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Results for “ACOUSTIC MONITORING”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Passive Acoustic Monitoring of a Riverine Turbine with Stationary Hydrophones

In this study, we characterize the sound generated by a cross-flow riverine turbine in the Kvichak River near Igiugig, Alaska, United States. To do this, we follow the International Electro-technical Commission (IEC) technical specification for characterization of the acoustic emissions from marine energy converters. While marine mammals do not inhabit the test site, the U.S. National Marine Fisheries Service (NMFS) guidelines for assessing the effects of anthropogenic sound on marine mammal hearing were implemented to provide context for the deployment of similar turbines in other areas. The results indicate that turbine sound at the measurement locations was not predicted to be harmful to marine mammals. Results also provide insight into the acoustic characteristics of current energy converters and the complex acoustic propagation in rivers.

13 HYDRO ENERGY↗
DOE OSTI2020

Operando Acoustic Monitoring of SEI Formation and Long-Term Cycling in NMC/SiGr Composite Pouch Cells

Stable long-term cycling and solid-electrolyte-interphase (SEI) formation are key challenges in the design of Si/graphite composites as Li-ion battery (LIB) anode materials. Typically, these long-term cycling properties are examined in flooded half-cell settings making use of a Li-metal counter electrode and a Si/graphite working electrode. This form factor has the advantage of offering an unlimited supply of Li-ions and electrolyte, thus isolating performance degradation to the passivation of the working electrode. However, half-cell studies are ineffective in revealing performance and degradation mechanisms of the Si/graphite composite in a more commercially realistic full cell setting. This paper outlines an operando acoustic technique that can offer insights on SEI formation and capacity degradation of Si/graphite composites in a full cell setting. Through a combination of electrochemical and chemical analyses, we show that increasing passivation of the silicon particles in the Si/graphite composite anode is correlated with an increase in the acoustic time-of-flight shift. We further show that temporary loss of the acoustic signal during the first cycle is associated with significant gassing of the cell. The operando acoustic technique outlined here is low-cost, simple to setup and has the potential for localized resolution, indicating usefulness in commercial-scale Si/graphite cell quality control and diagnosis.

42 ENGINEERING↗
DOE OSTI2025

Unsteady- and Steady-State Relative Permeability Study with X-ray and Acoustic Monitoring for CO 2 Storage in Deep Saline Aquifers

In this study, we link the multiphase flow measurements with controls of sedimentary structures (e.g., heterogeneity and anisotropy) on relative permeability to variations in ultrasonic velocities for two deep saline aquifer formations (Entrada and Bluff Sandstones) in the San Juan Basin of the Southwestern USA. The rock specimens were extracted from outcrop sites near Durango, CO, USA. They have distinct differences in grain size, cementation composition, and individual chemical amounts, despite both formations being eolian sandstones. We performed a series of unsteady- and steady-state CO 2 -brine relative permeability experiments under capillary-controlled displacement rates. Unsteady-state experiments were conducted at 71 °C and 9.65 MPa; steady-state experiments were conducted at 85 °C and 22.8 MPa and 89 °C and 24.1 MPa for the Bluff and Entrada Sandstones, respectively. During the unsteady experiments, X-ray computed tomography was used to visualize multiphase flow in porous media and quantify saturations during brine drainage under various flow rates. Scan images and saturation profiles indicate that the CO 2 distribution in the pore volume was strongly impacted by the presence of high-angle cross-laminations, heterogeneous rock structure, and direction of bedding orientation. Those factors contribute to dramatic and quick initial breakthroughs and affect the overall saturation dynamics. Steady-state relative permeability tests were conducted at net flow rates of 1 mL/min for both brine drainage and imbibition. During the experimental steps, the CO 2 fractional flow was increased and decreased for both drainage and imbibition scenarios to mimic the front when CO 2 contacts brine and behind the front when brine enters space previously occupied by CO 2 . It was found that compressional velocity decreased, while shear waves slightly increased as brine saturation decreased. The hysteresis effects for the relative permeability and acoustic velocities were distinct. Furthermore, the CO 2 /brine front stability is quantified by applying a mobility ratio approach to spot saturations at which the boundary line between fluids becomes uneven. The results presented in this work can potentially boost the quality and precision of forecasts for the CO 2 storage projects in which the vertical and horizontal core-scale heterogeneity and anisotropy impact the plume migration within host reservoirs.

carbon dioxide (CO2)↗
DOE OSTI2023

Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes

Abstract Predicting failure in solids has broad applications including earthquake prediction which remains an unattainable goal. However, recent machine learning work shows that laboratory earthquakes can be predicted using micro-failure events and temporal evolution of fault zone elastic properties. Remarkably, these results come from purely data-driven models trained with large datasets. Such data are equivalent to centuries of fault motion rendering application to tectonic faulting unclear. In addition, the underlying physics of such predictions is poorly understood. Here, we address scalability using a novel Physics-Informed Neural Network (PINN). Our model encodes fault physics in the deep learning loss function using time-lapse ultrasonic data. PINN models outperform data-driven models and significantly improve transfer learning for small training datasets and conditions outside those used in training. Our work suggests that PINN offers a promising path for machine learning-based failure prediction and, ultimately for improving our understanding of earthquake physics and prediction.

