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A robust diffuse interface method for simulation of realistic two-phase flows

Event Type
Department of Mechanical Science and Engineering
wifi event
Apr 9, 2021   12:00 pm  
Shahab Mirjalili, Postdoctoral Fellow at Center for Turbulence Research, Stanford University
Lindsey Henson
Originating Calendar
MechSE Seminars

Seminar Abstract:

Two-phase flows are ubiquitous in natural and industrial settings, from oceanic waves to liquid jet atomization in engines. Many challenges must be overcome to simulate realistic two-phase flows, especially when multi-physics effects are involved. In this study, we introduce a novel diffuse interface method that addresses these challenges for simulation of incompressible, immiscible two-phase flows. The boundedness of this mass-conserving interface-capturing method is proven analytically. We then demonstrate how mass-momentum consistency is achieved in this framework, resulting in a two-phase flow method that discretely conserves kinetic energy, a first in the field. A comparison of the fully coupled solver with a state-of-the-art Volume-of-Fluid solver is provided, confirming the cost-efficiency and advantages of our approach. Finally, by assuming an interfacial microstructure, we derive a model for simulating heat and mass transfer in two-phase flows within the framework of our diffuse interface method.



Shahab Mirjalili is a postdoctoral fellow at the Center for Turbulence Research at Stanford University where his research focuses mainly on numerical modeling of two-phase flows in the presence of multi-physics effects. He received his PhD in Mechanical Engineering under the supervision of Professor Ali Mani at Stanford University in 2019. Prior to that, he earned his MS from Stanford University and a BS from Sharif University of Technology, both in Mechanical Engineering. He is the recipient of the Gallery of Fluid Motion Award, American Physical Society Division of Fluid Dynamics (2018). Shahab’s research interests include numerical methods and physics of two-phase flows, fluid modeling of plasmas, and machine learning.


Host:  Professor Laura Villafane

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