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Proper Orthogonal Decomposition and Radial Basis Functions for Fast Simulations

  • Vladimir BuljakEmail author
Chapter
Part of the Computational Fluid and Solid Mechanics book series (COMPFLUID)

Abstract

Proper Orthogonal Decomposition (POD) is a powerful method for low-order approximation of some high dimensional processes. It is widely used in the situations where model reduction is required. The most favorable feature of the method is its optimality: it provides the most efficient way of capturing the dominant components of high-dimensional processes with, sometimes surprisingly small number of “modes”. This chapter will present an algorithm that combines POD with Radial Basis Functions (RBF) used for the interpolation of the data with previously reduced dimensionality by the POD.

Keywords

Radial Basis Function Singular Value Decomposition Proper Orthogonal Decomposition Nodal Displacement Proper Orthogonal Decomposition Mode 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Dipartimento di Ingegneria StrutturalePolitecnico di MilanoMilanoItaly

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