Consistency in statistical moments as a test for bubble cloud clustering

Frequency dependent measurements of attenuation and/or sound speed through clouds of gas bubbles in liquids are often inverted to find the bubble size distribution and the void fraction of gas. The inversions are often done using an effective medium theory as a forward model under the assumption that the bubble positions are Poisson distributed (i.e., statistically independent). Under circumstances in which single scattering does not adequately describe the pressure field, the assumption of independence in position can yield large errors when clustering is present, leading to errors in the inverted bubble size distribution. It is difficult, however, to determine the existence of clustering in bubble clouds without the use of specialized acoustic or optical imaging equipment. A method is described here in which the existence of bubble clustering can be identified by examining the consistency between the first two statistical moments of multiple frequency acoustic measurements

An Estimate of the Gas Transfer Rate from Oceanic Bubbles Derived from Multibeam Sonar Observations of a Ship Wake

Measurements of gas transfer rates from bubbles have been made in the laboratory, but these are difficult to extrapolate to oceanic bubbles where populations of surfactants and particulate matter that inhibit gas transfer are different. Measurements at sea are complicated by unknown bubble creation rates that make it difficult to uniquely identify and observe the evolution of individual bubble clouds. One method that eliminates these difficulties is to measure bubbles in a ship wake where bubble creation at any given location is confined to the duration of the passing ship. This method assumes that the mechanisms slowing the gas dissolution of naturally created bubbles act in a similar manner to slow the dissolution of bubbles in a ship wake. A measurement of the gas transfer rate for oceanic bubbles using this method is reported here. A high-frequency upward-looking multibeam echosounder was used to measure the spatial distribution of bubbles in the wake of a twin screw 61-m research vessel. Hydrodynamic forcing functions are extracted from the multibeam data and used in a bubble cloud evolution model in which the gas transfer rate is treated as a free parameter. The output of model runs corresponding to different gas transfer rates is compared to the time-dependent wake depth observed in the data. Results indicating agreement between the model and the data show that the gas transfer rate must be approximately 15 times less then it would be for surfactant-free bubbles in order to explain the bubble persistence in the wake

Algebraic structure of stochastic expansions and efficient simulation

We investigate the algebraic structure underlying the stochastic Taylor solution expansion for stochastic differential systems.Our motivation is to construct efficient integrators. These are approximations that generate strong numerical integration schemes that are more accurate than the corresponding stochastic Taylor approximation, independent of the governing vector fields and to all orders. The sinhlog integrator introduced by Malham & Wiese (2009) is one example. Herein we: show that the natural context to study stochastic integrators and their properties is the convolution shuffle algebra of endomorphisms; establish a new whole class of efficient integrators; and then prove that, within this class, the sinhlog integrator generates the optimal efficient stochastic integrator at all orders.Comment: 19 page

A Visual Environment for Real-Time Image Processing in Hardware (VERTIPH)

Real-time video processing is an image-processing application that is ideally suited to implementation on FPGAs. We discuss the strengths and weaknesses of a number of existing languages and hardware compilers that have been developed for specifying image processing algorithms on FPGAs. We propose VERTIPH, a new multiple-view visual language that avoids the weaknesses we identify. A VERTIPH design incorporates three different views, each tailored to a different aspect of the image processing system under development; an overall architectural view, a computational view, and a resource and scheduling view

Scattering statistics of rock outcrops: Model-data comparisons and Bayesian inference using mixture distributions

The probability density function of the acoustic field amplitude scattered by the seafloor was measured in a rocky environment off the coast of Norway using a synthetic aperture sonar system, and is reported here in terms of the probability of false alarm. Interpretation of the measurements focused on finding appropriate class of statistical models (single versus two-component mixture models), and on appropriate models within these two classes. It was found that two-component mixture models performed better than single models. The two mixture models that performed the best (and had a basis in the physics of scattering) were a mixture between two K distributions, and a mixture between a Rayleigh and generalized Pareto distribution. Bayes' theorem was used to estimate the probability density function of the mixture model parameters. It was found that the K-K mixture exhibits significant correlation between its parameters. The mixture between the Rayleigh and generalized Pareto distributions also had significant parameter correlation, but also contained multiple modes. We conclude that the mixture between two K distributions is the most applicable to this dataset.Comment: 15 pages, 7 figures, Accepted to the Journal of the Acoustical Society of Americ

A Solidification Phenomenon in Random Packings

We prove that uniformly random packings of copies of a certain simply connected figure in the plane exhibit global connectedness at all sufficiently high densities, but not at low densities