data were made to show these convolution effects in the return pulse waveform due to: (1) water depth, and (2) changes in bottom surface reflectivity.
This final report is comprised of the abstract of a masters thesis research grant. The abstract of the thesis, 'An Investigation of Acoustic Emission Techniques for the Discrimination of Damage Mechanisms in Ceramic Matrix Composites', is as follows: In order to further advance the understanding of the mechanical behavior of ceramic matrix composites (CMS's), acoustic emission (AE) techniques were implemented to monitor and identify damage mechanisms in CMC's under tensile loading. In addition to real-time AE monitoring techniques, a data acquisition system was developed and implemented in order to capture AE waveforms resulting from stress-induced damage. Waveforms were inspected for multiple events, separated in distinct events, and then analyzed to determine waveform characteristics in the time and frequency domains. Waveform characteristics included peak amplitude, event duration, MARSE, energy, and dominant and centroidal frequency. In addition to conventional methods for determining a damage discrimination criteria, a study of the distribution and correlation of the waveform characteristics criteria and a study of the distribution and correlation of the waveform characteristics were performed to aid in the determination of a damage discrimination criteria. The damage discrimination criteria was tested for 'uniqueness', i.e., the effectiveness of the criteria to identify and monitor damage independent of the stress-strain relationship. Insitu radiography was used to substantiate the damage accumulation. A simulation test was also performed over the loading history to study the changes in the waveform characteristics of the system response from a constant excitation. This thesis demonstrates the use of waveform analysis to study the AE activity resulting from stress-induced damage in CMC's in conjunction with other nondestructive evaluation techniques to investigate the mechanical behavior of CMC's.
In order to further advance the understanding of the mechanical behavior of ceramic matrix composites (CMCs), acoustic emission (AE) techniques were imple mented to monitor and identify damage mechanisms in CMCs under tensile loading. In addition to real-time AE monitoring techniques, a data acquisition system was developed and implemented in order to capture AE waveforms resulting from stress-induced damage. Waveforms were inspected for multiple events, separated in distinct events, and then analyzed to determine waveform characteristics in the time and frequency domains. Waveform characteristics included peak amplitude, event duration, MARSE, energy, and dominant and centroidal frequency. In addition to conventional methods for determining a damage discrimination criteria, a study of the distribution and correlation the waveform characteristics was performed to aid in the determination of a damage discrimination criteria. The damage discrimination criteria was tested for "uniqueness", i.e., the effectiveness of the criteria to identify and monitor damage independent of the stress-strain relationship. Insitu radiography was used to substantiate the damage accumulation.
General relativity predicts the gravitational radiation signatures of mergers of compact binaries,such as coalescing binary black hole systems. Derivations of waveform predictions for such systems are required for optimal scientific analysis of observational gravitational wave data, and have so far been achieved primarily with the aid of the post-Newtonian (PN) approximation. The quaIity of this treatment is unclear, however, for the important late inspiral portion. We derive late-inspiral wave forms via a complementary approach, direct numerical simulation of Einstein's equations, which has recently matured sufficiently for such applications. We compare waveform phasing from simulations covering the last approximately 14 cycles of gravitational radiation from an equal-mass binary system of nonspinning black holes with corresponding 3PN and 3.5PN waveforms. We find phasing agreement consistent with internal error estimates based in either approach, at the level of one radian over approximately 10 cycles. The result suggests that PN waveforms for this system are effective roughly until the system reaches its last stable orbit just prior to the final merger.
