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At least 127 records · Page 7

High-Performance Scanning Acousto-Ultrasonic System

A high-performance scanning acousto-ultrasonic system, now undergoing development, is designed to afford enhanced capabilities for imaging microstructural features, including flaws, inside plate specimens of materials. The system is expected to be especially helpful in analyzing defects that contribute to failures in polymer- and ceramic-matrix composite materials, which are difficult to characterize by conventional scanning ultrasonic techniques and other conventional nondestructive testing techniques. Selected aspects of the acousto-ultrasonic method have been described in several NASA Tech Briefs articles in recent years. Summarizing briefly: The acousto-ultrasonic method involves the use of an apparatus like the one depicted in the figure (or an apparatus of similar functionality). Pulses are excited at one location on a surface of a plate specimen by use of a broadband transmitting ultrasonic transducer. The stress waves associated with these pulses propagate along the specimen to a receiving transducer at a different location on the same surface. Along the way, the stress waves interact with the microstructure and flaws present between the transducers. The received signal is analyzed to evaluate the microstructure and flaws. The specific variant of the acousto-ultrasonic method implemented in the present developmental system goes beyond the basic principle described above to include the following major additional features: Computer-controlled motorized translation stages are used to automatically position the transducers at specified locations. Scanning is performed in the sense that the measurement, data-acquisition, and data-analysis processes are repeated at different specified transducer locations in an array that spans the specimen surface (or a specified portion of the surface). A pneumatic actuator with a load cell is used to apply a controlled contact force. In analyzing the measurement data for each pair of transducer locations in the scan, the total (multimode) acousto-ultrasonic response of the specimen is utilized. The analysis is performed by custom software that extracts parameters of signals in the time and frequency domains. The computer hardware and software provide both real-time and postscan processing and display options. For example, oscilloscope displays of waveforms and power spectral densities are available in real time. Images can be computed while scanning continues. Signals can be digitally preprocessed and/or post-processed by filtering, windowing, time-segmenting, and running-waveform-averaging algorithms. In addition, the software affords options for off-line simulation of the waveform-data-acquisition and scanning processes. In tests, the system has been shown to be capable of characterizing microstructural changes and defects in SiC/SiC and C/SiC ceramic-matrix composites. Delaminations, variations in density, microstructural changes attributable to infiltration by silicon, and crack-space indications (defined in the next sentence) have been revealed in images formed from several time- and frequency-domain parameters of scanning acousto-ultrasonic signals. The crack-space indications were image features that were not revealed by other nondestructive testing methods and are so named because they turned out to mark locations where cracking eventually occurred.

Roth, Don↗

AI Applications to Physics Experiments at Jefferson Lab

We survey how AI/ML is being deployed across Jefferson Lab's experimental and accelerator programs. In EPSCI, Hydra applies computer vision to automate real-time data-quality monitoring across all four experimental halls, replacing manual inspection of hundreds to thousands of histograms per shift. AIEC (AI Experiment Controls) uses ML to stabilize drift chamber gains and is now part of standard CEBAF production running, while AI Optimized Polarization (AIOP) targets autonomous control of polarized targets and photon beam angular alignment. In CASA, cavity fault classification models identify faulted cavities and trip types from waveform data with ~85% and ~78% agreement to labeled data, respectively, and are deployed in production; a separate effort applies LLMs and hybrid search to make the CEBAF operations logbook AI-ready. QCD-focused work includes transformer- and GAN-based generative models for particle-level event simulation, with distributed GAN training scaling studies on Polaris. Additional efforts span ML-on-FPGA for the EIC and a new Data Science Department coordinating anomaly detection, uncertainty quantification, and HPC-scalable ML lab-wide. Collectively, these projects illustrate AI's growing role in improving efficiency across JLab's nuclear physics mission.

