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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A transfer learning approach for acoustic emission zonal localization on steel plate-like structure using numerical simulation and unsupervised domain adaptation

The detection and localization of damage in metallic structures using acoustic emission (AE) monitoring and artificial intelligence technology such as deep learning has been widely studied. However, a current challenge of this approach is the difficulty of obtaining sufficient labeled historical AE signals for the training process of deep learning models. This problem can be approached through the implementation of transfer learning. The innovation of this paper lies in the development of a transfer learning approach for AE source localization on a stainless-steel structure when no historical labeled AE signals are available for training. A finite element model is developed to generate numerical AE signals for the training. Unsupervised domain adaptation (UDA) technology is utilized to reduce the distribution difference between the numerical and the realistic AE signals and to derive the localization results of the unlabeled realistic AE signals. Finally, the results suggest that the proposed approach is capable of localizing AE signals with high accuracy in the absence of labeled training data.

42 ENGINEERING↗
DOE OSTI2022

Acoustics Reveals Short–Term Air Temperature Fluctuations Near Mars' Surface

Acoustics is new on Mars: it allows the characterization of turbulence at smaller scales than previously possible within the lowest part of the Planetary Boundary Layer. Sound speed measurements, by the SuperCam instrument and its microphone onboard the NASA Perseverance rover, allow the retrieval of atmospheric temperatures at 0.77 m above the ground, at 3 Hz, with a ~10 ms response time that is 20–100 times shorter than for typical thermocouple sensors used on Mars. Here we report on the first measurements of the sound speed-derived temperature and its fluctuations near the surface. Data highlight large and rapid fluctuations up to ±7 K/s, whose amplitude over such a timescale has never been reported, nor predicted by atmospheric models. These fluctuations follow the daytime pattern of the turbulence and highlight occasional high amplitude events that are likely due to the conjunction of low thermal inertia and strong winds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Comparisons Between Array Derived Dynamic Strain Rate (ADDS) and Fiber‐Optic Distributed Acoustic Sensing (DAS) Strain Rate

Abstract Distributed acoustic sensing (DAS) strain rate and particle velocity can be compared through approximate scaling with medium velocity. We instead performed a direct comparison between array derived dynamic strain (ADDS) rate and DAS strain rate for six frequency bands. The PoroTomo project at Brady's Hot Springs, Nevada, deployed a 240‐geophone 3C array co‐located with fiber‐optic DAS system and 8.7 km of buried cable. We selected subsets of the geophone array to create four smaller arrays and computed ADDS. The horizontal components of the ADDS were rotated into the direction of the fiber‐optic cable and then compared with the observed DAS strain rates. From three example regional earthquakes of local magnitudes 2.9, 4.1, and 4.3, the ADDS are found to be coherent with DAS for frequencies ≤1 Hz. For frequencies >1‐Hz, this correlation decays quickly. Small differences between linear and areal dynamic strains at 1‐Hz suggest poor signal‐to‐noise or localized strain that is perturbed by shallow heterogeneities compare to the average strain propagating across the geophone array. The implication is that around 1‐Hz, straight fiber DAS is measuring axial strain along the fiber and can provide good approximations to translational particle motions. However, above 1‐Hz, DAS becomes more sensitive to shallow velocity gradients that can be beneficial for geophysical imaging yet becomes a limitation for traditional seismic analysis methods depending on absolute amplitude and phase from translational particle motions.

58 GEOSCIENCES↗
DOE OSTI2023

Using Dark Fiber and Distributed Acoustic Sensing to Characterize a Geothermal System in the Imperial Valley, Southern California

The Imperial Valley, CA, is a tectonically active transtensional basin located south of the Salton Sea; the area hosts numerous geothermal fields, including significant hidden hydrothermal resources without surface manifestations. Development of inexpensive, rugged, and highly sensitive exploration techniques for undiscovered geothermal systems is critical for accelerating geothermal power deployment as well as unlocking a low-carbon energy future. We present a case study utilizing distributed acoustic sensing (DAS) and ambient noise interferometry for geothermal reservoir imaging, utilizing unlit fiber-optic telecommunication infrastructure (dark fiber). The study exploits two days of passive DAS data acquired in early November 2020 over a ~28-km section of fiber from Calipatria, CA to Imperial, CA. We apply ambient noise interferometry to retrieve coherent signals from DAS records and develop a bin stacking technique to attenuate the effects from persistent localized noise sources and to enhance retrieval of coherent surface waves. As a result, we are able to obtain high-resolution two-dimensional (2D) S wave velocity ($V_s$) structure to 3 km depth, based on joint inversion of both the fundamental and higher overtones. We observe a previously unmapped high $V_s$ and low $V_p$/$V_s$ ratio feature beneath the Brawley geothermal system, which we interpret to be a zone of hydrothermal mineralization and lower porosity. This interpretation is consistent with a host of other measurements including surface heat flow, gravity anomalies, and available borehole wireline data. These results demonstrate the potential utility of DAS deployed on dark fiber for geothermal system exploration and characterization in the appropriate geological settings.

