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# Applied Dynamics Seminar Series

# Applied Dynamics Seminar Series

## Thursdays, 12:30 p.m.

## IREAP Large Conference Room (ERF 1207)

### February 9, 2017

#### Integrability of Matrix Riccati Equations that Arise in Hydrodynamics

University of Maryland | Department of Mathematics

*Abstract: TBA*

### February 16, 2017

#### Plasmon Resonances in Nanoparticles and the Reimann Hypothesis

University of Maryland | Department of Electrical and Computer Engineering

*Abstract: TBA*

### February 23, 2017

#### Observation of Localizad Stress Fluctuations that Drive Shear Thinning in Dense Suspensions

Georgetown University | Department of Physics

*Abstract: TBA*

### March 2, 2017

#### Helicity Dynamics

University of Maryland | Department of Physics

*Abstract: Helicity is a conserved quantity that arises in ideal fluid flows and ideal magnetohydrodynamic magnetic fields. I will first review the background theory of Helicity in those two cases, a famous paper by Finn and Antonsen, and another by Keith Moffatt. I will follow by covering some basic phenomenology of quantized vortices, reconnection, and Kelvin waves, and background of our visualization studies in superfluid helium. These topics lead into a discussion of what has been done, what we know, and what is predicted about Helicity dynamics. Some observations about the untangling of vortices via reconnection lead to predictions regarding the Helicity we are exploring experimentally. Some puzzles and questions about the role of invariants like the Helicity in the Gross-Pitaevskii (nonlinear Schrodinger) equation play a role in thinking about this phenomenon.*

### March 9, 2017

#### Toward a theory of reservoir computing prediction

Brian Hunt and Zhixin Lu

University of Maryland | Department of Mathematics and University of Maryland | IREAP

*Abstract: We consider the problem of predicting a chaotic time series from a system whose equations of motion are unknown. We use a machine-learning technique called reservoir computing, which we find is often able to learn the dynamics of the system that generated the time series, in the following sense. In addition to making accurate short-term predictions, the reservoir predictor can generate a long-term "climate" forecast that stays close to the attractor of the actual system. We give examples, and we discuss a preliminary theory relating reservoir predictor performance to Lyapunov exponents and generalized synchronization in an associated dynamical system.*

### March 16, 2017

#### Flames, Fire Whirls, and Blue Whirls: What more can there be?

University of Maryland | Department of Aerospace Engineering

*Abstract: As we were investigating the efficiency of fire-whirl burning on water, we observed the usual transformation of a pool fire to a fire whirl, and then suddenly, we saw the fire undergo a third transition. A blue cup appeared around the base of the fire whirl, surrounding the yellow flame, the yellow flame receded into the cup and finally disappeared. What remained was a small, rapidly spinning blue flame that burned until the fuel on the water was consumed. The blue whirl was shaped like a spinning cup, closed at the bottom near the water surface, and spreading in radius moving upwards towards the rim. Above the blue cup lip, there was a purple cone-shaped mist. The fuel initially used was n-heptane, but now it has been varied and includes crude oil, and still the blue whirl formed naturally. The height of the fire whirl on the laboratory pan was larger than a half meter, and this evolved into a blue whirl about 4–8 cm high. Occasionally the blue whirl would become “unstable” and revert to a transitional state of blue cup holding a yellow flame. When the blue whirl formed, turbulence seemed to disappear, and the flame became quiet. Videos of the experiments are used to show how this happened and discuss the evolution of the fire whirl to the blue whirl in vortex-breakdown concepts.*

### March 23, 2017

#### Spring Break - No Seminar

### March 30, 2017

#### Some Adjoint Methods in Physics and Engineering or How the solution to not my problem just might be the answer to your problem

