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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Shallow Soil Response to a Buried Chemical Explosion With Geophones and Distributed Acoustic Sensing

Abstract Shallow sediments can respond non‐linearly to large dynamic strains and undergo a subsequent healing phase as the material gradually recovers following the passing of seismic waves. This study focuses on the physical changes in the subsurface caused by the shaking from a buried chemical explosion detonated in a borehole in Nevada, USA, as a part of the Source Physics Experiment Phase II. The explosion damaged the shallow subsurface and modified the frequency content recorded by 491 geophones and 2240 Distributed Acoustic Sensing (DAS) channels within 2.5 km from surface ground zero. We observe a gradual shift of resonance frequencies in the 10–25 Hz frequency band in the hours following the explosion and develop a method to characterize the related logarithm‐type healing process of the shallow (i.e., upper ∼25 m) subsurface. We find that stronger levels of ground motion increase the relative degree of damage and duration of the subsurface healing; with the spall region exhibiting the largest degree of damage and longest healing recovery time. We observe coherent spatial patterns of damage with the region located to the southeast of the explosion exhibiting more damage than the southwest region. This study demonstrates that both DAS and co‐located geophones capture similar temporal changes associated with the physical processes occurring in the subsurface, with the high‐density sampling of DAS measurements enabling a new capability to monitor the fine‐scale changes of the Earth's shallow subsurface following the detonation of a buried explosion.

Viens, Loïc↗
DOE OSTI2024

DASEventNet: AI‐Based Microseismic Detection on Distributed Acoustic Sensing Data From the Utah FORGE Well 16A (78)‐32 Hydraulic Stimulation

Abstract Distributed acoustic sensing (DAS) has emerged as a promising seismic technology for monitoring microearthquakes (MEQs) with high spatial resolution. Efficient algorithms are needed for processing large DAS data volumes. This study introduces a deep learning (DL) model based on a Residual Convolutional Neural Network (ResNet) for detecting MEQs using DAS data, named as DASEventNet. The test data were collected from the Utah FORGE 16A (78)‐32 hydraulic stimulation experiments conducted in April 2022. The DASEventNet model achieves a remarkable accuracy of 100% when discriminating MEQs from noise in the raw test set of 260 examples. Surprisingly, the model identified weak MEQ signatures that have been manually categorized as noise. The decision‐making process with the model is decoded by the classic activation map, which illuminates learning features of the DASEventNet model. These features provide clear illustrations of weak MEQs and varied noise types. Finally, we apply the trained model to the entire period (∼7 days) of continuous DAS recordings and find that it discovers >5,700 new MEQs, previously unregistered in the public Silixa DAS catalog. The DASEventNet model significantly outperforms the traditional seismic method Short‐Term Average/Long‐Term Average (STA/LTA), which detected only 1,307 MEQs. The DASEventNet detection threshold is M w −1.80 compared to the minimum magnitude of M w −1.14 detected by STA/LTA. The spatiotemporal distribution of the newly identified MEQs defines an extensive stimulation zone and more accurately characterizes fracture geometry. Our results highlight the potential of DL for long‐term, real‐time microseismic monitoring that can improve enhanced geothermal systems and other activities that include subsurface hydraulic fracturing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Distributed Acoustic Sensing to Estimate the Permeability

Optical fiber in a borehole can be interrogated with distributed acoustic sensors (DAS) to capture fracture displacements with the potential to map surrounding fracture networks. We designed a laboratory experiment to test the capability of DAS to determine borehole flow characteristics, and we show that for the first time DAS can be used to remotely estimate permeability. Optical fiber was wrapped around a bead filled pipe and the pressure drop and flow velocity were measured to directly calculate permeability. A machine learning model using statistical features from continuous DAS estimated the bulk permeability. Fluid interactions with the permeable material demonstrate insufficient resolution using DAS amplitude-based measurements for estimating pressure drop to infer permeability. Variations in the spectral domain relate DAS measurements to the pressure drop and provide consistent permeability estimates. Resolution with DAS is sufficient to estimate permeability and provides a reliable method to monitor at depth in borehole conditions.