Mei, Xinxin [Thomas Jefferson National Accelerator↗

Fourier-DeepONet: Fourier-enhanced deep operator networks for full waveform inversion with improved accuracy, generalizability, and robustness

In this article, full waveform inversion (FWI) infers the subsurface structure information from seismic waveform data by solving a non-convex optimization problem. Data-driven FWI has been increasingly studied with various neural network architectures to improve accuracy and computational efficiency. Nevertheless, the applicability of pre-trained neural networks is severely restricted by potential discrepancies between the source function used in the field survey and the one utilized during training. Here, we develop a Fourier-enhanced deep operator network (Fourier-DeepONet) for FWI with the generalization of seismic sources, including the frequencies and locations of sources. Specifically, we employ the Fourier neural operator as the decoder of DeepONet, and we utilize source parameters as one input of Fourier-DeepONet, facilitating the resolution of FWI with variable sources. To test Fourier-DeepONet, we develop three new and realistic FWI benchmark datasets (FWI-F, FWI-L, and FWI-FL) with varying source frequencies, locations, or both. Our experiments demonstrate that compared with existing data-driven FWI methods, Fourier-DeepONet obtains more accurate predictions of subsurface structures in a wide range of source parameters. Moreover, the proposed Fourier-DeepONet exhibits superior robustness when handling data with Gaussian noise or missing traces and sources with Gaussian noise, paving the way for more reliable and accurate subsurface imaging across diverse real conditions.

42 ENGINEERING↗

Polar Plasma Wave Observations in the Auroral Region and Polar Cap

Auroral kilometric radiation (AKR), sometimes associated with auroral myriametric radiation (AMR), has been observed by the plasma wave instrument on board Polar on almost every northern hemisphere pass. High spectral resolution plots of the AKR obtained by the wide-band receiver of the plasma wave instrument on board the spacecraft often show discrete, negative-slope striations each extending over a period of several seconds. A preliminary survey of over 4000 spectrograms (each for 48 seconds of data) indicates that the striations are seen in the northern hemisphere near apogee about 5% of the time. The frequency range is 40 kHz less than f less than 100 kHz, but a few observations of signatures have been made at higher frequency (f less than 225 khz. The frequency drift rates R, are similar ranging from -9.0 kHz/sec less than R less than -1.0 kHz/sec. No data is currently available for perigee (southern hemisphere) passes. The paucity of positive-slope features may be due to the location of the satellite at altitudes well above the AKR source region. Past studies have suggested these features are due to AKR wave growth stimulated by the propagation of electromagnetic ion cyclotron waves travelling up (-R) or down (+R) the field line, through the source region. High-resolution waveform data from both Polar and FAST show the presence of solitary waves in the auroral region which may also be a source of these striations. AMR is seen as diffuse emission associated with, but at lower frequency than the lower AKR. Direction finding of these emissions is not conclusive, but for one case, they have a source region distinct from the magnetic field line containing the AKR source, but possibly associated with the auroral cavity density gradient.

Menietti, J. D.↗

Evaluation of a Seismic Event, 12 May 2010, in North Korea

We assess seismological evidence bearing on claims that North Korea conducted a small nuclear test on 12 May 2010 in the vicinity of known underground nuclear tests in 2006, 2009, 2013, and 2016. First, we use Lg -wave cross-correlation and more traditional methods to locate the 2010 event between about 4 and 10 km southwest of the 2009 test. Second, we compare the relative sizes of regional P-waves and S-waves, using stations within 400 km of the known North Korean nuclear tests, to assess the nature of the event. We measured P / S ratios at different frequencies, at first using data from the open station MDJ in northeast China, for training sets of earthquakes and of explosions. We developed a linear discriminant function (LDF), that, in application to P / S measured at MDJ, is most effective in separating the earthquake and explosion populations. MDJ lacks usable data for the event of interest, but we have obtained regional data from stations of the nearby Dongbei Broadband Seismographic Network (DBSN), for the event of 12 May 2010 and for nearby underground nuclear tests conducted in 2006 and 2009. When our LDF is applied to DBSN data, and to data from stations SMT and NE3C in China, the LDF values measured from P/S ratios from known explosions are explosion-like; but for the event of 12 May 2010 the LDF values are earthquake-like for frequencies between 6 and 12 Hz. Furthermore, our method for characterizing earthquakes and explosions on the basis of their regional signals can be widely applied. Measurements of P / S based upon three-component waveform data provide better discrimination power than do those based upon vertical-component data alone.