University of Maryland | Department of Physics

*Abstract: Physicists and engineers frequently encounter situations where calculations of the governing equations of a system of interest appear to need to be repeated many times to describe or optimize the system. It is often the case that only a particular state dependent quantity or metric needs to be determined. In this case a computational savings can be achieved if an “adjoint problem” can be found that produces the desired information without requiring multiple computations. A simple example is the design of a receiving antenna. One wishes to know and optimize the signal received as a function of the incident angle and polarization of incoming waves. It might appear that solution of Maxwell’s field equations would have to be repeated for each possible incident direction and polarization. However, due to the reciprocal property of the governing equations, the desired information is obtained by treating the antenna as a transmitter and calculating the far field radiation pattern. Thus, one computation replaces many. In this talk I will review some problems from the area of charged particle dynamics where adjoint methods have proven useful. A new example is the optimization of electron beam optics in beam sources used in microwave and millimeter wave amplifiers.*

### April 6, 2017

#### Why Have Network Modulation of Sensory Cortex that Causes Variability to Sensory Processing?

University of Maryland | Department of Biology

*Abstract: A fundamental goal in brain research is to understand how electrical activity of individual neurons represents information relevant for brain function. This is most often studied in sensory systems, where neural activity can be directly related to sensory stimuli that can be experimentally controlled. However, recordings in awake animals can reveal an enormous amount to variability — that is, different responses to the same stimuli. Such variability has traditionally been characterized as noise that imposes limits on sensory processing. However, with experimental technology allowing for access to large amounts of simultaneously recorded neurons, it is becoming clear that this noise is shared and purposeful, and likely relates to a larger view of the function of sensory cortex. My lab has been developing new methods for analyzing population activity (and its dynamics) to infer what information is being represented by this variability, and how it relates to the larger functions of sensory cortex. This points to a picture where sensory processing does not occur in a vacuum, but is implicitly tied to the behavioral and motivational context of the animal.*

### April 13, 2017

#### Chaotic Dynamics in the Physical Sciences

University of Maryland | Department of Electrical Engineering and Department of Physics

*Ed Ott will be the recipient of the 2017 Lewis Fry Richardson Medal from The European Geosciences Union (E.G.U.). In connection with this award, he will give a lecture at the annual E.G.U. Assembly in Vienna, Austria, later this month. This Applied Dynamics Seminar will be a preview of his talk in Vienna.*

*Abstract: Chaos was discovered at the end of the 19th century by Poincare in his famous work on the motion of N>2 celestial bodies interacting through gravitational attraction. Although steady progress was made by mathematicians following Poincare's work, the widespread impact and development of chaos in the physical sciences is comparatively recent, i.e., approximately starting in the 1970's. This talk will review and comment on this history and will give some examples illustrating the types of questions, problems and results arising from perspectives resulting from the widespread participation of physical scientists in chaos research.*

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### April 20, 2017

#### Multi Chaos: A low dimensional Paradigm for higher-dimensional chaos

University of Maryland | Department of Mathematics

*Abstract: The most frequently studied dynamical systems are low dimensional and all the periodic orbits in a chaotic set have the same number of unstable dimensions, but this property seems to fail in high dimensional systems. In this paper, we define a property called ``multi-chaos'', in which, along with the usual properties of chaos, there is a dense set of k-dimensionally unstable periodic orbits, and this holds for more than one k. We provide examples including a piecewise linear generalized Baker map. *

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### April 27, 2017

#### Dynamics of Granular Clogging

University of Pennsylvania | Department of Physics

*Abstract: The gravity-driven flow of grains from a hole in a hopper is an iconic granular phenomenon. It’s different from a fluid in that the rate is constant also in that it can suddenly and unexpectedly clog. How does the the susceptibility to clogging decrease with increasing hole size, and is there a well-defined clogging transition above which the system never clogs? This problem is distinct from jamming due to presence of boundaries and gradients. We show how the fraction F of flow configurations that cause a clog may be deduced from the average mass discharged between clogs. We construct a simple model to account for the observation that F decays exponentially in hole width to the power of dimensionality. Thus the clogging transition is not sharp but rather is defined by observation limits similar to the glass transition. When the system is immersed in water, F barely changes. Therefore, the crucial microscopic variables are the grain positions; grain momenta play only a secondary role in destabilizing weak incipient arches. There is also a surprising effect whereby the discharge causes water to be pumped downwards, faster than the grains. *

