New Technical Area Picks
Every three months, we ask four Technical Committee (TC) chairs to select one article from the past nine months that they think is a representative of their TC’s published work over that time period. The newest round of Technical Area Picks have been selected, and will be free to read from March 1st to May 31st. Read on to find out which articles the chairs selected, along with a little insight from each chair about why they chose the article they did.
Education in Acoustics
“Mechanical-acoustical analogy: From laboratory to home during the COVID-19 pandemic,” by F. Arturo Machuca-Tzili, A. L. Padilla-Ortiz, and Daniel Martınez-Gutierrez
Education in Acoustics Editor Preston Wilson says, “For those learning acoustics for the first time, analogies are a great way to convey an existing understanding of a topic from a different field into understanding of a new topic in acoustics. This Education in Acoustics article describes the use of mechanical-acoustical analogies to teach the fundamentals of the simple harmonic oscillator in an undergraduate setting, using demonstrations that were conducted virtually during the COVID-19 era. The paper also describes the use of free smart-phone software that allows anyone with access to a smart phone conduct a simple demonstrative experiment with a Helmholtz resonator at home.”
Fig 9. Screenshot of the smartphone at the moment of measuring Helmholtz’s resonator frequency (air volume was 250 cm3 for this image).
Physical Acoustics
“Particle size effects on stable levitation positions in acoustic standing waves,” by Wolfgang Rueckner, Joseph Peidle, Allen Crockett, and Daniel Davis
TC Chair Christopher Kube says, “In this article, Rueckner et al. investigated the locations in which objects could be stably levitated in an acoustic standing wave. They provided experimental evidence that objects levitate at either a pressure antinode or node depending on the objects size relative to the wavelength of the acoustic field. This article is commendable as understanding size effects are critical to enable the many exciting levitation applications in the future.”
Fig. 2. Unprocessed schlieren image of a levitating 4 mm diameter Styrofoam ball centered on a pressure node.
Structural Acoustics and Vibration
“Analysis of geometric defects in square locally resonant phononic crystals: A comparative study of modeling approaches,” by L. Katch, M. Moghaddaszadeh, C. L. Willey, A. T. Juhl, M. Nouh, and A. P. Argüelles
TC Chair Christina Naify says, “This article presents a computationally efficient modeling approach to predict the dynamic response of a defect in an elastic lattice. Defects and geometric abnormalities are often present in structures manufactured by additive manufacturing. Models with varying ranges of fidelity are compared for varying degrees of deviation from the pristine designed geometry. In general, this article touches on many hot topics in structural acoustics and vibrations including the effects of defects, additive manufacturing, and metamaterials.”
Fig. 1. Details of the unit cell
Underwater Acoustics
“Evaluating machine learning architectures for sound event detection for signals with variable signal-to-noise-ratios in the Beaufort Sea,” by Malek Ibrahim, Jason D. Sagers, Megan S. Ballard, Minh Le, and Vasilis Koutsomitopoulos
TC Chair Jie Yang says, “This paper was chosen as a Technical Area Pick because it explores the challenging polyphonic sound event detection problem using machine learning architectures. An established architecture from the image classification domain composed of >20M parameters is compared to lightweight model (1.2 M parameters) specifically designed for polyphonic sound event detection. The candidate architectures were investigated and evaluated on nine classes of signals broadcast from moored sources that were recorded over the course of a yearlong experiment. These signals represent a high degree of variability with respect to time-frequency characteristics, changes in signal-to-noise ratio, and class imbalances providing an excellent data set to evaluate model performance.”
Fig. 5. Comparison of results from window-level and frame-level architectures for three classes on a 1-min data sample from session 1472 recorded on 21 June 2017.
Congratulations to all the authors whose work has been highlighted by the TC chairs and Editors!
