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At least 163 records · Page 9

Characteristics of upward-connecting-leader current leading to attachment in downward negative cloud-to-ground lightning strokes

For this work, we analyzed currents associated with upward connecting leaders (UCLs) initiated from the Kennedy Space Center Industrial Area Tower in two negative cloud-to-ground strokes that struck the tower. One stroke was also recorded using a high-speed video camera located 760 m from the KSC IAT. The NLDN-reported peak currents for the two strokes were – 31.7 and – 98.5 kA. During the UCL development phase the current waveforms exhibited a monotonically (quasi-exponentially) increasing “background” current overlaid with 10-μs scale pulses with a median amplitude of 51.1 A. The UCL current durations for the two strokes were 1039 and 449 μs, respectively. During the pre-attachment processes (UCL and slow front) the total negative charge effectively transferred to ground were 70.2 and 55 mC, respectively. For the stroke captured on high-speed video, the average line-charge-density for the 109-m long UCL was found to be 0.5 mC/m. The average UCL 2-D speed was 2.4 × 10 5 m/s, and it was observed to accelerate toward the downward leader prior to attachment. We observed that UCL-pulse amplitudes are larger, background currents are higher, and interpulse intervals are shorter at later times during UCLs, which can be attributed to the intensification of the local electric field due to the approaching downward negative leader. The median positive charge injected into the UCL by a pulse was 297 μC. The UCL associated with the higher peak-current stroke produced the highest injected pulse-charge values about three times sooner during its development, likely due to the 2–2.7 times faster average downward leader vertical speeds.

54 ENVIRONMENTAL SCIENCES↗

Characteristics and Preliminary Observations of the Influence of Electromyostimulation on the Size and Function of Human Skeletal Muscle During 30 Days of Simulated Microgravity

During 30 days (d) of bedrest, the practicality of using Elec- troMyoStimulation (EMS) as a deterrent to atrophy and strength loss of lower limb musculature was examined. An EMS system was developed that provided variable but quantifiable levels of EMS, and measured torque. The dominant log of three male subjects was stimulated twice daily in a 3-d on/1-d off cycle during bedrest. The non-dominant leg of each subject acted as a control. A stimulator, using a 0.3 ms monophasic 60 Hz pulse waveform, activated muscle tissue for 4 s. The output waveform from the stimulator was sequenced to the Knee Extensors (KE), Knee Flex- ors (KF), Ankle Extensors (AE), and Ankle Flexors (AF), and caused three isometric contractions of each muscle group per minute. Subject tolerance determined EMS Intensity. Each muscle group received four 5-min bouts of EMS each session with a 10 -min rest between bouts. EMS and torque levels for each muscle action were recorded directly an a computer. Overall average EMS Intensity was 197, 197, 195, and 188 mA for the KE, KF, AF, and AE, respectively. Overall average torque development for these muscle groups was 70, 16, 12, and 27 Nm, respectively. EMS intensity doubled during the study, and average torque increased 2.5 times. Average maximum torque throughout a session reached 54% of maximal voluntary for the KE and 29% for the KF. Reductions in leg volume, muscle compartment size, cross-sectional area of slow and fast-twitch fibers, strength, and aerobic enzyme activities, and increased log compliance were attenuated in the legs which received EMS during bedrest. These results indicate that similar EMS levels induce different torques among different muscle groups and that repeated exposure to EMS increases tolerance and torque development. Longer orien- tation periods, therefore, may enhance its effectiveness. Our preliminary data suggest that the efficacy of EMS as an effective countermeasure for muscle atrophy and strength loss during long duration space travel warrants further investigation.

Duvoisin, Marc R.↗

Toward more-robust, AI-enabled subsurface seismic imaging for geotechnical applications

