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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Infrasound and Gravity Waves Over the Andes Observed by a Pressure Sensor on Board a Stratospheric Balloon

The study of infrasound (acoustic) and gravity waves sources and propagation in the atmosphere of a planet gives us precious insight on atmosphere dynamics, climate, and even internal structure. The implementation of modern pressure sensors with high rate sampling on stratospheric balloons is improving their study. In our work we analyzed the data from the National Aeronautics and Space Administration Ultra Long Duration Balloon mission (16 May to 30 June 2016). Here, we focus on the balloon's transit of the Andes Mountains. We detected gravity waves that are associated to troposphere convective activity and mountain waves. An increase of the horizontal wavelengths from 50 to 70 km with increasing distance to the mountains is favoring the presence of mountain waves. We also report on the detection of infrasounds generated by the mountains in the 0.01–0.1 Hz range with a pressure amplitude increase by a factor 2 relative background signal. Besides, we characterized the decrease of microbaroms power when the balloon was flying away from the ocean coast. These observations suggest, in a way similar to microseisms for seismometers, that microbaroms are the main background noise sources recorded in the stratosphere even far from the ocean sources. Finally, we observed a broadband signal above the Andes, between 0.45 and 2 Hz, probably associated with a thunderstorm. The diversity of geophysical phenomena captured in less than a day of observation stresses the interest of high rate pressure sensors on board long-duration balloon missions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Monitoring Fracture Saturation With Internal Seismic Sources and Twin Neural Networks

Seismic coda-wave analysis is a well-developed method for detecting subtle physical changes in complex media by measuring arrival times in the late-arriving energy from multiply scattered or reflected waves. However, a challenge arises when multiply scattered waves are not sufficiently separated in time from the direct arrivals to provide a clear coda wave train. Additional complications for monitoring changes in fracture systems arise when the signals originate from unsynchronized internal sources, such as natural or induced seismicity, from acoustic emission, or from transportable intra-fracture sources (chattering dust), that generate uncontrolled signals that vary in arrival time, amplitude and frequency content. Here, we use a twin neural network (TNN also known as a Siamese neural network) for dimensionality reduction to analyze signals from chattering dust to classify the fluid saturation state of a synthetic fracture system. The TNN with shared weights generates a low-dimensional representation of the data input by minimizing contrastive loss, serving as the input to a multiclass classifier that accurately classifies whether multiple fractures in a fracture system are fully saturated or partially saturated, or whether a change in saturation has occurred in different fractures in the system. Furthermore, these results show that information buried in unresolved codas from uncontrolled sources can be extracted using machine learning to monitor the evolution of fracture systems caused by physical and chemical processes even when the scattered and direct wave fields overlap.

58 GEOSCIENCES↗
DOE OSTI2026

Multi‐Sensor Trajectory Reconstruction of the 24 April 2025 Alaska Fireball and Implications for Planetary Defense

On 24 April 2025 at 18:30:57 UTC, a bright daytime fireball over Southcentral Alaska was detected by 37 seismic stations, 16 single infrasound sensors, and four infrasound arrays, yielding 30 ballistic and multiple fragmentation arrivals. Here, the unprecedented density of seismoacoustic coverage enabled detailed reconstruction of the event using acoustic signals, with fragmentation source locations further guiding the identification of Doppler weather radar signatures of a meteorite fall. Incorporation of a radar-derived terminal point yielded a final trajectory solution, which agreed closely with an independent optical trajectory solution from video analysis. The reconstructed entry parameters from seismoacoustic analysis indicate a velocity of 25.3 km/s, an entry angle of 19°, and an energy release of ∼38 t TNT equivalent. Assuming a chondritic composition, the pre-entry object diameter was ∼0.7 m. Using orbital parameters from the optical solution, we estimate meteoroid composition as most likely an L-type ordinary chondrite. The event occurred in the sub-Arctic, where space-based optical systems face challenges in detection, demonstrating the critical role of dense ground-based seismoacoustic networks in characterizing high-latitude atmospheric entries. This uniquely well-recorded event demonstrates the capability of dense seismoacoustic networks to constrain bolide trajectories, energetics, and fragmentation, with radar and optical data providing critical confirmation and complementary perspectives. These results bridge the methodological gap between planetary-defense monitoring of natural impactors and space-traffic analyses of artificial reentries, illustrating how multi-sensor integration can deliver calibration-grade trajectories even for unpredicted events.

