2aPA8 – Taming Tornadoes: Controlled Trapping and Rotation with Acoustic Vortices

Asier Marzo – amarzo@hotmail.com
Mihai Caleap
Bruce Drinkwater

Bristol University
Senate House, Tyndall Ave,
Bristol, United Kingdom

Popular version of paper 2aPA8, “Taming tornadoes: Controlling orbits inside acoustic vortex traps”
Presented Tuesday afternoon, May 24, 2016, 11:05 AM, Salon H
171st ASA Meeting Salt Lake City

Tractor beams are mysterious beams that have the ability to attract objects towards the source of the emission (Figure 1). These beams have attracted the attention of both scientists and sci-fi fans. For instance, it is quite an iconic device in Star Wars or Star Trek where it is used by big spaceships to trap and capture smaller objects.

Figure-01

Figure 1. A sonic tractor beam working on air.

In the scientific community, they have been studied theoretically for decades and in 2014, a tractor beam made with light was realized [1]. It used the energy of the photons bouncing on a microsphere to keep it trapped laterally and at the same time heated the back of the sphere with different light patterns to pull it towards the laser source. The sphere had a diameter of 50 micrometres, was made of glass and coated with gold.

A tractor beam made with light can only manipulate very small particles and made of specific materials. Making a tractor beam which uses mechanical waves (i.e. sound or ultrasound) would enable the trapping of a much wider range of particle sizes and allow almost any combination of particle and host fluid materials, for example drug delivery agents within the human body.

Recently, it has been proven experimentally that a Vortex beam can act as a tractor beam both in air [2] and in water [3]. A Vortex beam (such as a first order Bessel beam) is analogous to a tornado of sound which is hollow in the middle and spirals about a central axis, the particles get trapped in the calm eye of the tornado (Figure 2).

Figure-02 - Acoustic Vortices

Figure 2. Intensity iso-surface of an Acoustic Vortex. 54 ultrasonic speakers emitting at 40kHz arranged in a hemisphere (see [2] for fuller details) create an acoustic vortex that traps the particle in the middle.

The problem is, that only very small particles are stably trapped inside the vortex. As the particles get bigger, they start to spin and orbit until being ejected (Figure 3). As in a tornado, only the small particles remain within the vortex whereas the larger ones get ejected.

Figure-03

Figure 3. Particle behaviour depending on its size: a small particle is trapped (a), a middle particle orbits (b) and big particles gets ejected (c).

Here we show that, contrary to a tornado, we can change the direction of an acoustic vortex thousands of times per second. In our paper, we prove that by rapidly switching the direction of the acoustic vortex it is possible to produce stable trapping of particles of various sizes. Furthermore, by adjusting the proportion of time that each vortex direction is emitted, the spinning speed of the particle can be controlled (Figure 4).

Figure-04 - Acoustic Vortices

Figure 4. Taming the vortex: a) the vortex rotates all the time in the same direction and this rotation is transferred to the particle. b) the vortex switches direction and thus the angular momentum is completely or partially cancelled, providing rotational control.

The ability to levitate and controllably rotate inside acoustic vortices particles such as liquids, crystals or even living cells enables new possibilities and processes for a variety of disciplines.

References

  1. Shvedov, V., Davoyan, A. R., Hnatovsky, C., Engheta, N., & Krolikowski, W. (2014). A long-range polarization-controlled optical tractor beam. Nature Photonics, 8(11), 846-850.
  2. Marzo, A., Seah, S. A., Drinkwater, B. W., Sahoo, D. R., Long, B., & Subramanian, S. (2015). Holographic acoustic elements for manipulation of levitated objects. Nature communications, 6.
  3. Baresch, D., Thomas, J. L., & Marchiano, R. (2016). Observation of a single-beam gradient force acoustical trap for elastic particles: acoustical tweezers. Physical Review Letters, 116(2), 024301.