### May 4, 2017

#### Nonlinear Dynamics, Chaos and Complex Systems: a Historical Perspective

Universidad Rey Juan Carlos | Department of Physics

*Abstract: "When we talk about dynamics, we do not only understand the motion of celestial bodies and solid mechanical systems, but any changes with respect to time of one or more variables. From that point of view, we can find dynamics everywhere, in any field of science. Thus, now we have a more general vision, including stock market movements and economic variables, concentration changes in chemical reactions, changes in physiological, biological and medical variables, action potentials of neurons, etc ... providing a more interdisciplinary perspective. The various interactions between the constituent parts of a physical system and their feedback mechanisms, are a source of nonlinearity and complexity, which added to the sensitivity dependence to initial conditions which is a hallmark of chaotic behavior, constitutes a change of perspective in dynamical systems with important consequences for the understanding of science. I will give a historical perspective of Nonlinear Dynamics, Chaos Theory and Complex Systems, including some of the different sources that have contributed to the construction of the discipline as we know it today. Among them, the three-body problem in celestial mechanics, turbulence in fluid dynamics, irreversibility and fundamentals of statistical physics and the logistic map and population dynamics in biology. Many schools of mathematics and physics have played an essential role in the historical development of the subject, including the French, Russian, Japanese and American school. The knowledge of this historical perspective allows us to understand the breadth of the discipline itself and the multiple interdisciplinary applications to various fields of science. " *

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### May 11, 2017

#### Non-Monotonic Aging and Memory Retention in Disordered Mechanical Systems

Harvard University | Harvard John A. Paulson School of Engineering and Applied Sciences

*Abstract: From materials such as polymers and glass to properties of interfaces leading to friction and even earthquakes, many disordered systems exhibit a similar repertoire of far-from-equilibrium behaviors such as non-exponential relaxations, aging and memory effects. Yet, in spite of numerous studies of these recurring motifs, identifying the mechanisms underlying the unusual dynamics of disordered systems remains a challenge. I will describe the observation of slow relaxations, aging and memory effects - hallmarks of glassy dynamics – in two disordered mechanical systems: crumpled thin sheets and elastic foams. In particular, I’ll report the observation of a non-monotonic aging response that can last many hours. I will then describe ongoing experiments that exploit the macroscopic nature of these systems to try and uncover the underlying mechanisms. The experimental results are in good agreement with a theoretical model recently used to describe observations of monotonic aging in several glassy systems. This suggests not only a general mechanism, but also that the non-monotonic behavior we observe may be generic and that a-thermal systems can show genuine glassy behavior. *

### Special Seminar - Tuesday May 16 at 11am (ERF 1027), 2017

#### Dynamics of Rewired Networks

Indian Institute of Science Education and Research

*Abstract: We will show how spatio-temporal chaos in networks with strongly chaotic nodal dynamics can be tamed by dynamically changing links. Specifically, we will illustrate the results in examples ranging from neuronal networks to disease spreading models. Further we will show how random links can prevent blow-ups in coupled nonlinear systems suffering from unbounded growth. *

*Special Seminar - May 18, 2017 *

*Topological methods for analyzing two dimensional flows *

*Kyoto University of Education | Department of Mathematics *

*Abstract: We introduce tree representations of two dimensional flows. Applying the topological methods to an evolution of an incompressible and viscid flow around an inclined flat plate placed in a uniform flow, we can estimate when the lift-to-drag ratios of the plate are maximal and can determine transient streamline patterns between structurally stable streamline patterns. Moreover, we state the possibilities of analyzing ocean phenomena and medical phenomena. Finally, we discuss low-dimensional dynamical systems which are theoretical backgrounds of the methods. *

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*2016 Archive | 2015 Archive *

*2016 Archive | 2015 Archive*