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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Joint Conference on Sensing of Environmental Pollutants, 2nd, Washington, D.C., December 10-12, 1973, Proceedings

Subjects considered are related to the remote passive sensing of atmosphere pollutants, the extension of laboratory measurement techniques for field use, instrument quality and measurement standardization, the remote active sensing of atmospheric pollutants, stationary source sensing, and air quality standards and measurement accuracy. Aspects of radiological, electromagnetic, and acoustic pollution monitoring are discussed together with new methods in particulate analysis, the measurement of meteorological variables that impact on atmospheric pollutants, and the impact of meteorological parameters on pollution analysis. The in-situ sensing of acoustic chemical and biological pollutants is reported along with global scale pollution monitoring and the remote sensing of water pollutants. Individual items are announced in this issue.

Source record↗
DOE OSTI2022

Developing a heterogeneous ensemble learning framework to evaluate Alkali-silica reaction damage in concrete using acoustic emission signals

The monitoring and evaluation of Alkali-silica reaction (ASR) damage in concrete structures are required to ensure the serviceability and integrity of concrete infrastructures such as bridges and dams. The innovation of this paper lies in the development of an automatic ASR monitoring and evaluation approach by leveraging acoustic emission (AE) and a heterogeneous ensemble learning framework. Here, in this paper, ASR was monitored by AE sensors attached to a concrete specimen, which was placed in a chamber with high humidity and temperature. The recorded AE signals were filtered and divided by four ASR phases according to signal strength, crack width and expansion strain. A heterogeneous ensemble network including convolutional neural networks (CNN) and random forest models was employed to learn different features from AE signals and classify the AE signals into their corresponding phases. The results suggest that the proposed model has a high performance and classifies the signals into the assigned phases with high accuracy.

42 ENGINEERING↗
DOE OSTI2021

Experimental study correlating damage and permeability in concrete using confined, flattened Brazilian disks

This research experimentally studies coupled hydro-mechanical relationships using flattened Brazilian disks under confinement, with concurrent permeability measurements and acoustic emission monitoring. A series of tests are performed on concrete, as representative samples of brittle geo-materials, under a range of confining stresses between 2.76 and 13.79 MPa. Acoustic emission data is used to quantify damage and identify damage thresholds. Damage is then correlated to pre-peak changes in permeability. The advancement of models that couple transport properties to mechanical responses are of interest in the fields of carbon sequestration, hydrofracking, production of geothermal energy, induced seismicity, and underground nuclear waste storage, and these experiments validate a novel experimental approach towards investigating hydro-mechanical relationships.

Boyce, S.↗
NASA NTRS2015

Tracking Three-Dimensional Fish Behavior with a New Marine Acoustic Telemetry System

The persistent monitoring capability provided by acoustic telemetry systems allows us to study behavior, movement, and resource selection of mobile marine animals. Current marine acoustic telemetry systems are challenged by localization errors and limits in the number of animals that can be tracked simultaneously. We designed a new system to provide detection ranges of up to 1 km, to reduce localization errors to less than 1 m, and to increase to 500 the number of unique tags simultaneously tracked. The design builds on HTIs experience of more than a decade developing acoustic telemetry systems for freshwater environments. A field trial of the prototype system was conducted at the University of Washingtons Friday Harbor Marine Laboratory (Friday Harbor, WA). Copper rockfish (Sebastes caurinus) were selected for field trials of this new system because their high site-fidelity and small home ranges provide ample opportunity to track individual fish behavior while testing our ability to characterize the movements of a species of interest to management authorities.

acoustic telemetry↗
DOE OSTI2014

Continuous wavelet transform analysis and modal location analysis acoustic emission source location for nuclear piping crack growth monitoring

Source location is an important feature of acoustic emission (AE) damage monitoring in nuclear piping. The ability to accurately locate sources can assist in source characterisation and early warning of failure. This paper describe the development of a novelAE source location technique termed 'Wavelet Transform analysis and Modal Location (WTML)' based on Lamb wave theory and time-frequency analysis that can be used for global monitoring of plate like steel structures. Source location was performed on a steel pipe of 1500 mm long and 220 mm outer diameter with nominal thickness of 5 mm under a planar location test setup using H-N sources. The accuracy of the new technique was compared with other AE source location methods such as the time of arrival (TOA) techniqueand DeltaTlocation. Theresults of the study show that the WTML method produces more accurate location resultscompared with TOA and triple point filtering location methods. The accuracy of the WTML approach is comparable with the deltaT location method but requires no initial acoustic calibration of the structure.

