ABSTRACT
This work compares four different image processing algorithms for the analysis of image data obtained during the Multiscale Boiling Experiment of ESA, executed on-board the International Space Station. Two separate experimental campaigns have been performed in 2019 and 2020, aiming to investigate boiling phenomena in microgravity, with and without the presence of shear flow and electric field. A heated substrate, at the bottom of the test cell, creates a temperature profile across the liquid bulk above it. A laser beam hits a designated microcavity at the middle of the substrate, to initiate nucleation of a single, isolated bubble. In the presence of shear flow or electric field forces, the bubble slides or detaches respectively, leaving the cavity free for the nucleation and growth of a new bubble. The growth of such a bubble within the prescribed temperature profile is studied for varying experimental conditions (i.e. pressure, heat flux, subcooling temperature) by capturing high speed, black and white video images. The presence of light reflections at random locations around the bubble contour vary with bubble size and population. This, combined with the refraction induced optical distortion of vertical image dimension close to the heater, make the accurate detection of bubbles contour a real challenge. Four research teams, namely the University of Pisa (UNIPI), the Institute of Fluid Mechanics of Toulouse (IMFT), the joint group of Aix Marseille University (AMU) and Kutateladze Institute of Thermophysics (IT), and the joined group of Aristotle University of Thessaloniki (AUTH), Technical University of Darmstadt (TUD) and Foundation of Research and Technology in Crete (FORTH), developed separate specialized algorithms to: a) detect bubble edges and b) use these edges to calculate basic bubble geometrical features, such as contact line diameter, bubble diameter and contact angles. These four different approaches diverge in complexity and concept. In the absence of reference measurements at microgravity conditions, measurements efficiency is evaluated based on the comparison of the estimated bubble geometrical features along with pertinent physical arguments. Results show that the efficiency of each approach varies with the nature of measurement. The studied benchmark dataset is published allowing other research groups to test further their own image processing algorithms.
ABSTRACT
Drop motility at liquid surfaces is attracting growing interest because of its potential applications in microfluidics and artificial cell design. Here we report the unique highly ordered pattern that sets in when a millimeter-size drop of dichloromethane spreads on an aqueous substrate under the influence of surface tension, both phases containing a surfactant. Evaporation induces a Marangoni flow that forces the development of a marked rim at the periphery of the spreading film. At some point this rim breaks up, giving rise to a ring of droplets, which modifies the aqueous phase properties in such a way that the film recoils. The process repeats itself, yielding regular large-amplitude pulsations. Wrinkles form at the film surface due to an evaporative instability. During the dewetting stage, they emit equally spaced radial strings of droplets which, combined with those previously expelled from the rim, make the top view of the system resemble a flower.