Fireball↗
DOE OSTI2023

Proto-neutron star convection and the neutrino-driven wind: implications for the r-process

The neutrino-driven wind from proto-neutron stars is a proposed site for r-process nucleosynthesis, although most previous work has found that a wind heated only by neutrinos cannot produce the third r-process peak. However, several groups have noted that introducing a secondary heating source within the wind can change the hydrodynamic conditions sufficiently for a strong r-process to proceed. One possible secondary heating source is gravito-acoustic waves, generated by convection inside the proto-neutron star. As these waves propagate into the wind, they can both accelerate the wind and shock and deposit energy into the wind. Additionally, the acceleration of the wind by these waves can reduce the total number of neutrino captures and thereby reduce the final electron fraction of the wind. In neutron rich conditions, all of these effects can make conditions more favourable for r-process nucleosynthesis. Here, we present a systematic investigation of the impact of these convection-generated gravito-acoustic waves within the wind on potential nucleosynthesis. We find that wave effects in the wind can generate conditions favourable for a strong r-process, even when the energy flux in the waves is a factor of 10 –4 smaller than the total neutrino energy flux and the wind is marginally neutron rich. Nevertheless, this depends strongly on the radius at which the waves become non-linear and form shocks. We also find that both entropy production after shock formation and the acceleration of the wind due to stresses produced by the waves prior to shock formation impact the structure and nucleosynthesis of these winds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Data Challenges in Multi-Sensor Data Science System for Monitoring a Solvent Extraction Process

Idaho National Laboratory (INL) is maintaining and gaining knowledge into the nuclear fuel cycle by building a test bed to allow researchers the opportunity to study nuclear fuel processing operations. This includes studying solvent extraction processes that use centrifugal contactors. As part of INL’s mission, the goal of this project is to develop a system that utilizes non-traditional measurement sources such as vibration, acoustics, current, light, flow, and temperature in conjunction with data-based, machine learning techniques that will allow for signal discovery. This multisensory data can support the development of safeguards by design, provide operator process awareness, and discover process anomalies. This poster will highlight some of the data collection and analytics challenges for the multi-sensor system as well as the mitigation strategies to build a robust system. Additionally, some preliminary data from the first testing campaign will be shown to help illustrate the data needs of the system.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Preliminary Results of a Multi-Sensor Data Science System for Monitoring a Solvent Extraction Process

Idaho National Laboratory is building a test bed to allow researchers the opportunity to study nuclear fuel processing operations. This includes studying the solvent extraction process and the use of centrifugal contactors. The goal of this project is to develop a system that utilizes non-traditional measurement sources such as vibration, acoustics, current, color, flow, and temperature in conjunction with data-based, machine learning techniques that will allow for signal discovery. This multi-sensor data supports the development of safeguards by design, provides operator process awareness, and aids in the discovery of process anomalies. This paper highlights some of the preliminary results from initial data collection campaigns and shares some of the lessons learned.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Development of a Multi-Sensor Data Science System Used for Signature Development on Solvent Extraction Processes in support of safeguards- an overview

A new nuclear fuel cycle test bed is being built at Idaho National Laboratory to support the purification of special nuclear material recovered from used fuel. The test bed provides an opportunity to research process flow and the application of computational tools in solvent extraction processes. A deeper understanding of process and equipment behavior coupled with real time data collection can indicate whether a process failure is accidental or purposeful. The goal of this project is to develop a system that utilizes non-traditional measurement sources such as vibration, acoustics, current, light, flow, and temperature in conjunction with data-based, machine learning techniques that will allow for signal discovery. This multi-sensor data can support the development of safeguards by design and security by design measures for such a facility. Additionally, it can aid in early detection and identification of removed materials indicating diversion, which is essential for initiating material recovery and actor identification. This overview encompasses the current research and testing of sensors to develop a spectrum of process signatures. To be followed by planned experiments aimed to characterize said signatures and study potential feature extraction techniques to identify a fault in the system (i.e. flow diversion).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Evaluation of Potential DAS Array Geometries for the Source Physics Experiment, Phase III

