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At least 289 records · Page 16

Sensing Modalities Deployed - Acoustic

Acoustic approaches to OLM are based on analyzing changes in various forms of pressure waves propagating in solids, fluids or gases. These pressure waves can vary in frequency content from infrasound (seismic events) to the megahertz region (acoustic emissions). A wide variety of commercially available pressure or stain sensing devices are used to make acoustic measurements. These sensors differ in the transduction mechanism used to convert the pressure or strain signal to an electrical output, the sensitivity, dynamic range, bandwidth, directional characteristics, and physical size. All acoustic sensors must be integrated with signal conditioning electronics to convert the sensors’ analog output to discrete digital signals that can then be further analyzed for OLM. Ultimately, the sensing properties listed above will be a function of the sensor transduction mechanism, the sensor design and the conditioning electronics.

47 OTHER INSTRUMENTATION↗

Cooperative implementation of a high temperature acoustic sensor

The current status and results of a cooperative program aimed at the implementation of a high-temperature acoustic/strain sensor onto metallic structures are reported. The sensor systems that are to be implemented under this program will measure thermal expansion, maneuver loads, aircraft buffet, sonic fatigue, and acoustic emissions in environments that approach 1800 F. The discussion covers fiber development, fabrication of an extrinsic Fabry-Perot interferometer acoustic sensor, sensor mounting/integration, and results of an evaluation of the sensor capabilities.

Baldini, S. E.↗

Method and system to measure gas flow

A system for measuring gas flow generally including a passive acoustic wave generator disposed in a gas flow stream to passively generate an audio signal through vortex shedding, a sound capturing instrument disposed outside the gas stream to produce an electrical signal representative of the acoustic signal, a temperature sensor to obtain temperature measurements indicative of the temperature of the gas flow stream and a control system for determining the gas flow, such as velocity or flow rate, as a function of the acquired acoustic and temperature measurements. The acoustic wave generator includes a corrugated flow channel whose geometric design is so tuned to generate an acoustic emission whose frequency signature varies as a function of the gas flow velocity. The control system may acquires time-domain acoustic data, and process that data to obtain a frequency-domain representation from which gas velocity or gas flow rate can be determined.

Cetiner, Mustafa S.↗

Applications of Advanced, Waveform Based AE Techniques for Testing Composite Materials

Advanced, waveform based acoustic emission (AE) techniques have been previously used to evaluate damage progression in laboratory tests of composite coupons. In these tests, broad band, high fidelity acoustic sensors were used to detect signals which were then digitized and stored for analysis. Analysis techniques were based on plate mode wave propagation characteristics. This approach, more recently referred to as Modal AE, provides an enhanced capability to discriminate and eliminate noise signals from those generated by damage mechanisms. This technique also allows much more precise source location than conventional, threshold crossing arrival time determination techniques. To apply Modal AE concepts to the interpretation of AE on larger composite structures, the effects of wave propagation over larger distances and through structural complexities must be well characterized and understood. In this research, measurements were made of the attenuation of the extensional and flexural plate mode components of broad band simulated AE signals in large composite panels. As these materials have applications in a cryogenic environment, the effects of cryogenic insulation on the attenuation of plate mode AE signals were also documented.

Prosser, William H.↗

Framework for National Airspace System (NAS) Level Sustainability Assessment of New Aircraft

This paper introduces a framework for investigating the future sustainability benefits of conceptual vehicles. The framework considers the complex interactions between such vehicles and how it can be flown in the National Airspace System. Aggregate benefits for reduction in fuel use and emissions need to consider fleet wide operations, demand distributions, NAS Infrastructure, and differing business models. To extract true system level benefits multi-objective function optimization for operational energy use, acoustics, emissions and NAS Wide efficiency and interoperability incorporating physic-based system-wide flight simulations in the National Airspace system is required. The framework marries traditional vehicle synthesis processes with a NAS Simulation environment to simulate how a new synthesized vehicle will behave in the NAS.

