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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Investigation of the effects of turbulence modeling on the prediction of compression-ignition combustion unsteadiness

Adverse effects of global warming due to the greenhouse gas emissions is changing the actual paradigm for the use energy resources. In the absence of a mid-term solution for reducing these emissions in transportation, internal combustion (IC) engines are going to coexist in the social spheres in the foreseeable future. Therefore, the study of other IC engine-related problems remains relevant to ensuring the health of the society. In this investigation, a numerical methodology for comprehensive understanding of Noise, Vibration and Harshness in internal combustion engines is proposed. Due to its inherent complexity and lack of awareness, the main objective is to evaluate the impact of the turbulence modeling framework on the in-cylinder acoustic field recreation. Modal decomposition methods have been applied to isolate the coherent flow structures and to analyze how they change with the turbulence approach. Results demonstrate that the choice of the turbulence model is a critical aspect for noise modeling. Unsteady Reynolds-Averaged Navier-Stokes schemes predict a raw estimation of the internal acoustic field with the added value of being computationally less expensive. However, the use of more complex turbulence approaches such us large eddy simulation offers an accurate prediction of the acoustic structures and their cyclic dispersion.

Broatch, A.↗
DOE OSTI2025

Room‐Temperature Mid‐Infrared Detection Using Metasurface‐Absorber‐Integrated Phononic Crystal Oscillator

Mid-infrared (MIR) detectors find extensive applications in chemical sensing, spectroscopy, communications, biomedical diagnosis, and space exploration. Alternative to semiconductor MIR photodiodes and bolometers, mechanical-resonator-based MIR detectors show advantages in higher sensitivity and lower noise at room temperature, especially toward longer wavelength infrared. Here, uncooled room-temperature MIR detectors based on lithium niobate surface acoustic wave phononic crystal (PnC) resonators integrated with wavelength-and-polarization-selective metasurface absorber arrays are demonstrated. The detection is based on the resonant frequency shift induced by the local temperature change due to MIR absorptions. The PnC resonator is configured in an oscillating mode, enabling active readout and low-frequency noise. The 1-GHz oscillator-based MIR detector shows a relative frequency deviation of 5.24 × 10 −10 Hz −1/2 at an integration time of 50 µs, leading to an incident noise equivalent power of 197 pW Hz −1/2 when input 6-µm MIR light is modulated at 1.8 kHz, and a large dynamic range of 10 7 in incident MIR power. The device architecture is compatible with the scalable manufacturing process and can be readily extended to a broader spectral range by tailoring the absorbing wavelengths of metasurface absorbers.

Xi, Zichen [Virginia Polytechnic Inst. and State U↗
DOE OSTI2025

Comprehensive defect evaluation of advanced nuclear fuels using high-resolution acoustic signals and optimized sensor separation

Graphite pebble composite structures based on TRistructural-ISOtropic (TRISO) particles are being developed as core nuclear fuels in advanced power reactors, promising safe operation at increased temperatures. Ensuring the structural integrity of these nuclear fuels requires comprehensive and accurate non-destructive evaluation (NDE) techniques to characterize defects and damage in the pebbles. However, traditional acoustic evaluation methods face limitations in defect characterization due to the highly attenuative, and geometrically and compositionally complex nature of these structures. This study proposes an improved acoustic NDE technique for accurate detection and classification of anticipated relevant defects and damage in graphite pebbles using high-resolution acoustic signals and optimized transmit-receive sensor networks. The proposed approach utilizes a triangular three-sensor network as the base unit, comprising three transmit-receive sensors. The sensor separation distance, as well as acoustic excitation center frequency, pulse-width, and bandwidth are optimized to enhance spatial resolution and improve signal-to-noise ratio, enabling effective characterization of the smallest size and widest range of defects in pebbles. Furthermore, the use of the triangular sensor configuration instead of a more conventional transmit-receive sensor pair expands the inspection region from a one-dimensional linear path to a two-dimensional area, increasing spatial coverage. To mitigate challenges associated with processing of complex acoustic signals arising from high-frequency, high-bandwidth excitation in these structures, a machine-learning-based signal processing algorithm is integrated with the sensor network. In the machine-learning-based algorithm, multi-domain features are extracted from the acoustic signals to capture intricate signal characteristics, significantly improving defect identification and classification compared to traditional approaches. The proposed acoustic NDE technique offers considerable promise for practical and reliable defect/damage diagnostics of advanced nuclear pebble fuels.

