Information geometry analysis example for absolute and relative transmission loss in a shallow ocean.

The model manifold, an information geometry tool, is a geometric representation of a model that can quantify the expected information content of modeling parameters. For a normal-mode sound propagation model in a shallow ocean environment, transmission loss (TL) is calculated for a vertical line array and model manifolds are constructed for both absolute and relative TL. For the example presented in this paper, relative TL yields more compact model manifolds with seabed environments that are less statistically distinguishable than manifolds of absolute TL. This example illustrates how model manifolds can be used to improve experimental design for inverse problems.

Inference of source signatures of merchant ships in shallow ocean environmentsa).

An ocean acoustics experiment in 2017 near a shipping lane on the New England continental shelf in about 75 m of water provided an opportunity to evaluate a methodology to extract source signatures of merchant ships in a bottom-limited environment. The data of interest are the received acoustic levels during approximately 20 min time intervals centered at the closest position of approach (CPA) time for each channel on two 16-element vertical line arrays. At the CPA ranges, the received levels exhibit a frequency-dependent peak and null structure, which possesses information about the geophysical properties of the seabed, such as the porosity and sediment thickness, and the characterization of the source, such as an effective source depth. The modeled seabed is represented by two sediment layers, parameterized with the viscous grain shearing (VGS) model, which satisfies causality, over a fixed deep layered structure. Inferred estimates of the implicit source levels require averaging an error function over the full 20 min time intervals. Within the 200-700 Hz band, the Wales-Heitmeyer model captures the inferred frequency dependence of the source levels.

Mentored student research: A case study evaluation of benefits and best practices.

Efforts to mentor undergraduates in research require time, energy, and resources but can yield significant benefits. A review of education research on undergraduate research is presented followed by a case study of how technical and educational principles from the literature have been implemented and practiced in a new underwater acoustics lab. This case study involves the students who have joined this lab over its first three years. The results highlight the importance of several key factors that mentors can implement to improve their students' research experience. In order to meet the steep learning curve that new students face, faculty mentors should establish a culture of research (i.e., well established norms, expectations, and practices associated with being a part of a research group) through clear expectations, open communication, and student-led peer mentorship supported by carefully selected or designed resources (i.e., scaffolding). This paper seeks to share these education research resources with the acoustics community while providing a case study for review as a specific application of these key principles into an acoustics laboratory setting.

Sounds to Astound: An acoustics outreach show.

Sounds to Astound is an acoustics demonstration show, produced for the community twice yearly by the Brigham Young University Student Chapter of the Acoustical Society of America. The free, interactive demonstration show explores the science of sound for a target audience of fifth- to eighth-grade students. Introductory acoustics concepts, such as longitudinal wave motion, wave properties, propagation effects, and standing waves, are taught with live demonstrations, animations, and videos. The goal of this paper is to inspire and encourage readers in their outreach efforts by describing the purposes of Sounds to Astound and technical details of several entertaining and educational demonstrations. Lessons learned from a decade of these student-produced shows serve as an aid for future efforts and highlight the benefits of outreach efforts, particularly for the students involved.

Magnetised quark nuggets in the atmosphere.

A search for magnetised quark nuggets (MQN) is reported using acoustic signals from hydrophones placed in the Great Salt Lake (GSL) in the USA. No events satisfying the expected signature were seen. This observation allows limits to be set on the flux of MQNs penetrating the Earth's atmosphere and depositing energy in the GSL. The expected signature of the events was ​derived from pressure pulses caused by high-explosive cords between the lake surface and bottom at various locations in the GSL. The limits obtained from this search are compared with those obtained from previous searches and are compared to models for the formation of MQNs.

Seabed classification from merchant ship-radiated noise using a physics-based ensemble of deep learning algorithms.

Merchant ship-radiated noise, recorded on a single receiver in the 360-1100 Hz frequency band over 20 min, is employed for seabed classification using an ensemble of deep learning (DL) algorithms. Five different convolutional neural network architectures and one residual neural network are trained on synthetic data generated using 34 seabed types, which span from soft-muddy to hard-sandy environments. The accuracy of all of the networks using fivefold cross-validation was above 97%. Furthermore, the impact of the sound speed and water depth mismatch on the predictions is evaluated using five simulated test cases, where the deeper and more complex architectures proved to be more robust against this variability. In addition, to assess the generalizability performance of the ensemble DL, the networks were tested on data measured on three vertical line arrays in the Seabed Characterization Experiment in 2017, where 94% of the predictions indicated that mud over sand environments inferred in previous geoacoustic inversions for the same area were the most likely sediments. This work presents evidence that the ensemble of DL algorithms has learned how the signature of the sediments is encoded in the ship-radiated noise, providing a unified classification result when tested on data collected at-sea.

