Applications of Efficient POD Model Order Reduction to Direct and Inverse Problems of Fluid Dynamics
The complexity of mathematical models used to simulate geophysical fluid dynamics model has researchers looking for simpler and cheaper reduced order models. These models require hundreds of millions or even billions of degrees of freedom that preclude simulation with different values of the model parameters as occur in optimal design or flow control problems in geophysical fluid dynamics. This book will concentrate mainly on Proper Orthogonal Decomposition (POD) the most popular model reduction technique that reduces the dimensionality of a PDE system by transforming the high fidelity unknowns into a much smaller new set of variables
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Produktdetails
Weitere Autoren: Navon, I. M. / Pain, C. C.
- ISBN: 978-1-4987-3272-7
- EAN: 9781498732727
- Produktnummer: 32778209
- Verlag: Taylor & Francis Ltd.
- Sprache: Englisch
- Erscheinungsjahr: 2023
- Seitenangabe: 400 S.
- Plattform: PDF
- Auflage: 1. Auflage
Über den Autor
DR. Fangxin Fang, Now, Research Fellow in Earth Science and Engineering, Imperial College, London, UK Dr. I. Michael Navon is Professor of Mathematics, Department of Scientific Computing , Florida State University and Program Director, Optimization and Optimal ControlC.C. Pain is Professor in the Department of Earth Science and Engineering at Imperial College London (ICL), UK and head of the Applied Computation and Modelling Group (AMCG), the largest department research group at ICL
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Applications of Efficient POD Model Order Reduction to Direct and Inverse Problems of Fluid Dynamics
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