In this paper we present a compact review on the mostly used techniques for computational reduction in numerical approximation of partial differential equations. We highlight the common features of these techniques and provide a detailed presentation of the reduced basis method, focusing on greedy algorithms for the construction of the reduced spaces. An alternative family of reduction techniques based on surrogate response surface models is briefly recalled too. Then, a simple example dealing with inviscid flows is presented, showing the reliability of the reduced basis method and a comparison between this technique and some surrogate models.

Computational Reduction for Parametrized PDEs: Strategies and Applications

MANZONI, ANDREA;QUARTERONI, ALFIO MARIA;
2012-01-01

Abstract

In this paper we present a compact review on the mostly used techniques for computational reduction in numerical approximation of partial differential equations. We highlight the common features of these techniques and provide a detailed presentation of the reduced basis method, focusing on greedy algorithms for the construction of the reduced spaces. An alternative family of reduction techniques based on surrogate response surface models is briefly recalled too. Then, a simple example dealing with inviscid flows is presented, showing the reliability of the reduced basis method and a comparison between this technique and some surrogate models.
2012
Primary 78M34; Secondary 49J20; 65N30; 76D55; Computational reduction; Reduced basis methods; Proper orthogonal decomposition; Parametrized partial differential equations
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/802740
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