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

Complexitatea modelelor matematice utilizate pentru a simula modelul de dinamica a fluidelor geofizice ii face pe cercetatori sa caute modele de ordine redusa mai simple si mai ieftine. Aceste modele necesita sute de milioane sau chiar miliarde de grade de libertate care impiedica simularea cu valori diferite ale parametrilor modelului, care apar in probleme de proiectare optima sau de control al fluxului in dinamica fluidelor geofizice.