This paper discusses scatterometer measurements collected with multi-mode Digital Beamforming Synthetic Aperture Radar (DBSAR) during the SMAP-VEX 2008 campaign. The 2008 SMAP Validation Experiment was conducted to address a number of specific questions related to the soil moisture retrieval algorithms. SMAP-VEX 2008 consisted on a series of aircraft-based.flights conducted on the Eastern Shore of Maryland and Delaware in the fall of 2008. Several other instruments participated in the campaign including the Passive Active L-Band System (PALS), the Marshall Airborne Polarimetric Imaging Radiometer (MAPIR), and the Global Positioning System Reflectometer (GPSR). This campaign was the first SMAP Validation Experiment. DBSAR is a multimode radar system developed at NASA/Goddard Space Flight Center that combines state-of-the-art radar technologies, on-board processing, and advances in signal processing techniques in order to enable new remote sensing capabilities applicable to Earth science and planetary applications [l]. The instrument can be configured to operate in scatterometer, Synthetic Aperture Radar (SAR), or altimeter mode. The system builds upon the L-band Imaging Scatterometer (LIS) developed as part of the RadSTAR program. The radar is a phased array system designed to fly on the NASA P3 aircraft. The instrument consists of a programmable waveform generator, eight transmit/receive (T/R) channels, a microstrip antenna, and a reconfigurable data acquisition and processor system. Each transmit channel incorporates a digital attenuator, and digital phase shifter that enables amplitude and phase modulation on transmit. The attenuators, phase shifters, and calibration switches are digitally controlled by the radar control card (RCC) on a pulse by pulse basis. The antenna is a corporate fed microstrip patch-array centered at 1.26 GHz with a 20 MHz bandwidth. Although only one feed is used with the present configuration, a provision was made for separate corporate feeds for vertical and horizontal polarization. System upgrades to dual polarization are currently under way. The DBSAR processor is a reconfigurable data acquisition and processor system capable of real-time, high-speed data processing. DBSAR uses an FPGA-based architecture to implement digitally down-conversion, in-phase and quadrature (I/Q) demodulation, and subsequent radar specific algorithms. The core of the processor board consists of an analog-to-digital (AID) section, three Altera Stratix field programmable gate arrays (FPGAs), an ARM microcontroller, several memory devices, and an Ethernet interface. The processor also interfaces with a navigation board consisting of a GPS and a MEMS gyro. The processor has been configured to operate in scatterometer, Synthetic Aperture Radar (SAR), and altimeter modes. All the modes are based on digital beamforming which is a digital process that generates the far-field beam patterns at various scan angles from voltages sampled in the antenna array. This technique allows steering the received beam and controlling its beam-width and side-lobe. Several beamforming techniques can be implemented each characterized by unique strengths and weaknesses, and each applicable to different measurement scenarios. In Scatterometer mode, the radar is capable to.generate a wide beam or scan a narrow beam on transmit, and to steer the received beam on processing while controlling its beamwidth and side-lobe level. Table I lists some important radar characteristics
Extensive flight testing was conducted over flat terrain, hilly terrain, and open freshwater settings to examine performance of an air-ground command and control radio link for unmanned aerial vehicles. The flight data collected on bidirectional radio range, signal fading, and transmitted data loss were necessary to validate a proposed air-ground radio waveform that was being considered by a U.S. standards organization. The NASA test system operated at C-band frequencies and utilized a prototype, software-defined radio developed in cooperation with a commercial avionics supplier. Results are presented for multiple altitudes, ranges, and flight conditions, indicating the signal fade depths, occurrence rates, and durations for each flight environment.
The power spectra of the wideband (10 Hz to 100 kHz) magnetic field signals in a number of lightning return strokes (primarily first return strokes) measured during a lightning storm which occurred in Lindau, West Germany in August, 1984 have been calculated. The RF magnetic field data were obtained with the engineering unit of the Galileo Jupiter Probe lightning experiment. The spectra of the magnetic field data definitely show fine structure, with two or three distinct peaks appearing in the spectra of many of the waveforms. An enhancement of power at frequencies of about 60-70 kHz is often seen in the spectra of the waveform time segments preceding and following the rise-to-peak amplitude of the return stroke.
A 1/17-scale research model of the AH-1 series helicopter main rotor was tested. Model-rotor acoustic and simultaneous blade pressure data were recorded at high speeds where full-scale helicopter high-speed impulsive noise levels are known to be dominant. Model-rotor measurements of the peak acoustic pressure levels, waveform shapes, and directively patterns are directly compared with full-scale investigations, using an equivalent in-flight technique. Model acoustic data are shown to scale remarkably well in shape and in amplitude with full-scale results. Model rotor-blade pressures are presented for rotor operating conditions both with and without shock-like discontinuities in the radiated acoustic waveform. Acoustically, both model and full-scale measurements support current evidence that above certain high subsonic advancing-tip Mach numbers, local shock waves that exist on the rotor blades ""delocalize'' and radiate to the acoustic far-field.