Influence of seabed on very low frequency sound recorded during passage of merchant ships on the New England shelf.

An examination of the received spectrogram levels of about twenty merchant ship recordings on two vertical line arrays deployed on the New England continental shelf during the Seabed Characterization Experiment 2017 has identified an acoustic feature that can be attributed to the group velocities of modes 1 and 2 being equal at a frequency f=F. The observation of such a feature is a result of ßnm(2πF)=∞, where ßnm is the waveguide invariant for modes n and m. For the New England Mudpatch, the average value of F is about 24.5 Hz. An effective seabed model is inferred from a feature inversion method that has a deep sediment layer which lies between 190 m and 290 m beneath the seafloor with sound speeds on the order of 1810 m/s. This effective sediment model appears to be consistent with a previous seismic survey on the New England shelf that identified a deep low speed layer about 250 m beneath the water sediment interface.

Seabed type and source parameters predictions using ship spectrograms in convolutional neural networks.

Broadband spectrograms from surface ships are employed in convolutional neural networks (CNNs) to predict the seabed type, ship speed, and closest point of approach (CPA) range. Three CNN architectures of differing size and depth are trained on different representations of the spectrograms. Multitask learning is employed; the seabed type prediction comes from classification, and the ship speed and CPA range are estimated via regression. Due to the lack of labeled field data, the CNNs are trained on synthetic data generated using measured sound speed profiles, four seabed types, and a random distribution of source parameters. Additional synthetic datasets are used to evaluate the ability of the trained CNNs to interpolate and extrapolate source parameters. The trained models are then applied to a measured data sample from the 2017 Seabed Characterization Experiment (SBCEX 2017). While the largest network provides slightly more accurate predictions on tests with synthetic data, the smallest network generalized better to the measured data sample. With regard to the input data type, complex pressure spectral values gave the most accurate and consistent results for the ship speed and CPA predictions with the smallest network, whereas using absolute values of the pressure provided more accurate results compared to the expected seabed types.

Validating deep learning seabed classification via acoustic similarity.

While seabed characterization methods have often focused on estimating individual sediment parameters, deep learning suggests a class-based approach focusing on the overall acoustic effect. A deep learning classifier-trained on 1D synthetic waveforms from underwater explosive sources-can distinguish 13 seabed classes. These classes are distinct according to a proposed metric of acoustic similarity. When tested on seabeds not used in training, the classifier obtains 96% accuracy for matching such a seabed to one of the top-3 most acoustically similar classes from the 13 training seabeds. This approach quantifies the performance of a seabed classifier in the face of real seabed variability.

Bandwidth extension of intensity-based sound power estimates.

The traditional method for intensity-based sound power estimates often used in engineering applications is limited in bandwidth by microphone phase mismatch at low frequencies and by microphone spacing at high frequencies. To overcome these limitations, the Phase and Amplitude Gradient Estimator (PAGE) method [Gee, Neilsen, Sommerfeldt, Akamine, and Okamoto, J. Acoust. Soc. Am. 141(4), EL357-EL362 (2017)] is applied to sound power for a reference sound source, a blender, and a vacuum cleaner. Sound power measurements taken according to ISO 3741:2010 (2010) are compared against traditional- and PAGE-processed intensity-based sound power estimates measured according to ANSI S12.12-1992 (R2017). While the traditional method underestimates the sound power at the spatial Nyquist frequency by 7-10 dB, the PAGE-based sound power is accurate up to the spatial Nyquist frequency, and above when phase unwrapping is successful.

Seabed and range estimation of impulsive time series using a convolutional neural network.

In ocean acoustics, many types of optimizations have been employed to locate acoustic sources and estimate the properties of the seabed. How these tasks can take advantage of recent advances in deep learning remains as open questions, especially due to the lack of labeled field data. In this work, a Convolutional Neural Network (CNN) is used to find seabed type and source range simultaneously from 1 s pressure time series from impulsive sounds. Simulated data are used to train the CNN before application to signals from a single hydrophone signal during the 2017 Seabed Characterization Experiment. The training data includes four seabeds representing deep mud, mud over sand, sandy silt, and sand, and a wide range of source parameters. When applied to measured data, the trained CNN predicts expected seabed types and obtains ranges within 0.5 km when the source-receiver range is greater than 5 km, showing the potential for such algorithms to address these problems.

