- You are here:
- GT Home
- Home
- News & Events

Monday, January 11, 2010 - 13:00 ,
Location: Skiles 255 ,
Peter Blomgren ,
San Diego State University ,
Organizer: Sung Ha Kang

We describe two computational frameworks for the assessment of contractileresponses of enzymatically dissociated adult and neonatal cardiac myocytes.The proposed methodologies are variants of mathematically sound andcomputationally robust algorithms very well established in the imageprocessing community. The physiologic applications of the methodologies areevaluated by assessing the contraction in enzymatically dissociated adultand neonatal rat cardiocytes. Our results demonstrate the effectiveness ofthe proposed approaches in characterizing the true 'shortening' in thecontraction process of the cardiocytes. The proposed method not onlyprovides a more comprehensive assessment of the myocyte contraction process,but can potentially eliminate historical concerns and sources of errorscaused by myocyte rotation or translation during contraction. Furthermore,the versatility of the image processing techniques makes the methodssuitable for determining myocyte shortening in cells that usually bend ormove during contraction. The proposed method can be utilized to evaluatechanges in contractile behavior resulting from drug intervention, diseasemodeling, transgeneity, or other common applications to mammaliancardiocytes.This is research is in collaboration with Carlos Bazan, David Torres, andPaul Paolini.

Monday, November 30, 2009 - 12:00 ,
Location: Skiles 269 ,
David Hu ,
Georgia Tech ME ,
Organizer:

How do animals move without legs? In this experimental and theoretical

study, we investigate the slithering of snakes on flat surfaces.

Previous studies of slithering have rested on the assumption that

snakes slither by pushing laterally against rocks and branches. In this

combined experimental and theoretical study, we develop a model for

slithering locomotion by observing snake motion kinematics and

experimentally measuring the friction coefficients of snake skin. Our

predictions of body speed show good agreement with observations,

demonstrating that snake propulsion on flat ground, and possibly in

general, relies critically on the frictional anisotropy of their

scales. We also highlight the importance of the snake's dynamically

redistributing its weight during locomotion in order to improve speed

and efficiency. We conclude with an overview of our experimental

observations of other methods of propulsion by snakes, including

sidewinding and a unidirectional accordion-like mode.

study, we investigate the slithering of snakes on flat surfaces.

Previous studies of slithering have rested on the assumption that

snakes slither by pushing laterally against rocks and branches. In this

combined experimental and theoretical study, we develop a model for

slithering locomotion by observing snake motion kinematics and

experimentally measuring the friction coefficients of snake skin. Our

predictions of body speed show good agreement with observations,

demonstrating that snake propulsion on flat ground, and possibly in

general, relies critically on the frictional anisotropy of their

scales. We also highlight the importance of the snake's dynamically

redistributing its weight during locomotion in order to improve speed

and efficiency. We conclude with an overview of our experimental

observations of other methods of propulsion by snakes, including

sidewinding and a unidirectional accordion-like mode.

Monday, November 23, 2009 - 13:00 ,
Location: Skiles 255 ,
Xiaoming Huo ,
Georgia Tech (School of ISyE) ,
xiaoming@isye.gatech.edu ,
Organizer: Sung Ha Kang

Many algorithms were proposed in the past ten years on utilizing manifold structure for dimension reduction. Interestingly, many algorithms ended up with computing for eigen-subspaces. Applying theorems from matrix perturbation, we study the consistency and rate of convergence of some manifold-based learning algorithm. In particular, we studied local tangent space alignment (Zhang & Zha 2004) and give a worst-case upper bound on its performance. Some conjectures on the rate of convergence are made. It's a joint work with a former student, Andrew Smith.

Monday, November 16, 2009 - 13:00 ,
Location: Skiles 255 ,
Chris Rycroft ,
UC-Berkeley ,
Organizer:

Due to an incomplete picture of the underlying physics, the simulation

of dense granular flow remains a difficult computational challenge.