4aPA4 – Acoustic multi-pole source inversions of volcano infrasound

Keehoon Kim – kkim32@alaska.edu
University of Alaska Fairbanks
Wilson Infrasound Observatory, Alaska Volcano Observatory, Geophysical Institute
903 Koyukuk Drive, Fairbanks, Alaska 99775

David Fee – dfee1@alaska.edu
University of Alaska Fairbanks
Wilson Infrasound Observatory, Alaska Volcano Observatory, Geophysical Institute
903 Koyukuk Drive, Fairbanks, Alaska 99775

Akihiko Yokoo – yokoo@aso.vgs.kyoto-u.ac.jp
Kyoto University
Institute for Geothermal Sciences
Kumamoto, Japan

Jonathan M. Lees – jonathan.lees@unc.edu
University of North Carolina Chapel Hill
Department of Geological Sciences
104 South Road, Chapel Hill, North Carolina 27599

Mario Ruiz – mruiz@igepn.edu.ec
Escuela Politecnica Nacional
Instituto Geofisico
Quito, Ecuador

Popular version of paper 4aPA4, “Acoustic multipole source inversions of volcano infrasound”
Presented Thursday morning, May 21, 2015, at 9:30 AM in room Kings 1
169th ASA Meeting, Pittsburgh
Click here to read the abstract

Volcano infrasound
Volcanoes are outstanding natural sources of infrasound (low-frequency acoustic waves below 20 Hz). In the last few decades local infrasound networks have become an essential part of geophysical monitoring systems for volcanic activity. Unlike seismic networks dedicated to monitoring subsurface activity (c.f., magma or fluid transportation) infrasound monitoring facilitates detecting and characterizing eruption activity at the earth’s surface. Figure 1a shows Sakurajima Volcano in southern Japan and an infrasound network deployed in July 2013. Figure 1b is an image of a typical explosive eruption during the field experiment, which produces loud infrasound.

Sakurajima Volcano - Kim1Figure 1. a) A satellite image of Sakurajima Volcano, adapted from Kim and Lees (2014). Five stand-alone infrasound sensors were deployed around Showa Crater in July 2013, indicated by inverted triangles. b) An image of a typical explosive eruption observed during the field campaign.

Source of volcano infrasound
One of the major sources of volcano infrasound is a volume change in the atmosphere. Mass discharge from volcanic eruptions displaces the atmosphere near and around the vent and this displacement propagates into the atmosphere as acoustic waves. Infrasound signals can, therefore, represent a time history of the atmospheric volume change during eruptions. Volume flux inferred from infrasound data can be further converted into mass eruption rate with the density of the erupting mixture. Mass eruption rate is a critical parameter for forecasting ash-cloud dispersal during eruptions and consequently important for aviation safety. One of the problems associated with the volume flux estimation is that observed infrasound signals can be affected by propagation path effects between the source and receivers. Hence, these path effects must be appropriately accounted for and removed from the signals in order to obtain the accurate source parameter.

Infrasound propagation modeling
vent of Sakurajima Volcano - Kim2Figure 2. a) Sound pressure level in dB relative to the peak pressure at the source position. b) Variation of infrasound waveforms across the network caused by propagation path effects.

Figure 2 shows the results of numerical modeling of sound propagation from the vent of Sakurajima Volcano. The sound propagation is simulated by solving the acoustic wave equation using a Finite-Difference Time-Domain method taking into account volcanic topography. The synthetic wavefield is excited by a Gaussian-like source time function (with 1 Hz corner frequency) inserted at the center of Showa Crater (Figure 2a). Homogeneous atmosphere is assumed since atmospheric heterogeneity should have limited influence in this local range (< 7 km). The numerical modeling demonstrates that both amplitude and waveform of infrasound are significantly affected by the local topography. In Figure 2a, Sound Pressure Level (SPL) relative to the source amplitude is calculated at each computational grid node on the ground surface. The SPL map indicates an asymmetric radiation pattern of acoustic energy. Propagation paths to the northwest of Showa Crater are obstructed by the summit of the volcano (Minamidake), and as a result acoustic shadow zones are created northwest of the summit. Infrasound waveform also shows significant variation across the network. In Figure 2b, synthetic infrasound signals computed at the station positions (ARI – SVO) show bipolar pulses followed by oscillations in pressure while the pressure time history at the source location exhibits only a positive unipolar pulse. This result indicates that the oscillatory infrasound waveforms can be produced by not only source effects but also propagation path effects. Hence, this waveform distortion must be considered for source parameter inversion.

