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Applications of Efficient POD Model Order Reduction to Direct and Inverse Problems of Fluid Dynamics

Fangxin Fang, I. M. Navon, C. C. Pain (Autoren)

Buch | Hardcover

400 Seiten

2021
Productivity Press (Verlag)
978-1-4987-3268-0 (ISBN)

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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

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 Control C.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

Erscheint lt. Verlag	1.1.2021
Reihe/Serie	Advances in Applied Mathematics
Verlagsort	Portland
Sprache	englisch
Maße	156 x 235 mm
Themenwelt	Mathematik / Informatik ► Mathematik
	Naturwissenschaften ► Physik / Astronomie ► Plasmaphysik
	Naturwissenschaften ► Physik / Astronomie ► Strömungsmechanik
ISBN-10	1-4987-3268-2 / 1498732682
ISBN-13	978-1-4987-3268-0 / 9781498732680
Zustand	Neuware