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Systems and methods of detecting and identifying a leak from a container or building. Acoustic pressure and velocity are measured. Acoustic properties are acquired from the measured values. The acoustic properties are converted to infiltration/leakage information. Nearfield Acoustic Holography (NAH) may be one method to detect the leakages from a container by locating the noise sources.
A key enabling capability for enrichment plant safeguards being considered by the International Atomic Energy Agency (IAEA) is high-accuracy, noninvasive, unattended measurement of UF6 gas density and mass flow rate. Acoustic techniques are currently used to noninvasively monitor gas flow in industrial applications; however, the operating pressures at gaseous centrifuge enrichment plants (GCEPs) are roughly two orders magnitude below the capabilities of commercial instrumentation. Pacific Northwest National Laboratory is refining acoustic techniques for estimating density and mass flow rate of UF6 gas in scenarios typical of GCEPs, with the goal of achieving 1% measurement accuracy. Proof-of-concept laboratory measurements using a surrogate gas for UF6 have demonstrated signatures sensitive to gas density at low operating pressures such as 10–50 Torr, which were observed over the background acoustic interference. Current efforts involve developing a test bed for conducting acoustic measurements on flowing SF6 gas at representative flow rates and pressures to ascertain the viability of conducting gas flow measurements under these conditions. Density and flow measurements will be conducted to support the evaluation. If successful, the approach could enable an unattended, noninvasive approach to measure mass flow in unit header pipes of GCEPs.
Marine and hydrokinetic (MHK) energy devices are early-stage technologies and their impacts to ocean life and environment are largely unknown, which consequently limits the progress of deploying these devices at commercial scale. Optical and acoustic imaging have been the primary technologies for monitoring marine animals’ behavior at existing or potential MHK sites. However, these technologies lack the ability to identify individual animals, which makes them less useful in identifying protected species as well as studying the animals’ long-term behavior. Implantable acoustic transmitters with unique identification codes could be used as a complementary technology. To minimize the tag burden on the tagged animal (and hence the resulting bias) and to satisfy the long-term monitoring needs, it is desired that the implanted transmitter be as small and light as possible and can last for as long as possible. To date, the smallest acoustic transmitters suitable for marine animal tracking have relatively short service life and detection range (up to 200 m). In this report, we introduce a new miniaturized acoustic transmitter which operates at 208.3 kHz. It offers a smaller dry weight (0.45 g), a significantly longer service life (140 days at a 5-second ping rate) as well as a greater detection range than the existing commercial counterparts, which will help obtain more comprehensive movement and behavioral information of animals around MHK energy devices.
Apparatus (10) and methods for measurement of pore pressure in rock formations through a metal borehole casing (32) after a well is cased and cemented, are described. Such measurements may be accomplished by using the Dynamic Acoustic Elasticity (DAE) method for characterizing nonlinear parameters by perturbing a selected rock formation region with a High Amplitude, Low Frequency (HALF) acoustic strain wave, and probing this region using a Low Amplitude, High Frequency (LAHF) acoustic wave (18), (22). Time reversal techniques (36) may be employed for focusing acoustic energy into the formation in the vicinity of the pipe or open hole. The change in wave speed of the probe pulses as the HALF induced strain wave oscillation propagates through the formation, as a function of the induced strain, may be used to determine the nonlinear elastic parameters α, β, δ, and A of the pore pressure, from which the pore pressure may be determined in the region of the HALF wave.
A device employing the generation and enhancement of surface acoustic waves on a highly doped p-type III-V semiconductor substrate (e.g., GaAs, GaSb, InAs, or InGaAs). The device includes two SiO 2 /ZnO islands, each including a SiO 2 buffer layer deposited on the doped p-type III-V semiconductor substrate and a ZnO layer deposited on the SiO 2 buffer layer. An input interdigital transducers (IDT) and an output IDT are each patterned on one of the SiO 2 /ZnO islands. The IDTs generates surface acoustic waves along an exposed surface of the highly doped p-type III-V semiconductor substrate. The surface acoustic waves improve the photoelectric and photovoltaic properties of the device. The device is manufactured using a disclosed technique for propagating strong surface acoustic waves on weak piezoelectric materials. Also disclosed is a photodetector developed using that technique.