Sustainability↗

Wave energy in white dwarf atmospheres. I - Magnetohydrodynamic energy spectra for homogeneous DB and layered DA stars

The radiative damping of acoustic and MHD waves that propagate through white dwarf photospheric layers is studied, and other damping processes that may be important for the propagation of the MHD waves are calculated. The amount of energy remaining after the damping processes have occurred in different types of waves is estimated. The results show that lower acoustic fluxes should be expected in layered DA and homogeneous DB white dwarfs than had previously been estimated. Acoustic emission manifests itself in an enhancement of the quadrupole term, but this term may become comparable to or even lower than the dipole term for cool white dwarfs. Energy carried by the acoustic waves is significantly dissipated in deep photospheric layers, mainly because of radiative damping. Acoustically heated corona cannot exist around DA and DB white dwarfs in a range T(eff) = 10,000-30,000 K and for log g = 7 and 8. However, relatively hot and massive white dwarfs could be exceptions.

Musielak, Zdzislaw E.↗

The effects of initial jet exit conditions on plume resonance

The acoustic emission and boundary layer of a cold jet issuing from an underexpanded sonic nozzle have been measured for lip thicknesses of the nozzle exit varying from 0.015-0.625 nozzle diameters. Near-field acoustic data demonstrate that the amplitude and frequency of certain modes of screech and the dominant mode of instability which exists in the shear layer are dependent on nozzle lip thickness. Changes in momentum thickness due to variations in the nozzle exit were also quantified.

Ponton, Michael K.↗

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

36 MATERIALS SCIENCE↗

Aeroacoustic Assessment of Wind Plant Controls

The Aeroacoustic Assessment project aims to quantify changes in aeroacoustic noise generation by a utility scale wind turbine operating under imposed yaw offsets common for wake steering and wind plant control strategies. Active plant control utilizing wake deflection control strategies have been shown experimentally and computationally to reliably produce 1-2% of additional annual energy production (AEP) without significant changes in turbine structural loads, the potential impact on aeroacoustic emissions has yet to be quantified or completely understood. Yawed operation of a wind turbine changes the three-dimensional aerodynamic interaction between the rotor blades and the incoming atmospheric flow, leading to changes in noise generation. This work quantifies the extent to which active control induces additional aeroacoustic emissions from additional separation and other flow interaction dynamic effects. Given public concerns about wind turbine noise and the need for observational data required for regulators to establish noise restrictions, we must understand potential acoustic emissions resulting from active control prior to commercial deployment and the development of practical noise reduction methods and technologies. The work outlined in this report details the new aeroacoustic measurement capability developed at NREL and its application to making full-field observations of noise from a utility-scale wind turbine. Preliminary noise modeling with the aeroacoustics module in OpenFAST helped to establish the design of the experiment, specifically targeting the noise observed at observers distributed around the DOE-owned GE 1.5 MW wind turbine. Low-frequency and infrasound measurement capability implemented in this project establish an operational baseline for the wind turbine, setting the stage for future control, rotor blade, and turbine design research.

17 WIND ENERGY↗

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

42 ENGINEERING↗

Physics informed neural network can retrieve rate and state friction parameters from acoustic monitoring of laboratory stick-slip experiments

Various machine learning (ML) and deep learning (DL) techniques have been recently applied to the forecasting of laboratory earthquakes from friction experiments. The magnitude and timing of shear failures in stick-slip cycles are predicted using features extracted from the recorded ultrasonic or acoustic emission (AE) signals. In addition, the Rate and State Friction (RSF) constitutive laws are extensively used to model the frictional behavior of faults. In this work, we use data from shear experiments coupled with passive acoustic (variance, kurtosis, and AE rate) interleaved with active source ultrasonic monitoring (transmitted wave amplitude) to develop physics-informed neural network (PINN) models incorporating the RSF law and AE rate generation equation with wave amplitude serving as a proxy for friction state variable. This PINN framework allows learning RSF parameters from stick-slip experiments rather than measuring them through a series of velocity step experiments. We observe that when the stick-slip cycles are irregular, the PINN models outperform the data-driven DL models. Transfer learning (TL) PINN models are also developed by pre-training on data collected at one normal stress level followed by forecasting shear failures and retrieving RSF parameters at other stress levels (i.e., with different recurrence intervals) after retraining on a limited amount of new data. Our findings suggest that TL models perform better compared to standalone models. Both standalone and TL PINN-estimated RSF parameters and their ground truth values show excellent agreements thus demonstrating that RSF parameters can be retrieved from laboratory stick-slip experiments using the corresponding acoustic data and that the transmitted wave amplitude provides a good representation of the evolving frictional state during stick-slips.

