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HallerGroupETH
Switzerland
เข้าร่วมเมื่อ 13 ม.ค. 2022
We develop mathematical and numerical methods for complex, nonlinear dynamical systems in nature and engineering. Our approach combines applied mathematics, dynamical systems theory and numerical methods to produce algorithms directly applicable to experimental and numerical data sets. Areas of current interest include nonlinear vibrations of multi-degree-of-freedom structures, rigorous model reduction in very high dimensional systems, complicated transport processes in the ocean and the atmosphere, and the definition and identification of coherent structures in turbulence.
Nonlinear Reduced-Order Modeling from Data by Prof. George Haller.
NODY Webinar, February 22, 2024.
DOI: doi.org/10.52843/cassyni.jrr0qt
I discuss a recent dynamical-systems-based alternative to machine learning in the data-driven reduced-order modeling of nonlinear phenomena. Specifically, spectral submanifolds (SSMs) represent very low-dimensional attractors in a large family of physical problems ranging from wing oscillations to transitions in pipe flows. A data-driven identification of the reduced dynamics on these SSMs gives a rigorous way to construct accurate and predictive reduced-order models for solids, fluids, and controls without the use of governing equations. I illustrate this on problems that include accelerated finite-element simulations of large structures, prediction of transitions in pipe flows, reduced-order modeling of fluid sloshing in a tank, and model-predictive control of soft robots.
DOI: doi.org/10.52843/cassyni.jrr0qt
I discuss a recent dynamical-systems-based alternative to machine learning in the data-driven reduced-order modeling of nonlinear phenomena. Specifically, spectral submanifolds (SSMs) represent very low-dimensional attractors in a large family of physical problems ranging from wing oscillations to transitions in pipe flows. A data-driven identification of the reduced dynamics on these SSMs gives a rigorous way to construct accurate and predictive reduced-order models for solids, fluids, and controls without the use of governing equations. I illustrate this on problems that include accelerated finite-element simulations of large structures, prediction of transitions in pipe flows, reduced-order modeling of fluid sloshing in a tank, and model-predictive control of soft robots.
มุมมอง: 913
วีดีโอ
NLDC-II Lecture 20
มุมมอง 6610 หลายเดือนก่อน
Proof Existence of Invariant Manifolds, Lyapunov-Perron Method, Hadamard's Method, Wasewsky Method
NLDC-II Lecture 18
มุมมอง 7210 หลายเดือนก่อน
Singular Perturbation Theory, Slow Manifold, Inertial Clustering
2:38 31:37 55:41
1:12:29, 1:24:49 1:28:50
A very good lecture.
Thanks for providing these lectures
Can you please provide the notes and the problems here on youtube?
Awesome work. Thank you for sharing!
Thank you very much for sharing this valuable course online. Is there a way to access the lecture notes?
Yes, there is a course website and you can find the notes there. In the first class, the lecturer has announced the website.
Fabulous lecture!
thank you for sharing. would there be more recordings?
Yes we are working on uploading the second part of the course.
Will NLDC-II also be uploaded?
Yes we are currently working on it. It will be uploaded in the coming days.
Thank you so much for sharing
Thanks for sharing.
Thank you very much for uploading the lectures.
Excellent talk!