A SAW sensor is optimized for detection of refrigerant leakage in a refrigerant system or other gases, vapors, explosives or chemicals of interest. The SAW sensor includes a piezoelectric substrate; an interdigitated transducer deposited on the piezoelectric substrate, the interdigitated transducer having an input portion that receives input surface acoustic waves and an output portion that emits output surface acoustic waves; and a refrigerant sensor film located between the input portion and the output portion of the interdigitated transducer, the refrigerant sensor film including a sorbent material that is selected for preferential adsorption of a target refrigerant over atmospheric gases. Adsorption of the target refrigerant by the sorbent material results in a frequency shift of a frequency of the output surface acoustic waves relative to a frequency of the input surface acoustic waves. The sorbent material may be a metal organic framework (MOF) material, a covalent organic framework (COF) material, a porous organic cage or organic macrocyles such as calix [n] arene and its related derivatives.
The contamination of aquatic systems with microplastics is becoming a severe threat to living organisms. Microplastics found in the environment consist of a wide range of particle sizes thus give rise to several challenges to current purification methods. Acoustic focusing has been utilized as a particle concentrating method in biological and non-biological applications. In this study, we investigate the feasibility of using acoustic focusing technology to isolate microplastics in aqueous samples and find that a two-stage mechanism is essential to concentrate microplastics of wide size ranges of the same material. We demonstrate for the first time experimentally that when the particle size is comparable to the resonance wavelength, they deviate from typical pressure nodal focusing and show pressure antinodal focusing. Further, we have expanded microplastics isolation beyond microfluidic systems and demonstrate their extraction capabilities relatively at higher flow rates using microplastics of polystyrene, polyethylene, and polymethyl methacrylate ranging from 6 µm to 300 µm diameter and in devices fabricated with cylindrical steel tubes. We could extract 70% of microplastics smaller than 180 µm and 82% of microplastics greater than 180 µm in diameter from an aqueous sample at a flow rate of 12 mL/min. In conclusion, we demonstrate that small microplastics focus on acoustic pressure nodes regardless of the medium density. However, focusing of large microplastics of the same material depends on the medium density.
We report in the past decade, acoustics at the nanoscale (i.e., nanoacoustics) has evolved rapidly with continuous and substantial expansion of capabilities and refinement of techniques. Motivated by research innovations in the last decade, for the first time, recent advancements of acoustics-associated nanomaterials/nanostructures and nanodevices for different applications are outlined in this comprehensive review, which is written in two parts. As part I of this two-part review, firstly, active and passive nanomaterials and nanostructures for acoustics are presented. Following that, representative applications of nanoacoustics including material property characterization, nanomaterial/nanostructure manipulation, and sensing, are discussed in detail. Finally, a summary is presented with point of views on the current challenges and potential solutions in this burgeoning field.
The Juvenile Salmon Acoustic Telemetry System (JSATS) project supported by the U.S. Army Corps of Engineers, Portland District, has yielded the smallest acoustic fish tag transmitter commercially available to date. In order to study even smaller fish populations and make the transmitter injectable by needles, the JSATS acoustic micro transmitter needs to be further downsized. This study focuses on the optimization of microbattery design based on Li/CFx chemistry. Through appropriate modifications, a steady high-rate pulse current with desirable life time has been achieved while the weight and volume of the battery is largely reduced. The impedance variation in as-designed microbatteries is systematically compared with that of currently used watch batteries in JSATS with an attempt to understand the intrinsic factors that control the performances of microbatteries under the real testing environments.
As computational capabilities continue to grow, exploring the limits of computational fluid dynamics to capture complex and elusive phenomena, which are otherwise difficult to study by experimental techniques, is one of the main targets for the research community. This paper presents a detailed analysis of the physical processes that lead to combustion noise emissions in internal combustion engines. In particular, diesel combustion in a compression-ignition (CI) engine is studied in order to understand the singular behavior of the in-cylinder flow field responsible for the acoustic emissions. The main objective is, therefore, to improve the understanding of the phenomena involved in CI engine noise using large eddy simulations. Several visualization methods are employed to investigate the connection between combustion behavior and its effects on the pressure field. In addition, proper orthogonal decomposition is used to analyze the modal energy distribution among all the acoustic modes. The results show that the acoustic signature is fundamentally conditioned by the intensity of the premixed combustion rather than by the pressure oscillations generated by turbulent fluctuations in the flame surface established during the diffusion stage.
