Computational Investigation of the Effects of Surfactants on Bubble Dynamics, Bubble Swarm Interactions and Turbulent Flow

University Of Colorado At Denver-Downtown Campus, Denver CO

Investigators

Abstract

Surface active materials or surfactants in two-phase, bubbly flow mixtures are used in a number of areas of important scientific and technological interest, including those in chemical, bio-molecular, power and petroleum engineering applications. They can significantly change the interfacial dynamics, fluid motion and structure of macroscale bubble aggregates, and are known to cause clustering of bubbles and turbulence suppression near walls. However, the fundamental details of the underlying physical mechanisms associated with such observations are not yet completely known, and elucidation through modeling will have direct impact on the design and scale-up and the operation of engineering systems. Such complex fluid systems involve both bulk and molecular effects, which are mediated by the interfacial dynamics and driven by the fluid motion present major challenges. Their understanding, especially for bubble swarm interactions in the inertia dominated flow regimes, is generally limited to experimental visualization results and empirical data. This project aims to perform large scale simulations using innovative computational techniques at the forefront in their development for the investigation and elucidation of the underlying processes in prototypical flows of surfactant-laden two-phase bubbly systems and swarms. Successful implementation of this research will yield new tools, rich sets of data and physical insights under unprecedented conditions that will be of interest to a wide community of researchers. The project will impact the education in a number of ways, including interdisciplinary training and research participation of graduate and undergraduate students. The results of this proposed research, which lies at the borderline between mechanical/chemical engineering, and physics and computational science, will be disseminated broadly in journal papers and conferences, and the new methods and codes developed under this project will be readily available as open sources. This project has the potential to transform the way the surfactant effects are modeled, qualitative and quantitative understanding of the surfactant-laden bubbly flows in various nonlinear flow regimes. The application of a three-dimensional multiphase flow model using a cascaded lattice Boltzmann (LB) formulation is at the cutting edge of current research and will potentially make fundamental advances in the modeling and simulation capabilities to study the role of surfactant effects on convection dominated bubble dynamics and swarm interactions. Its kinetic origins facilitate incorporation of mesoscopic models and the LB method is remarkably successful in complex fluid flow applications with natural parallelization capabilities. The surfactants and the bulk fluids are represented as dipoles and van der Waals fluids, respectively, which, in turn, generate surfactant-fluid, surfactant-surfactant mean-field force interactions at mesoscopic scales that govern the alignment of the surface agents, phase segregation and surface tension effects. The use of a central moment formulation in the cascaded LB method offers enhanced physical and numerical simulation capabilities. This innovative computational approach will be brought to bear on performing a systematic study of the effect of the characteristic parameters to elucidate physical understanding for the following prototypical cases: surfactant-laden bubble breakup processes in homogeneous turbulence, surfactant effects on the motion of a single bubble in a shear-driven turbulent channel flow, and buoyancy-driven motion of a single and a pair of surfactant-laden bubbles to study their path instabilities, rise velocities, drag and lift forces and wake structures. This will offer researchers fundamental insights into the underlying mechanisms involved, including the role of surfactants on cluster formation in swarms and phase diagrams based on characteristic parameters delineating the various regimes of bubble paths and deformations thereby clarifying the role of surfactants on path instabilities (Leonardo's paradox). Another major outcome will be in the development of predictive closure relations incorporating surfactant effects for mixture models.