Distributed Acoustic Sensing (DAS) is a rapidly developing technology that can record acoustic wavefields at high sampling rates and with dense spatial spacing difficult to achieve with seismometers. However, the geophysical community has not fully explored DAS survey parameters to characterize the ideal array design. A better quantitative understanding of DAS array behavior prior to SPE Phase III acquisition can help improve the quality of the data recorded by guiding the DAS array design. Here we use array response functions as well as beamforming and backprojection results from forward modelling calculations to assess the performance of varying DAS array geometries to record regional and local sources. A seven-sided polygon DAS array demonstrated improved capabilities for recording regional sources over segmented linear arrays, with potential improvements in recording and locating local sources. These results help reveal DAS array performance as a function of geometry.

58 GEOSCIENCES↗
DOE OSTI2022

Outsourced hearing in an orb-weaving spider that uses its web as an auditory sensor

Hearing is a fundamental sense of many animals, including all mammals, birds, some reptiles, amphibians, fish, and arthropods. The auditory organs of these animals are extremely diverse in anatomy after hundreds of millions of years of evolution, yet all are made up of cellular tissue and are morphologically part of the bodies of animals. Here, we show that hearing in the orb-weaving spider Larinioides sclopetarius is not constrained by the organism’s body but is extended through outsourcing hearing to its extended phenotype, the proteinaceous, self-manufactured orb web. We find that the wispy, wheel-shaped orb web acts as a hyperacute acoustic antenna to capture the sound-induced air particle movements that approach the maximum physical efficiency better than the acoustic responsivity of all previously known eardrums. By sensing the motion of web threads, the spider remotely detects and localizes the source of an incoming airborne acoustic wave, such as those emitted by approaching prey or predators. By outsourcing its acoustic sensors to its web, the spider is released from body size constraints and permits the araneid spider to increase its sound-sensitive surface area enormously, up to 10,000 times greater than the spider itself. The spider also enables the flexibility to functionally adjust and regularly regenerate its external "eardrum" according to its needs. The outsourcing and supersizing of auditory function in spiders provides unique features for studying extended and regenerative sensing and designing novel acoustic flow detectors for precise fluid dynamic measurement and manipulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Towards more accurate sound field verification using directional acoustic filtering

Attributing omnidirectional sound levels to a specific source in the ocean can be challenging when there are multiple competing sources of sound such as boats, or biological activity. Here, we present a method to directionally filter acoustic measurements based on vector measurements of acoustic pressure and particle velocity. The directional discrimination is applied to estimate sound energy from two marine energy sources: sound generated during the decommissioning of an oil platform and those from an operating tidal energy converter. The application of a directional mask leads to distinctly different spectra and some differences in energy, relative to the unmasked scenarios.

Barosin, Emily (ORCID:0009000765495939)↗
DOE OSTI2023

A Multimodal Event Catalog and Waveform Data Set That Supports Explosion Monitoring from Nevada, U.S.A.

Multimodal, curated data sets and nuisance event catalogs remain rare in the explosion monitoring community relative to curated seismic data sets. The source of this relative absence is the difficultly in deploying multimodal receivers that sense the seismic, acoustic, and other modalities from multiphysics sources. We provide such a data set in this study that delivers seismic, infrasound, and electromagnetic (magnetometer) sensor records collected over a two–week period, within 255 km of a 10 ton buried chemical explosion called DAG–4 that was located at 37.1146°, –116.0693° on 22 June 2019 21:06:19.88 UTC. This catalog includes 485 seismic, seismoacoustic, and infrasound–only events that an expert analyst manually built by reviewing waveforms from 29 seismic and infrasound sensors. Our data release includes waveforms from these 29 seismic, infrasound, and seismoacoustic stations and two magnetometer stations and their station metadata. We deliver these waveforms in NNSA KB Core CSS.w format (i4) with a corresponding wfdisc table that provides the header information. Here, we expect that this data set will provide a valuable, benchmark resource to develop signal processing algorithms and explosion monitoring methods against manual, human observations.