42 ENGINEERING↗
DOE OSTI2020

Detection and Perception of Sound by Eagles and Surrogate Raptors

One overarching objective of this program of study was the accumulation of objective, scientifically valid information relating to auditory performance of bald and golden eagles that may be used to guide the development of acoustic alerting/deterrence technologies intended to discourage encroachment into wind energy air spaces. To that end, analyses aimed at the characterization of sensitivity to sound in bald and golden eagles, along with findings in the supra-threshold, dynamic frequency spaces related to response latencies and amplitudes, leads us to conclude that bald, and golden eagles navigate the same basic working auditory space, as in other known and thus far characterized members of the diurnal raptor family. Specifically, bald and golden eagles, along with other raptor species within the group, operate in an auditory space characterized by a frequency band at least four octaves wide and centered on 2 kHz, with an upper frequency limit between 6 and 10 kHz at 80 dB SPL and a lower frequency limit that almost certainly extends below 0.2 kHz. Consequently, we recommend that signal designers use these data as a guideline in efforts to design effective and efficient acoustic alerting/deterrent systems. It is important to note that signal energy broadcast outside of this frequency band at moderate levels will not contribute to the efficacy of a deterrent but will add an unnecessary fraction to the overall acoustic pollution budget. The importance of this consideration is heightened by contemporaneous concerns related to the transmission of noise broadcast by wind energy farms. In addition, based on analyses of data acquired from red-tailed hawks using the same experimental paradigm and data acquisition system, we conclude that auditory function in the red-tailed hawk is sufficiently like that observed in bald and golden eagles to permit its use as a surrogate species. Response waveforms, threshold-frequency curves, and input-output characteristics match those of eagles closely. It should be noted however, that differences in sensitivity and slightly extended high-frequency limits of hearing should be taken into account when extrapolating findings from one species to the others. Although the inclusion of behavioral tests of red-tailed hawks to acoustic stimuli was beyond the scope of this investigation, future efforts to assess response parameters like signal-type preference and habituation rate will further elucidate their suitability to serve as eagle surrogates in behavioral studies; nonetheless, the species in question are well matched with respect to basic auditory performance. A second essential objective of this program of study was the acoustic characterization of a subset of calls comprising the vocal repertoires of bald and golden eagles that may be used to supplement auditory performance findings in the effort to guide the development of acoustic alerting signals. With regard to that objective, the vocal repertoires of both bald and golden eagle species are rich and varied. While similar in spectrographic structure, distinctive differences are also clear. Generally, golden eagles produce some calls with shorter durations, and similar “sounding” calls exhibit distinctively different spectrographic patterns than those of bald eagles. Both species produce calls that contain a wide variety of nonlinear elements that operate to enhance the rich and varied nature of commonly observed vocal products. Comparison of the average power spectra of commonly observed bald and golden eagle calls with threshold-frequency curves leads to the conclusion that call energies fall within the frequency bounds of hearing. Further, the acoustic energy of calls considered in this report tend to fall into overlapping, but different frequency ranges of the acoustic sensitivity curve. This condition may encourage signal designers to vary the frequency content of acoustic deterrence signals in the field. Finally, preliminary observations relating to the tendencies and proclivities of bald eagles to attend to the acoustic landscape lead to the conclusion that eagles monitor their immediate sound environment assiduously. Individuals respond to a variety of natural and synthetic sound signals reliably and, perhaps most relevant in the context of the engineering of acoustic alerting/deterrence technologies, habituation to most sounds considered in this effort was minimal. These preliminary results, while calling for extended behavioral testing, are promising and set the stage for the exportation of behavioral studies into real world scenarios.

17 WIND ENERGY↗
DOE OSTI2026

Evaluation of geophysical and anthropogenic sources of hydroacoustic noise in the Alaskan arctic

Quantifying the ocean soundscape is crucial for ocean-based seismoacoustic monitoring; it sets a baseline for the kinds and sizes of signals that can be detected above the background noise. As sea ice recedes, human activity in and around the Arctic Ocean is increasing, elevating sound levels and heightening the urgency of monitoring. Here, seven years of passive acoustic recordings from a National Oceanographic and Atmospheric Administration hydrophone in the Beaufort Sea are analyzed, focusing on frequencies between 1 and 125 Hz, a band of interest for detecting regional earthquakes and similar events. Sound is related to geophysical and anthropogenic sources, and seasonal and intraseasonal variations in the soundscape are examined. Sea ice emerges as a keystone feature of the Arctic Ocean acoustic environment, controlling or contributing to ambient sound levels at all frequencies studied. During low-ice months, sound levels are dominated by wind and sea surface waves, and in ice-covered months, wind-driven ice noise dominates. Seismic air gun surveys are prominent during low-ice periods, with sound levels decreasing with increasing distance and bathymetric complexity along the propagation path. The implications of this baseline soundscape for event detection in the Alaskan Arctic are discussed.