Non-invasive seismic imaging has the potential to cost-effectively evaluate large volumes of subsurface material to inform geotechnical site investigation. However, seismic imaging using full waveform inversion (FWI) requires significant computational time and is dependent on an initial starting model. As a result, FWI has not yet been widely adopted into geotechnical practice. Previous efforts, on relatively simple two-layered models, indicate that data-driven artificial intelligence (AI) models may be as effective as FWI at predicting 2D images of shear wave velocity (V s ). Furthermore, the AI model predictions can be made almost instantaneously after data acquisition and do not require an initial starting model. We examine the generality of these findings by developing a new AI model for subsurface seismic imaging, whereby we make several notable contributions. First, we architect a multimodal AI model that combines time- and frequency-domain representations of the seismic wavefield to predict a 50 m by 20 m subsurface image of V s . Second, we developed a new diverse dataset of 100,000 images with their corresponding seismic wavefields to train the AI model. Third, we propose four physics-informed data augmentations for data-driven seismic imaging. Fourth, we develop two prediction consistency tests to evaluate the model’s performance when the true subsurface is unknown. Our final model, which has been made publicly available, is capable of predicting a subsurface V s image from a single seismic wavefield with an average, mean absolute percent error (MAPE) of 24 %. The predictive model is applied to a field dataset and shown to be consistent with local geology and shear-wave refraction measurements from the same location.

Artificial intelligence↗

Crowdsourcing Felt Reports Using the MyShake Smartphone App

MyShake is a free citizen science smartphone app that provides a range of features related to earthquakes. Features available globally include rapid postearthquake notifications, live maps of earthquake damage as reported by MyShake users, safety tips, and various educational features. The app also uses the accelerometer in the mobile device to detect earthquake shaking, and to record and submit waveforms to a central archive. In addition, MyShake delivers earthquake early warning alerts in California, Oregon, and Washington. Here, in this study, we compare the felt shaking reports provided by MyShake users in California with the U.S. Geological Survey’s (USGSs) “Did You Feel It?” intensity reports. The MyShake app simply asks, “What strength of shaking did you feel?” and users report on a five-level scale. When the MyShake reports are averaged in spatial or time bins, we find strong correlation with the Modified Mercalli Intensity scale values reported by the USGS based on the DYFI surveys. The MyShake felt reports can therefore contribute to the creation of shaking intensity maps.

58 GEOSCIENCES↗

Pulsed multiwavelength laser ranging system

A pulsed multiwavelength laser ranging system for measuring atmospheric delay was built and tested, and its theoretical performance limits were calculated. The system uses a dye modelocked ND:YAG laser, which transmits 70 psec wide pulses simultaneously at 1064, 532, and 355 nm. The differential delay of the 1064 and 355 nm pulses is measured by a specially calibrated waveform digitizer to estimate the dry atmospheric delay. The delay time of the 532 nm pulse is used to measure the target distance. Static crossed field photomultipliers are used as detectors for all wavelengths. Theoretical analysis shows that path curvature and atmospheric turbulence are fundamental limits to the ranging accuracy of both single and multicolor systems operating over horizontal paths. For two color systems, an additional error is caused by the uncertainty in the path averaged water vapor. The standard deviation of the multicolor instrument's timing measurements is directly proportional to the laser pulse width plus photomultiplier jitter divided by the square root of the received photoelectron number. The prototype system's maximum range is km, which is limited by atmospheric and system transmission losses at 355 nm. System signal detection and false alarm calculations are also presented.

Abshire, J. B.↗

Automatic microseismic event picking via unsupervised machine learning

SUMMARY Effective and efficient arrival picking plays an important role in microseismic and earthquake data processing and imaging. Widely used short-term-average long-term-average ratio (STA/LTA) based arrival picking algorithms suffer from the sensitivity to moderate-to-strong random ambient noise. To make the state-of-the-art arrival picking approaches effective, microseismic data need to be first pre-processed, for example, removing sufficient amount of noise, and second analysed by arrival pickers. To conquer the noise issue in arrival picking for weak microseismic or earthquake event, I leverage the machine learning techniques to help recognizing seismic waveforms in microseismic or earthquake data. Because of the dependency of supervised machine learning algorithm on large volume of well-designed training data, I utilize an unsupervised machine learning algorithm to help cluster the time samples into two groups, that is, waveform points and non-waveform points. The fuzzy clustering algorithm has been demonstrated to be effective for such purpose. A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseismic events, even in the case of moderately strong background noise.