58 GEOSCIENCES↗

Multicolor Photometric Observation of Lightning from Space: Comparison with Radio Measurements

This study evaluates the effectiveness of spectrophotometric measurements from space in revealing properties of lightning flash. The multicolor optical waveform data obtained by FORMOSAT-2/Imager of Sprites and Upper Atmospheric Lightning (ISUAL) were analyzed in relation to National Lightning Detection Network (NLDN), North Alabama Lightning Mapping Array (LMA). As of July 2011, we found six lightning events which were observed by ISUAL and North Alabama LMA. In two of these events, NLDN showed clear positive cloud-to-ground (CG) discharges with peak current of +139.9 kA and +41.6 kA and, around that time, LMA showed continuous intra-cloud (IC) leader activities at 4-6 km altitudes. ISUAL also observed consistent optical waveforms of the IC and CG components and, interestingly, it was found that the blue/red spectral ratio clearly decreased by a factor of 1.5-2.5 at the time of CG discharges. Other four lightning events in which NLDN did not detect any CG discharges were also investigated, but such a feature was not found in any of these cases. These results suggest that the optical color of CG component is more reddish than that of IC component and we explain this as a result of more effective Rayleigh scattering in blue light emissions coming from lower-altitude light source. This finding suggests that spectral measurements could be a new useful technique to characterize ICs and CGs from space. In this talk, we will also present a result from lightning statistical analysis of ISUAL spectrophotometric data and ULF magnetic data.

Adachi, Toru↗

Seismic source characterization of the Arabian Peninsula and Zagros Mountains from regional moment tensor and coda envelopes

Reliable estimates of moment magnitude and source mechanism for seismic events in the Middle East can be challenging due to a small number of openly available stations, the complex tectonic setting, and regions of high attenuation. Access to high-quality waveform data from well-calibrated regional seismic stations is fundamental in producing robust and stable estimates of earthquake source parameters, particularly when measurements of absolute ground motion amplitudes are required. Earthquake source mechanism and moment magnitude are invaluable information in the assessment of seismic hazard, plate motions, and the characterization of faults and regional stress field. The expansion of the Kingdom of Saudi Arabia’s national seismic network in the past several decades provides an opportunity to develop the capabilities of routine focal mechanism and moment magnitude estimations. In this study, we use time-domain full waveform moment tensor inversion and coda envelope–derived amplitude measurements to solve for earthquake source mechanism, moment magnitudes, and their source type. Furthermore, we compared the moment magnitudes calculated from the two methods and publicly available earthquake catalogs and discuss the implications of the obtained source parameters.

58 GEOSCIENCES↗

Peak Ground Displacement Saturates Exactly When Expected: Implications for Earthquake Early Warning

The scaling of rupture properties with magnitude is of critical importance to earthquake early warning (EEW) systems that rely on source characterization using limited snapshots of waveform data. ShakeAlert, a prototype EEW system that is being developed for the western United States, provides real-time estimates of earthquake magnitude based on P-wave peak ground displacements calculated at stations triggered by the event. The algorithms used in ShakeAlert assume that the displacement measurements at each station are statistically independent and that there exists a linear and time-independent relation between log peak ground displacement and earthquake magnitude. Here we challenge this basic assumption using the largest dataset assembled for this purpose to date: a comprehensive database of more than 140,000 vertical-component waveforms from M4.5–M9 earthquakes occurring near Japan from 1997 through 2018 and recorded by the K-NET and KiK-net strong-motion networks. By analyzing the time-evolution of P-wave peak ground displacements for these earthquakes, we show that there is a break, or saturation, in the magnitude-displacement scaling that depends on the length of the measurement time window. We demonstrate that the magnitude at which this saturation occurs is well-explained by a simple and non-deterministic model of earthquake rupture growth. We then utilize the predictions of this saturation model to develop a Bayesian framework for estimating posterior uncertainties in real-time magnitude estimates.