58 GEOSCIENCES↗
DOE OSTI2025

Insights Into Seismicity Associated With Flexibly Operating Enhanced Geothermal System From Real‐Time Distributed Acoustic Sensing

Enhanced Geothermal Systems (EGS) have the capacity to broaden the accessible resource pool for geothermal power generation. Traditionally viewed as a “baseload” resource, their flexible operation might also enable dispatchable load‐following generation and long‐term energy storage, aligning them with the evolving landscape of decarbonized electricity systems. However, increasing permeability and extracting energy during EGS operations can induce microseismic events; for many prior EGS efforts, some associated seismicity has been observed. While energetically beneficial, the flexibility of EGS operations prompts our inquiry into whether new types of operations will yield previously unseen seismicity patterns. We demonstrate the use of distributed acoustic sensing (DAS) with real‐time edge computing to monitor seismicity during a pilot test of a cyclically operated EGS facility at the Blue Mountain geothermal field. Our focus lies in uncovering seismicity insights from the real‐time microseismic catalog, particularly during load‐following dispatchability tests simulating flexible EGS operation. Here, we find that variations in pore pressure consistently correlate with seismicity, and that controlling pressure cycles during flexible operations appears to constrain microseismic activity during subsequent cycles. The spatio‐temporal evolution of microseismic clouds recorded during cyclic injection cycles fits diffusive models over our available observation period. Additionally, seismicity elevation lags behind pore pressure increases, likely due to pressure diffusion to the fracture system boundary. Through real‐time monitoring, we offer novel insights into seismicity associated with flexibly operating EGS. Our findings suggest that leveraging DAS and edge computing can inform EGS operations and help mitigate induced seismicity.

Chamarczuk, Michal [Rice Univ., Houston, TX (Unite↗
DOE OSTI2026

Neural Network‐Based Methods for Ocean Surface Wave Measurement Using Submarine Distributed Acoustic Sensing (DAS)

Two new data-driven models for estimating ocean surface waves from distributed acoustic sensing (DAS) submarine cable strain rate are developed using supervised machine learning on a 10-day data set collected offshore of Oliktok Point, Alaska. The new models were trained on target data from seafloor pressure moorings at three sites spaced evenly along 27.1 km of cable and were benchmarked against an empirical transfer function method previously used to estimate waves from DAS. A model which uses convolutional neural networks to transform 2-km frequency-wavenumber strain spectra to seafloor pressure spectra outperforms the benchmark in wave height prediction (RMSE of 0.15 vs. 0.41 m) and period prediction (0.29 vs. 0.37 s) when evaluated on a held-out test data set. When applied to a DAS data set collected on the same cable 2 years prior, the CNN-based model maintained similar significant wave height performance (RMSE = 0.23 m) relative to available satellite altimetry data. A two-hidden-layer, fully connected neural network which transforms 1-D strain spectra to seafloor pressure spectra also outperforms the benchmark in wave height prediction (RMSE of 0.19 vs. 0.41 m), but does not generalize as well to the prior data. Regression-based machine learning is useful for estimating waves from DAS data when the pressure-strain relationship varies temporally and spatially across different wave conditions. Models can be applied to DAS data to measure waves with higher spatial resolution and longer temporal coverage than traditional methods, which often measure waves only at a single point.

Davis, Jacob R. [Univ. of Washington, Seattle, WA ↗
DOE OSTI2020

Dimer rattling mode induced low thermal conductivity in an excellent acoustic conductor

A solid with larger sound speeds usually exhibits higher lattice thermal conductivity. Here, we report an exception that CuP2 has a quite large mean sound speed of 4155 m s –1 , comparable to GaAs, but single crystals show very low lattice thermal conductivity of about 4 W m –1 K –1 at room temperature, one order of magnitude smaller than GaAs. To understand such a puzzling thermal transport behavior, we have thoroughly investigated the atomic structures and lattice dynamics by combining neutron scattering techniques with first-principles simulations. This compound crystallizes in a layered structure where Cu atoms forming dimers are sandwiched in between P atomic networks. In this work, we reveal that Cu atomic dimers vibrate as a rattling mode with frequency around 11 meV, which is manifested to be remarkably anharmonic and strongly scatters acoustic phonons to achieve the low lattice thermal conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Probing phonon focusing, thermomechanical behavior, and moiré patterns in van der Waals architectures using surface acoustic waves

Surface acoustic waves (SAWs) propagate along solid-air, solid-liquid, and solid-solid interfaces. Their characteristics depend on the elastic properties of the solid. Combining transmission electron microscopy (TEM) experiments with molecular dynamics (MD) simulations, we probe atomic environments around intrinsic defects that generate SAWs in vertically stacked two-dimensional (2D) bilayers of MoS 2 . Our joint experimental-simulation study provides insights into SAW-induced structural and dynamical changes and thermomechanical responses of MoS 2 bilayers. Using MD simulations, we compute mechanical properties from the SAW velocity and thermal conductivity from thermal diffusion of SAWs. The results for Young’s modulus and thermal conductivity of an MoS 2 monolayer are in good agreement with experiments. The presence of defects, such as nanopores which generate SAWs, reduces the thermal conductivity of 2D-MoS 2 by an order of magnitude. We also observe dramatic changes in moiré patterns, phonon focusing, and cuspidal structures on 2D-MoS 2 layers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Pines’ demon observed as a 3D acoustic plasmon in Sr2RuO4