Chen, Yangkang↗

Acoustic Optimization for Anti-Phase Asymmetric Rotor

This investigation seeks to optimize the implementation of anti-phase alternating trailing edge (TE) patterns for rotor noise suppression. The design objective is to maximize reduction of noise perceived by the community while maintaining the aerodynamic thrust. Computations using a three-dimensional Unsteady-Reynolds-Averaged-Navier-Stokes (URANS) with k-w Shear Stress Transport (SST) turbulence model and Ffowcs-Williams and Hawkings (FW-H) formula are used to obtain aerodynamic thrust and far-field noise level. A parametric acoustic study of 13 configurations of KDE rotor with variable alternating trailing edge period, alternating trailing edge length, and trailing edge deflection angle is conducted. The best design candidate for the KDE rotor has a four-period TE waveform which results in a reduction in far-field noise level of 2.1 dB in the hover condition and a reduction of 1.1 dB in the forward flight condition at 9.7 m/s. A further parametric acoustic study is conducted for a different rotor manufactured by APC. Six APC rotor design candidates are simulated. The best design candidate 4H for the APC rotor results in a reduction in far-field noise level of 4.0 dB in the hover condition and a reduction of 1.3 dB in the forward flight condition at 9.7 m/s. A series of acoustic experiments in the Penn State University (PSU) anechoic chamber have been conducted. In the forward flight condition at 9.7 m/s, the APC anti-phase 4H rotor offers clear evidence of noise suppression capability across a wide range of the azimuthal angle. In the broadband frequency range of 2000-4000 Hz, the APC anti-phase 4H rotor produces as much as 6 dB noise reduction. The experimental results appear to confirm the noise suppression capability of the proposed anti-phase rotor design concepts.

Xiong, Juntao↗

Features of Point Clouds Synthesized from Multi-View ALOS/PRISM Data and Comparisons with LiDAR Data in Forested Areas

LiDAR waveform data from airborne LiDAR scanners (ALS) e.g. the Land Vegetation and Ice Sensor (LVIS) havebeen successfully used for estimation of forest height and biomass at local scales and have become the preferredremote sensing dataset. However, regional and global applications are limited by the cost of the airborne LiDARdata acquisition and there are no available spaceborne LiDAR systems. Some researchers have demonstrated thepotential for mapping forest height using aerial or spaceborne stereo imagery with very high spatial resolutions.For stereo imageswith global coverage but coarse resolution newanalysis methods need to be used. Unlike mostresearch based on digital surface models, this study concentrated on analyzing the features of point cloud datagenerated from stereo imagery. The synthesizing of point cloud data from multi-view stereo imagery increasedthe point density of the data. The point cloud data over forested areas were analyzed and compared to small footprintLiDAR data and large-footprint LiDAR waveform data. The results showed that the synthesized point clouddata from ALOSPRISM triplets produce vertical distributions similar to LiDAR data and detected the verticalstructure of sparse and non-closed forests at 30mresolution. For dense forest canopies, the canopy could be capturedbut the ground surface could not be seen, so surface elevations from other sourceswould be needed to calculatethe height of the canopy. A canopy height map with 30 m pixels was produced by subtracting nationalelevation dataset (NED) fromthe averaged elevation of synthesized point clouds,which exhibited spatial featuresof roads, forest edges and patches. The linear regression showed that the canopy height map had a good correlationwith RH50 of LVIS data with a slope of 1.04 and R2 of 0.74 indicating that the canopy height derived fromPRISM triplets can be used to estimate forest biomass at 30 m resolution.

LiDARD↗

Coping with Trial-to-Trial Variability of Event Related Signals: A Bayesian Inference Approach

In electro-neurophysiology, single-trial brain responses to a sensory stimulus or a motor act are commonly assumed to result from the linear superposition of a stereotypic event-related signal (e.g. the event-related potential or ERP) that is invariant across trials and some ongoing brain activity often referred to as noise. To extract the signal, one performs an ensemble average of the brain responses over many identical trials to attenuate the noise. To date, h s simple signal-plus-noise (SPN) model has been the dominant approach in cognitive neuroscience. Mounting empirical evidence has shown that the assumptions underlying this model may be overly simplistic. More realistic models have been proposed that account for the trial-to-trial variability of the event-related signal as well as the possibility of multiple differentially varying components within a given ERP waveform. The variable-signal-plus-noise (VSPN) model, which has been demonstrated to provide the foundation for separation and characterization of multiple differentially varying components, has the potential to provide a rich source of information for questions related to neural functions that complement the SPN model. Thus, being able to estimate the amplitude and latency of each ERP component on a trial-by-trial basis provides a critical link between the perceived benefits of the VSPN model and its many concrete applications. In this paper we describe a Bayesian approach to deal with this issue and the resulting strategy is referred to as the differentially Variable Component Analysis (dVCA). We compare the performance of dVCA on simulated data with Independent Component Analysis (ICA) and analyze neurobiological recordings from monkeys performing cognitive tasks.