The Juvenile Salmon Acoustic Telemetry System (JSATS) project supported by the U.S. Army Corps of Engineers, Portland District, has yielded the smallest acoustic fish tag transmitter commercially available to date. In order to study even smaller fish populations and make the transmitter injectable by needles, the JSATS acoustic micro transmitter needs to be further downsized. As part of the transmitter downsizing effort some of the design parameters of the lead zirconate titanate (PZT) ceramic tube transducer in the transmitter were studied, including the type of PZT, the backing material, the necessary drive voltage, the transmitting bandwidth and the length of the transducer. It was found that, to satisfy the 156-dB source level requirement of JSATS, a square wave with a 10-volt amplitude is required to drive 'soft' PZT transducers. PZT-5H demonstrated the best source level performance. For Navy types I and II, 16 volts or 18 volts were needed. Ethylene-propylene-diene monomer (EPDM) closed-cell foam was found to be the backing material providing the highest source level. The effect of tube length on the source level is also demonstrated in this paper, providing quantitative information for downsizing of small piezoelectric transmitters.
The next generation of acoustic sensors is emerging to supplement legacy sensors traditionally used in regional and global networks. These devices operate under similar principles as traditional sensors, without the need of a separate external digitizer. The calibration of these sensors against their predecessors is crucial to the modernization of conventional technologies. This work describes the characterization of the next-generation MB3 digital microbarometer and the iPrecision smartphone microphone in a non-isolated calibration room across the infrasound (i.e., 0.01–20 Hz) range. The intent is to evaluate nominal instrument performance before deployment. A portable rotary subwoofer is used as a controllable infrasound source to generate single-tone sinusoidal and broadband noise pressure waves in a room configured for calibration purposes. For each device, comparison measurements are made, from which the digital sensitivity and the parametric response is developed. The results provide insight into the performance of the sensors in non-isolated environments. By overlapping the responses of the test sensors, digital sensor performance across the infrasound range can be benchmarked. These responses may serve as a double-reference scheme in future pressure measurements and digital calibrations of acoustic sensors.
Acoustic waves with periods of 2–4 min and gravity waves with periods of 6–16 min have been detected at ionospheric heights (25–350 km) using GPS total electron content measurements. The area disturbed by these waves and the wave amplitudes have been associated with underlying thunderstorm activity. A statistical study comparing Next Generation Weather Radar thunderstorm measurements with ionospheric acoustic and gravity waves in the midlatitude U.S. Great Plains region was performed for the time period of May–July 2005. An increase of ionospheric acoustic wave disturbed area and amplitude is primarily associated with large thunderstorms (mesoscale convective systems). Ionospheric gravity wave disturbed area and amplitude scale with thunderstorm activity, with even small storms (i.e., individual storm cells) producing an increase of gravity waves.
Noise reduction remains an important priority in the modern society, in particular, for urban areas and highly populated cities. Insulation of buildings and transport systems such as cars, trains, and airplanes has accelerated the need to develop advanced materials. Various porous materials, such as commercially available foams and granular and fibrous materials, are commonly used for sound mitigating applications. In this review, a special class of advanced porous materials, aerogels, is examined, and an overview of the current experimental and theoretical status of their acoustic properties is provided. Aerogels can be composed of inorganic matter, synthetic or natural polymers, as well as organic/inorganic composites and hybrids. Aerogels are highly porous nanostructured materials with a large number of meso‐ and small macropores; the mechanisms of sound absorption partly differ from those of traditional porous absorbers possessing large macropores. The understanding of the acoustic properties of aerogels is far from being complete, and experimental results remain scattered. It is demonstrated that the structure of the aerogel provides a complex three‐dimensional architecture ideally suited for promising high‐performance materials for acoustic mitigation systems. This is in addition to the numerous other desirable properties that include low density, low thermal conductivity, and low refractive index.