An experimental testing procedure is proposed for generating creep-dominant creep-fatigue interaction in Alloy 617 at 950 °C. Most experimental studies on Alloy 617 at elevated temperatures employ a purely strain-controlled loading waveform with a tensile hold period. Strain-controlled loading can only generate interaction in the fatigue-dominant regime of the damage interaction diagram, due to the saturation effect of increasing hold time on cycle life. This saturation is caused by the rapid stress relaxation of Alloy 617 at high temperatures. Design codes for components undergoing creep-fatigue interaction at high temperatures require creep-fatigue testing data in the creep-dominant regime. Here this study investigates multiple creep-fatigue loading waveforms with the objective of producing creep-dominant interaction. The custom loading waveforms are implemented on a servo-hydraulic load frame with a furnace. A hybrid-control scheme with strain-controlled ramps and load-controlled hold periods is proposed due to its flexibility in generating varying proportions of creep and fatigue damage. Experimental data is presented and different loading schemes are compared. Special emphasis is on the creep and fatigue damage contributions by the newly proposed testing method. Several conclusions are discussed and an extension of this current work is suggested to improve the damage interaction diagram for design purposes.
The proliferation of low-cost sensors in smartphones has facilitated numerous applications; however, large-scale deployments often encounter performance issues. Sensing heterogeneity, which refers to varying data quality due to factors such as device differences and user behaviors, presents a significant challenge. In this research, we perform an extensive analysis of 3-axis accelerometer data from the MyShake system, a global seismic network utilizing smartphones. We systematically evaluate the quality of approximately 22 million 3-axis acceleration waveforms from over 81 thousand smartphone devices worldwide, using metrics that represent sampling rate and noise level. We explore a broad range of factors influencing accelerometer data quality, including smartphone and accelerometer manufacturers, phone specifications (release year, RAM, battery), geolocation, and time. Our findings indicate that multiple factors affect data quality, with accelerometer model and smartphone specifications being the most critical. In addition, we examine the influence of data quality on earthquake parameter estimation and show that removing low-quality accelerometer data enhances the accuracy of earthquake magnitude estimation.
We visually examined surface seismic data from the Source Physics Experiment (SPE) Phase-1 chemical explosions in preparation for waveform analysis and interpretation. Recording stations included far-field (near source) geophone lines, and both permanent network, reoccupied USArray, and temporary stations at local and regional distances. We found that near-source waveforms are dominated by broad band compressional (P), and band limited surface wave (Rg) (< 10 Hz) phases. Distinct, consistent shear (S) phases are difficult to observe visually even with a comprehensive bank of frequency bands. Secondary phases are indistinct at near-local distances, unlike for earthquake sources, especially at the high frequencies of interest for discrimination (e.g. 4-8 Hz), likely due to intense near surface scattering. S phases begin to emerge from the scattered background at and beyond 100 km. We identified regional Pn, Pg and Lg phases to 446 km for SPE-5. The data set is, unfortunately, plagued by poorly recorded instrument responses, or, possibly, time varying site amplification due to human interaction with sensors. Instrument response issues should be fixable, and this should be attempted to make this a truly, high-quality data set for use by the monitoring community.
The internetworking of grid-connected power electronics converters (PECs) in photovoltaic (PV) farms has inevitably expanded the cyber-attack surfaces. Here this paper presents a comprehensive study on cyber-attack detection and diagnosis for PEC-enabled PV farms via single waveform sensor to distinguish between normal conditions, open-circuit faults, short-circuit faults, and cyber-attacks. To our knowledge, this has not been attempted before. Firstly, we propose frequency-domain magnitude-based residuals to identify short-circuit faults and a time-domain mean current vector-based feature to distinguish open-circuit faults from other threats. These features can fully reflect the specific physical characteristics of PV farms during threat duration. Secondly, unlike micro phasor measurement units (µPMU) and raw electric waveform-based methods, the proposed innovative features can address novel cyber-attacks that are excluded from the training process. Thirdly, an online hardware-in-the-loop (HIL) testbed using the OPAL-RT real-time digital simulator has verified the effectiveness. The monitoring system runs in real-time while using HIL as an operational solar farm and a National Instruments (NI) data acquisition card as the electric waveform sensor at the point of coupling.