Currently, modeling in practical and industrial situations would

typically be carried out by using the Discrete-Element Method (DEM),

individually simulating particles according to Newton's Laws. The

contact models in these simulations are stiff and require very small

timesteps to integrate accurately, meaning that even relatively small

problems require days or weeks to run on a parallel computer. These

brute-force approaches often provide little insight into the relevant

collective physics, and they are infeasible for applications in

real-time process control, or in optimization, where there is a need to

run many different configurations much more rapidly.

of dense granular flow remains a difficult computational challenge.

Currently, modeling in practical and industrial situations would

typically be carried out by using the Discrete-Element Method (DEM),

individually simulating particles according to Newton's Laws. The

contact models in these simulations are stiff and require very small

timesteps to integrate accurately, meaning that even relatively small

problems require days or weeks to run on a parallel computer. These

brute-force approaches often provide little insight into the relevant

collective physics, and they are infeasible for applications in

real-time process control, or in optimization, where there is a need to

run many different configurations much more rapidly.

Based upon a number of recent theoretical advances, a general

multiscale simulation technique for dense granular flow will be

presented, that couples a macroscopic continuum theory to a discrete

microscopic mechanism for particle motion. The technique can be applied

to arbitrary slow, dense granular flows, and can reproduce similar flow

fields and microscopic packing structure estimates as in DEM. Since

forces and stress are coarse-grained, the simulation technique runs two

to three orders of magnitude faster than conventional DEM. A particular

strength is the ability to capture particle diffusion, allowing for the

optimization of granular mixing, by running an ensemble of different

possible configurations.

Monday, November 9, 2009 - 13:00 ,
Location: Skiles 255 ,
Nicola Guglielmi ,
Università di L&#039;Aquila ,
guglielm@univaq.it ,
Organizer: Sung Ha Kang

This is a joint work with Michael Overton (Courant Institute, NYU). The epsilon-pseudospectral abscissa and radius of an n x n matrix are respectively the maximum real part and the maximal modulus of points in its epsilon-pseudospectrum. Existing techniques compute these quantities accurately but the cost is multiple SVDs of order n, which makesthe method suitable to middle size problems. We present a novel approach based on computing only the spectral abscissa or radius or a sequence of matrices, generating a monotonic sequence of lower bounds which, in many but not all cases, converges to the pseudospectral abscissa or radius.

Monday, November 2, 2009 - 13:00 ,
Location: Skiles 255 ,
Rustum Choksi ,
Simon Fraser University ,
Organizer:

A density functional theory of Ohta and Kawasaki gives rise to nonlocal perturbations of the well-studied Cahn-Hilliard and isoperimetric variational problems. In this talk, I will discuss these simple but rich variational problems in the context of diblock copolymers. Via a combination of rigorous analysis and numerical simulations, I will attempt to characterize minimizers without any preassigned bias for their geometry.

Energy-driven pattern formation induced by competing short and long-range interactions is ubiquitous in science, and provides a source of many challenging problems in nonlinear analysis. One example is self-assembly of diblock copolymers. Phase separation of the distinct but bonded chains in dibock copolymers gives rise to an amazingly rich class of nanostructures which allow for the synthesis of materials with tailor made mechanical, chemical and electrical properties. Thus one of the main challenges is to describe and predict the self-assembled nanostructure given a set of material parameters.

