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PhD Seminar: Christiana Mavroyiakoumou and Vishwas Goel

October 28, 2021 @ 4:00 pm - 5:00 pm

Venue: Zoom Event

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The Ph.D. in Scientific Computing program is intended for students who will make extensive use of large-scale computation, computational methods, or algorithms for advanced computer architectures in their doctoral studies. This seminar series showcases the breadth of research covered by the program. 

Featured Speakers:

Portrait of Christiana Mavroyiakoumou

CHRISTIANA MAVROYIAKOUMOU, PhD Candidate, Applied and Interdisciplinary Mathematics, and Scientific Computing

Bio: Christiana Mavroyiakoumou is a 5th year PhD candidate in Applied and Interdisciplinary Mathematics, working on extensible membrane flutter in inviscid flow using theoretical and computational tools. Her advisor is Professor Silas Alben at the Department of Mathematics.

DYNAMICS OF TETHERED MEMBRANES IN INVISCID FLOW: We study the dynamics of membranes (with stretching stiffness but zero bending stiffness) that shed vortex wakes in inviscid flows. Previous studies have focused on membranes with fixed ends, where only static deflection occurs. Here we consider instead membranes held by tethers with hinged ends, and find that a variety of unsteady large-amplitude motions, both periodic and chaotic, may occur. We characterize the dynamics over ranges of the key parameters: membrane mass density, stretching stiffness, pretension, and tether length. We find the region of instability and the small-amplitude behavior in a linearized model by solving a nonlinear eigenvalue problem. We also derive asymptotic scaling laws by considering a simplified model: an infinite periodic membrane. We find qualitative similarities among all three models in terms of the oscillation frequencies and membrane shapes at small and large values of the parameters.

VISHWAS GOEL, PhD Candidate, MATERIALS SCIENCE AND ENGINEERING, and Scientific Computing

Bio: I am a 4th Ph.D. student in the Department of Materials Science and Engineering. My research is focused on multi-scale modeling of electrochemical processes such as energy storage, energy conversion, and corrosion.

MODELING BASED OPTIMIZATION OF HOLE ARCHITECTURE FOR ENABLING FAST CHARGING IN LI-ION BATTERIES: For the widespread adoption of electric vehicles, we need Li-ion batteries (LIBs) that are energy and power dense. However, we cannot realize both these properties even in state-of-the-art commercial Li-ion batteries. This inability is caused by the electrode design used in LIBs. In such a design, to increase the energy density, one needs to increase the active material loading (either in terms of active material mass fraction or the electrode thickness). However, such a design proves to be highly tortuous for the transport of Li-ions in the electrolyte, which causes the electrode to exhibit poor fast charging performance.

In our previous work [1], we demonstrated that the rate performance of the energy-dense electrodes can be improved by employing 3D architectures such as highly ordered laser-patterned electrodes (HOLE). The architecture alleviates the electrolyte mass transport limitations by providing rapid mass transport via laser-ablated channels through the electrode thickness. In this study, we investigate how the geometric parameters of the HOLE design, such as inter-channel spacing and channel radius, affect the fast-charging performance of the HOLE graphite anodes with > 3 mAh/cm2 loading. We conduct this analysis using a fully parameterized continuum scale model based on the porous electrode theory. Our results show that for a constant volume retained (after the laser ablation), the smaller and closer channels exhibit better 4C charging performance than the larger and farther channels.

1. K.-H. Chen et al., J. Power Sources, 471, 228475 (2020) doi.org/10.1016/j.jpowsour.2020.228475


 

This event is part of MICDE’s Fall 2021 seminar series featuring Ph.D. students in the Scientific Computing program. This series is open to all. University of Michigan faculty and students interested in computational and data sciences are encouraged to attend.

Questions? Email [email protected]

 

Details

Date:
October 28, 2021
Time:
4:00 pm - 5:00 pm
Event Categories:
,

Venue

Zoom Event
MI United States