Applied Math Seminar
Spring 2018
All talks are from 12:001:00 p.m. in the Seminar Room CH351, unless otherwise specified.

May04

Dylan PoulsonWashington College

Apr13

Andrew DorsettWolfram MathematicaLocation: CH 110 (Note the room change)
View Abstract
This technical talk will show live calculations in Mathematica 11 and other Wolfram technologies relevant to courses and research. Specific topics include: * Enter calculations in everyday English, or using the flexible Wolfram Language * Visualize data, functions, surfaces, and more in 2D or 3D * Store and share documents locally or in the Wolfram Cloud * Use the Predictive Interface to get suggestions for the next useful calculation or function options * Access trillions of bits of ondemand data * Use semantic import to enrich your data using Wolfram curated data * Easily turn static examples into mousedriven, dynamic applications * Access 10,000 free courseready applications * Utilize the Wolfram Language's wide scope of builtin functions, or create your own * Get deep support for specialized areas including machine learning, time series, image processing, parallelization, and control systems, with no addons required Current users will benefit from seeing the many improvements and new features of Mathematica 11 (https://www.wolfram.com/mathematica/newin11/), but prior knowledge of Mathematica is not required.

Apr06

A Conditional Gaussian Framework for Uncertainty Quantification, Data Assimilation and Prediction of Nonlinear Turbulent Dynamical SystemsNan ChenNew York University
View Abstract
A conditional Gaussian framework for uncertainty quantification, data assimilation and prediction of nonlinear turbulent dynamical systems will be introduced in this talk. Despite the conditional Gaussianity, the dynamics remain highly nonlinear and are able to capture strongly nonGaussian features such as intermittency and extreme events. The conditional Gaussian structure allows efficient and analytically solvable conditional statistics that facilitates the realtime data assimilation and prediction. This talk will include three applications of such conditional Gaussian framework. The first part regards the state estimation and data assimilation of multiscale and turbulent ocean flows using noisy Lagrangian tracers. Rigorous analysis shows that an exponential increase in the number of tracers is required for reducing the uncertainty by a fixed amount. This indicates a practical information barrier. In the second part, an efficient statistically accurate algorithm is developed that is able to solve a rich class of highdimensional FokkerPlanck equation with strong nonGaussian features and beat the curse of dimensions. In the last part of this talk, a physicsconstrained nonlinear stochastic model is developed, and is applied to predicting the MaddenJulian oscillation indices with strongly nonGaussian intermittent features.

Mar30

Ryan EvansNational Institute of Standards and Technology

Mar23

Modeling Sound Scattering from Subsea buried Targets using inair Laboratory MeasurementsEarl WilliamsNaval Research Laboratory
View Abstract
Identification of unexploded ordinance (UXO) buried in the sediment in the littoral waters throughout the world is a problem of great concern. An estimated 200 million pounds of dangerous bombs, missiles, projectiles and other ordnance exists in the world’s waterways. An approach developed at the Naval Research Laboratory aims to help in the identification by capitalizing on acoustic resonances of the UXO target. When illuminated by lowfrequency sonar many of these targets exhibit a unique vibration pattern that can be used to identify them. This vibration behavior is embodied and identified by a quantity called the in vacuo structural admittance matrix Ys, a relationship between the sonarinduced forces f and resulting vibration v of its surface, given by the simple linear algebra equation v=Ys f. Nearly impossible to measure in situ, Ys can be measured in air in a simple, acoustically unaltered laboratory space using an array of loudspeakers and the crosscorrelations of velocity and pressure measurements made on the target’s surface. When coupled with computed matrices that describe the subsea sediment, one can predict the dominant directions and intensity of the sound scattered off the UXO as a function of frequency (called the acoustic color). This scattered field is picked up by surface ships or unmanned undersea vehicles and complex algorithms are used to identify the UXO from the acoustic color. The objective of this seminar is to demonstrate the range and type of mathematical principles at play, and how they lead to a solution of a naval problem of significant practical importance. The need for a strong and varied mathematical background is crucial to success. Furthermore, a physical experiment is critical and serves as a proof of the approach for mathematicians and acousticians alike. Mathematical theories meet their ultimate test in the cross hairs of experimentation. Work supported by the Office of Naval Research.

Mar09

Stochastic Modeling of Multiscale Biochemical NetworksHye Won KangUniversity of Maryland Baltimore County
View Abstract
Stochastic effects may play an important role in mathematical modeling of biological and chemical processes in case the copy number of some component involved in the system is small. This talk will present the recent work on stochastic modeling of biochemical networks. First, I will introduce a continuoustime Markov chain model for chemical reaction networks when the systems are well stirred. The relationship between the stochastic and deterministic models will be considered. This model is extended to describe reaction and diffusion in the spatially distributed systems. Next, multiscale algorithms for stochastic simulation of reactiondiffusion processes will be introduced, that couple different modeling schemes for better efficiency of the simulation. The algorithms apply to the systems including the region with a few molecules where a continuoustime Markov chain model is used and the region with a large number of molecules where stochastic partial differential equations (SPDEs) are applied. Short Bio: HyeWon Kang is an Assistant Professor in the Department of Mathematics and Statistics at the University of Maryland at Baltimore County since 2013. She finished her Ph.D. in Mathematics (Probability) at the University of Wisconsin, Madison under the supervision of Thomas G. Kurtz with the dissertation on "Multiple scaling methods in chemical reaction networks." She was a postdoctoral researcher at the University of Minnesota during 20082011 and in the Mathematical Biosciences Institute at the Ohio State University during 20112013. Her research interest lies in stochastic modeling, analysis, and simulation of reactiondiffusion systems in biology and chemistry.

Mar02

Flutter: The Waltz of the Wave and Plate EquationsJustin WebsterUniversity of Maryland Baltimore CountyTime: 12:00 PM
View Abstract
When a thin elastic structure is immersed in a fluid flow, certain conditions may bring about structural excitations. That is, the dynamic loading of the fluid feeds back with the natural oscillatory modes of the structure. In this case we have a boundedresponse instability, and the oscillatory behavior may persist until the flow parameters change or energy is adequately dissipated from the structure. This onset of this interactive phenomenon is referred to as flutter. Beyond the obvious applications in aeroscience (projectile paneling and flaps, flags, and airfoils), the flutter phenomenon arises in: (i) the biomedical realm (in treating sleep apnea), and (ii) sustainable energies (in providing a lowcost power generating mechanisms). Modeling, predicting, and controlling flutter (as well as understanding post flutter nonlinear dynamics) has been a foremost problems in engineering for nearly 70 years. In this talk we describe the basics of modeling a flowstructure interaction in the simplest configuration (an aircraft panel) using differential equations and dynamical systems. After discussing the partial differential equation model, we will discuss theorems that can be proved about solutions to these equations using modern analysis (e.g., nonlinear functional analysis, semigroups, monotone operator theory, the theory of global attractors). We will relate these dynamical systems results back to experimental observations in engineering and recent numerical work. We will also describe very recent (and very open) problems in the analysis of "flaglike" configurations, where a portion of the structure is unsupported.