58 GEOSCIENCES↗

Acquisition and analysis of angle-beam wavefield data

Angle-beam ultrasonic testing is a common practical technique used for nondestructive evaluation to detect, locate, and characterize a variety of material defects and damage. Greater understanding of the both the incident wavefield produced by an angle-beam transducer and the subsequent scattering from a variety of defects and geometrical features is anticipated to increase the reliability of data interpretation. The focus of this paper is on acquiring and analyzing propagating waves from angle-beam transducers in simple, defect-free plates as a first step in the development of methods for flaw characterization. Unlike guided waves, which excite the plate throughout its thickness, angle-beam bulk waves bounce back and forth between the plate surfaces, resulting in the well-known multiple “skips” or “V-paths.” The experimental setup consists of a laser vibrometer mounted on an XYZ scanning stage, which is programmed to move point-to-point on a rectilinear grid to acquire waveform data. Although laser vibrometry is now routinely used to record guided waves for which the frequency content is below 1 MHz, it is more challenging to acquire higher frequency bulk waves in the 1–10 MHz range. Signals are recorded on the surface of an aluminum plate that were generated from a 5 MHz, 65° refracted angle, shear wave transducer-wedge combination. Data are analyzed directly in the x-t domain, via a slant stack Radon transform in the τ-p (offset time-slowness) domain, and via a 2-D Fourier transform in the ω-k domain, thereby enabling identification of specific arrivals and modes. Results compare well to those expected from a simple ray tracing analysis except for the unexpected presence of a strong Rayleigh wave.

42 ENGINEERING↗

Major disruption of D" beneath Alaska

D'' represents one of the most dramatic thermal and compositional layers within our planet. In particular, global tomographic models display relatively fast patches at the base of the mantle along the circum-Pacific which are generally attributed to slab debris. Such distinct patches interact with the bridgmanite (Br) to post-bridgmanite (PBr) phase boundary to generate particularly strong heterogeneity at their edges. Most seismic observations for the D'' come from the lower mantle S wave triplication (Scd). Here, in this work, we exploit the USArray waveform data to examine one of these sharp transitions in structure beneath Alaska. From west to east beneath Alaska, we observed three different characteristics in D'': (1) the western region with a strong Scd, requiring a sharp δVs = 2.5% increase; (2) the middle region with no clear Scd phases, indicating a lack of D'' (or thin Br-PBr layer); and (3) the eastern region with strong Scd phase, requiring a gradient increase in δVs. To explain such strong lateral variation in the velocity structure, chemical variations must be involved. We suggest that the western region represents relatively normal mantle. In contrast, the eastern region is influenced by a relic slab that has subducted down to the lowermost mantle. In the middle region, we infer an upwelling structure that disrupts the Br-PBr phase boundary. Such an interpretation is based upon a distinct pattern of travel time delays, waveform distortions, and amplitude patterns that reveal a circular-shaped anomaly about 5° across which can be modeled synthetically as a plume-like structure rising about 400 km high with a shear velocity reduction of ~5%, similar to geodynamic modeling predictions of upwellings.

58 GEOSCIENCES↗

Detection of random noise and anatomy of continuous seismic waveforms in dense array data near Anza California

We develop a methodology to separate continuous seismic waveforms into random noise (RN), not random noise (NRN) produced by earthquakes, wind, traffic and other sources of ground motions, and an undetermined mixture of signals. The analysis is applied to continuous records from a dense seismic array on the San Jacinto fault zone. To detect RN signals, we cut hourly waveforms into non-overlapping 1 s time windows and apply cross-correlations to separate RN candidates from outliers. The cross-correlation coefficients between different RN candidates fall into a tight range (i.e. 0.09–0.35), while cross-correlation coefficients of RN candidates with NRN signals (e.g. seismic or air-traffic events) are lower. The amplitude spectra of RN candidates have a well-defined level, while the amplitude spectra of other signals deviate from that level. Using these properties, we examine the amplitude spectra of moving time windows and cross-correlation coefficients with RN templates in each hour. The hourly RN is quasi-stationary and the results cluster tightly in the parameter space of cross-correlation coefficients and L2 norm deviations from the mean spectra of RN candidates. Time windows with parameters in this tight cluster are identified as RN, windows that deviate significantly from the RN cluster are identified as NRN and windows with values in between are identified as mixed signals. Several iterations on each hourly data are used to update and stabilize the selection of RN templates and mean noise spectra. For the days examined, the relative fractions of RN, NRN and mixed signals in local day (night) times are about 26 (42 percent), 40 (33 percent) and 34 percent (25 percent), respectively.