Vp/Vs imaging↗
DOE OSTI2025

Monitoring strain evolution in water-sand systems using distributed acoustic sensing for geohazard early warning

Rainfall-driven hazards such as landslides, debris flows, and earthen dam failures often arise when water changes the internal strain within sand. This study evaluates the ability of distributed acoustic sensing to monitor these strain changes in real time. We embed a fiber-optic cable in a sand-filled glass cylinder and run controlled dry- and wet-sand experiments to measure how strain develops as water infiltrates, saturates, and drains from the sand. The sensing system detects uneven water movement in dry sand and enables millimeter-scale estimates of infiltration rates, and in wet sand it tracks rising water levels, delayed strain peaks after saturation, and abrupt strain shifts during drainage. These results show that fiber-optic sensing captures subtle strain evolution throughout the full water-sand interaction cycle. The study demonstrates that fiber-optic sensing offers promising potential for real-time and cost-effective monitoring and early warning of rainfall-induced geohazards.

58 GEOSCIENCES↗
DOE OSTI2020

Nonlinear coupling of electromagnetic and electron acoustic waves in multi-species degenerate astrophysical plasma

Nonlinear wave-coupling is studied in a multispecies degenerate astrophysical plasma consisting of two electron species (at different temperatures): a highly degenerate main component plus a smaller classical relativistic flow immersed in a static neutralizing ion background. It is shown that the high frequency electromagnetic waves through their strong nonlinear interactions with the electron-acoustic waves [sustained by a multielectron component (degenerate) plasma surrounding a compact astrophysical object] can scatter to lower frequencies so that the radiation observed faraway will be spectrally shifted downward. It is also shown that, under definite conditions, the electromagnetic waves could settle into stationary solitonic states. It is expected that the effects of such structures may persist as detectable signatures in forms of modulated micropulses in the radiation observed far away from the accreting compact object. Both these effects will advance our abilities to interpret the radiation coming out of the compact objects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Nonlinear spectral analysis of ion acoustic solitons arising from a streaming charged object using the numerical inverse scattering transform

Observations of nonlinear coherent plasma phenomena in spacecraft and terrestrial experiments often rely on visual identification of solitary modes because nonlinear coherent modes are broadband in a Fourier transform based analysis. We implement an alternative spectral decomposition known as the inverse scattering transform and demonstrate its ability to successfully isolate nonlinear modes on the homogeneous and forced Korteweg–De Vries equation which models these nonlinear modes. We also demonstrate for the first time that this decomposition is useful when forcing is applied. This is because the stable modes generated by localized forcing are similar to the homogeneous solutions where the inverse scattering transform is a rigorous decomposition. This spectral technique is then applied to simulations of ion acoustic waves generated by a 10 mm spherical debris object interacting with the ionospheric plasma orbiting at 2000 km altitude. The algorithm is found to successfully detect the resultant solitons. This demonstrates the feasibility of using this spectral technique as a real time analysis tool for screening spacecraft data for nonlinear solitary modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Nonlinear evolution, propagation, electron-trapping, and damping effects of ion-acoustic solitons using fully kinetic PIC simulations

We investigate ion acoustic solitary waves (solitons) of varying amplitudes in a one-dimensional plasma using fully kinetic particle-in-cell simulations. The initial soliton conditions are based on the Korteweg–de Vries (KdV) equation, treating ions as a cold species and electrons with finite temperature. Our findings reveal that KdV solitons evolve nonlinearly to a saturated state at higher amplitude, deviating from KdV predictions for ion density and electric potential, and from the Boltzmann relation for electron density. At this saturated state, the KdV model cannot accurately describe the soliton behavior. For small amplitudes, Sagdeev's model describes the saturated state, but not the soliton width; for larger amplitudes, it models the width accurately, but not the amplitude. These discrepancies arise from assuming a Boltzmann relation for electron density, while electron trapping creates non-Boltzmann densities—a deviation that increases with soliton amplitude. Additionally, we observe that the soliton amplitude oscillates roughly at the electron bounce frequency. The soliton is better described by Schamel's electron density formulation and a modified KdV equation incorporating electron trapping. The soliton velocity matches best with predictions from Sagdeev's and Schamel's models. Moreover, the soliton speed–amplitude relationship differs from existing theoretical predictions. Finally, we find minimal ion and electron Landau damping effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Impact of ultrafast laser pulse repetition rate on filament acoustic and emission signatures

