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Computational Acoustics in Oceanography Computational Acoustics in Timothy F. Duda Oceanography: The Research Roles Address: Applied Ocean Physics and of Sound Field Simulations Engineering Department Woods Hole Oceanographic Institution Simulation of underwater sound to understand processes is an indispensable tool MS 11 in modern oceanography. Woods Hole, Massachusetts 02543 USA Lobsters, icebergs, and submarines have little in common except that they produce sound, like many other marine occupants. Noisy occupants include animals (from Email: shrimp to whales), geophysical phenomena (from earthquakes to storms), and [email protected] man’s devices (from ships to energy turbines). Together, they create an underwater cacophony, now called the marine soundscape (Miksis-Olds et al., 2018). Interest- Julien Bonnel ingly, even silent things (such as a piece of muddy seabed or a parcel of warm water) Address: may impact the soundscape because they afect the sound propagation. Applied Ocean Physics and Engineering Department Although sound provides a great deal of information about the underwater envi- Woods Hole Oceanographic Institution ronment, unraveling and using the underwater clamor is not at all simple. In MS 11 particular, one needs to understand the sound propagation. An excellent tool for Woods Hole, Massachusetts 02543 understanding is computer modeling. USA Computing simulated sound felds to understand sensed underwater sound is now Email: a common practice in ocean science and engineering. Te value for naval defense [email protected] activities is perhaps obvious, but these simulations are fnding a growing number of research applications. Applications include inversion and inference, study of Emanuel Coelho marine fauna, system performance predictions, improved source localization, and Address: improved navigation. Applied Ocean Sciences 11006 Clara Barton Drive Accurate, detailed simulations of underwater sound can also motivate research Fairfax Station, Virginia 22039 expeditions by uncovering propagation behavior that may be difficult to tease USA out of sparse untargeted acoustic datasets but that are visible in computer simulations and then provable with targeted data collection. For our purposes, Email: simulations mean computed predictions of spatial sound fields (amplitude and emanuel.coelho@ phase) from specified sources or sound pressure time series predictions for appliedoceansciences.com known emitted waveforms. Kevin D. Heaney Sound Field Structure Address: Figure 1 shows an example computed feld of harmonic 1,100-Hz sound refract- Applied Ocean Sciences ing away from a layering anomaly in a shallow sea. Te highly structured feld 11006 Clara Barton Drive that results from sound undergoing dispersion and refraction in this deceptively Fairfax Station, Virginia 22039 simple environment is of typical complexity for underwater sound. Underwater USA sound computation uses many approaches, partly because the complexity does not yield to any single approach (Jensen et al., 2011). In this article, we explore Email: how the oceanographic community (as opposed to sonar system users) came to kevin.heaney@ adopt computed sound simulation as a primary tool, what research it enables, and appliedoceansciences.com to what research it is indispensable. 28 | Acoustics Today | Fall 2019 | volume 15, issue 3 ©2019 Acoustical Society of America. All rights reserved. https://doi.org/10.1121/AT.2019.15.3.28 in nonpolar seas, away from the ocean surface and bottom. At that time, mathematical ray tracing, computed using some clever approximations, was used to predict sound propaga- tion behavior. Te ray trajectories undulate vertically in the channel, with sound speed gradients controlling the refrac- tion. Te predictions were rudimentary by today’s standards but were simulations nonetheless. Simulated propagation has changed in the last 40 years to be dominated by computational simulations that allow full-wave physics, moving on from the ray model of wave propagation (geometric model) dating back to Newton and transforming how oceanography involving Figure 1. Depicted is a 15-km 3-D simulation of a 1,100-Hz harmonic acoustics is tackled. sound emitted from a source at 50 m depth (y = −150 m; x = 0 [*]) in a 95-m deep volume (z-axis upward). At y = 0 lies a tilted warm/cold Computations foster progress in at least two ways: stimulat- water boundary (subsurface front). Te Woods Hole Oceanographic ing discoveries and enabling better outcomes of data-based Institution three-dimensional (3-D) parabolic equation solver was research. One example of the importance of simulation is that used. To the lef (y > 0), a surface layer of warm water (fast sound the Ocean Acoustics Library website (oalib-acoustics.org), speed) extends deeper than it