Collision dynamics of compound droplets in microchannels: a combined numerical and data-driven study
Author ORCID Identifier
0000-0002-5277-3203
Document Type
Dissertation
Date of Award
8-31-2024
Degree Name
Doctor of Philosophy in Mechanical Engineering - (Ph.D.)
Department
Mechanical and Industrial Engineering
First Advisor
Samaneh Farokhirad
Second Advisor
Pushpendra Singh
Third Advisor
Peter E. Balogh
Fourth Advisor
Simone Marras
Fifth Advisor
Shima Parsa
Abstract
Understanding and predicting the hydrodynamic interactions of micron-scale droplets is crucial in a wide range of industrial and real-life applications, including microfluidics, pharmaceutics, drug delivery, food science, and enhanced oil recovery. These multi-phase and multi-scale phenomena are further complicated by the presence of core droplets of an immiscible fluid within shell droplets, known as compound droplets. The collisions and interactions of droplets in emulsions are influenced by various physical and geometric parameters, leading to distinct rheological and dynamic responses. This research employs numerical methods for a systematic parametric study of both simple and compound droplet pair collisions under confined shear flow. The primary focus is on analyzing three collision modes: pass-over, coalescence, and reverse-back motions, analyzing their trajectories and morphological evolution. A literature review reveals that most previous studies have predominantly focused on the collisions of simple droplet pairs in confined conditions, with density and viscosity ratios typically low, near unity. Additionally, the dynamic behavior of compound droplet pairs remains unexplored and unquantified. This study extends previous works for simple droplet pair collision to include a wider range of density ratios (up to 800) and viscosity ratios (up to 60), and delves into the less studied dynamics of compound droplet pairs. This includes the pair-wise interactions involving one or two core droplets, in order to bring fundamental understanding necessary for designing emulsion-based systems and devices. Numerical simulations were conducted using the free-energy binary-liquid lattice Boltzmann method. In addition to physical parameters such as Capillary number, and density and viscosity ratios, the research further examines how interplay among geometric variables such as core-shell size ratio, initial offset of droplets, and wall confinement affects the transition between collision modes, morphology, trajectory, and final states of the droplet pairs. Considering the growing prominence of machine learning based data-driven approaches, this research also investigates the potential of using deformed shape data to predict collision outcomes. A convolutional neural network-based classifier model has been successfully developed, and shown high accuracy in predicting these outcomes. The findings drawn from this study provide valuable insights into the intricate dynamics of compound droplet interactions, which can be instrumental for optimizing processes across diverse applications.
Recommended Citation
Mamun, S M Abdullah Al, "Collision dynamics of compound droplets in microchannels: a combined numerical and data-driven study" (2024). Dissertations. 1798.
https://digitalcommons.njit.edu/dissertations/1798
Included in
Biomechanical Engineering Commons, Biomedical Engineering and Bioengineering Commons, Complex Fluids Commons, Computational Engineering Commons, Dynamics and Dynamical Systems Commons, Transport Phenomena Commons