Niklasson, Siobhan [Los Alamos National Laboratory↗
DOE OSTI2022

Seismic monitoring of well integrity

Seismic tube waves, produced by flexure of the well boundary, pressure changes in the fluid in the well, and deformation of the material immediately surrounding the well, are particularly sensitive to variations in the state of the well. In this work, we evaluate a direct approach for generating and observing tube waves as a means of detecting well damage. While we find that it can be difficult to reliably excite observable tube waves without a very strong surface source, time-frequency techniques can be employed to increase the detectability of tube wave reflections. New technologies, particularly distributed acoustic sensing, hold great promise for evaluating well integrity by monitoring tube waves, temperature changes, and seismic noise due to well deformation and fluid leakage.

58 GEOSCIENCES↗
DOE OSTI2020

Distributed fiber sensor and machine learning data analytics for pipeline protection against extrinsic intrusions and intrinsic corrosions

This paper presents an integrated technical framework to protect pipelines against both malicious intrusions and piping degradation using a distributed fiber sensing technology and artificial intelligence. A distributed acoustic sensing (DAS) system based on phase-sensitive optical time-domain reflectometry (φ-OTDR) was used to detect acoustic wave propagation and scattering along pipeline structures consisting of straight piping and sharp bend elbow. Signal to noise ratio of the DAS system was enhanced by femtosecond induced artificial Rayleigh scattering centers. Data harnessed by the DAS system were analyzed by neural network-based machine learning algorithms. The system identified with over 85% accuracy in various external impact events, and over 94% accuracy for defect identification through supervised learning and 71% accuracy through unsupervised learning.

Peng, Zhaoqiang↗
DOE OSTI2021

Humming Trains in Seismology: An Opportune Source for Probing the Shallow Crust

Abstract Seismologists are eagerly seeking new and preferably low-cost ways to map and track changes in the complex structure of the top few kilometers of the crust. By understanding it better, they can build on what is known regarding important, practical issues. These include telling us whether imminent earthquakes and volcanic eruptions are generating telltale underground signs of hazard, about mitigation of induced seismicity such as from deep injection of wastewater, how the Earth and its atmosphere couple, and where accessible natural resources are. Passive seismic imaging usually relies on blind correlations within extended recordings of Earth’s ceaseless “hum” or coda of well-mixed, small vibrations. In this article, we propose a complementary approach. It is seismic interferometry using opportune sources—specifically ones not stationary in time and moving in a well-understood configuration. Its interpretation relies on an accurate understanding of how these sources radiate seismic waves, precise timing, careful placement of pairs of listening stations, and seismic phase differentiation (surface and body waves). Massive freight trains were only recently recognized as such a persistent, powerful cultural (human activity-caused) seismic source. One train passage may generate a tremor with an energy output of a magnitude 1 earthquake and be detectable for up to 100 km from the track. We discuss the source mechanisms of train tremors and review the basic theory on sources. Finally, we present case studies of body- and surface-wave retrieval as an aid to mineral exploration in Canada and to monitoring of a southern California fault zone. We believe noise recovery from this new signal source, together with dense data acquisition technologies such as nodes or distributed acoustic sensing, will deeply transform our ability to monitor activity in the shallow crust at sharpened resolution in time and space.

Geochemistry & Geophysics↗
DOE OSTI2023

Noise Reduction Capability of the Trampoline Fabric Wind Dome

Low frequency sound below 20 Hz, also known as infrasound, is generated by both natural and anthropogenic sources. Local surface winds also generate signals within this frequency band and can dominate signals. Effectively monitoring sources of interest requires filtering out the influence of wind. Recently, the National Center for Physical Acoustics developed a 1 m fabric dome made from trampoline material that can serve as a wind filter for temporary field deployments. We assess the performance of this new dome by quantifying its overall noise reduction and show that it is an acceptable wind filter for temporary infrasound field deployments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Quick-connect scanning tunneling microscope head with nested piezoelectric coarse walkers

