Angielski
This book provides a basic introduction to Reduced Basis (RB) methods for problems involving the repeated solution of partial differential equations (PDEs), such as PDEs depending on several parameters, PDE-constrained optimization, etc., arising from engineering and applied sciences.§§We present a general mathematical formulation of RB methods, analyze their fundamental theoretical properties, discuss the related algorithmic and implementation aspects, and finally we highlight their built-in algebraic and geometrical structures.§§More specifically, we carry on both a priori and a posteriori error analysis, discuss alternative techniques for constructing accurate RB spaces, and analyze Offline-Online decomposition strategies aimed at the reduction of computational complexity.§§The whole mathematical discussion is made more stimulating thanks to the use of several representative examples of applicative interest, in the context of both linear and nonlinear PDEs.§
