Seminars and Colloquia by Series

Fungal fluid mechanics

Series
Applied and Computational Mathematics Seminar
Time
Monday, February 27, 2012 - 14:05 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Marcus RoperUCLA Mathematics Dept.
Although fungi are the most diverse eukaryotic organisms, we have only a very fragmentary understanding of their success in so many niches or of the processes by which new species emerge and disperse. I will discuss how we are using math modeling and perspectives from physics and fluid mechanics to understand fungal life histories and evolution: #1. A growing filamentous fungi may harbor a diverse population of nuclei. Increasing evidence shows that this internal genetic flexibility is a motor for diversification and virulence, and helps the fungus to utilize nutritionally complex substrates like plant cell walls. I'll show that hydrodynamic mixing of nuclei enables fungi to manage their internal genetic richness. #2. The forcibly launched spores of ascomycete fungi must eject through a boundary layer of nearly still air in order to reach dispersive air flows. Individually ejected microscopic spores are almost immediately brought to rest by fluid drag. However, by coordinating the ejection of thousands or hundreds of thousands of spores fungi, such as the devastating plant pathogen Sclerotinia sclerotiorum are able to create a flow of air that carries spores across the boundary layer and around any intervening obstacles. Moreover the physical organization of the jet compels the diverse genotypes that may be present within the fungus to cooperate to disperse all spores maximally.

Variational Image Registration

Series
Applied and Computational Mathematics Seminar
Time
Monday, February 20, 2012 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Benjamin BerkelsSouth Carolina University
Image registration is the task of transforming different images, or more general data sets, into a common coordinate system. In this talk, we employ a widely used general variational formulation for the registration of image pairs. We then discuss a general gradient flow based minimization framework suitable to numerically solve the arising minimization problems. The registration framework is next extended to handle the registration of hundreds of consecutive images to a single image. This registration approach allows us to average numerous noisy scanning transmission electron microscopy (STEM) images producing an improved image that surpasses the quality attainable by single shot STEM images.We extend these general ideas to develop a joint registration and denoising approach that allows to match the thorax surface extracted from 3D CT data and intra-fractionally recorded, noisy time-of-flight (ToF) range data. This model helps track intra-fractional respiratory motion with the aim of improving radiotherapy for patients with thoracic, abdominal and pelvic tumors.

Reconstruction of Binary function from Incomplete Frequency Information

Series
Applied and Computational Mathematics Seminar
Time
Monday, January 30, 2012 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
David MaoInstitute for Mathematics and Its Applications (IMA) at University of Minnesota
Binary function is a class of important function that appears in many applications e.g. image segmentation, bar code recognition, shape detection and so on. Most studies on reconstruction of binary function are based on the nonconvex double-well potential or total variation. In this research we proved that under certain conditions the binary function can be reconstructed from incomplete frequency information by using only simple linear programming, which is far more efficient.

Linear and nonlinear vibration-based energy harvesting

Series
Applied and Computational Mathematics Seminar
Time
Monday, January 23, 2012 - 14:05 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Alper ErturkGeorgia Tech, School of Mechanical Engineering
The transformation of vibrations into low-power electricity has received growing attention over the last decade. The goal in this research field is to enable self-powered electronic components by harvesting the vibrational energy available in their environment. This talk will be focused on linear and nonlinear vibration-based energy harvesting using piezoelectric materials, including the modeling and experimental validation efforts. Electromechanical modeling discussions will involve both distributed-parameter and lumped-parameter approaches for quantitative prediction and qualitative representation. An important issue in energy harvesters employing linear resonance is that the best performance of the device is limited to a narrow bandwidth around the fundamental resonance frequency. If the excitation frequency slightly deviates from the resonance condition, the power output is drastically reduced. Energy harvesters based on nonlinear configurations (e.g., monostable and bistable Duffing oscillators with electromechanical coupling) offer rich nonlinear dynamic phenomena and outperform resonant energy harvesters under harmonic excitation over a range of frequencies. High-energy limit-cycle oscillations and chaotic vibrations in strongly nonlinear bistable beam and plate configurations are of particular interest. Inherent material nonlinearities and dissipative nonlinearities will also be discussed. Broadband random excitation of energy harvesters will be summarized with an emphasis on stochastic resonance in bistable configurations. Recent efforts on aeroelastic energy harvesting as well as underwater thrust and electricity generation using fiber-based flexible piezoelectric composites will be addressed briefly.

Dynamics of Active Suspensions

Series
Applied and Computational Mathematics Seminar
Time
Monday, November 28, 2011 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Christel HoheneggerMathematics, Univ. of Utah
One of the challenges in modeling the transport properties of complex fluids (e.g. many biofluids, polymer solutions, particle suspensions) is describing the interaction between the suspended micro-structure with the fluid itself. Here I will focus on understanding the dynamics of semi-dilute active suspensions, like swimming bacteria or artificial micro-swimmers modeled via a simple kinetic model neglecting chemical gradients and particle collisions. I will then present recent results on the linearized structure of such an active system near a state of uniformity and isotropy and on the onset of the instability as a function of the volume concentration of swimmers, both for a periodic domain. Finally, I will discuss the role of the domain geometry in driving the flow and the large-scale flow instabilities, as well as the appropriate boundary conditions.