To meet changing research demands, new scanning tunneling microscope (STM) features must constantly evolve. We describe the design, development, and performance of a modular plug-in STM, which is compact and stable. The STM head is equipped with a quick-connect socket that is matched to a universal connector plug, enabling it to be transferred between systems. This head can be introduced into a vacuum system via a load-lock and transferred to various sites equipped with the connector plug, permitting multi-site STM operation. Its design allows for reliable operation in a variety of experimental conditions, including a broad temperature range, ultra-high vacuum, high magnetic fields, and closed-cycle pulse-tube cooling. The STM’s compact size is achieved by a novel nested piezoelectric coarse walker design, which allows for large orthogonal travel in the X, Y, and Z directions, ideal for studying both bulk and thin film samples ranging in size from mm to μm. Its stability and noise tolerance are demonstrated by achieving atomic resolution under ambient conditions on a laboratory desktop with no vibrational or acoustic isolation. The operation of the nested coarse walkers is demonstrated by successful navigation to a μm-sized 2D sample.

Instruments & Instrumentation↗
DOE OSTI2025

Retrospective on decadal progress of the NOAA/NPS ocean noise reference station network

The National Oceanic and Atmospheric Administration (NOAA), in partnership with the U.S. National Park Service (NPS), established the Ocean Noise Reference Station Network (NRS) in 2014 as a foundational component of NOAA’s Ocean Noise Strategy. This long-term effort aims to characterize baseline ocean ambient sound conditions across diverse marine environments and to inform management of noise impacts on protected species and habitats within U.S. waters. The NRS is now composed of 13 autonomous passive acoustic monitoring stations strategically positioned across the U.S. Exclusive Economic Zone (EEZ), extending from Arctic regions to tropical waters in depths ranging from 33 to 4,790 m. These locations include several National Marine Sanctuaries and National Parks, such as the recently designated Chumash Heritage National Marine Sanctuary off the coast of California. Each station is equipped to continuously sample low-frequency underwater sound at five kHz, enabling the detection of anthropogenic, geophysical, and biological acoustic signals. To date the network has sampled over 72 years of calibrated acoustic data. The spatial breadth and consistent methodology of the NRS allow for comparative acoustic assessments across diverse marine ecosystems. In addition to applied research functions, the NRS has served as a platform for education and training, offering opportunities for students to develop skills for marine science and data analysis. Looking forward, the NRS project team is focused on network expansion, improved data delivery, and broader integration with collaborative scientific initiatives. NRS recordings are being archived in partnership with NOAA’s National Centers for Environmental Information to enhance accessibility and long-term utility. Efforts are underway to develop standardized metadata and summary products to accompany raw audio files, making the data more usable for a wide range of stakeholders in the ocean science community. The NRS is evolving into a fully integrated national framework for ocean sound monitoring that supports scientific inquiry, management decision-making, national security interests, and public engagement with ocean acoustic environments.

Long-term monitoring↗
DOE OSTI2023

Design of an ultra-low mode volume piezo-optomechanical quantum transducer

Coherent transduction of quantum states from the microwave to the optical domain can play a key role in quantum networking and distributed quantum computing. We present the design of a piezo-optomechanical device formed in a hybrid lithium niobate on silicon platform, that is suitable for microwave-to-optical quantum transduction. Our design is based on acoustic hybridization of an ultra-low mode volume piezoacoustic cavity with an optomechanical crystal cavity. The strong piezoelectric nature of lithium niobate allows us to mediate transduction via an acoustic mode which only minimally interacts with the lithium niobate, and is predominantly silicon-like, with very low electrical and acoustic loss. We estimate that this transducer can realize an intrinsic conversion efficiency of up to 35% with <0.5 added noise quanta when resonantly coupled to a superconducting transmon qubit and operated in pulsed mode at 10 kHz repetition rate. The performance improvement gained in such hybrid lithium niobate-silicon transducers make them suitable for heralded entanglement of qubits between superconducting quantum processors connected by optical fiber links.

Chiappina, Piero↗
DOE OSTI2020

Identifications and classifications of human locomotion using Rayleigh-enhanced distributed fiber acoustic sensors with deep neural networks

Abstract This paper reports on the use of machine learning to delineate data harnessed by fiber-optic distributed acoustic sensors (DAS) using fiber with enhanced Rayleigh backscattering to recognize vibration events induced by human locomotion. The DAS used in this work is based on homodyne phase-sensitive optical time-domain reflectometry (φ-OTDR). The signal-to-noise ratio (SNR) of the DAS was enhanced using femtosecond laser-induced artificial Rayleigh scattering centers in single-mode fiber cores. Both supervised and unsupervised machine-learning algorithms were explored to identify people and specific events that produce acoustic signals. Using convolutional deep neural networks, the supervised machine learning scheme achieved over 76.25% accuracy in recognizing human identities. Conversely, the unsupervised machine learning scheme achieved over 77.65% accuracy in recognizing events and human identities through acoustic signals. Through integrated efforts on both sensor device innovation and machine learning data analytics, this paper shows that the DAS technique can be an effective security technology to detect and to identify highly similar acoustic events with high spatial resolution and high accuracies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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 OSTI2020