Geochemistry & Geophysics↗

Synchronized Waveforms – A Frontier of Data-Based Power System and Apparatus Monitoring, Protection, and Control

Voltage and current waveforms contain the most authentic and granular information on the behaviors of power systems. In recent years, it has become possible to synchronize waveform data measured from different locations. Thus large-scale coordinated analyses of multiple waveforms over a wide area are within our reach. This development could unleash a set of new concepts, strategies, and tools for monitoring, protecting, and controlling power systems and apparatuses. This paper presents an in-depth review and analysis of the advancements in synchronized waveform data, including measurement devices, data characteristics, use cases, and comparisons with synchrophasor data. Based on the findings, five strategies are proposed to discover and develop synchronized waveform based applications over multiple application areas. The paper also presents three complementary measurement platforms and two data screening algorithms for application implementation. It further discusses committee activities and standard developments useful to explore the full potential of the data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Dynamic Networks Experiments: Virtual Experiments to Quantify Gains in Nuclear Explosion Monitoring

We describe an ongoing series of virtual experiments conducted collaboratively by four United States National Laboratories: Sandia National Laboratories, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory. These Dynamic Network Experiments (DNEs) provide an experimental framework to evaluate the potential impact of new research tools on nuclear explosion monitoring. The second DNE (DNE2), completed in 2024, exploited waveform data (seismic, infrasound, and electromagnetic) that was recorded by multi-modal sensors within and near the Nevada National Security Site and synthetic radionuclide signatures over multiple time periods. During the execution of DNE2, we processed and analyzed data through a multi-stage event processing pipeline that ingested raw data, performed quality control, detected signals, built events from these signals, located these events, and characterized the events’ source types and sizes. For each stage and over the entire event processing pipeline, we evaluated performance changes by comparing the performance of new data processing methods, models, and algorithms against a baseline. We also performed an additional execution phase to assess event processing pipeline function, speed, and efficiency against that of an expert analyst, including computational and manual efforts. Finally, we assessed the impact and effort of modern computing infrastructure on the monitoring pipeline. This paper describes key elements of the DNEs, from formulation through execution, as demonstrated in DNE2. The DNEs introduce several novel concepts to quantitatively measure the potential impact of new methods on explosion monitoring, including the collaborative design of multi-modal datasets, performance and logistical metrics, and integrated analyses.

42 ENGINEERING↗

The role of source geometry and atmospheric propagation in global bolide infrasound detectability

Global infrasound monitoring provides a persistent means of detecting energetic bolide atmospheric entries, complementing optical observations and extending coverage over remote regions. We present a global assessment of the physical factors governing bolide infrasound detectability by correlating 623 bolide events reported by the Center for Near-Earth Object Studies between 2007 and 2025 with waveform data from the International Monitoring System. We identify 311 events with confirmed infrasound detections, corresponding to a detection rate of approximately 50%, substantially higher than inferred from earlier surveys, reflecting both the maturation of the global infrasound network and advances in automated, multi-frequency array processing. Analysis of flight parameters shows that infrasound detectability is selective rather than uniform across the bolide population. Detected events are preferentially associated with steeper entry angles and lower-altitude energy deposition, while shallow, high-altitude trajectories are less consistently observed. Very high-energy events remain detectable regardless of geometry, but for the more common lower-energy regime, observability depends on specific combinations of entry parameters and propagation conditions. This geometric dependence persists across comparable energy ranges and atmospheric conditions, indicating that entry angle exerts a primary control on detectability, with energy and propagation acting as secondary modulating factors. Furthermore, these results provide new physical constraints on bolide-atmosphere interactions and improve interpretation of global infrasound observations for planetary defense and atmospheric-entry studies.