Characterizing distinct components of tactical aircraft noise sources.

Noise from a tactical aircraft can impact operations due to concerns regarding military personnel noise exposure and community annoyance and disturbance. The efficacy of mission planning can increase when the distinct, complex acoustic source mechanisms creating the noise are better understood. For each type of noise, equivalent acoustic source distributions are obtained from a tied-down F-35B operating at various engine conditions using the hybrid method for acoustic source imaging of Padois, Gauthier, and Berry [J. Sound Vib. 333, 6858-6868 (2014)]. The source distributions for the distinct noise types are obtained using different sections of a 71 element, ground-based linear array. Using a subarray close to the nozzle exit plane, source distributions are obtained for fine-scale turbulent mixing noise and broadband shock-associated noise, although grating lobes complicate interpretations at higher frequencies. Results for a subarray spanning the maximum sound region show that the multiple frequency peaks in tactical aircraft noise appear to originate from overlapping source regions. The observation of overlapping spatial extent of competing noise sources is supported by the coherence properties of the source distributions for the different subarrays.

Data-educed broadband equivalent acoustic source model for supersonic jet noise.

A broadband equivalent acoustic source distribution can be used to model the sound field near a high-speed jet. Such models must account for the spatiospectral variation of the sound levels. This work presents a technique for obtaining such a model using a spectral decomposition method associated with large and fine-scale turbulent mixing noise to create broadband equivalent source distributions for each noise type. The large-scale turbulent mixing noise is represented by frequency-dependent wavepackets, while the fine-scale turbulent mixing noise is modeled as a frequency-dependent incoherent, extended source distribution. This technique is applied to acoustical measurements from an ideally expanded, unheated Mach 1.8 jet. The wavepackets model the sound field levels in the maximum radiation region, but the second incoherent source distribution is required to obtain the levels at the other locations. The combination of the incoherent source distribution and the wavepacket provides a broadband, equivalent acoustic source representation that adequately models the sound field for Strouhal numbers between 0.04 and 0.25. At higher Strouhal numbers, better agreement is obtained when accounting for a frequency-dependent shift in the apparent acoustic source region. This frequency-dependent source region is more important closer to the jet than in the far field.

Source characterization of full-scale tactical jet noise from phased-array measurements.

Application of phased-array algorithms to acoustic measurements in the vicinity of a high-performance military aircraft yields equivalent source reconstructions over a range of engine conditions. Beamforming techniques for aeroacoustics applications have undergone significant advances over the past decade to account for difficulties that arise when traditional methods are applied to distributed sources such as those found in jet noise. The hybrid method, an inverse method approached via beamforming, is applied to jet noise measured along a 50 element, 30 m linear array to obtain equivalent source distributions. The source distribution extent decreases with increasing frequency or with a decrease in engine condition. A source coherence analysis along the axial dimension of the jet plume reveals that the source coherence lengths scale inversely with increasing engine condition. In addition, a method for extending the array bandwidth to frequencies beyond the spatial Nyquist frequency limit is also implemented. A directivity analysis of the beamforming results reveals that sources near the nozzle radiate to the sideline from a relatively stationary point irrespective of frequency, while the noise source origin of downstream radiating noise varies significantly with frequency.

University student musician noise-dosage study measuring both ensemble and full-day noise exposure.

A risk factor shared by all musicians is a potential for noise-induced hearing loss. A study was conducted to explore what factors determine noise dosage during musical events experienced by college student musicians. First, noise exposure during specific activities was explored, including during ensemble rehearsal and personal practice. Next, full-day noise exposure was investigated by measuring levels experienced by student musicians during a typical daily routine. Factors such as instrument played, type of activity, location within ensemble, and room environment were related to noise dosage. Disparities in results using different standards to calculate noise dosage were also explored. Risk of noise overexposure was found to be greater in some instrument classes, such as wind instruments, than in others, such as string instruments, and can yield vastly different results depending on the metric used for noise dosage calculation.

Bandwidth extension of narrowband-signal intensity calculation using additive, low-level broadband noise.