58 GEOSCIENCES↗
DOE OSTI2025

Injection Locking of Gigahertz‐Frequency Surface Acoustic Wave Phononic Crystal Oscillator

Low-noise gigahertz (GHz) frequency sources are essential for applications in signal processing, sensing, and telecommunications. Surface acoustic wave (SAW) resonator-based oscillators offer compact form factors and low-phase noise due to their short mechanical wavelengths and high-quality (Q) factors. However, their small footprint makes them vulnerable to environmental variation, resulting in their poor long-term frequency stability. Injection locking is widely used to suppress frequency drift of lasers and oscillators by synchronizing to an ultra-stable reference. Here, injection locking of a 1-GHz SAW phononic-crystal oscillator is demonstrated, achieving 40-dB phase noise reduction at low offset frequencies and unperturbed low noise at large offset frequencies. Compared to a free-running SAW oscillator, which typically exhibits frequency drifts of several hundred hertz over minutes, the injection-locked oscillator reduces the frequency deviation to below 0.35 Hz. The locking range and oscillator dynamics is also investigated in the injection pulling region. The demonstrated injection-locked SAW oscillator could find applications in high-performance portable telecommunications and sensing systems.

injection locking↗
DOE OSTI2023

Demonstration of acoustic monitoring for structural health of microreactors: Through use of neural networks and resonant ultrasound spectroscopy

Nuclear microreactors prioritize modularity and portability and are intended to be a cost-effective technology for non-conventional nuclear markets. As such, the development of microreactors into a safe and feasible solution for energy security applications will necessitate the development of non-destructive technologies to monitor the integrity of inaccessible reactors components during operation. This demonstration applies linear and nonlinear acoustic techniques, in combination with machine learning, to detect and classify mechanical changes (stress and damage) in a test article which are broadly representative of potential operating challenges within a functioning microreactor. All necessary data has been collected for this demonstration, with minor experimental issues identified that can be addressed in follow-on work. Motivated by the expected conditions within a functioning microreactor, we have demonstrated our monitoring techniques on a core-block-like test article using an unstructured excitation source that approximates the noisy acoustic environment expected during reactor operation. At all stress states mechanically applied to the test article, a machine learning model using an artificial neural network was able to classify with 100% accuracy whether a 3D laser vibrometry point measurement was made on an intact or artificially defective test article. Further, model predictions about whether the defect interface was rough or smooth were 95% accurate, indicating the ability of acoustic techniques to recover defect characteristics. Resonant ultrasound spectroscopy (RUS) was also applied to the dataset to provide further quantitative insights about material properties. RUS analysis was ultimately hampered by several minor experimental and data issues, limiting results to certain cases for this demonstration. Last, analysis using nonlinear RUS exhibited sensitivity to changing levels of applied stresses for each intact and defective state. As presented in this demonstration, acoustic monitoring exhibits sensitivity to stress changes, which are of concern due to high thermal gradients expected during startup and operation. Further, our techniques distinguish between measurements made on intact and damaged test articles.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Journey to Time-Variable Moment Tensors through Inversion of Acoustic and Seismoacoustic Data