Monday, October 26, 2009 - 13:00 ,
Location: Skiles 255 ,
Chiu-Yen Kao ,
Ohio State University (Department of Mathematics) ,
kao@math.ohio-state.edu ,
Organizer: Sung Ha Kang

The Kadomtsev-Petviashvili (KP) equation is a two-dimensional dispersivewave equation which was proposed to study the stability of one solitonsolution of the KdV equation under the influence of weak transversalperturbations. It is well know that some closed-form solutions can beobtained by function which have a Wronskian determinant form. It is ofinterest to study KP with an arbitrary initial condition and see whetherthe solution converges to any closed-form solution asymptotically. Toreveal the answer to this question both numerically and theoretically, weconsider different types of initial conditions, including one-linesoliton, V-shape wave and cross-shape wave, and investigate the behaviorof solutions asymptotically. We provides a detail description ofclassification on the results. The challenge of numerical approach comes from the unbounded domain andunvanished solutions in the infinity. In order to do numerical computationon the finite domain, boundary conditions need to be imposed carefully.Due to the non-periodic boundary conditions, the standard spectral methodwith Fourier methods involving trigonometric polynomials cannot be used.We proposed a new spectral method with a window technique which will makethe boundary condition periodic and allow the usage of the classicalapproach. We demonstrate the robustness and efficiency of our methodsthrough numerous simulations.

Monday, October 19, 2009 - 13:00 ,
Location: Skiles 255 ,
Helga S. Huntley ,
University of Delaware ,
Organizer:

Biologists tracking crab larvae, engineers designing pollution mitigation strategies, and

climate scientists studying tracer transport in the oceans are among many who rely on

trajectory predictions from ocean models. State-of-the-art models have been shown to

produce reliable velocity forecasts for 48-72 hours, yet the predictability horizon for

trajectories and related Lagrangian quantities remains significantly shorter. We

investigate the potential for decreasing Lagrangian prediction errors by applying a

constrained normal mode analysis (NMA) to blend drifter observations with model velocity

fields. The properties of an unconstrained NMA and the effects of parameter choices are

discussed. The constrained NMA technique is initially presented in a perfect model

simulation, where the “true” velocity field is known and the resulting error can be

directly assessed. Finally, we will show results from a recent experiment in the East

Asia Sea, where real observations were assimilated into operational ocean model hindcasts.

climate scientists studying tracer transport in the oceans are among many who rely on

trajectory predictions from ocean models. State-of-the-art models have been shown to

produce reliable velocity forecasts for 48-72 hours, yet the predictability horizon for

trajectories and related Lagrangian quantities remains significantly shorter. We

investigate the potential for decreasing Lagrangian prediction errors by applying a

constrained normal mode analysis (NMA) to blend drifter observations with model velocity

fields. The properties of an unconstrained NMA and the effects of parameter choices are

discussed. The constrained NMA technique is initially presented in a perfect model

simulation, where the “true” velocity field is known and the resulting error can be

directly assessed. Finally, we will show results from a recent experiment in the East

Asia Sea, where real observations were assimilated into operational ocean model hindcasts.

Wednesday, October 14, 2009 - 13:00 ,
Location: Skiles 269 ,
Edson Denis Leonel ,
Universidade Estadual Paulista, Rio Claro, Brazil ,
Organizer:

Fermi acceleration is a phenomenon where a classical particle canacquires unlimited energy upon collisions with a heavy moving wall. Inthis talk, I will make a short review for the one-dimensional Fermiaccelerator models and discuss some scaling properties for them. Inparticular, when inelastic collisions of the particle with the boundaryare taken into account, suppression of Fermi acceleration is observed.I will give an example of a two dimensional time-dependent billiardwhere such a suppression also happens.

Monday, October 12, 2009 - 13:00 ,
Location: Skiles 255 ,
Wei Zhu ,
University of Alabama (Department of Mathematics) ,
wzhu7@bama.ua.edu ,
Organizer: Sung Ha Kang

The Rudin-Osher-Fatemi (ROF) model is one of the most powerful and popular models in image denoising. Despite its simple form, the ROF functional has proved to be nontrivial to minimize by conventional methods. The difficulty is mainly due to the nonlinearity and poor conditioning of the related problem. In this talk, I will focus on the minimization of the ROF functional in the one-dimensional case. I will present a new algorithm that arrives at the minimizer of the ROF functional fast and exactly. The proposed algorithm will be compared with the standard and popular gradient projection method in accuracy, efficiency and other aspects.