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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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Vladimir Rosenhaus Date
April 12th, 2022
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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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Daniel Floryan Date
November 3rd, 2021
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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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Carlos Pérez De Jesús Date
November 3rd, 2021
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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, Kevin Zeng Date
October 27th, 2021
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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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Michael Graham, Alec Linot Date
October 20th, 2021
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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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Alper Erturk Date
November 4th, 2020
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