This research project aims to develop mathematical and computational tools, methods, and algorithms for simulating and understanding a class of multiphase multicomponent flow problems that are of practical engineering significance and fundamental physical importance. The systems under study in this project have relevance to the environment, energy, and materials science. For example, such multiphase systems occur in modeling for remediation of oil spills. Another example is the novel class of functional surfaces called liquid infused surfaces discovered in the past decade, which exhibit a variety of attractive properties such as self-cleaning, anti-icing and anti-fouling. These multiphase multicomponent problems underlie numerous technological advances, from printed electronic circuits and sensors, to opto-fluidic microscopes and waveguides, to water-resistant fabrics, to oil recovery and carbon sequestration. The project aims to develop improved efficient and effective computational methods to tackle the challenges in simulations for such systems. This project provides research training opportunities for graduate and undergraduate students.

The research aims at devising efficient and effective methods for simulating and understanding the dynamics of a system of three or more immiscible incompressible fluids with different physical properties such as densities, viscosities, and pairwise surface tensions. These systems pose enormous computational and algorithmic challenges to numerical simulations, because of the multitude of fluid interfaces, three-phase lines, and contact lines and contact angles involved. The project builds upon the reduction-consistent and thermodynamically-consistent formulations developed in recent years and will provide computational prediction capability and effective techniques for illuminating and understanding the interactions among multiple fluid components, multiple types of fluid interfaces, and multiple types of contact lines.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

National Science Foundation (NSF)
Division of Mathematical Sciences (DMS)
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Yuliya Gorb
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Purdue University
West Lafayette
United States
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