We explore the capability of acoustic and seismoacoustic datasets to directly resolve a complex, time-variable source consisting of a buried mechanism, represented as a moment tensor, and a spall mechanism, represented as a vertical force at the surface. Traditionally, each component of a resolved moment tensor assumes one underlying source time function, which likely fails to capture the full evolution of a dynamic source, such as an explosion followed by slip on near-source joints or development of spallation. Specifically, we expand previous work to resolve a time-variable moment tensor using single-modality and joint-modality inversion frameworks through analysis of infrasound and seismoacoustic data recorded as part of the Source Physics Experiment Phase II: Dry Alluvium Geology (DAG). We investigate the impact of including signals from seismic-to-air coupling that are local to each infrasound sensor in comparison to mainly atmosphere-propagating acoustic signals, which occur from coupling of the wavefield from the subsurface to the atmosphere directly above the source. Additionally, we assess the ability of our inversion algorithm to fit observed infrasound data using a variety of time-variable source mechanisms. First, we consider the buried moment tensor source alone, which assumes that the determined Green’s functions incorporate effects from spallation or that the impact from spallation is minimal. Second, we examine the estimated buried moment tensor and vertical surface spallation as terms that must both be resolved in the inversion. Third, we assess the ability for an estimated vertical surface spallation source to fit the acoustic data on its own. Finally, we compare results from the joint inversion of both seismic geophone and infrasound acoustic data for the buried-only source compared to buried and spallation sources. Our results are a preliminary investigation into the applications of the inversion technique to recorded datasets and show the technique has limited capabilities using acoustic data alone. Instead, this method shows promise for seismic and seismoacoustic datasets to resolve the time-variable mechanisms of a buried source.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Seismoacoustic Signatures Observed During a Long-Term Deployment of Infrasound Sensors at the Nevada National Security Site

Earthquakes have repeatedly been shown to produce inaudible acoustic signals (<20 Hz), otherwise known as infrasound. These signals can propagate hundreds to thousands of kilometers and still be detected by ground-based infrasound arrays depending on the source strength, distance between source and receiver, and atmospheric conditions. Another type of signal arrival at infrasound arrays is the seismic induced motion of the sensor itself, or ground-motion-induced sensor noise. Measured acoustic and seismic waves produced by earthquakes can provide insight into properties of the earthquake such as magnitude, depth, and focal mechanism, as well as information about the local lithology and atmospheric conditions. Large earthquakes that produce strong acoustic signals detected at distances greater than 100 km are the most commonly studied; however, more recent studies have found that smaller magnitude earthquakes ($M$ w <2.0) can be detected at short ranges. In that vein, this study will investigate the ability for a long-term deployment of infrasound sensors (deployed as part of the Source Physics Experiments [SPE] from 2014 to 2020) to detect both seismic and infrasonic signals from earthquakes at local ranges (<50 km). Methods used include a combination of spectral analysis and automated array processing, supported by U.S. Geological Survey earthquake bulletins. Further, this investigation revealed no clear acoustic detections for short range earthquakes. However, secondary infrasound from an $M$ w 7.1 earthquake over 200 km away was detected. Important insights were also made regarding the performance of the SPE networks including detections of other acoustic sources such as bolides and rocket launches. Finally, evaluation of the infrasound arrays is performed to provide insight into optimal deployments for targeting earthquake infrasound.

58 GEOSCIENCES↗
DOE OSTI2025

Estimating an airborne dipole source using 3-D wavefield simulations and seismic receivers on the ground

Acoustic signals can couple to the ground, providing an opportunity to use seismic stations to investigate airborne sources. The study of Bishop et al. used wavefield simulations in a fluid-solid medium to quantify the role of topography on the seismic (ground) recordings of a monopole source in the air. We build upon this study by linking wavefield forward modelling with the source estimation code MTUQ, which can accommodate point forces or moment tensors in a solid medium, as well as sources in the air (or water) if they are enabled by the forward-modelling solver. We perform a series of synthetic numerical experiments to demonstrate that a dipole airborne source can be estimated using ground-based receivers, even within the presence of realistic topography. We investigate the influence of receiver coverage, topography, and assumed source location on the estimated results. The established capabilities raise the prospects for future efforts to estimate dipole sources in 3-D models that include heterogeneity in the air and the earth in addition to topography.

58 GEOSCIENCES↗