epshteyn (at)
math.utah.edu) or to
Akil Narayan (akil (at) sci.utah.edu) January 25. Claremont & Utah Joint Applied Math
Seminar.
Speaker: Chiu-Yen Kao, Department of Mathematical Sciences, Claremont McKenna College
Title: Minimization of the First Nonzero Eigenvalue Problem for Two-Phase Conductors with
Neumann Boundary Conditions
Abstract: We consider the problem of minimizing the first nonzero eigenvalue of an
elliptic operator with Neumann boundary conditions with respect to the distribution
of two conducting materials with a prescribed area ratio in a given domain. In one
dimension, we show monotone properties of the first nonzero eigenvalue with respect
to various parameters and find the optimal distribution of two conducting materials
on an interval under the assumption that the region that has lower conductivity is
simply connected. On a rectangular domain in two dimensions, we show that the strip
configuration of two conducting materials can be a local minimizer. For general
domains, we propose a rearrangement algorithm to find the optimal distribution
numerically. Many results on various domains are shown to demonstrate the efficiency
and robustness of the algorithms. Topological changes of the optimal configurations
are discussed on circles, ellipses, annuli, and L-shaped domains.
February 1. Claremont & Utah Joint Applied Math
Seminar.
Speaker: Di Kang,
Department of Mathematics and Statistics, McMaster University
Title: Searching for singularities in Navier-Stokes flows using variational optimization
methods
Abstract:
In the presentation we will discuss our research program concerning the search for the most singular behaviors possible in viscous incompressible flows. These events are characterized by extremal growth of various quantities, such as the enstrophy, which control the regularity of the solution. They are therefore intimately related to the question of possible singularity formation in the 3D Navier-Stokes system, known as the hydrodynamic blow-up problem. We demonstrate how new insights concerning such questions can be obtained by formulating them as variational PDE optimization problems which can be solved computationally using suitable discrete gradient flows. More specifically, such an optimization formulation allows one to identify "extreme" initial data which, subject to certain constraints, leads to the most singular flow evolution. In offering a systematic approach to finding flow solutions which may saturate known estimates, the proposed paradigm provides a bridge between mathematical analysis and scientific computation. In particular, it makes it possible to determine whether or not certain mathematical estimates are "sharp", in the sense that they can be realized by actual vector fields, or if these estimates may still be improved. In the presentation we will review a number of results concerning 1D and 2D flows characterized by the maximum possible growth of different Sobolev norms of the solutions. As regards 3D flows, we focus on the enstrophy which is a well-known indicator of the regularity of the solution. We find a family of initial data with fixed enstrophy which leads to the largest possible growth of this quantity at some prescribed final time. Since even with such worst-case initial data the enstrophy remains finite, this indicates that the 3D Navier-Stokes system reveals no tendency for singularity formation in finite time.
February 8. Claremont & Utah Joint Applied Math
Seminar.
Speaker: Aaron Barrett,
Department of Mathematics, University of Utah
Title: Complex Fluids in the Immersed Boundary Method: From Viscoelasticity to
Blood
Clots
Abstract: The immersed boundary method was first developed in the 1970s to model the
motion of heart valves and has since been utilized to study many different
biological systems. While the IB method has seen countless modifications and
advancements from the perspective of fluid-structure interaction, the use
of a
Newtonian fluid model remains a fundamental component of many
implementations.
However, many biological fluids exhibit non-Newtonian responses to stresses,
and as such, a Newtonian fluid model falls short to fully describe the
system.
In this talk, we will discuss models of two different systems: polymeric
fluids
and blood clotting, and we will address the numerical challenges associated
with each system.
February 15. Claremont & Utah Joint Applied Math
Seminar.
Speaker: Peter Hinow,
Mathematical Sciences, University of Wisconsin, Milwaukee
Title: Modeling and Simulation of Ultrasound-mediated Drug Delivery to the Brain
Abstract:
We use a mathematical model to describe the delivery of a drug to a specific region of the brain. The drug is carried by liposomes that can release their cargo by application of focused ultrasound. Thereupon, the drug is absorbed through the endothelial cells that line the brain capillaries and form the physiologically important blood-brain barrier. We present a compartmental model of a capillary that is able to capture the complex binding and transport processes the drug undergoes in the blood plasma and at the blood-brain barrier. We apply this model to the delivery of L-dopa, (used to treat Parkinson's disease) and doxorubicin (an anticancer agent). The goal is to optimize the delivery of drug while at the same time minimizing possible side effects of the ultrasound. In a second project, we present a mathematical model for drug delivery through capillary networks with increasingly complex topologies with the goal to understand the scaling behavior of model predictions on a coarse-to-fine sequence of grids.
February 22. Claremont & Utah Joint Applied Math
Seminar.