Ding, Mingzhou↗

Incipient Failure Detection (IFD) of antifriction ball bearings

Two methods were investigated for retrieving the ball bearing signals buried by the overall signature of an operating large engine such as the main space shuttle engine. The signal averaging method averages n** signals over a time duration equaling the known period of the ball bearing defect frequency. With this method, the desired ball bearing defect signal will be enhanced over the noise by a factor of the square root of n. A second method is to perform a further frequency analysis on the logarithmic spectrum in order to detect and separate different families of harmonics and sidebands, thereby giving information about modulating frequencies. These two alternate IFD methods were carried out with a Norland 3001 waveform and data system. The obtained results are then compared with the power spectral density (PSD) of the overall machine signals and conclusions are made accordingly.

Wang, D. Y.↗

Measured Effects of Turbulence on the Loudness and Waveforms of Conventional and Shaped Minimized Sonic Booms

Turbulence has two distinctive effects on sonic booms: there is distortion in the form of random perturbations that appear behind the shock waves, and shock rise times are increased randomly. A first scattering theory by S.C. Crow in the late 1960s quantified the random distortions, and Crow's theory was shown to agree with available flight test data. A variety of theories for the shock thickness have been presented, all supporting the role of turbulence in increasing rise time above that of a basic molecular-relaxation structure. The net effect of these phenomena on the loudness of shaped minimized booms is of significant interest. Initial analysis suggests that there would be no change to average loudness, but this had not been experimentally investigated. The January 2004 flight test of the Shaped Sonic Boom Demonstrator (SSBD), together with a reference unmodified F-5E, included a 12500- foot linear ground sensor array with 28 digitally recorded sensor sites. This data set provides an opportunity to re-test Crow's theory for the post-shock perturbations, and to examine the net effect of turbulence on the loudness of shaped sonic booms.

Plotkin, Kenneth J.↗

Regional seismic velocity changes following the 2019 M w 7.1 Ridgecrest, California earthquake from autocorrelations and P / S converted waves

SUMMARY We examine regional transient changes of seismic velocities generated by the 2019 Mw 7.1 Ridgecrest earthquake in California, using autocorrelations of moving time windows in continuous waveforms recorded at regional stations. We focus on traveltime differences in a prominent phase generated by an interface around 2 km depth, associated with transmitted Pp waves and converted Ps waves from the ongoing microseismicity. Synthetic tests demonstrate the feasibility of the method for monitoring seismic velocity changes. Taking advantage of the numerous aftershocks in the early period following the main shock, we obtain a temporal resolution of velocity changes up to 20 min in the early post-main-shock period. The results reveal regional coseismic velocity drops in the top 1–3 km with an average value of ∼2 per cent over distances up to 100 km from the Ridgecrest event. These average velocity drops are likely dominated by larger changes in the shallow materials and are followed by rapid recoveries on timescales of days. Around the north end of the Ridgecrest rupture and the nearby Coso geothermal region, the observed coseismic velocity drops are up to ∼8 per cent. The method allows monitoring temporal changes of seismic velocities with high temporal resolution, fast computation and precise spatial mapping of changes. The results suggest that significant temporal changes of seismic velocities of shallow materials are commonly generated on a regional scale by large events.

58 GEOSCIENCES↗

Engineering studies related to the GEOS-C radar altimeter

Experiment requirements, technical characteristics, and GEOS-C radar altimeter related analyses are discussed along with results of a study on engineering test data requirements. Statistical analyses related to determination of wave height resolution achievable as a function of system characteristics and averaging period are described, in addition to a discussion on the desirability of using computer procedures to compensate for altitude tracker time-jitter. Data processing considerations for the GEOS-C system are examined. An extensive analysis of the spatial filter effect is given and results of a computation of geoidal power spectral density, based on Skylab altimeter data, is displayed and interpreted in terms of projected GEOS-C random errors. This information is then used in deriving minimum-mean-square filter procedures for both geoid undulation and slope data. The characteristics of mean received waveforms as a function of off-nadir angle are used to obtain tracker bias as a function of sea state and pointing angle. The angle estimation process proposed by the GEOS-C hardware contractor is also investigated from a standpoint of achievable angular resolution.