Volume flux estimates
Because wavelengths of volcano infrasound are usually longer than the dimension of source region, the acoustic sources are typically treated as a monopole, which is a point source approximation of volume expansion or contraction. Then, infrasound data represent the convolution of volume flux history at the source and the response of the propagation medium, called Green’s function. Volume flux history can be obtained by deconvolving the Green’s functions from the data. The Green’s functions can be obtained by two different ways: 3-D numerical modeling considering local topography (Case 1) and the analytic solution in a half-space neglecting volcanic topography (Case 2). Resultant volume histories for a selected infrasound event are compared in Figure 3. Case 1 results in gradually decreasing volume flux curve, but Case 2 shows pronounced oscillation in volume flux. In Case 2, propagation path effects are not appropriately removed from the data leading to misinterpretation of the source effect.

Summary
Proper Green’s function is critical for accurate volume flux history estimation. We obtained a reasonable volume flux history using the 3-D numerical Green’s function. In this study only simple source model (monopole) was considered for volcanic explosions. More general representation can be obtained by multipole expansion of acoustic sources. In 169th ASA Meeting presentation, we will further discuss source complexity of volcano infrasound, which requires the higher-order terms of the multipole series.

Kim3Figure 3. Volume flux history inferred from infrasound data. In Case 1, the Green’s function is computed by 3-D numerical modeling considering volcanic topography. In Case 2, the analytic solution of the wave equation in a half-space is used, neglecting the topography.

References

Kim, K. and J. M. Lees (2014). Local Volcano Infrasound and Source Localization Investigated by 3D Simulation. Seismological Research Letters, 85, 1177-1186

3aPA8 – Using arrays of air-filled resonators to reduce underwater man-made noise

Kevin M. Lee – klee@arlut.utexas.edu
Andrew R. McNeese – mcneese@arlut.utexas.edu
Applied Research Laboratories
The University of Texas at Austin

Preston S. Wilson – wilsonps@austin.utexas.edu
Mechanical Engineering Department and Applied Research Laboratories
The University of Texas at Austin

Mark S. Wochner – mark@adbmtech.com
AdBm Technologies

Popular version of paper 3aPA8
Presented Wednesday Morning, October 29, 2014
168th Meeting of the Acoustical Society of America, Indianapolis, Indiana
See also: Using arrays of air-filled resonators to attenuate low frequency underwater sound in POMA

Many marine and aquatic human activities generate underwater noise and can have potentially adverse effects on the underwater acoustical environment. For instance, loud sounds can affect the migratory or other behavioral patterns of marine mammals [1] and fish [2]. Additionally, if the noise is loud enough, it could potentially have physically damaging effects on these animals as well.

Examples of human activities that that can generate such noise are offshore wind farm installation and operation; bridge and dock construction near rivers, lakes, or ports; offshore seismic surveying for oil and gas exploration, as well as oil and gas production; and noise in busy commercial shipping lanes near environmentally sensitive areas, among others. All of these activities can generate noise over a broad range of frequencies, but the loudest components of the noise are typically at low frequencies, between 10 Hz and about 1000 Hz, and these frequencies overlap with the hearing ranges of many aquatic life forms. We seek to reduce the level of sound radiated by these noise sources to minimize their impact on the underwater environment where needed.

A traditional noise control approach is to place some type of barrier around the noise source. To be effective at low frequencies, the barrier would have to be significantly larger than the noise source itself and more dense than the water, making it impractical in most cases. In underwater noise abatement, curtains of small freely rising bubbles are often used in an attempt to reduce the noise; however, these bubbles are often ineffective at the low frequencies at which the loudest components of the noise occur. We developed a new type of underwater air-filled acoustic resonator that is very effective at attenuating underwater noise at low frequencies. The resonators consist of underwater inverted air-filled cavities with combinations of rigid and elastic wall members. They are intended to be fastened to a framework to form a stationary array surrounding an underwater noise source, such as the ones previously mentioned, or to protect a receiving area from outside noise.