Femtosecond filaments formed at standoff distances can be used for interrogating various types of matter, making them of potential interest for remote sensing. However, the physical aspects of the filaments generated at standoff distances are influenced by various environmental and laser properties, including the repetition rate of the laser. In this study, we evaluate the role of the predecessor pulse on the properties of filaments by varying the repetition rate of the laser in the range of 10–1000 Hz and using acoustic and emission signatures to diagnose filament properties. Our results show that filaments are brighter at high repetition rates while they are elongated at low repetition rates. The repetition rate has minimal influence on the downstream edge of the filament generation, while the upstream edge becomes elongated. The shadowgram images showed that the turbulence generated by the predecessor pulse may influence the next pulse when the laser is operating at high repetition rates.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Acoustic force spectroscopy reveals subtle differences in cellulose unbinding behavior of carbohydrate-binding modules

Protein adsorption to solid carbohydrate interfaces is critical to many biological processes, particularly in biomass deconstruction. To engineer more-efficient enzymes for biomass deconstruction into sugars, it is necessary to characterize the complex protein–carbohydrate interfacial interactions. A carbohydrate-binding module (CBM) is often associated with microbial surface-tethered cellulosomes or secreted cellulase enzymes to enhance substrate accessibility. However, it is not well known how CBMs recognize, bind, and dissociate from polysaccharides to facilitate efficient cellulolytic activity, due to the lack of mechanistic understanding and a suitable toolkit to study CBM–substrate interactions. Our work outlines a general approach to study the unbinding behavior of CBMs from polysaccharide surfaces using a highly multiplexed single-molecule force spectroscopy assay. Here, we apply acoustic force spectroscopy (AFS) to probe a Clostridium thermocellum cellulosomal scaffoldin protein (CBM3a) and measure its dissociation from nanocellulose surfaces at physiologically relevant, low force loading rates. An automated microfluidic setup and method for uniform deposition of insoluble polysaccharides on the AFS chip surfaces are demonstrated. The rupture forces of wild-type CBM3a, and its Y67A mutant, unbinding from nanocellulose surfaces suggests distinct multimodal CBM binding conformations, with structural mechanisms further explored using molecular dynamics simulations. Applying classical dynamic force spectroscopy theory, the single-molecule unbinding rate at zero force is extrapolated and found to agree with bulk equilibrium unbinding rates estimated independently using quartz crystal microbalance with dissipation monitoring. However, our results also highlight critical limitations of applying classical theory to explain the highly multivalent binding interactions for cellulose–CBM bond rupture forces exceeding 15 pN.

09 BIOMASS FUELS↗
DOE OSTI2024

Impurity gas detection for SNF canisters using probabilistic deep learning and acoustic sensing *

Abstract Monitoring impurity gases in spent nuclear fuel (SNF) canisters is a novel structural health monitoring approach for SNF in dry storage. The SNF canisters are sealed containers that do not facilitate visual access to the inside. Acoustic sensing can be deployed by taking advantage of the pathways unobstructed by internal hardware. Although the ultrasonic time-of-flight measurement can provide valuable information, it is limited in its ability to discern the concentration of only one impurity gas. As such, deep learning algorithms, particularly convolutional neural networks (CNNs), offer a promising solution. In this study, CNN-based probabilistic deep learning models were implemented to detect and quantify multiple impurity gases in helium. An experimental platform was established to simulate canister conditions, and ultrasonic test data were collected. The presence of argon and air in helium at concentrations ranging from 0% to 1.2% at increments of 0.05% was considered. The multi-layer perceptron, decision tree, and logistic regression classifiers achieved high accuracies when distinguishing pure helium from helium with impurities. CNN with dropout layers and CNN using maximum likelihood estimation showed a similar performance, indicating their ability to capture uncertainties. The ensemble CNN model exhibited improved predictions and the ability to balance individual gas concentration by integrating 1D- and 2D-CNN models. These findings contribute probabilistic deep learning solutions for impurity gas detection and analysis within SNF canisters, thus ensuring safe storage and management of SNFs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Cement sensors with acoustic bandgaps using carbon nanotubes