Abstract The characteristic excitation of a metal is its plasmon, which is a quantized collective oscillation of its electron density. In 1956, David Pines predicted that a distinct type of plasmon, dubbed a ‘demon’, could exist in three-dimensional (3D) metals containing more than one species of charge carrier 1 . Consisting of out-of-phase movement of electrons in different bands, demons are acoustic, electrically neutral and do not couple to light, so have never been detected in an equilibrium, 3D metal. Nevertheless, demons are believed to be critical for diverse phenomena including phase transitions in mixed-valence semimetals 2 , optical properties of metal nanoparticles 3 , soundarons in Weyl semimetals 4 and high-temperature superconductivity in, for example, metal hydrides 3,5–7 . Here, we present evidence for a demon in Sr 2 RuO 4 from momentum-resolved electron energy-loss spectroscopy. Formed of electrons in the β and γ bands, the demon is gapless with critical momentum q c = 0.08 reciprocal lattice units and room-temperature velocity v = (1.065 ± 0.12) × 10 5 m s −1 that undergoes a 31% renormalization upon cooling to 30 K because of coupling to the particle–hole continuum. The momentum dependence of the intensity of the demon confirms its neutral character. Our study confirms a 67-year old prediction and indicates that demons may be a pervasive feature of multiband metals.

Science & Technology - Other Topics↗
DOE OSTI2021

Utilizing distributed acoustic sensing and ocean bottom fiber optic cables for submarine structural characterization

The sparsity of permanent seismic instrumentation in marine environments often limits the availability of subsea information on geohazards, including active fault systems, in both time and space. One sensing resource that provides observational access to the seafloor environment are existing networks of ocean bottom fiber optic cables; these cables, coupled to modern distributed acoustic sensing (DAS) systems, can provide dense arrays of broadband seismic observations capable of recording both seismic events and the ambient noise wavefield. Here, we report a marine DAS application which demonstrates the strength and limitation of this new technique on submarine structural characterization. Based on ambient noise DAS records on a 20 km section of a fiber optic cable offshore of Moss Landing, CA, in Monterey Bay, we extract Scholte waves from DAS ambient noise records using interferometry techniques and invert the resulting multimodal dispersion curves to recover a high resolution 2D shear-wave velocity image of the near seafloor sediments. We show for the first time that the migration of coherently scattered Scholte waves observed on DAS records can provide an approach for resolving sharp lateral contrasts in subsurface properties, particularly shallow faults and depositional features near the seafloor. Our results provide improved constraints on shallow submarine features in Monterey Bay, including fault zones and paleo-channel deposits, thus highlighting one of many possible geophysical uses of the marine cable network.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

In-Petri-dish acoustic vortex tweezers

This study presents an acoustic vortex tweezers platform that enables contactless, precise, multi-degree-of-freedom, and multifunctional manipulation of micro- to millimeter-sized objects within a Petri dish.

Biochemistry & Molecular Biology↗
DOE OSTI2021

An algorithm to locate the centers of baryon acoustic oscillations

The cosmic structure formed from baryon acoustic oscillations (BAO) in the early universe is imprinted in the galaxy distribution observable in large-scale surveys and is used as a standard ruler in contemporary cosmology. Typically, BAOs are detected as a preferential length scale in two-point statistics, which gives little information about the location of the BAO structures in real space. The aim of the algorithm described in this paper is to find probable centers of BAOs in the cosmic matter distribution. The algorithm convolves the three-dimensional distribution of matter density with a spherical shell kernel of variable radius placed at different locations. The locations that correspond to the highest values of the convolution correspond to the probable centers of BAOs. This method is realized in an open-source, computationally efficient algorithm. Here, we describe the algorithm and present the results of applying it to the SDSS DR9 CMASS survey and associated mock catalogs. A detailed performance study demonstrates the ability of the algorithm to locate BAO centers and in doing so presents a novel detection of the BAO scale in galaxy surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Studying baryon acoustic oscillations using photometric redshifts from the DESI Legacy Imaging survey DR9