Abstract We present a machine learning workflow to discover signatures in acoustic measurements that can be utilized to create a low-dimensional model to accurately predict the location of keyhole pores formed during additive manufacturing processes. Acoustic measurements were sampled at 100 kHz during single-layer laser powder bed fusion (LPBF) experiments, and spatio-temporal registration of pore locations was obtained from post-build radiography. Power spectral density (PSD) estimates of the acoustic data were then decomposed using non-negative matrix factorization with custom $$\varvec{k}$$ k -means clustering (NMF $$\varvec{k}$$ k ) to learn the underlying spectral patterns associated with pore formation. NMF $$\varvec{k}$$ k returned a library of basis signals and matching coefficients to blindly construct a feature space based on the PSD estimates in an optimized fashion. Moreover, the NMF $$\varvec{k}$$ k decomposition led to the development of computationally inexpensive machine learning models which are capable of quickly and accurately identifying pore formation with classification accuracy of supervised and unsupervised label learning greater than 95% and 90%, respectively. The intrinsic data compression of NMF k , the relatively light computational cost of the machine learning workflow, and the high classification accuracy makes the proposed workflow an attractive candidate for edge computing toward in-situ keyhole pore prediction in LPBF.
In this article, we present a modeling approach to estimate the energy release due to ductile crack initiation in conjunction to the energy dissipation associated with the formation and propagation of transient stress waves typically referred to as acoustic emission. To achieve this goal, a ductile fracture problem is investigated computationally using the finite element method based on a compact tension geometry under Mode I loading conditions. To quantify the energy dissipation associated with acoustic emission, a crack increment is produced given a pre-determined notch size in a 3D cohesive-based extended finite element model. The computational modeling methodology consists of defining a damage initiation state from static simulations and linking such state to a dynamic formulation used to evaluate wave propagation and related energy redistribution effects. The model relies on a custom traction separation law constructed using full field deformation measurements obtained experimentally using the digital image correlation method. The amount of energy release due to the investigated first crack increment is evaluated through three different approaches both for verification purposes and to produce an estimate of the portion of the energy that radiates away from the crack source in the form of transient waves. The results presented herein propose an upper bound for the energy dissipation associated to acoustic emission, which could assist the interpretation and implementation of relevant nondestructive evaluation methods and the further enrichment of the understanding of effects associated with fracture.
Additive manufacturing (AM) has attracted considerable attention in recent years. This technology overcomes the geometrical limits of workpieces produced with the traditional subtractive methods and so gives the opportunity to manufacture highly complex shapes. Unfortunately, the repeatability of the manufacturing process and the monitoring of quality are not reliable enough to be utilized in mass production. The quality monitoring of AM processes in commercial equipment has been largely based on temperature measurements of the process zone or high-resolution imaging of the layers. However, both techniques lack information about the physical phenomena taking place in the depth of the materials medium and this limits their reliability in real-life applications. To overcome those restrictions, we propose to combine acoustic emission and reinforcement learning. The former captures the information about the subsurface dynamics of the process. The latter is a branch of machine learning that allows interpreting the received data in terms of quality. The combination of both is an original method for in situ and real-time quality monitoring. Acoustic data were collected during a real process using a commercial AM machine. The process parameters were selected to achieve three levels of quality in terms of porosity concentration while manufacturing a stainless steel 316L cuboid shape. Using our method, we demonstrated that each level of quality produced unique acoustic signatures during the build that were recognized by the classifier. The classification accuracy reached in this work proves that the proposed method has high potential to be used as in situ and real-time monitoring of AM quality.
Ultrasonic inspection was used to detect regions of recrystallization (RX) within a single crystal of Ni. RX can produce polycrystalline regions within single-crystal (SX) materials. Because RX regions act as initiator sites for failure by fatigue-crack growth in otherwise SX Ni-based superalloys, RX is an issue of direct concern for the service life of high-performance turbine blades. Detection and discrimination of RX regions in single-crystal materials are significant challenges for current nondestructive inspection technologies. The present study leverages the elastic anisotropy of single crystals, which produces acoustic anisotropy, to ultrasonically detect and characterize RX regions produced within single-crystal specimens. Single crystals of pure Ni were processed to create controlled regions of RX. These specimens were ultrasonically examined in an immersion tank using a high-resolution, polyvinylidene fluoride transducer to detect acoustic impedance changes across the boundaries between different crystals (i.e., grains) within the RX region. Data from time-of-flight and absolute peak amplitude measurements were used to create acoustic images that were compared against electron microscope images of the RX regions. The ultrasonic inspection technique described here successfully detected not only the locations of RX regions, but also the approximate sizes and shapes of the RX regions.