Cement is widely used in wellbores to stabilize the steel casing used in wellbore operations for oil and gas production, enhanced geothermal systems and carbon sequestration, and to limit fluid movement between sub-surface strata. Flaws such as microcracks in wellbore cement can lead to leakage along the wellbore compromising wellbore integrity. There is an increasing need for methods to monitor cement crack propagation in wellbore environments. In this study, we develop and report the first cementitious sensors capable of exhibiting high frequency acoustic bandgaps (ABGs) using carbon nanotubes (CNTs). Computational simulations of a sensor unit cell are used to design cement-multi walled carbon nanotubes (MWCNTs) sensors that show a wide bandgap. When the cement-MWCNTs sensors is embedded in cement specimens, bandgaps were measured experimentally under 300 kHz and under 600 kHz, consistent with the computationally predicted bandgaps in the range of 290–360 kHz, 410–460 kHz and 515–585 kHz. These bandgap features were absent in homogeneous cement specimens. X-ray tomographic reconstructions showed microscopic debonding at cement-MWCNTs sensor interface. Frequency response analysis of a three-dimensional computational model indicated a shift of frequency of minimum transmission due to the interface debonding, but no perturbation of bandgap response was observed. Here, the cement-MWCNTs sensors developed in this study show the potential of a packed CNT inclusion material in cementitious matrix to create ABGs in a cement matrix.

36 MATERIALS SCIENCE↗
DOE OSTI2025

DESI 2024 IV: Baryon Acoustic Oscillations from the Lyman alpha forest

We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman-α(Lyα) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over 420 000 Lyα forest spectra and their correlation with the spatial distribution of more than 700 000 quasars. An essential facet of this work is the development of a new analysis methodology on a blinded dataset. We conducted rigorous tests using synthetic data to ensure the reliability of our methodology and findings before unblinding. Additionally, we conducted multiple data splits to assess the consistency of the results and scrutinized various analysis approaches to confirm their robustness. For a given value of the sound horizon (r d ), we measure the expansion at z eff = 2.33 with 2% precision, H(z eff ) = (239.2 ± 4.8) (147.09 Mpc /r d ) km/s/Mpc. Similarly, we present a 2.4% measurement of the transverse comoving distance to the same redshift, DM(z eff ) = (5.84 ± 0.14) (r d /147.09 Mpc) Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Optimal reconstruction of baryon acoustic oscillations for DESI 2024

Baryon acoustic oscillations (BAO) provide a robust standard ruler to measure the expansion history of the Universe through galaxy clustering. Density-field reconstruction is now a widely adopted procedure for increasing the precision and accuracy of the BAO detection. With the goal of finding the optimal reconstruction settings to be used in the DESI 2024 galaxy BAO analysis, we assess the sensitivity of the post-reconstruction BAO constraints to different choices in our analysis configuration, performing tests on blinded data from the first year of DESI observations (DR1), as well as on mocks that mimic the expected clustering and selection properties of the DESI DR1 target samples. Overall, we find that BAO constraints remain robust against multiple aspects in the reconstruction process, including the choice of smoothing scale, treatment of redshift-space distortions, fiber assignment incompleteness, and parameterizations of the BAO model. We also present a series of tests that DESI followed in order to assess the maturity of the end-to-end galaxy BAO pipeline before the unblinding of the large-scale structure catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

DESI 2024 III: baryon acoustic oscillations from galaxies and quasars

We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1 < z < 2.1. Divided by tracer type, we utilize 300,017 galaxies from the magnitude-limited Bright Galaxy Survey with 0.1 < z < 0.4, 2,138,600 Luminous Red Galaxies with 0.4 < z < 1.1, 2,432,022 Emission Line Galaxies with 0.8 < z < 1.6, and 856,652 quasars with 0.8 < z < 2.1, over a ∼ 7,500 square degree footprint. The analysis was blinded at the catalog-level to avoid confirmation bias. All fiducial choices of the BAO fitting and reconstruction methodology, as well as the size of the systematic errors, were determined on the basis of the tests with mock catalogs and the blinded data catalogs. We present several improvements to the BAO analysis pipeline, including enhancing the BAO fitting and reconstruction methods in a more physically-motivated direction, and also present results using combinations of tracers. We employ a unified BAO analysis method across all tracers. We present a re-analysis of SDSS BOSS and eBOSS results applying the improved DESI methodology and find scatter consistent with the level of the quoted SDSS theoretical systematic uncertainties. With the total effective survey volume of ∼ 18 Gpc3, the combined precision of the BAO measurements across the six different redshift bins is ∼0.52%, marking a 1.2-fold improvement over the previous state-of-the-art results using only first-year data. We detect the BAO in all of these six redshift bins. The highest significance of BAO detection is 9.1σ at the effective redshift of 0.93, with a constraint of 0.86% placed on the BAO scale. We find that our observed BAO scales are systematically larger than the prediction of the Planck 2018-ΛCDM at z < 0.8. We translate the results into transverse comoving distance and radial Hubble distance measurements, which are used to constrain cosmological models in our companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Extensive analysis of reconstruction algorithms for DESI 2024 baryon acoustic oscillations

