The formation of bubbles from breaking waves has a significant effect on air-sea gas transfer and aerosol production. Detailed data in situ about the bubble populations are required to understand these processes. However, these data are difficult to acquire because bubble populations are complex, spatially inhomogeneous, and short lived. This paper describes the design and development of a novel high-resolution underwater optical instrument for imaging oceanic bubbles at the sea. The instrument was successfully deployed in 2013 as part of the HiWINGS campaign in the North Atlantic Ocean. It contains a high-resolution machine vision camera, strobe flash unit to create a light sheet, and single board computer to control system operation. The instrument is shown to successfully detect bubbles of radii in the range 20-10 000 µm.
11Accurate, in situ measurements of oceanic bubble size distributions beneath breaking waves 12 are needed for a better understanding of air-sea gas transfer and aerosol production processes.
13To achieve this goal, a novel high-resolution optical instrument for imaging oceanic bubbles 14 was designed and built in 2013 for the HiWINGS campaign in the North Atlantic Ocean. The 15 instrument is able to operate autonomously and can continuously capture high resolution 16 images at 15 frames/sec over an 8 hour deployment. The large number of images means that it 17 is essential to use an automated processing algorithm to process these images. This paper 18 describes an automated algorithm for processing oceanic images based on a robust feature 19 extraction technique. The main advantages of this robust algorithm are it is significantly less 20 sensitive to the noise and insusceptible to the background changes in illumination, can extract 21 circular bubbles as small as 1 pixel (approximately 20 µm) in radius accurately, has low 22 computing time (approximately 5 seconds per image), and is simple to implement. The23
Abstract-Measurements of the frequency dependence of ultrasonic attenuation can be used as the basis for the estimation of particle size distributions (PSDs) in solid-in-liquid suspensions. The method requires matching the attenuation simulated by a candidate PSD in combination with a wave propagation model to the measured function in a fitting procedure. Uncertainty in the type of candidate PSD, whether based on fractional volume or fractional number of the dispersed particles, can cause errors in the overall estimation process, particularly for the median particle size. These uncertainties are investigated in the first part of this paper. The second part deals with uncertainties associated with the values for the physical properties of the suspended particles, seven of which are required in the simulation stage. It is shown that the particle sizing exercise is relatively insensitive to all of the physical properties except density, for which values are necessary to an accuracy commensurable with that required for the two principal parameters associated with the PSD-median size and standard deviation. The discussion is limited to small (less than 1-μm) silica particles dispersed in water. The results will have more general application.
Estimates of particle size distributions (PSDs) in solid-in-liquid suspensions can be made on the basis of measurements of ultrasonic wave attenuation combined with a mathematical propagation model, which typically requires seven physical parameters to describe each phase of the mixture. The estimation process is insensitive to all of these except the density of the solid particles, which may not be known or difficult to measure. This paper proposes that an unknown density value is incorporated into the sizing computation as a free variable. It is shown that this leads to an accurate estimate of PSD, as well as the unknown density.
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