Miller, L. S.↗

Experimental study of outdoor propagation of spherically speading periodic acoustic waves of finite amplitude

The outdoor propagation of spherically spreading sound waves of finite amplitude was investigated. The main purpose of the experiments was to determine the extent to which the outdoor environment, mainly random inhomogeneity of the medium, affects finite amplitude propagation. Periodic sources with fundamental frequencies in the range 6 to 8 kHz and source levels SPLlm from 140 to 149 dB were used. The sources were an array of 7 to 10 horn drivers and a siren. The propagation path was vertical and parallel to an 85 m tower, whose elevator carried the traveling microphone. The general conclusions drawn from the experimental results were as follows. The inhomogeneities caused significant fluctuations in the instantaneous acoustic signal, but with sufficient time averaging of the measured harmonic levels, the results were comparable to results expected for propagation in a quiet medium. Propagation data for the fundamental of the siren approached within 1 dB of the weak shock saturation levels. Extra attenuation on the order of 8 dB was observed. The measurements generally confirmed the predictions of several theoretical models. The maximum propagation distance was 36 m. The narrowbeam arrays were much weaker sources. Nonlinear propagation distortion was produced, but the maximum value of extra attenuation measured was 1.5 dB. The maximum propagation distance was 76 m. The behavior of the asymetric waveforms received in one experiment qualitatively suggested that beam type diffraction effects were present. The role of diffraction of high intensity sound waves in radiation from a single horn was briefly investigated.

Theobald, M. A.↗

Rain and cloud effects on a satellite dual-frequency radar altimeter system operating at 13.5 and 35 GHz

The influence of clouds and rain on the return waveform signatures from satellite borne radar altimeters operating at 13.5 and 35 GHz are examined. It is specifically demonstrated that spatial nonuniformity in the cloud liquid water content or variations of the rain rate may result in significant distortions of the altimeter signature. The distorted signal is produced as a result of nonuniform attenuation occurring at the different range bins associated with the reflected signal. Determination of the mean sea height by employing tracking algorithms on these distorted echoes may result in gross errors. Although the influence of clouds on the altimeter signature and hence tracking precision is minimal at 13.5 GHz (e.g., less than 4 cm for a 1-s average), it may produce unacceptable mean sea level uncertainties at 35 GHz (e.g., 20 cm for a 1-s average) assuming a significant waveheight of 4 m. On the other hand, the signatures at both 13.5 GHz and 35 GHz become grossly distorted for rain rates of 10 mm/h and higher resulting in mean sea height errors of 46 and 65 cm, respectively, for significant wave heights of 2 m.

Walsh, E. J.↗

An OFDM System Using Polyphase Filter and DFT Architecture for Very High Data Rate Applications

This paper presents a conceptual architectural design of a four-channel Orthogonal Frequency Division Multiplexing (OFDM) system with an aggregate information throughput of 622 megabits per second (Mbps). Primary emphasis is placed on the generation and detection of the composite waveform using polyphase filter and Discrete Fourier Transform (DFT) approaches to digitally stack and bandlimit the individual carriers. The four-channel approach enables the implementation of a system that can be both power and bandwidth efficient, yet enough parallelism exists to meet higher data rate goals. It also enables a DC power efficient transmitter that is suitable for on-board satellite systems, and a moderately complex receiver that is suitable for low-cost ground terminals. The major advantage of the system as compared to a single channel system is lower complexity and DC power consumption. This is because the highest sample rate is half that of the single channel system and synchronization can occur at most, depending on the synchronization technique, a quarter of the rate of a single channel system. The major disadvantage is the increased peak-to-average power ratio over the single channel system. Simulation results in a form of bit-error-rate (BER) curves are presented in this paper.