Speaker: Christina Durón,
Mathematics Department, The University of Arizona
Title: Heatmap Centrality: A New Measure to Identify Super-spreader Nodes in Scale-Free Networks
Abstract: The identification of potential super-spreader nodes within a network is a
critical part of the study and analysis of real-world networks. Motivated by a new
interpretation of the "shortest path" between two nodes, this talk will explore the
properties of the recently proposed measure, the heatmap centrality, by comparing
the farness of a node with the average sum of farness of its adjacent nodes in order
to identify influential nodes within the network. As many real-world networks are
often claimed to be scale-free, numerical experiments based upon both simulated and
real-world undirected and unweighted scale-free networks are used to illustrate the
effectiveness of the new "shortest path" based measure with regards to its CPU run
time and ranking of influential nodes.
March 1. Claremont & Utah Joint Applied Math
Seminar.
Speaker: Xiang
Xu, Department of Mathematics & Statistics, Old Dominion University
Title: Blowup rate estimates of a singular potential in the Landau-de Gennes theory
for liquid crystals
Abstract: The Landau-de Gennes theory is a type of continuum theory that describes
nematic liquid crystal configurations in the framework of the Q-tensor order
parameter. In the free energy, there is a singular bulk potential which is
considered as a natural enforcement of a physical constraint on the eigenvalues of
symmetric, traceless Q-tensors. In this talk we shall discuss some analytic
properties related to this singular potential. More specifically, we provide precise
estimates of both this singular potential
and its gradient as the Q-tensor approaches its physical boundary.
March 8. Claremont & Utah Joint Applied Math
Seminar.
Speaker: Henry
Schellhorn, Department of Mathematics, Claremont
Graduate School
Title: Optimal Control of the SIR Model in the Presence of Transmission and Treatment
Uncertainty
Abstract: The COVID-19 pandemic illustrates the importance of treatment-related decision making in populations. This article considers the case where the transmission rate of the disease as well as the efficiency of treatments is subject to uncertainty. We consider two different regimes, or submodels, of the stochastic SIR model, where the population consists of three groups: susceptible, infected and recovered. In the first regime the proportion of infected is very low, and the proportion of susceptible is very close to 100%. This corresponds to a disease with few deaths and where recovered individuals do not acquire immunity. In a second regime, the proportion of infected is moderate, but not negligible. We show that the first regime corresponds almost exactly to a well-known problem in finance, the problem of portfolio and consumption decisions under mean-reverting returns (Wachter, JFQA 2002), for which the optimal control has an analytical solution. We develop a perturbative solution for the second problem. To our knowledge, this paper represents one of the first attempts to develop analytical/perturbative solutions, as opposed to numerical solutions to stochastic SIR models.
March 22. Claremont & Utah Joint Applied Math
Seminar.
Speaker: Dmitry Pelinovsky,
Department of Mathematics and Statistics, McMaster University
Title: Periodic travelling waves in nonlinear wave equations: modulation instability and rogue waves
Abstract: TBA
March 29 (student's talk). Claremont & Utah Joint Applied Math
Seminar.
Speaker: Dihan Dai,
Department of Mathematics, University of Utah
Title: TBA
Abstract: TBA
April 12. Claremont & Utah Joint Applied Math
Seminar.
Speaker: Traian Iliescu,
Department of Mathematics, Virginia Tech
Title: TBA
Abstract: TBA
April 19. Claremont & Utah Joint Applied Math
Seminar.
Speaker: Ryan Murray,
Department of Mathematics, North Carolina State University
Title: TBA
Abstract: TBA
April 26. Claremont & Utah Joint Applied Math
Seminar.
Speaker: Anna Little,
Department of Mathematics, University of Utah
Title: TBA
Abstract: TBA
epshteyn (at)
math.utah.edu) and Akil Narayan (akil (at)sci.utah.edu).
Past lectures: Fall 2020, Spring 2020, Fall 2019, Spring 2019, Fall 2018, Spring 2018, Fall 2017, Spring 2017, Fall 2016, Spring 2016, Fall 2015, Spring 2015, Fall 2014, Spring 2014, Fall 2013, Spring 2013, Fall 2012, Spring 2012, Fall 2011, Spring 2011, Fall 2010, Spring 2010, Fall 2009, Spring 2009, Fall 2008, Spring 2008, Fall 2007, Spring 2007, Fall 2006, Spring 2006, Fall 2005, Spring 2005, Fall 2004, Spring 2004, Fall 2003, Spring 2003, Fall 2002, Spring 2002, Fall 2001, Spring 2001, Fall 2000, Spring 2000, Fall 1999, Spring 1999, Fall 1998, Spring 1998, Winter 1998, Fall 1997, Spring 1997, Winter 1997, Fall 1996, Spring 1996, Winter 1996, Fall 1995.