Calculation of acoustic intensity using the phase and amplitude gradient estimator (PAGE) method has been shown to increase the effective upper frequency limit beyond the traditional p-p method when the source of interest is broadband in frequency [Torrie, Whiting, Gee, Neilsen, and Sommerfeldt, Proc. Mtgs. Acoust. 23, 030005 (2015)]. PAGE processing calculates intensity for narrowband sources without bias error up to the spatial Nyquist frequency [Succo, Sommerfeldt, Gee, and Neilsen, Proc. Mtgs. Acoust. 30, 030015 (2018)]. The present work demonstrates that for narrowband sources with frequency content above the spatial Nyquist frequency, additive low-level broadband noise can improve intensity calculations. To be effective, the angular separation between the source and additive noise source should be less than 30°, while using phase unwrapping with a smaller angular separation will increase the usable bandwidth. The upper frequency limit for the bandwidth extension depends on angular separation, sound speed, and probe microphone spacing. Assuming the signal-to-additive-noise ratio (SNRa) is larger than 10 dB, the maximum level and angular bias errors incurred by the additive broadband noise beneath the frequency limit-or up until probe scattering effects must be taken into account-are less than 0.5 dB and 2.5°, respectively. Smaller angular separation yields smaller bias errors.

The effects of contaminating noise on the calculation of active acoustic intensity for pressure gradient methods.

Bias errors for two-dimensional active acoustic intensity using multi-microphone probes have been previously calculated for both the traditional cross-spectral and the Phase and Amplitude Gradient Estimator (PAGE) methods [Whiting, Lawrence, Gee, Neilsen, and Sommerfeldt, J. Acoust. Soc. Am. 142, 2208-2218 (2017)]. Here, these calculations are expanded to include errors due to contaminating noise, as well as probe orientation. The noise can either be uncorrelated at each microphone location or self-correlated; the self-correlated noise is modeled as a plane-wave with a varying angle of incidence. The intensity errors in both magnitude and direction are dependent on the signal-to-noise ratio (SNR), frequency, source properties, incidence angles, probe configuration, and processing method. The PAGE method is generally found to give more accurate results, especially in direction; however, uncorrelated noise with a low SNR (below 10-15 dB) and low frequency (wavelengths more than 1/4 the microphone spacing) can yield larger errors in magnitude than the traditional method-though a correction for this is possible. Additionally, contaminating noise does not necessarily impact the possibility of using the PAGE method for broadband signals beyond a probe's spatial Nyquist frequency.

Highly directional pressure sensing using the phase gradient.

Many methods of two-microphone directional sensing have limited bandwidth. For active intensity, finite-difference error can be removed by using the phase and amplitude gradient estimator method. Using similar principles, a directional pressure sensor based on the phase gradient is developed that is accurate up to the spatial Nyquist frequency, and beyond if phase unwrapping is applied. A highly directional frequency-independent array response of arbitrary order can be achieved with two microphones. The method is compared against beamforming and traditional gradient sensing for single and multiple sources and is found to have improved localization capabilities and increased bandwidth.

Partial-field decomposition analysis of full-scale supersonic jet noise using optimized-location virtual references.

Supersonic jet noise reduction efforts benefit from targeted source feature extraction and high-resolution acoustic imaging. Another useful tool for feature extraction is partial field decomposition of sources into independent contributors. Since such decomposition processes are nonunique, care must be taken in the physical interpretation of decomposed partially coherent aeroacoustic fields. The optimized-location virtual reference method (OLVR) is a partial field decomposition designed to extract physically meaningful source and field information through the strategic placement of virtual references within a reconstructed field. The OLVR method is applied here to obtain spatially distinct and ordered partial sources at multiple frequencies of a full-scale, high-performance supersonic jet engine operating at 100% engine power. Partial sources are shown to mimic behaviors of the total source distributions including monotonic growth and decay. Because of finite spatial coherence, multiple partial sources are used to reproduce far-field radiation away from the main lobe, and the number of required sources increases with increasing frequency. An analytical multiwavepacket model is fitted to the partial sources to demonstrate how OLVR partial fields can be leveraged to produce reduced-order models.

Broadband shock-associated noise from a high-performance military aircraft.

Broadband shock-associated noise (BBSAN) is a prominent noise component from nonideally expanded jets in the forward and sideline directions. BBSAN from laboratory-scale jets has been studied extensively, and spatial trends in BBSAN spectral peak characteristics-frequency, level, and width-have been established. These laboratory-scale trends are compared to those for BBSAN from a tied-down F-35B operated at four engine conditions. While the peak frequency varies as expected, both spatially and across engine condition, the peak level and width do not, pointing to the need for additional research into BBSAN for high-performance military aircraft.