Data-driven Detection and Early Prediction of Thermoacoustic Instability in a Multi-nozzle Combustor

Thermoacoustic instability (TAI) is a critical issue in modern lean-burn gas-turbine combustors, which is induced by a strong coupling between the resonant combustor acoustics and fluctuations in the heat release rate. This instability may lead to high-amplitude pressure waves that generate undesirable noise levels as well as fatigue stresses in mechanical structures of the combustor. The intense pressure fluctuations due to TAI may also cause large flow perturbations and possibly flow reversal that may lead to flame oscillations, flame liftoff, and even flame blow-out. Hence, there is a strong need for exercising control actions in a timely fashion to mitigate the TAI phenomena. Anomaly detection is an essential prerequisite to the design of a good controller and such a detector must be able to reliably predict a forthcoming TAI. To detect and predict the onset of a TAI from an ensemble of pressure time series, this paper investigates three data-driven methods: Fast Fourier transform (FFT), symbolic time series analysis (STSA), and hidden Markov modeling (HMM). The main focus of the paper is to make a comparative evaluation of these three anomaly detection methods for classification of the current regime of operation into stable and unstable categories as well as for real-time identification of precursors to impending instabilities with short-length time series of measured variables (e.g., pressure oscillations). Finally, the results, generated on experimental data from a multi-nozzle combustor apparatus, have been compared to evaluate the performance of FFT, STSA, and HMM methods for TAI analysis.

42 ENGINEERING↗
DOE OSTI2020

Towards a self-consistent analysis of the anisotropic galaxy two- and three-point correlation functions on large scales: application to mock galaxy catalogues

We establish a practical method for the joint analysis of anisotropic galaxy two- and three-point correlation functions (2PCF and 3PCF, respectively) on the basis of the decomposition formalism of the 3PCF using tripolar spherical harmonics. We perform such an analysis with MultiDark-Patchy mock catalogues to demonstrate and understand the benefit of the anisotropic 3PCF. We focus on scales above $80\, h^{-1}\, {\rm Mpc}$, and use information from the shape and the baryon acoustic oscillation (BAO) signals of the 2PCF and 3PCF. We also apply density field reconstruction to increase the signal-to-noise ratio of BAO in the 2PCF measurement, but not in the 3PCF measurement. In particular, we study in detail the constraints on the angular diameter distance and the Hubble parameter. We build a model of the bispectrum or 3PCF that includes the non-linear damping of the BAO signal in redshift space. We carefully account for various uncertainties in our analysis including theoretical models of the 3PCF, window function corrections, biases in estimated parameters from the fiducial values, the number of mock realizations to estimate the covariance matrix, and bin size. The joint analysis of the 2PCF and 3PCF monopole and quadrupole components shows a $30{{\ \rm per\ cent}}$ and $20{{\ \rm per\ cent}}$ improvement in Hubble parameter constraints before and after reconstruction of the 2PCF measurements, respectively, compared to the 2PCF analysis alone. Furthermore, this study clearly shows that the anisotropic 3PCF increases cosmological information from galaxy surveys and encourages further development of the modelling of the 3PCF on smaller scales than we consider.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Acoustics Examination of Kappa West Firing ARMAG for Personnel Occupancy

In April of 2023, LANL conducted a series of explosive tests at the Kappa West firing mound at BEEF, NNSS, to examine noise levels within the diagnostics ARMAG next to the firing mound. The intent was to establish an explosive mass that could be detonated on the mound without generating blast noise inside the ARMAG which would be unsafe for personnel. The blast noise threshold for personnel safety during intentional firing operations is 140 dB. Based on data collected during prior experiments, it was anticipated that the noise levels inside the ARMAG would be 20-30 dB lower than noise levels outside the ARMAG. However, data from prior experiments were collected from charges that were not consistent geometries and test layouts, so it was unknown what quantity of explosive would generate the threshold noise level. A prediction was made using the BEC-O standard blast calculator from the DDESB, from which it was estimated that a single, consolidated 60-pound charge at 180 feet would generate blast noise levels of about 170 dB, with noise levels falling to a predicted 166 dB at 250 feet.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