The key idea behind our approach is that our air-filled resonator in water behaves like a mass on a spring, and hence it vibrates in response to an excitation. A good example of this occurring in the real world is when you blow over the top of an empty bottle and it makes a tone. The specific tone it makes is related to three things: the volume of the bottle, the length of its neck, and the size of the opening. In this case, a passing acoustic wave excites the resonator into a volumetric oscillation. The air inside the resonator acts as a spring and the water the air displaces when it is resonating acts as a mass. Like a mass on a spring, a resonator in water has a resonance frequency of oscillation, which is inversely proportional to its size and proportional to its depth in the water. At its resonance frequency, energy is removed from the passing sound wave and converted into heat through compression of the air inside the resonator, causing attenuation of the acoustic wave. A portion of the acoustic energy incident upon an array of resonators is also reflected back toward the sound source, which reduces the level of the acoustic wave that continues past the resonator array. The resonators are designed to reduce noise at a predetermined range of frequencies that is coincident with the loudest noise generated by any specific noise source.

air-filled resonators

Underwater photograph of a panel array of air-filled resonators attached to a framework. The individual resonators are about 8 cm across, 15 cm tall, and open on the bottom. The entire framework is about 250 cm wide and about 800 cm tall.

We investigated the acoustic properties of the resonators in a set of laboratory and field experiments. Lab measurements were made to determine the properties of individual resonators, such as their resonance frequencies and their effectiveness in damping out sound. These lab measurements were used to iterate the design of the resonators so they would have optimal acoustic performance at the desired noise frequencies. Initially, we targeted a resonance frequency of 100 Hz—the loudest components of the noise from activities like marine pile driving for offshore wind farm construction are between 100 Hz and 300 Hz. We then constructed a large number of resonators so we could make arrays like the panel shown in the photograph. Three or four such panels could be used to surround a noise source like an offshore wind turbine foundation or to protect an ecologically sensitive area.

The noise reduction efficacy of various resonator arrays were tested in a number of locations, including a large water tank at the University of Texas at Austin and an open water test facility also operated by the University of Texas in Lake Travis, a fresh water lake near Austin, TX. Results from the Lake Travis tests are shown in the graph of sound reduction versus frequency. We used two types of resonator—fully enclosed ones called encapsulated bubbles and open-ended ones (like the ones shown in the photograph). The number or total volume of resonators used in the array was also varied. Here, we express the resonator air volume as a percentage relative to the total volume of the array framework. Notice, our percentages are very small so we don’t need to use much air. For a fixed percentage of volume, the open-ended resonators provide up to 20 dB more noise reduction than the fully encapsulated resonators. The reader should note that noise reduction of 10 dB means the noise levels were reduced by a factor of three. A 30 dB reduction is equivalent to the noise be quieted by a factor of about 32. Because of the improved noise reduction performance of the open-ended resonators, we are currently testing this type of resonator at offshore wind farm installations in the North Sea, where government regulations require some type of noise abatement to be used to protect the underwater acoustic environment.

sound_reduction

Sound level reduction results from an open water experiment in a fresh water lake.

Various types of air-filled resonators were tested including fully encapsulated resonator and open-ended resonators like the ones shown in the photograph. Because a much total volume (expressed as a percentage here) is needed, the open-ended resonators are much more efficient at reducing underwater noise.

References:

[1] W. John Richardson, Charles R. Greene, Jr., Charles I. Malme, and Denis H. Thomson, Marine Mammals and Noise (Academic Press, San Diego, 1998).

[2] Arthur Popper and Anthony Hawkins (eds.), The Effects of Noise on Aquatic Life, Advances in Experimental Medicine and Biology, vol. 730, (Springer, 2012).