A direct comparison of the droplet size and number measurements using in-line holography and shadow imaging is presented in three dynamically evolving laboratory scale experiments. The two experimental techniques and image processing algorithms used to measure droplet number and radii are described in detail. Droplet radii as low as $$r = 14$$ r = 14 µm are measured using in-line holography and $$r = 50$$ r = 50 µm using shadow imaging. The droplet radius measurement error is estimated using a calibration target (reticle) and it was found that the holographic technique is able to measure droplet radii more accurately than shadow imaging for droplets with $$r \le 625$$ r ≤ 625 µm. Using the measurements of droplet number and size we quantitatively cross-validate and assess the accuracy of the two measurement techniques. The droplet size distributions, N(r), are measured in all three experiments and are found to agree well between the two measurement techniques. In one of the laboratory experiments, simultaneous measurements of droplets ($$r \ge 14$$ r ≥ 14 µm, using holography) and dry aerosols ($$0.07 \lessapprox r \lessapprox 2$$ 0.07 ⪅ r ⪅ 2 µm, using an scanning mobility particle sizer and $$0.15 \lessapprox r \lessapprox 5$$ 0.15 ⪅ r ⪅ 5 µm using an optical particle sizer) are reported, one of the first such comparison to the best of our knowledge. The total number and volume of droplets is found to agree well between both techniques in the three experiments. We demonstrate that a relatively simple shadow imaging technique can be just as reliable when compared to a more sophisticated holographic measurement technique over their common droplet radius measurement range. The agreement in results is shown to be valid over a large range of droplet concentrations, which include experiments with relatively sparse droplet concentrations as low as 0.02 droplets per image. Advantages and disadvantages for the two techniques are discussed in the context of our results. The main advantages to in-line holography are the greater accuracy in droplet radius measurement, greater spatial resolution, larger depth of field, and the high repetition rate and short pulse duration of the laser light source. In comparison, the main advantages to shadow imaging are the simpler experimental setup, image processing algorithm, and fewer computer resources necessary for image processing. Droplet statistics like number and size are found to be very reliable between the two methods for large range of droplet densities, $${\mathcal {P}}_{r>50}$$ P r > 50 , ranging from $$10^{-4} \le {\mathcal {P}}_{r>50} \le 10^{-1}$$ 10 - 4 ≤ P r > 50 ≤ 10 - 1 cm$$^{-3}$$ - 3 , when the two techniques are implemented as shown in this paper.
We experimentally investigate the depth distributions and dynamics of air bubbles entrained by breaking waves in a wind‐wave channel over a range of breaking wave conditions using high‐resolution imaging and three‐dimensional bubble tracking. Below the wave troughs, the bubble concentration decays exponentially with depth. Patches of entrained bubbles are identified for each breaking wave, and statistics describing the horizontal and vertical transport are presented. Aggregating our results, we find a stream‐wise transport faster than the associated Stokes drift and modified Stokes drift for buoyant particles, which is an effect not accounted for in current models of bubble transport. This enhancement in transport is attributed to the flow field induced by the breaking waves and is relevant for the transport of bubbles, oil droplets, and microplastics at the ocean surface.
Laboratory measurements of droplet size, velocity, and accelerations generated by mechanically and wind‐forced water breaking waves are reported. The wind free stream velocity is up to 12 m/s, leading to wave slopes from 0.15 to 0.35 at a fetch of 23 m. The ratio of wind free stream and wave phase speed ranges from 5.9 to 11.1, depending on the mechanical wave frequency. The droplet size distribution in all configurations can be represented by two power laws, N(d) ∝ d−1 for drops from 30 to 600 μm and N(d) ∝ d−4 above 600 μm. The horizontal and vertical droplet velocities appear correlated, with drops with slower horizontal speed more likely to move upward. The velocity and acceleration distributions are found to be asymmetric, with the velocity probability density functions (PDFs) being described by a normal‐inverse‐Gaussian distribution. The horizontal acceleration PDF are found to follow a shape close to the one predicted for small particles in homogeneous and isotropic turbulence, while the vertical distribution follows an asymmetric normal shape, showing that both acceleration components are controlled by different physical processes.
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