Bolides↗

Visualization of hydraulic fracture using physics-informed clustering to process ultrasonic shear waves

Ultrasonic transmission is sensitive to the spatial variation in mechanical properties of materials due to the presence of cracks/fractures. Wave propagation through fractured media introduces changes in the frequency content, travel time and transmission coefficient of the wave. A workflow based on physics-informed unsupervised learning is developed to process the transmitted ultrasonic-shear waveforms to non-invasively visualize the geomechanical alterations due to hydraulic fracturing. Novelty of the work involves the assignment of both statistically consistent and physically consistent clusters to the measurements of shear waveforms acquired across the one axial and two frontal planes. Physically consistent/relevant information is incorporated by considering the travel time of the peak of spectral energy and transmission coefficient of the transmitted waveform. The proposed workflow generates maps of geomechanical alterations across the frontal and axial planes of the sample. The outputs of the workflow are in good agreement with independent techniques viz. acoustic emission and X-ray computed tomography. Finally, the proposed workflow can be adapted for improved fracture characterization in the subsurface when processing sonic-logging, cross-wellbore seismic or surface seismic waveform data.

42 ENGINEERING↗

Machine-Learning-Based Analysis of the Guy-Greenbrier, Arkansas Earthquakes: A Tale of Two Sequences

Here, we revisited the June 2010 to October 2011 Guy-Greenbrier earthquake sequence in central Arkansas using PhaseNet, a deep neural network trained to pick P and S arrival times. We applied PhaseNet to continuous waveform data and used phase association and hypocenter relocation to locate nearly 90,000 events. Our catalog suggests that the sequence consists of two adjacent earthquake sequences on the same fault and that the second sequence may be associated with the wastewater disposal well to the west of the Guy-Greenbrier Fault, rather than the wells to the north and the east that were previously implicated. We find that each sequence is composed of many small clusters that exhibit diffusion along the fault at shorter timescales. Our study demonstrates that machine-learning-based earthquake catalog development is now feasible and will yield new insights into earthquake behavior.

58 GEOSCIENCES↗

The Spatiotemporal Evolution of Granular Microslip Precursors to Laboratory Earthquakes

Laboratory earthquake experiments provide important observational constraints for our understanding of earthquake physics. Here we leverage continuous waveform data from a network of piezoceramic sensors to study the spatial and temporal evolution of microslip activity during a shear experiment with synthetic fault gouge. We combine machine learning techniques with ray theoretical seismology to detect, associate, and locate tens of thousands of microslip events within the gouge layer. Microslip activity is concentrated near the center of the system but is highly variable in space and time. While microslip activity rate increases as failure approaches, the spatiotemporal evolution can differ substantially between stick-slip cycles. These results illustrate that even within a single, well-constrained laboratory experiment, the dynamics of earthquake nucleation can be highly complex.

58 GEOSCIENCES↗

Combined Optical and Radio-Frequency Measurements of a Lightning Megaflash by the FORTE Satellite

The optical and VHF instrumentation on the Fast On-Orbit Recording of Transient Events (FORTE) satellite is used to document the combined phenomenology evolution of a lightning “megaflash” – mesoscale lightning that propagates laterally over exceptional distances. We identify a FORTE flash whose maximum extent was 82 km and inferred length over multiple distinct branches exceeded 100 km. This flash lasted 1.2 s and produced 250 optical and 591 RF events. We find that the channel development mapped by FORTE’s pixelated lightning imager (LLS) occurred at a typical speed of 2.6x10 5 m s -1 and was accompanied by sustained periods of VHF emission that could individually exceed 100 ms in duration. The impulsive IC events generated by the flash indicate that this development occurred at altitudes between 3 and 8 km. Four +CG strokes were identified in the VHF waveform data that are responsible for two of the three highly-radiant LLS groups (two of the +CGs were not as optically bright as the others). These strokes occurred at different locations throughout the flash footprint with the most distant strokes separated by approximately 50 km. These space-based observations match previous observations of megaflashes as well as ground-based measurements of negative leader development during “spider” lightning, suggesting that FORTE is sensing the same phenomena.

Peterson, Michael Jay↗