SUMMARY Meteorite impacts have proved to be a significant source of seismic signal on the Moon, and have now been recorded on Mars by InSight seismometers. Understanding how impacts produce seismic signal is key to the interpretation of this unique data, and to improve their identification in continuous seismic records. Here, we use the seismic Representation Theorem, and particularly the stress glut theory, to model the seismic motion resulting from impact cratering. The source is described by equivalent forces, some resulting from the impactor momentum transfer, and others from the stress glut, which represents the mechanical effect of plasticity and non linear processes in the source region. We condense these equivalent forces into a point-source with a time-varying single force and nine-component moment tensor. This analytical representation bridges the gap between the complex dynamics of crater formation, and the linear point-source representation classically used in seismology. Using the multiphysics modelling software HOSS, we develop a method to compute the stress glut of an impact, and the associated point-source from hypervelocity impact simulations. For a vertical and an oblique impact at 1000 m s−1, we show that the moment tensor presents a significant deviatoric component. Hence, the source is not an ideal isotropic explosion contrary to previous assumptions, and draws closer to a double couple for the oblique impact. The contribution of the point force to the seismic signal appears negligible. We verify this model by comparing two signals: (1) HOSS is coupled to SPECFEM3D to propagate the near-source signal elastically to remote seismic stations; (2) the point-source model derived from the stress-glut theory is used to generate displacements at the same distance. The comparison shows that the point-source model is accurately simulating the low-frequency impact seismic waveform, and its seismic moment is in trend with Lunar and Martian impact data. High-frequencies discrepancies exist, which are partly related to finite-source effects, but might be further explained by the difference in mathematical framework between classical seismology and HOSS’ numerical modelling.
We are developing an Arbitrary Waveform Generator (AWG) to provide enhanced capability for radar applications. The current design will accommodate two waveform generators on a single unit for dual frequency operation. The basic architecture of this unit employs a Field Programmable Gate Array (FPGA) and a high speed and high precision Digital to Analog Converter (DAC) for direct digital synthesis. This AWG will be capable of up to 450 MHz bandwidth with ability for frequency notching. Phase fidelity of less than 1.2(sup o) deviation RMS is also achievable. This AWG operates with lower power consumption as compared with other waveform generators, which is advantageous for future spaceborne applications. This will enable radars to return higher precision data, to be reduced in complexity, and to operate in any band without interfering with dedicated bandwidths.
Development and evaluation of Intensive Care Unit (ICU) decision-support systems would be greatly facilitated by the availability of a large-scale ICU patient database. Following our previous efforts with the MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) Database, we have leveraged advances in networking and storage technologies to develop a far more massive temporal database, MIMIC II. MIMIC II is an ongoing effort: data is continuously and prospectively archived from all ICU patients in our hospital. MIMIC II now consists of over 800 ICU patient records including over 120 gigabytes of data and is growing. A customized archiving system was used to store continuously up to four waveforms and 30 different parameters from ICU patient monitors. An integrated user-friendly relational database was developed for browsing of patients' clinical information (lab results, fluid balance, medications, nurses' progress notes). Based upon its unprecedented size and scope, MIMIC II will prove to be an important resource for intelligent patient monitoring research, and will support efforts in medical data mining and knowledge-discovery.
Abstract Accurate earthquake location and magnitude estimation play critical roles in seismology. Recent deep learning frameworks have produced encouraging results on various seismological tasks (e.g., earthquake detection, phase picking, seismic classification, and earthquake early warning). Many existing machine learning earthquake location methods utilize waveform information from a single station. However, multiple stations contain more complete information for earthquake source characterization. Inspired by recent successes in applying graph neural networks (GNNs) in graph‐structured data, we develop a Spatiotemporal Graph Neural Network (STGNN) for estimating earthquake locations and magnitudes. Our graph neural network leverages geographical and waveform information from multiple stations to construct graphs automatically and dynamically by adaptive message passing based on graphs' edges. Using a recent graph neural network and a fully convolutional neural network as baselines, we apply STGNN to earthquakes recorded by the Southern California Seismic Network from 2000 to 2019 and earthquakes collected in Oklahoma from 2014 to 2015. STGNN yields more accurate earthquake locations than those obtained by the baseline models and performs comparably in terms of depth and magnitude prediction, though the ability to predict depth and magnitude remains weak for all tested models. Our work demonstrates the potential of using GNNs and multiple stations for better automatic estimation of earthquake epicenters.