42 ENGINEERING↗
DOE OSTI2018

Structure of a Deformed Inhomogeneous Material on the Data of Acoustic Emission and X-Ray Computer Microtomography

Accumulation of defects at various stages of the deformation of a structurally inhomogeneous material (granite) has been studied using two nondestructive methods: acoustic emission (AE) and X-ray computer microtomorgaphy (CT). The quasi-static testing of cylindrical samples of a Westerly granite was carried out under uniaxial compression. The control of the defect formation was realized using the real-time monitoring of acoustic emission. For each sample under study, several steps of the loading and tomographic imaging have been performed. We have found that an exponential or power-law function of the energy distribution of the AE signals makes it possible to select a sample region, in which the system of defects has transited into a self-organized criticality state and large cracks have been formed. This result coincides with the data of the X-ray tomography Computer Microtomography.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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 OSTI2014

Stochastic dislocation kinetics and fractal structures in deforming metals probed by acoustic emission and surface topography measurements

We demonstrate that the fractal dimension (FD) of the dislocation population in a deforming material is an important quantitative characteristic of the evolution of the dislocation structure. Thus, we show that peaking of FD signifies a nearing loss of uniformity of plastic flow and the onset of strain localization. Two techniques were employed to determine FD: (i) inspection of surface morphology of the deforming crystal by white light interferometry and (ii) monitoring of acoustic emission (AE) during uniaxial tensile deformation. A connection between the AE characteristics and the fractal dimension determined from surface topography measurements was established. As a common platform for the two methods, the dislocation density evolution in the bulk was used. The relations found made it possible to identify the occurrence of a peak in the median frequency of AE as a harbinger of plastic instability leading to necking. It is suggested that access to the fractal dimension provided by AE measurements and by surface topography analysis makes these techniques important tools for monitoring the evolution of the dislocation structure during plastic deformation—both as stand-alone methods and especially when used in tandem.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Pipeline Monitoring Using Highly Sensitive Vibration Sensor Based on Fiber Ring Cavity Laser

A vibration fiber sensor based on a fiber ring cavity laser and an interferometer based single-mode-multimode-single-mode (SMS) fiber structure is proposed and experimentally demonstrated. The SMS fiber sensor is positioned within the laser cavity, where the ring laser lasing wavelength can be swept to an optimized wavelength using a simple fiber loop design. To obtain a better signal-to-noise ratio, the ring laser lasing wavelength is tuned to the maximum gain region biasing point of the SMS transmission spectrum. A wide range of vibration frequencies from 10 Hz to 400 kHz are experimentally demonstrated. In addition, the proposed highly sensitive vibration sensor system was deployed in a field-test scenario for pipeline acoustic emission monitoring. An SMS fiber sensor is mounted on an 18” diameter pipeline, and vibrations were induced at different locations using a piezoelectric transducer. The proposed method was shown to be capable of real-time pipeline vibration monitoring.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Fracture Analysis of Cohesive Zone Models for Modeling Residual Stress Induced Delamination in Composite Structures

A fracture study of coupon-scale composite cylinders with embedded defects was conducted with an objective to assess and validate a modeling approach using two available cohesive material models. The study included experimental and simulation evaluations of initiation of crack growth and progression. Interrupted thermal experiments used acoustic emissions monitoring to identify the onset of crack progression during each cooling interval and ultrasonic scanning provided images of defect growth. Verification, validation, and uncertainty quantification (VVUQ) processes were performed in the assessment of the simulation predicted temperature at which crack propagation begins (quantity of interest). The Sobol sensitivity analysis identified the hoop direction elastic modulus in the carbon fiber reinforced polymer (CFRP) plies as the most influential parameter for simulations using both cohesive models, accounting for at least 70% of the variation in the temperature at crack propagation. The UQ temperature range for the Tvergaard-Hutchinson model was higher (more conservative) than the experimental acoustic measurement indicators of crack progression, while the temperature range for the Thouless-Parmigiani model enveloped the experimental data points for the primary defect size of 0.75 x 1 in. The simulations could not capture the stable crack growth indicated in the experiments. This is likely due to the models’ inability to represent anisotropic fracture toughness attributed to the structure of the orthotropic fiber weave in a woven composite laminate.