58 GEOSCIENCES↗

Acoustical Testing Laboratory Developed to Support the Low-Noise Design of Microgravity Space Flight Hardware

The NASA John H. Glenn Research Center at Lewis Field has designed and constructed an Acoustical Testing Laboratory to support the low-noise design of microgravity space flight hardware. This new laboratory will provide acoustic emissions testing and noise control services for a variety of customers, particularly for microgravity space flight hardware that must meet International Space Station limits on noise emissions. These limits have been imposed by the space station to support hearing conservation, speech communication, and safety goals as well as to prevent noise-induced vibrations that could impact microgravity research data. The Acoustical Testing Laboratory consists of a 23 by 27 by 20 ft (height) convertible hemi/anechoic chamber and separate sound-attenuating test support enclosure. Absorptive 34-in. fiberglass wedges in the test chamber provide an anechoic environment down to 100 Hz. A spring-isolated floor system affords vibration isolation above 3 Hz. These criteria, along with very low design background levels, will enable the acquisition of accurate and repeatable acoustical measurements on test articles, up to a full space station rack in size, that produce very little noise. Removable floor wedges will allow the test chamber to operate in either a hemi/anechoic or anechoic configuration, depending on the size of the test article and the specific test being conducted. The test support enclosure functions as a control room during normal operations but, alternatively, may be used as a noise-control enclosure for test articles that require the operation of noise-generating test support equipment.

Cooper, Beth A.↗

The location of the source of high-frequency solar acoustic oscillations

Recently Libbrecht and Jefferies et al. have reported regular peaks in the solar oscillation power spectrum extending well above 5.3 mHz, the maximum frequency of trapped acoustic modes. Kumar et al. argued that these peaks are primarily due to the interference of traveling waves which are excited due to acoustic emission from turbulent convection. In contrast with the standing wave P-mode frequencies below 5.3 mHz, the positions of the high-frequency interference peaks (HIPs) are dependent on the location of the source of the acoustic oscillations. In the present work, Kumar et al.'s argument is strengthened, and more importantly, use is made of the above dependence to determine the acoustic source strength as a function of depth. It is found that the acoustic source profile, and thus the convective velocity, is peaked about 200 km deeper than what is expected from standard mixing length theory.

Kumar, Pawan↗

An Amplitude-Based Estimation Method for International Space Station (ISS) Leak Detection and Localization Using Acoustic Sensor Networks

The development of a robust and efficient leak detection and localization system within a space station environment presents a unique challenge. A plausible approach includes the implementation of an acoustic sensor network system that can successfully detect the presence of a leak and determine the location of the leak source. Traditional acoustic detection and localization schemes rely on the phase and amplitude information collected by the sensor array system. Furthermore, the acoustic source signals are assumed to be airborne and far-field. Likewise, there are similar applications in sonar. In solids, there are specialized methods for locating events that are used in geology and in acoustic emission testing that involve sensor arrays and depend on a discernable phase front to the received signal. These methods are ineffective if applied to a sensor detection system within the space station environment. In the case of acoustic signal location, there are significant baffling and structural impediments to the sound path and the source could be in the near-field of a sensor in this particular setting.

Tian, Jialin↗

Some fundamental acoustic observations in combusting turbulent jets

A study is presented of the possibility of using the acoustic radiation emitted from turbulent combustion zones to characterize the structure, mechanics and properties of turbulent combustion. Theoretical consideration is given to the acoustic characteristics of a nonpremixed open turbulent jet flame and the response of the acoustic spectrum to changes in combustion conditions. Experimental observations made of the acoustic emissions from a laboratory burner that establishes turbulent flames at the exit of a fully developed pipe flow as well as two commercial burners using methane, ethane and propane fuels are then presented which reveal changes in the acoustic amplitudes in three high-frequency bands associated with changes in the air-fuel ratio. Results suggest a means for combustion diagnostics and demonstrate the possibility of using acoustic measurements in investigations of combustion zone processes.