does at the right (y < 0), indicated by which was conceived by the US Ofce of Naval Research in the transparent surface. At the x = 15,000-m plane, the darker colors the 1990s and then developed and hosted for many years by Dr. (high intensity) indicate that the sound has refracted away from the Michael Porter, prominently features computational acoustic feature. Te bottom colors show a column average of sound energy in codes in its collection. Researchers from around the world use the water above, with intense refraction and focus evident. Te black those codes, and others, with regularity. lines are drawn for perspective. Stimulation of Reason by Observation or Simulation Major reasons that sound felds in water are so frequently The role of propagation simulation in wave-based remote numerically computed are that the sound speed in the gov- sensing is clear to most. An early application of this was erning wave equation has a four-dimensionally varying the use of seismic wave modeling to locate earthquakes nature with large spectral and dynamic ranges of variability, from recorded ground motion. This advanced, eventually and the boundary conditions are applied at a shaped sea- yielding joint solutions for earth structure, fault locations, foor. Te possible states of the sound feld are thus endless. shapes, and motions. Joint data/model analyses like this A few situations like water of uniform temperature over a may form the majority of computational acoustics appli- fat seafoor can be solved analytically with fair accuracy, but cations to ocean science, but something else can come to move forward, two-dimensional (2-D) and three-dimen- from computer simulations: pure discovery. The stimu- sional (3-D) numerical solutions have proven essential. lation of reason (theory) by observations is an ancient practice, often leading to discovery, and the interconnec- Simulation as a Tool tion between observational evidence and theory has been Faced with the vastness of the ocean and the richness of its subjected to some critical thinking (Bogen, 2017). This features and physical processes, oceanographers use what- includes considering the question of whether high-fidelity ever tools or methodologies are available. Tese tools can simulations of physical systems based on theories and rules be divided into three categories: observation, theory, and constitute observations in their own right, although the simulation. Many discoveries are made using a combina- predominant community answer is probably “no” at this tion of these. time. (Bogen states: “…scientists continue to find ways to produce data that can’t be called observational without In ocean acoustics, the third of these, simulation, argu- stretching the term to the point of vagueness.”) Neverthe- ably began with the discovery in the 1940s of the ocean less, we have found analysis of simulated ocean acoustic sound channel (sound fxing and ranging [SOFAR] chan- fields to stimulate many research directions as hypotheses; nel) that allows sound to efciently travel a long distance some are explored in the field. Fall 2019 | Acoustics Today | 29 Computational Acoustics in Oceanography Figure 2. Shallow-water modal dispersion. Top lef: an emitted sound waveform such as from a whale (central frequency of 50 Hz). Bottom lef: received signals at three ranges (5, 15, and 30 km; r) afer propagation in a shallow ocean of 100 m depth (about 3 wavelengths), wherein the sound interacts continually with the seabed and surface, efectively creating a waveguide. Use of a reference wave speed (c0 ) and reduced time (t − r/c0 ) places each signal initiation at zero. Te interference of slightly upgoing and downgoing waves makes modes. Each mode is a standing wave in the vertical (top right) and propagates horizontally as a cylindrical wave but with a frequency-dependent group speed (bottom right). Te scenario of variable group speed is called dispersion. As seen in the simulated waveforms, dispersion tends to lengthen the signal and to separate modes as range increases. Simulation Methods Normal Mode Method Tere are numerous simulation methods in use, and each Tis is based on the standard diferential equation math has strengths and weaknesses. Jensen et al. (2011) present method of the separation of variables, where the vertical and the methods, explain the theory behind them, and provide horizontal structures of the sound feld are given by diferent application examples. Ofen, the weaknesses stem from functions that are multiplied together to form the full solu- the short wavelength of underwater sound with respect to tion. Te vertical functions are the normal modes, which are ocean depth and width. For example, the 3-D solution for trapped in the ocean waveguide bounded by the surface and time-harmonic acoustics,
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