Reconstruction of the baryon acoustic oscillation (BAO) signal has been a standard procedure in BAO analyses over the past decade and has helped to improve the BAO parameter precision by a factor of ∼2 on average. The Dark Energy Spectroscopic Instrument (DESI) BAO analysis for the first year (DR1) data uses the “standard” reconstruction framework, in which the displacement field is estimated from the observed density field by solving the linearized continuity equation in redshift space, and galaxy and random positions are shifted in order to partially remove non-linearities. There are several approaches to solving for the displacement field in real survey data, including the multigrid (MG), iterative Fast Fourier Transform (iFFT), and iterative Fast Fourier Transform particle (iFFTP) algorithms. In this work, we analyze these algorithms and compare them with various metrics including two-point statistics and the displacement itself using realistic DESI mocks. We focus on three representative DESI samples, the emission line galaxies (ELG), quasars (QSO), and the bright galaxy sample (BGS), which cover the extreme redshifts and number densities, and potential wide-angle effects. We conclude that the MG and iFFT algorithms agree within 0.4% in post-reconstruction power spectrum on BAO scales with the RecSym convention, which does not remove large-scale redshift space distortions (RSDs), in all three tracers. The RecSym convention appears to be less sensitive to displacement errors than the RecIso convention, which attempts to remove large-scale RSDs. However, iFFTP deviates from the first two; thus, we recommend against using iFFTP without further development. In addition, we provide the optimal settings for reconstruction for five years of DESI observation. The analyses presented in this work pave the way for DESI DR1 analysis as well as future BAO analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Validation of the stochastic inversion algorithm for acoustic travel-time tomography: a large eddy simulation study

Acoustic tomography (AT) is explored as a remote sensing technique to obtain instantaneous snapshots of temperature and velocity fluctuations for wind energy applications. This study integrates Large Eddy Simulation (LES) with the Stochastic Inversion (SI) method to validate the algorithm’s capacity for accurate reconstruction of atmospheric fluctuations. The initial findings demonstrate the efficacy of the method in accurately capturing the predominant flow structures. Normalized L2 error evaluations further inform the algorithm’s precision, with errors accentuated in less sampled peripheral regions. The results underscore the method’s promise as a non-intrusive observational tool, with ongoing development poised to improve its precision and reliability.

17 WIND ENERGY↗
DOE OSTI2024

High-resolution source imaging and moment tensor estimation of acoustic emissions during brittle creep of basalt undergoing carbonation

SUMMARY As the high-frequency analogue to field-scale earthquakes, acoustic emissions (AEs) provide a valuable complement to study rock deformation mechanisms. During the load-stepping creep experiments with CO2-saturated water injection into a basaltic sample from Carbfix site in Iceland, 8791 AE events are detected by at least one of the seven piezoelectric sensors. Here, we apply a cross-correlation-based source imaging method, called geometric-mean reverse-time migration (GmRTM) to locate those AE events. Besides the attractive picking-free feature shared with other waveform-based methods (e.g. time-reversal imaging), GmRTM is advantageous in generating high-resolution source images with reduced imaging artefacts, especially for experiments with relatively sparse receivers. In general, the imaged AE locations are found to be scattered across the sample, suggesting a complicated fracture network rather than a well-defined major shear fracture plane, in agreement with X-ray computed tomography imaging results after retrieval of samples from the deformation apparatus. Clustering the events in space and time using the nearest-neighbour approach revealed a group of ‘repeaters’, which are spatially co-located over an elongated period of time and likely indicate crack, or shear band growth. Furthermore, we select 2196 AE events with high signal-to-noise-ratio (SNR) and conduct moment tensor estimation using the adjoint (backpropagated) strain tensor fields at the locations of AE sources. The resulting AE locations and focal mechanisms support our previously assertion that creep of basalt at the experimental conditions is accommodated dominantly by distributed microcracking.

58 GEOSCIENCES↗