42 ENGINEERING↗
DOE OSTI2013

FINAL TECHNICAL REPORT: Underwater Active Acoustic Monitoring Network For Marine And Hydrokinetic Energy Projects

This project saw the completion of the design and development of a second generation, high frequency (90-120 kHz) Subsurface-Threat Detection Sonar Network (SDSN). The system was deployed, operated, and tested in Cobscook Bay, Maine near the site the Ocean Renewable Power Company TidGen™ power unit. This effort resulted in a very successful demonstration of the SDSN detection, tracking, localization, and classification capabilities in a high current, MHK environment as measured by results from the detection and tracking trials in Cobscook Bay. The new high frequency node, designed to operate outside the hearing range of a subset of marine mammals, was shown to detect and track objects of marine mammal-like target strength to ranges of approximately 500 meters. This performance range results in the SDSN system tracking objects for a significant duration - on the order of minutes - even in a tidal flow of 5-7 knots, potentially allowing time for MHK system or operator decision-making if marine mammals are present. Having demonstrated detection and tracking of synthetic targets with target strengths similar to some marine mammals, the primary hurdle to eventual automated monitoring is a dataset of actual marine mammal kinematic behavior and modifying the tracking algorithms and parameters which are currently tuned to human diver kinematics and classification.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Analysis and Optimization of Seismo-Acoustic Monitoring Networks with Bayesian Optimal Experimental Design

The Bayesian optimal experimental design (OED) problem seeks to identify data, sensor configurations, or experiments which can optimally reduce uncertainty. The goal of OED is to find an experiment that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge about expected data. Therefore, within the context of seismic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types, and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize the ability to locate seismic events from arrival time data of detected seismic phases. In order to do utilize Bayesian OED we must develop four elements:1. A likelihood function that describes the uncertainty of detection and travel times; 2. A Bayesian solver that takes a prior and likelihood to identify the posterior; 3. An algorithm to compute EIG; and, 4. An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we can explore many relevant questions to monitoring such as: how and what multiphenomenology data can be used to optimally reduce uncertainty, how to trade off sensor fidelity and earth model uncertainty, and how sensor types, number, and locations influence uncertainty

47 OTHER INSTRUMENTATION↗
NASA NTRS1967

Study made of acoustical monitoring for mechanical checkout

Study demonstrates that sonic signal analysis technique provides a powerful tool for mechanical component checkout. The technique also provides the unique capability of predicting component failures by detecting incipient malfunctions.

Savelle, C.↗
NASA NTRS1972

Acoustic emission used as weld quality monitor

Acoustic emission technique is described for use as quality control tool in nondestructive inspection of welds. Stress mounts around weld defect until it exceeds yield strength of material. Pressure wave relieving the stress is emitted and followed by oscillations caused by multiple reflections. Acoustic emissions are then detected by sensor similar to ultrasonic sensor.

Jolly, W. O.↗
NASA NTRS2002

C-Coupon Studies of SiC/SiC Composites: Acoustic Emission Monitoring - Part 1

Modal acoustic emission (AE) was used to monitor the acoustic activity during room temperature and elevated temperature c-coupon tests for a variety of SiC/SiC systems including composites containing Sylramic (trademark), ZMI (trademark), or Hi-Nicalon (trademark) fibers with melt-infiltrated or polymer-infiltrated SiC matrices. Modal AE proved excellent at monitoring matrix cracking in the curved portion of the C-coupon specimen with increasing load. This included the load at which the first AE event occurred and the location of AE events during the test that were, presumably, caused by the formation and growth of interlaminar cracks and, at higher loads, transverse cracks. Graphical techniques were employed to estimate the load for first AE. It was determined that for this test with these material systems, the first AE could be estimated within the load range bounded by the load at which initial deviation from linearity of the load-displacement curve occurs and the load where the 98% offset of the linear regression fit intercepted the load-displacement curve. The calculation of interlaminar tensile (ILT) stress from the load for first AE was determined for all the systems. Ultimate ILT strength usually corresponded to ILT stress determined from the ultimate load to failure of the C-coupon test, which was considerably higher than the first cracking stress.

Morscher, Gregory N.↗
NASA NTRS1981

Acoustic emission monitoring of polymer composite materials

The techniques of acoustic emission monitoring of polymer composite materials is described. It is highly sensitive, quasi-nondestructive testing method that indicates the origin and behavior of flaws in such materials when submitted to different load exposures. With the use of sophisticated signal analysis methods it is possible the distinguish between different types of failure mechanisms, such as fiber fracture delamination or fiber pull-out. Imperfections can be detected while monitoring complex composite structures by acoustic emission measurements.

Bardenheier, R.↗
NASA NTRS1985

Acoustic emission monitoring crack propagation in single crystal silicon

The feasibility of acoustic emission (AE) monitoring of cracking and crack propagation in Si semiconductor materials was evaluated experimentally. A double torsion load relaxation method was employed wherein the propagation velocity and the AE levels in precracked (but not notched) boron-doped wafers were recorded simultaneously. A numerical model for the critical stress intensity factor (KIC) was used to relate the crack growth velocity, the instantaneous load and the load relaxation rate. All specimens were monitored with acoustic transducers at six points and examined with SEM after failure. The AE levels reached a peak amplitude of 70 dB at a KIC of 0.997 MNm to the -3/2 for cracking in the 111 plane. No AE was detected before the load reached the KIC, indicating that no subcritical crack growth occurs in Si. The results support the use of AE for monitoring crack propagation in crystal Si.

Chen, C. P.↗