Search for tag: "nonlinear science seminar"

Vladimir Rosenhaus - Feynman rules for wave turbulence

It has long been known that weakly nonlinear field theories can have a late-time stationary state that is not the thermal state, but a wave turbulent state (the Kolmogorov-Zakharov state) with a…

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Daniel Floryan - Charting dynamics from data

We often find ourselves working with systems for which governing equations are unknown, or if they are known, they may be high-dimensional to the point of being difficult to analyze and prohibitively…

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Carlos Pérez De Jesús - Data-driven estimation of inertial manifold dimension for chaotic Kolmogorov flow and time evolution on the manifold

Model reduction techniques have previously been applied to evolve the Navier-Stokes equations in time, however finding the minimal dimension needed to correctly capture the key dynamics is not a…

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Michael Graham, Kevin Zeng - Deep Reinforcement Learning Using Data-Driven Reduced-Order Models Discovers and Stabilizes Low Dissipation Equilibria

Part 2: Deep reinforcement learning (RL), a data-driven method capable of discovering complex control strategies for high-dimensional systems, requires substantial interactions with the target…

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Michael Graham, Alec Linot - Data-driven dimension reduction, dynamic modeling, and control of complex chaotic systems

PART 1Speaker Mike Graham Overview: Data-driven dimension reduction, dynamic modeling, and control of complex chaotic systemsOur overall aim is to combine ideas from dynamical systems theory and…

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Alper Erturk - Leveraging nonlinear dynamics in mechanical and electromechanical structures

This talk will review some of our recent and ongoing efforts on the leveraging of nonlinear dynamics in passive and active structures, spanning from nonlinear energy harvesting using piezoelectric…

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