Applied Math Colloquium  Spring 2018
Colloquium Schedule
Colloquia are held on Fridays at 11:30 a.m. in Cullimore Lecture Hall II, unless noted otherwise. Refreshments are served at 11:30 a.m. For questions about the seminar schedule, please contact David Shirokoff.
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Date  Speaker, Affiliation, and Title  Host 

February 2  Paulo Arratia, University of Pennsylvania Life in complex fluids Many microorganisms (e.g. bacteria, algae, sperm cells) move in fluids or liquids that contain (bio)polymers and/or solids. Examples include human cervical mucus, intestinal fluid, wet soil, and tissues. These socalled complex fluids often exhibit nonNewtonian rheological behavior due to the nontrivial interaction between the fluid microstructure and the applied stresses. In this talk, I will show how the presence of particles and polymers in the fluid medium can strongly affect the motility (i.e. swimming) behavior of microorganisms such as the bacterium E. coli. For bacteria moving in particle suspensions of different (particle) sizes, we find a regime in which larger (passive) particles can diffuse faster than smaller particles: the particle longtime effective diffusivity exhibits a peak in particle size, which is a deviation from classical thermal diffusion. A minimal model qualitatively explains the existence of the effective diffusivity peak and its dependence on bacterial concentration. These results have broad implications on characterizing active fluids using concepts drawn from classical thermodynamics. For swimmers (E. coli and C. reinhardtii) moving in polymeric liquids, we find that fluid elasticity can significantly affect the runandtumble mechanism characteristic of E. coli, for example, as well as the swimming speed and kinematics of both pushers and pullers. These results demonstrate the intimate link between swimming kinematics and fluid rheology and that one can control the spreading and motility of microorganisms by tuning fluid properties. 
Lou Kondic 
February 9  Uwe Beuscher, W. L. Gore & Associates Investigation of the correlation between gas/liquid porometry and particle filtration using simple network models In order to better understand the performance of microporous membranes for particle filtration, it is important to determine and measure the appropriate membrane structural properties that influence filtration. One such property is the pore size distribution and a common technique for measuring pore sizes or porous structures is gas/liquid capillary porometry. In this method, the pore size is determined by measuring the capillary pressure distribution of the sample, which is correlated to a pore size distribution using a very simple model structure of parallel capillaries. A numerical study using a simple network model for the porous material, however, has shown that the morphological structure strongly influences the porometry results. Model structures with different morphology and pore size information lead to varying porometry results at similar filtration behavior and vice versa. An attempt is made to correlate numerical porometry and filtration performance as is often done in experimental studies. Finally, the limitations of porometry in predicting filtration behavior are illustrated. 
Linda Cummings 
February 16  Aleksandar Donev, New York University Large Scale Brownian Dynamics of Confined Suspensions of Rigid Particles We introduce new numerical methods for simulating the dynamics of passive and active Brownian colloidal suspensions of particles of arbitrary shape sedimented near a bottom wall. The methods also apply for periodic (bulk) suspensions. Our methods scale linearly in the number of particles, and enable previously unprecedented simulations of tens to hundreds of thousands of particles. We demonstrate the accuracy and efficiency of our methods on a suspension of boomerangshaped colloids. We also model recent experiments on active dynamics of uniform suspensions of spherical microrollers. 
Lou Kondic 
February 23  Sue Ann Campbell, University of Waterloo Mean Field Analysis and the Dynamics of Large Networks of Neurons We use mean field analysis to study emergent behaviour in networks of alltoall coupled, pulsecoupled neurons. The individual neurons are represented using a class of twodimensional integrate and fire model. The mean field model is derived using a population density approach, moment closure assumptions and a quasisteady state approximation. The resulting model is a system of switching ordinary differential equations, which exhibits a variety of smooth and nonsmooth bifurcations. We show that the results of the mean field analysis are a reasonable prediction of the behaviour seen in numerical simulations of large networks and discuss how the presence of parameter heterogeneity and noise affects the results. This is joint work with Wilten Nicola. 
Casey Diekman 
March 2  Gene Wayne, Boston University Dynamical Systems and the TwoDimensional NavierStokes Equations Twodimensional fluid flows exhibit a variety of coherent structures such as vortices and dipoles which can often serve as organizing centers for the flow. These coherent structures can, in turn, sometimes be associated with the existence of special geometrical structures in the phase space of the equations and in these cases the evolution of the flow can be studied with the aid of dynamical systems theory. 
Roy Goodman 
March 9  Jerome Darbon, Brown University On Convex FiniteDimensional Variational Methods in Imaging Sciences, and HamiltonJacobi Equations We consider standard finitedimensional variational models used in signal/image processing that consist in minimizing an energy involving a data fidelity term and a regularization term. We propose new remarks from a theoretical perspective which give a precise description on how the solutions of the optimization problem depend on the amount of smoothing effects and the data itself. The dependence of the minimal values of the energy is shown to be ruled by HamiltonJacobi equations, while the minimizers u(x,t) for the observed images x and smoothing parameters t are given by u(x,t)=x  grad H( grad E(x,t)) where E(x,t) is the minimal value of the energy and H is a Hamiltonian related to the data fidelity term. Various vanishing smoothing parameter results are derived illustrating the role played by the prior in such limits. Finally, we briefly present an efficient numerical numerical method for solving certain HamiltonJacobi equations in high dimension and some applications in optimal control. 
David Shirokoff 
March 23  Sanjoy Mahajan, Olin College (secondary affiliation: Massachusetts Institute of Technology) StreetFighting Mathematics for Better Teaching and Thinking With traditional science and mathematics teaching, students struggle with fundamental concepts. For example, they cannot reason with graphs and have no feel for physical magnitudes. Their instincts remain Aristotelian: In their gut, they believe that force is proportional to velocity. With such handicaps in intuition and reasoning, students can learn only by rote. I'll describe these difficulties using mathematical and physical examples, and illustrate how streetfighting mathematics and sciencethe art of insight and approximationcan improve our thinking and teaching, the better to handle the complexity of the world. 
Jonathan Luke (cohosted by CSLA, Dept. of Physics, and the NJIT Institute for Teaching Excellence) 
April 6  Becca Thomases, University of California, Davis

YuanNan Young 
April 13  Michael Shelley, New York University / Flatiron Institute

Anand Oza 
April 20  Maxim Olshanskii, University of Houston Finite Element Methods for PDEs Posed on Surfaces Partial differential equations posed on surfaces arise in mathematical models for many natural phenomena: diffusion along grain boundaries, lipid interactions in biomembranes, pattern formation, and transport of surfactants on multiphase flow interfaces to mention a few. Numerical methods for solving PDEs posed on manifolds recently received considerable attention. In this talk we review recent developments in this field and focus on an Eulerian finite element method for the discretization of elliptic and parabolic partial differential equations on surfaces which may evolve in time. The method uses traces of finite element space functions on a surface to discretize equations posed on the surface. The talk explains the approach, reviews analysis and demonstrates results of numerical experiments. The problems addressed include diffusion along timedependent surfaces and fluid systems on manifolds. 
Shahriar Afkhami 
April 27  Yoichiro Mori, University of Minnesota

YuanNan Young 
Updated: March 16, 2018