Domain decomposition methods for large problems of elasticity

Series
Applied and Computational Mathematics Seminar
Time
Monday, November 14, 2011 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Olof Widlund Courant Institute,New York University, Mathematics and Computer Science
The domain decomposition methods considered are preconditioned conjugate gradient methods designed for the very large algebraic systems of equations which often arise in finite element practice. They are designed for massively parallel computer systems and the preconditioners are built from solvers on the substructures into whichthe domain of the given problem is partitioned. In addition, to obtain scalability, there must be a coarse problem, with a small number of degrees of freedom for each substructure. The design of this coarse problem is crucial for obtaining rapidly convergent iterations and poses the most interesting challenge in the analysis.Our work will be illustrated by overlapping Schwarz methods for almost incompressible elasticity approximated by mixed finite element and mixed spectral element methods. These algorithms is now used extensively at the SANDIA, Albuquerque laboratories and were developed in close collaboration with Dr. Clark R. Dohrmann. These results illustrate two roles of the coarse component of the preconditioner.Currently, these algorithms are being actively developed for problems posed in H(curl) and H(div). This work requires the development of new coarse spaces. We will also comment on recent work on extending domain decomposition theory to subdomains with quite irregular boundaries.  This work is relevant because of the use of mesh partitioners in the decomposition of large finite element matrices. 

An iterative filtering method for adaptive signal decomposition based on a PDE model

Series
Applied and Computational Mathematics Seminar
Time
Monday, November 7, 2011 - 14:00 for 30 minutes
Location
Skiles 006
Speaker
Jingfang LiuGT Math
The empirical mode decomposition (EMD) was a method developed by Huang et al as an alternative approach to the traditional Fourier and wavelet techniques for studying signals. It decomposes signals into finite numbers of components which have well behaved intataneous frequency via Hilbert transform. These components are called intrinstic mode function (IMF). Recently, alternative algorithms for EMD have been developed, such as iterative filtering method or sparse time-frequency representation by optimization. In this talk we present our recent progress on iterative filtering method. We develop a new local filter based on a partial differential equation (PDE) model as well as a new approach to compute the instantaneous frequency, which generate similar or better results than the traditional EMD algorithm.

Fast Spectral-Galerkin Methods for High-Dimensional PDEs and Applications to the electronic Schrodinger equation

Series
Applied and Computational Mathematics Seminar
Time
Monday, October 31, 2011 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Jie Shen Purdue University, Department of Mathematics
Many scientific, engineering and financial applications require solving high-dimensional PDEs. However, traditional tensor product based algorithms suffer from the so called "curse of dimensionality".We shall construct a new sparse spectral method for high-dimensional problems, and present, in particular,  rigorous error estimates as well as efficient numerical algorithms for  elliptic equations in both bounded and unbounded domains.As an application, we shall use the proposed sparse spectral method to solve the N-particle electronic  Schrodinger equation.

A fast algorithm for finding the shortest path by solving initial value ODE's

Series
Applied and Computational Mathematics Seminar
Time
Monday, October 24, 2011 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Jun LuGT Math
We propose a new fast algorithm for finding the global shortest path connecting two points while avoiding obstacles in a region by solving an initial value problem of ordinary differential equations (ODE's). The idea is based on the factthat the global shortest path possesses a simple geometric structure. This enables us to restrict the search in a set of feasible paths that share the same structure. The resulting search space is reduced to a finite dimensional set. We use a gradient descent strategy based on the intermittent diffusion (ID) in conjunction with the level set framework to obtain the global shortest path by solving a randomly perturbed ODE's with initial conditions.Compared to the existing methods, such as the combinatorial methods or partial differential equation(PDE) methods, our algorithm is faster and easier to implement. We can also handle cases in which obstacles shape are arbitrary and/or the dimension of the base space is three or higher.

Multiscale Besov Space Smoothing of Images

Series
Applied and Computational Mathematics Seminar
Time
Monday, October 10, 2011 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Bradley LucierPurdue University, Department of Mathematics
We consider a variant of Rudin--Osher--Fatemi variational image smoothing that replaces the BV semi-norm in the penalty term with the B^1_\infty(L_1) Besov space semi-norm. The space B^1_\infty(L_1$ differs from BV in a number of ways: It is somewhat larger than BV, so functions inB^1_\infty(L_1) can exhibit more general singularities than exhibited by functions in BV, and, in contrast to BV, affine functions are assigned no penalty in B^1_\infty(L_1). We provide a discrete model that uses a result of Ditzian and Ivanov to compute reliably with moduli of smoothness; we also incorporate some ``geometrical'' considerations into this model. We then present a convergent iterative method for solving the discrete variational problem. The resulting algorithms are multiscale, in that as the amount of smoothing increases, the results are computed using differences over increasingly large pixel distances. Some computational results will be presented. This is joint work with Greg Buzzard, Antonin Chambolle, and Stacey Levine.

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