Kifle, Muli↗

A Miniaturized Video System for Monitoring Drosophila Behavior

Long-term spaceflight may induce a variety of harmful effects in astronauts, resulting in altered motor and cognitive behavior. The stresses experienced by humans in space - most significantly weightlessness (microgravity) and cosmic radiation - are difficult to accurately simulate on Earth. In fact, prolonged and concomitant exposure to microgravity and cosmic radiation can only be studied in space. Behavioral studies in space have focused on model organisms, including Drosophila melanogaster. Drosophila is often used due to its short life span and generational cycle, small size, and ease of maintenance. Additionally, the well-characterized genetics of Drosophila behavior on Earth can be applied to the analysis of results from spaceflights, provided that the behavior in space is accurately recorded. In 2001, the BioExplorer project introduced a low-cost option for researchers: the small satellite. While this approach enabled multiple inexpensive launches of biological experiments, it also imposed stringent restrictions on the monitoring systems in terms of size, mass, data bandwidth, and power consumption. Suggested parameters for size are on the order of 100 mm3 and 1 kg mass for the entire payload. For Drosophila behavioral studies, these engineering requirements are not met by commercially available systems. One system that does meet many requirements for behavioral studies in space is the actimeter. Actimeters use infrared light gates to track the number of times a fly crosses a boundary within a small container (3x3x40 mm). Unfortunately, the apparatus needed to monitor several flies at once would be larger than the capacity of the small satellite. A system is presented, which expands on the actimeter approach to achieve a highly compact, low-power, ultra-low bandwidth solution for simultaneous monitoring of the behavior of multiple flies in space. This also provides a simple, inexpensive alternative to the current systems for monitoring Drosophila populations in terrestrial experiments, and could be especially useful in field experiments in remote locations. Two practical limitations of the system should be noted: first, only walking flies can be observed - not flying - and second, although it enables population studies, tracking individual flies within the population is not currently possible. The system used video recording and an analog circuit to extract the average light changes as a function of time. Flies were held in a 5-cm diameter Petri dish and illuminated from below by a uniform light source. A miniature, monochrome CMOS (complementary metal-oxide semiconductor) video camera imaged the flies. This camera had automatic gain control, and this did not affect system performance. The camera was positioned 5-7 cm above the Petri dish such that the imaging area was 2.25 sq cm. With this basic setup, still images and continuous video of 15 flies at one time were obtained. To reduce the required data bandwidth by several orders of magnitude, a band-pass filter (0.3-10 Hz) circuit compressed the video signal and extracted changes in image luminance over time. The raw activity signal output of this circuit was recorded on a computer and digitally processed to extract the fly movement "events" from the waveform. These events corresponded to flies entering and leaving the image and were used for extracting activity parameters such as inter-event duration. The efficacy of the system in quantifying locomotor activity was evaluated by varying environmental temperature, then measuring the activity level of the flies.

Bhattacharya, Sharmila↗

Using a Genetic Algorithm to Model Broadband Regional Waveforms for Crustal Structure in the Western United States

In this study, we analyze regional seismograms to obtain the crustal structure in the eastern Great Basin and western Colorado plateau. Adopting a for- ward-modeling approach, we develop a genetic algorithm (GA) based parameter search technique to constrain the one-dimensional crustal structure in these regions. The data are broadband three-component seismograms recorded at the 1994-95 IRIS PASSCAL Colorado Plateau to Great Basin experiment (CPGB) stations and supplemented by data from U.S. National Seismic Network (USNSN) stations in Utah and Nevada. We use the southwestern Wyoming mine collapse event (M(sub b) = 5.2) that occurred on 3 February 1995 as the seismic source. We model the regional seismograms using a four-layer crustal model with constant layer parameters. Timing of teleseismic receiver functions at CPGB stations are added as an additional constraint in the modeling. GA allows us to efficiently search the model space. A carefully chosen fitness function and a windowing scheme are added to the algorithm to prevent search stagnation. The technique is tested with synthetic data, both with and without random Gaussian noise added to it. Several separate model searches are carried out to estimate the variability of the model parameters. The average Colorado plateau crustal structure is characterized by a 40-km-thick crust with velocity increases at depths of about 10 and 25 km and a fast lower crust while the Great Basin has approximately 35- km-thick crust and a 2.9-km-thick sedimentary layer.

Bhattacharyya, Joydeep↗