Fundamentals of Reduced Basis Method for problems governed by parametrized PDEs and applications


Separated representations and PGD-based model reduction: fundamentals and applications), Springer, vol. 554




G. Rozza

In this chapter we consider Reduced Basis (RB) approximations of parametrized Partial Differential Equations (PDEs). The the idea behind RB is to decouple the generation and projection stages (Offline/Online computational procedures) of the approximation process in order to solve parametrized PDEs in a fast, inexpensive and reliable way. The RB method, especially applied to 3D problems, allows great computational savings with respect to the classical Galerkin Finite Element (FE) Method. The standard FE method is typically ill suited to (i) iterative contexts like optimization, sensitivity analysis and many-queries in general, and (ii) real time evaluation. We consider for simplicity coercive PDEs. We discuss all the steps to set up a RB approximation, either from an analytical and a numerical point of view. Then we present an application of the RB method to a steady thermal conductivity problem in heat transfer with emphasis on geometrical and physical parameters.

chapter = {Fundamentals of Reduced Basis Method for problems governed by parametrized
PDEs and applications},
publisher = {Springer},
year = {2014},
author = {Gianluigi Rozza},
volume = {554},
series = {CISM International Centre for Mechanical Sciences},
booktitle = {Separated representations and {PGD}-based model reduction: fundamentals
and applications},
doi = {10.1007/978-3-7091-1794-1_4},
organization = {Springer}

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