42 ENGINEERING↗
NASA NTRS2017

The Effects of Fiber Orientation and Adhesives on Tensile Properties of Carbon Fiber Reinforced Polymer Matrix Composite with Embedded Nickel-Titanium Shape Memory Alloys

Nickel-titanium (NiTi) shape memory alloy (SMA) sections were embedded within carbon fiber reinforced polymer matrix composite (CFRPPMC) laminates and their tensile properties were evaluated with simultaneous monitoring of modal acoustic emissions. The test specimens were fabricated in three different layup configurations and two different thin film adhesives were applied to bond the SMA with the PMC. A trio of acoustic sensors were attached to the specimens during tensile testing to monitor the modal acoustic emission (AE) as the materials experienced mechanical failure. The values of ultimate tensile strengths, strains, and moduli were obtained. Cumulative AE energy of events and specimen failure location were determined. In conjunction, optical and scanning electron microscopy techniques were used to examine the break areas of the specimens. The analysis of AE data revealed failure locations within the specimens which were validated from the microscopic images. The placement of 90 deg plies in the outer ply gave the strongest acoustic signals during break as well as the cleanest break of the samples tested. Overlapping 0 deg ply layers surrounding the SMA was found to be the best scenario to prevent failure of the specimen itself.

shape memory alloy↗
DOE OSTI2020

Detection, monitoring, and determination of location of changes in metallic structures using multimode acoustic signals

Methods for detection, monitoring, and determination of location of changes in rigid structures with arbitrarily complex geometries are described. Implementations include locating acoustic transducers that generate and receive acoustic signals at multiple locations along a surface of the rigid structure, wherein longitudinal spacing between the transducer locations define measurement zones. Acoustic signals with chosen amplitude-time-frequency characteristics excite multiple vibration modes in the structure within each zone. Small mechanical changes in the inspection zones lead to scattering and attenuation of broadband acoustic signals, which are detectable as changes in received signal characteristics as part of a through-transmission technique. Additional use of short, narrowband pulse acoustic signals as part of a pulse-echo technique allows determination of the relative location of the mechanical change within each zone based on the differential delay profiles.

42 ENGINEERING↗
DOE OSTI2015

Analysis of seismic sources for different mechanisms of fracture growth for microseismic monitoring applications

We have developed and illustrated an approach for geomechanic modeling of elastic wave generation (microsiesmic event occurrence) during incremental fracture growth. We then derived properties of effective point seismic sources (radiation patterns) approximating obtained wavefields. These results establish connection between geomechanic models of hydraulic fracturing and microseismic monitoring. Thus, the results of the moment tensor inversion of microseismic data can be related to different geomechanic scenarios of hydraulic fracture growth. In future, the results can be used for calibrating hydrofrac models. We carried out a series of numerical simulations and made some observations about wave generation during fracture growth. In particular when the growing fracture hits pre-existing crack then it generates much stronger microseismic event compared to fracture growth in homogeneous medium (radiation pattern is very close to the theoretical dipole-type source mechanism)

42 ENGINEERING↗
DOE OSTI2024

Time series methods for the analysis of soundscapes and other cyclical ecological data

Biodiversity monitoring has entered an era of ‘big data’, exemplified by a near-continuous collection of sounds, images, chemical and other signals from organisms in diverse ecosystems. Such data streams have the potential to help identify new threats, assess the effectiveness of conservation interventions, as well as generate new ecological insights. However, appropriate analytical methods are often still missing, particularly with respect to characterizing cyclical temporal patterns. Here, we present a framework for characterizing and analysing ecological responses that represent nonstationary, complex temporal patterns and demonstrate the value of using Fourier transforms to decorrelate continuous data points. In our example, we use a framework based on three approaches (spectral analysis, magnitude squared coherence, and principal component analysis) to characterize differences in tropical forest soundscapes within and across sites and seasons in Gabon. By reconstructing the underlying, cyclic behaviour of the soundscape for each site, we show how one can identify circadian patterns in acoustic activity. Soundscapes in the dry season had a complex diel cycle, requiring multiple harmonics to represent daily variation, while in the wet season there was less variance attributable to the daily cyclic patterns. Our framework can be applied to most continuous, or near-continuous ecological data collected at a fine temporal resolution, allowing ecologists to explore patterns of temporal autocorrelation at multiple levels for biologically meaningful trends. Such methods will become indispensable as biological big data are used to understand the impact of anthropogenic pressures on biodiversity and to inform efforts to mitigate them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The variable influence of anthropogenic noise on summer season coastal underwater soundscapes near a port and marine reserve