Context. The Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Survey DR9 (DR9 hereafter), with its extensive dataset of galaxy locations and photometric redshifts, presents an opportunity to study baryon acoustic oscillations (BAOs) in the region covered by the ongoing spectroscopic survey with DESI. Aims. We aim to investigate differences between different parts of the DR9 footprint. Furthermore, we want to measure the BAO scale for luminous red galaxies within them. Our selected redshift range of 0.6–0.8 corresponds to the bin in which a tension between DESI Y1 and eBOSS was found. Methods. We calculated the anisotropic two-point correlation function in a modified binning scheme to detect the BAOs in DR9 data. We then used template fits based on simulations to measure the BAO scale in the imaging data. Results. Our analysis reveals the expected correlation function shape in most of the footprint areas, showing a BAO scale consistent with Planck’s observations. Aside from identified mask-related data issues in the southern region of the South Galactic Cap, we find a notable variance between the different footprints. Conclusions. We find that this variance is consistent with the difference between the DESI Y1 and eBOSS data, and it supports the argument that that tension is caused by sample variance. Additionally, we also uncovered systematic biases not previously accounted for in photometric BAO studies. We emphasize the necessity of adjusting for the systematic shift in the BAO scale associated with typical photometric redshift uncertainties to ensure accurate measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

High sensitivity pump–probe measurements of magnetic, thermal, and acoustic phenomena with a spectrally tunable oscillator

We describe an optical pump/probe system for sensitive measurements of time-resolved optical measurements of material dynamics. The instrument design is optimized for time-resolved magneto-optic Kerr effect (TR-MOKE) measurements of dynamics in magnetic materials. The system also allows for time-domain thermoreflectance (TDTR) measurements of thermal transport properties and picosecond acoustic measurements of film thickness and/or elastic constants. The system has several advantages over the conventional designs for TRMOKE and/or TDTR systems. Measurements of pump-induced changes to the probe beam intensity are shot-noise limited. The system’s design allows for MOKE and/or thermoreflectance measurements of both sides of a sample. Pumping and probing the sample on opposite sides allows nanoscale flash diffusivity measurements of transport properties. The wavelengths of the pump and probe beams are straightforward to tune between 350–525 nm and 690–1050 nm. A tunable wavelength allows for optical resonances in a wide array of materials to be excited and/or probed. Finally, the setup is calibrated to allow for the real and imaginary components of Kerr signals to be separately quantified.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Excitation of zonal flow by nonlinear geodesic acoustic mode

Here, the zero frequency zonal flow (ZFZF) excitation due to the nonlinear geodesic acoustic mode (GAM) is investigated in the framework of gyro-kinetic equations, which were first investigated. We show that after integrating over the velocity space, the first order finite orbit width (FOW) term of nonlinear GAM disappears, and hence, the second order FOW term should be taken into account to generate the ZFZF. The anisotropy of the equilibrium is also considered.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Global geodesic acoustic mode in an ideal magnetohydrodynamic tokamak plasma

A concise and transparent second order ordinary differential equation (ODE) describing the radial structure of the global geodesic acoustic mode (GAM) is analytically presented in a low-β tokamak plasma. The large-aspect-ratio and circular cross section are assumed to linearize the ideal magnetohydrodynamic equations. We show clearly how finite β-dependent terms affect the global GAM frequency and radial mode structure. Here, a typical Wentzel–Kramers–Brillouin form of solution is found for some reversed shear equilibria. For some other equilibria with lower β, even also in a reversed shear tokamak, the GAM continuum is upraised by the high order β-dependent terms so that its maximum is beyond ω G , where ω G is the classical local frequency of GAM. As a result, no self-consistent solution to the ODE can be found.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Experimental observation of the geodesic acoustic frequency limit for the NBI-driven Alfvén eigenmodes in TJ-II

We study Alfvén Eigenmodes (AEs) in the TJ-II heliac in hydrogen plasmas heated by hydrogen cofield NBI. Taking advantage of the unique TJ-II flexibility in varying plasma current, we have observed strong variation of the AE frequency from f AE ~ 30 to ~ 220 kHz for selected modes. An advanced heavy ion beam probe diagnostic determines the spatial location and internal amplitudes of the modes. The modes satisfy a local AE dispersion relation including the geodesic acoustic frequency that represents the lowest frequency of the mode. Linear MHD-modeling with STELLGAP and FAR3D codes shows that the calculated temporal evolution of the mode frequency reproduces the observed maxima and minima at the same time intervals with a similar frequency range and the radial profile peaks near the outer edge of the observed one.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