SOUND PROPAGATION AND SCATTERING IN BUBBLY LIQUIDS

In the ocean, natural and artificial processes generate clouds of bubbles which scatter and attenuate sound. Measurements have shown that at the individual bubble resonance frequency, sound propagation in this medium is highly attenuated and dispersive. Theory to explain this behavior exists in the literature, and is adequate away from resonance. However, due to excessive attenuation near resonance, little experimental data exists for comparison. An impedance tube was developed specifically for exploring this regime. Using the instrument, unique phase speed and attenuation measurements were made for void fractions ranging from 6.2 × 10^−5 to 2.7 × 10^−3 and bubble sizes centered around 0.62 mm in radius. Improved measurement speed, accuracy and precision is possible with the new instrument, and both instantaneous and time-averaged measurements were obtained. Behavior at resonance was observed to be sensitive to the bubble population statistics and agreed with existing theory, within the uncertainty of the bubble population parameters. Scattering from acoustically compact bubble clouds can be predicted from classical scattering theory by using an effective medium description of the bubbly fluid interior. Experimental verification was previously obtained up to the lowest resonance frequency. A novel bubble production technique has been employed to obtain unique scattering measurements with a bubbly-liquid-filled latex tube in a large indoor tank. The effective scattering model described these measurements up to three times the lowest resonance frequency of the structure.

Structure Sharing and Parallelization in a GB Parser

By utilizing structure sharing among its parse trees, a GB parser can increase its efficiency dramatically. Using a GB parser which has as its phrase structure recovery component an implementation of Tomita's algorithm (as described in [Tom86]), we investigate how a GB parser can preserve the structure sharing output by Tomita's algorithm. In this report, we discuss the implications of using Tomita's algorithm in GB parsing, and we give some details of the structuresharing parser currently under construction. We also discuss a method of parallelizing a GB parser, and relate it to the existing literature on parallel GB parsing. Our approach to preserving sharing within a shared-packed forest is applicable not only to GB parsing, but anytime we want to preserve structure sharing in a parse forest in the presence of features.