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This paper presents novel insights about the influence of soluble surfactants on bubble flows obtained by Direct Numerical Simulation (DNS). Surfactants are amphiphilic compounds which accumulate at fluid interfaces and significantly modify the respective interfacial properties, influencing also the overall dynamics of the flow. With the aid of DNS local quantities like the surfactant distribution on the bubble surface can be accessed for a better understanding of the physical phenomena occurring close to the interface. The core part of the physical model consists in the description of the surfactant transport in the bulk and on the deformable interface. The solution procedure is based on an Arbitrary Lagrangian-Eulerian (ALE) Interface-Tracking method. The existing methodology was enhanced to describe a wider range of physical phenomena. A subgridscale (SGS) model is employed in the cases where a fully resolved DNS for the species transport is not feasible due to high mesh resolution requirements and, therefore, high computational costs. After an exhaustive validation of the latest numerical developments, the DNS of single rising bubbles in contaminated solutions is compared to experimental results. The full velocity transients of the rising bubbles, especially the contaminated ones, are correctly reproduced by the DNS. The simulation results are then studied to gain a better understanding of the local bubble dynamics under the effect of soluble surfactant. One of the main insights is that the quasi-steady state of the rise velocity is reached without ad-and desorption being necessarily in local equilibrium.

In this article, we present experimental and numerical techniques to investigate the transfer, transport, and reaction of a chemical species in the vicinity of rising bubbles. In the experiment, single oxygen bubbles of diameter d b = 0.55 . . . 0.85 mm are released into a measurement cell filled with tap water. The oxygen dissolves and reacts with sulfite to sulfate. Laser-induced fluorescence is used to visualize the oxygen concentration in the bubble wake from which the global mass transfer coefficient can be calculated. The ruthenium-based fluorescent dye seems to be surface active, such that the rise velocity is reduced by up to 50 % compared to the experiment without fluorescent dye and a recirculation zone forms in the bubble wake. To access the local mass transfer at the interface, we perform complementary numerical simulations. Since the fluorescence tracer is essential for the experimental method, the effect of surface contamination is also considered in the simulation. We employ several improvements in the experimental and numerical procedures which allow for a quantitative comparison (locally and globally). Rise velocity and mass transfer coefficient agree within a few percents between experiment, simulation and literature results. Because the fluorescence tracer is frequently used in mass transfer experiments, we discuss its potential surface activity.

A flexible modeling approach for the accurate approximation of convectiondominated reactive-species boundary layers is introduced. A substitute problem is solved numerically and analyzed by employing statistical methods. The numerical data are then used to train a machine learning model that can be used to approximate the reactive mass transfer locally if a direct resolution of the concentration boundary layer is infeasible. Compared to previous modeling approaches, the machine learning model replaces the analytical solution of a simplified substitute problem, which makes it applicable to more complicated and general settings.

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