Monitoring soundscapes is essential for assessing environmental conditions for soniferous species, yet little is known about sound levels and contributors in Oregon coastal regions. From 2017-2021, during June-September, two hydrophones were deployed near Newport, Oregon to sample 10-13,000Hz underwater sound. One hydrophone was deployed near the Port of Newport in a high vessel activity area, and another 17km north within a protected Marine Reserve. Vessel noise and whale vocalizations were detected at both sites, but whales were recorded on more days at the Marine Reserve. Median sound levels in frequencies related to noise from various vessel types and sizes (50-4,000Hz) were up to 6dB higher at the Port of Newport, with greater diel variability compared to the Marine Reserve. In addition to documenting summer season conditions in Oregon waters, these results exemplify how underwater soundscapes can differ over short distances depending on anthropogenic activity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Lessons learnt from post EIS evaluations of national road schemes in Ireland

The Irish National Roads Authority (NRA) recently completed over twenty post environmental impact assessment evaluations of noise chapters prepared as part of Environmental Impact Statements (EISs) for new national road schemes in Ireland. The study focused on a range of issues including a review of noise monitoring procedures, noise prediction methodologies and an assessment of the effectiveness of noise mitigation measures currently in use on national road schemes. This review was carried out taking cognisance of best international practices for noise assessment and methodologies used to mitigate road traffic noise. The primary focus of the study was to assess the actual noise impacts of national road scheme developments and to revise, where necessary, methodologies recommended in the current NRA guidance document describing the treatment of noise on national road schemes. This paper presents a summary of the study and identifies a number of key areas that should be considered prior to the development of future guidance documents. - Highlights: Black-Right-Pointing-Pointer Presents a post-EIS evaluation of noise assessments for national roads in Ireland. Black-Right-Pointing-Pointer The effectiveness of some noise mitigation measures is critically evaluated. Black-Right-Pointing-Pointer Issues related to the current EIS noise assessment methodologies are discussed. Black-Right-Pointing-Pointer Implications for alterations to the NRA noise guidelines.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Crack Propagation Analysis Using Acoustic Emission Sensors for Structural Health Monitoring Systems

Aerospace systems are expected to remain in service well beyond their designed life. Consequently, maintenance is an important issue. A novel method of implementing artificial neural networks and acoustic emission sensors to form a structural health monitoring (SHM) system for aerospace inspection routines was the focus of this research. Simple structural elements, consisting of flat aluminum plates of AL 2024‐T3, were subjected to increasing static tensile loading. As the loading increased, designed cracks extended in length, releasing strain waves in the process. Strain wave signals, measured by acoustic emission sensors, were further analyzed in post‐processing by artificial neural networks (ANN). Several experiments were performed to determine the severity and location of the crack extensions in the structure. ANNs were trained on a portion of the data acquired by the sensors and the ANNs were then validated with the remaining data. The combination of a system of acoustic emission sensors, and an ANN could determine crack extension accurately. The difference between predicted and actual crack extensions was determined to be between 0.004 in. and 0.015 in. with 95% confidence. These ANNs, coupled with acoustic emission sensors, showed promise for the creation of an SHM system for aerospace systems.

42 ENGINEERING↗
DOE OSTI2022

Influence of weather on gobbling activity of male wild turkeys

Gobbling activity of Eastern wild turkeys (Meleagris gallopavo silvestris; hereafter, turkeys) has been widely studied, focusing on drivers of daily variation. Weather variables are widely believed to influence gobbling activity, but results across studies are contradictory and often equivocal, leading to uncertainty in the relative contribution of weather variables to daily fluctuations in gobbling activity. Previous works relied on road-based auditory surveys to collect gobbling data, which limits data consistency, duration, and quantity due to logistical difficulties associated with human observers and restricted sampling frames. Development of new methods using autonomous recording units (ARUs) allows researchers to collect continuous data in more locations for longer periods of time, providing the opportunity to delve into factors influencing daily gobbling activity. We used ARUs from 1 March to 31 May to detail gobbling activity across multiple study sites in the southeastern United States during 2014–2018. We used state-space modeling to investigate the effects of weather variables on daily gobbling activity. Our findings suggest rainfall, greater wind speeds, and greater temperatures negatively affected gobbling activity, whereas increasing barometric pressure positively affected gobbling activity. Therefore, when using daily gobbling activity to make inferences relative to gobbling chronology, reproductive phenology, and hunting season frameworks, stakeholders should recognize and consider the potential influences of extended periods of inclement weather.

60 APPLIED LIFE SCIENCES↗