Ramohalli, K.↗

Advanced AE Techniques in Composite Materials Research

Advanced, waveform based acoustic emission (AE) techniques have been successfully used to evaluate damage mechanisms in laboratory testing of composite coupons. An example is presented in which the initiation of transverse matrix cracking was monitored. In these tests, broad band, high fidelity acoustic sensors were used to detect signals which were then digitized and stored for analysis. Analysis techniques were based on plate mode wave propagation characteristics. This approach, more recently referred to as Modal AE, provides an enhanced capability to discriminate and eliminate noise signals from those generated by damage mechanisms. This technique also allows much more precise source location than conventional, threshold crossing arrival time determination techniques. To apply Modal AE concepts to the interpretation of AE on larger composite specimens or structures, the effects of modal wave propagation over larger distances and through structural complexities must be well characterized and understood. To demonstrate these effects, measurements of the far field, peak amplitude attenuation of the extensional and flexural plate mode components of broad band simulated AE signals in large composite panels are discussed. These measurements demonstrated that the flexural mode attenuation is dominated by dispersion effects. Thus, it is significantly affected by the thickness of the composite plate. Furthermore, the flexural mode attenuation can be significantly larger than that of the extensional mode even though its peak amplitude consists of much lower frequency components.

Prosser, William H.↗

Aeroacoustic Measurements from the Aerodynamic and Acoustic Rotorprop Test (AART) in the National Full-Scale Aerodynamics Complex (NFAC) 40- by 80-Foot Wind Tunnel

Unmanned Aerial Vehicle (UAV) designs typically have aerodynamic configurations that result in complex aerodynamic and acoustic conditions, such as wing and propeller interaction. In response, the Aerodynamic and Acoustic Rotorprop Test (AART) Program was implemented, a primary objective of which was to determine the aerodynamics and acoustics related to an auxiliary propulsor mounted behind an isolated wing in the National Full-Scale Aerodynamics Complex (NFAC) 40-by 80-Foot Wind Tunnel. Three configurations (no wing, half wing, and full wing) were tested, with conditions including variation of the propeller speed, wind tunnel Mach number, and Yaw. The acoustic set up, processing, and analysis are discussed along with the known issues for this complex data set. The interaction of upstream bodies and the resulting substantial increase in acoustic emissions are discussed in detail.

Propeller↗

Time-Frequency Analysis of the Dispersion of Lamb Modes

Accurate knowledge of the velocity dispersion of Lamb modes is important for ultrasonic nondestructive evaluation methods used in detecting and locating flaws in thin plates and in determining their elastic stiffness coefficients. Lamb mode dispersion is also important in the acoustic emission technique for accurately triangulating the location of emissions in thin plates. In this research, the ability to characterize Lamb mode dispersion through a time-frequency analysis (the pseudo-Wigner-Ville distribution) was demonstrated. A major advantage of time-frequency methods is the ability to analyze acoustic signals containing multiple propagation modes, which overlap and superimpose in the time domain signal. By combining time-frequency analysis with a broadband acoustic excitation source, the dispersion of multiple Lamb modes over a wide frequency range can be determined from as little as a single measurement. In addition, the technique provides a direct measurement of the group velocity dispersion. The technique was first demonstrated in the analysis of a simulated waveform in an aluminum plate in which the Lamb mode dispersion was well known. Portions of the dispersion curves of the AO, A I , So, and S2 Lamb modes were obtained from this one waveform. The technique was also applied for the analysis of experimental waveforms from a unidirectional graphite/epoxy composite plate. Measurements were made both along and perpendicular to the fiber direction. In this case, the signals contained only the lowest order symmetric and antisymmetric modes. A least squares fit of the results from several source to detector distances was used. Theoretical dispersion curves were calculated and are shown to be in good agreement with experimental results.

Prosser, W. H.↗