College of Engineering at UMass Dartmouth

EAS PhD Dissertation Defense by Cory Hoi (CSE Option/Mechanical Engineering)

Date: March 20, 2025
Time: Noon-2pm

Topic: Advancing Surfactant Replacement Therapy: Novel Computational Simulations of Multi-Phase Flow of Non-Newtonian and Newtonian Fluids

Location: SENG 110
Zoom link: Please contact Dr. Raessi (mraessi@umassd.edu).

Abstract:

Prematurely born infants are at risk of developing respiratory distress syndrome (RDS) due to a deficiency of pulmonary surfactant. Without this surface tension reducing molecule, large pressure gradients in the lung can lead to atelectasis and increase mortality risk. Medical practitioners treat RDS with surfactant replacement therapy (SRT), a procedure which reintroduces exogenous surfactant into the airway. However, SRT has a 35% non-response rate, largely due to the challenges of delivering the surfactant uniformly, and reaching the distal regions of the lung.

Current research has focused on understanding the physics of Newtonian surfactant delivery, specifically how the plug propagates along the airway, deposits its mass onto the airway wall, and splits at each airway bifurcation. However, in practice, many of the surfactants used exhibit non-Newtonian shear thinning behavior. Additionally, the mucus in the lung forms a bilayer of periciliary fluid, composed of mostly Newtonian fluid. This complexity introduces additional challenges for computational simulations, as no established methods currently exist for simulating non-Newtonian liquid interactions, with Newtonian liquid, and gas.

This thesis addresses the current gap in research by developing a novel numerical method using the volume-of-fluid (VOF) approach. This method enables computational simulations that accurately capture interactions between a non-Newtonian shear-thinning liquid, a Newtonian liquid, and gas in the presence of a rigid body. To validate its accuracy, semi-analytical solutions are derived for multiphase Poiseuille ow of non-Newtonian and Newtonian fluids. Additionally, numerical simulations are conducted for canonical cases, such as bubbles rising in shear-thinning fluids.

Finally, the numerical method is applied to simulate non-Newtonian surfactant plugs propagating through straight capillary tubes and a bifurcating airway model. The interplay between non-Newtonian plugs and the pre-existing film is analyzed, highlighting its potential implications for improving SRT.

Acknowledgment: The research support from the National Science Foundation (NSF) under CBET grant 1904204 and partial support from NSF-DMS 2012011 grant are gratefully acknowledged.

Advisor:
(508-999-8496), Dept of Mechanical Engineering

Committee Members:
Dr. Geoffrey Cowles, SMAST
Dr. Alfa Heryudono, Dept. of Mathematics
Dr. Hangjian Ling, Dept. of Mechanical Engineering

Open to the public.  All MNE and EAS students are encouraged to attend.

For questions contact

EAS Doctoral Dissertation Defense by Benjamin Burnett

Date: Monday, March 24, 2025
Time: 3pm–4:30pm

Topic: Accelerating Implicit Runge-Kutta Methods with Mixed-Precision and Linearization Techniques

Zoom Link:
https://umassd.zoom.us/j/96334992315?pwd=KyrUYjs5KUduhldDk4cMxvJrIX5dAv.1
Meeting ID: 963 3499 2315
Passcode: 155913

Abstract:

Implicit Runge-Kutta (IRK) methods are notoriously expensive to compute, especially in the context of solving nonlinear partial differential equations (PDEs). In this dissertation we explore two main techniques that aim to accelerate solutions to these nonlinear PDEs when using IRK based methods. The first of these is the use of mixed-precision, wherein we use mixed-precision additive Runge-Kutta (MPARK) methods to solve implicit stages in low precision, then correct any errors introduced in high precision. In this portion of the dissertation, we explore implementation strategies for mixed precision computing by solving the Van der Pol equation and Viscous Burgers' Equation using the MPARK methods. The second portion of this dissertation focuses on the use of linearization as an acceleration technique, wherein we linearize the implicit stages using different strategies, including a novel linearization strategy based on a two-point Taylor series expansion. In this portion of the dissertation we focus on exploring the stability and performance of the two-point linearization strategy by solving several problems including the Viscous Burgers' Equation, Heat Equation, and Cahn-Hilliard Equation.

Advisor(s): , Dept of Mathematics

Committee members:
Dr. Zheng Chen, Department of Mathematics
Dr. Alfa Heryudono, Department of Mathematics
Dr. Gaurav Khanna, Department of Physics, University of Rhode Island

Note: All EAS Students are ENCOURAGED to attend.