Nonlinear Model Reduction Using Group Proper Orthogonal Decomposition

Nonlinear Model Reduction Using Group Proper Orthogonal Decomposition

Year:    2010

Author:    B. T. Dickinson, J. R. Singler

International Journal of Numerical Analysis and Modeling, Vol. 7 (2010), Iss. 2 : pp. 356–372

Abstract

We propose a new method to reduce the cost of computing nonlinear terms in projection based reduced order models with global basis functions. We develop this method by extending ideas from the group finite element (GFE) method to proper orthogonal decomposition (POD) and call it the group POD method. Here, a scalar two-dimensional Burgers' equation is used as a model problem for the group POD method. Numerical results show that group POD models of Burgers' equation are as accurate and are computationally more efficient than standard POD models of Burgers' equation.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2010-IJNAM-724

International Journal of Numerical Analysis and Modeling, Vol. 7 (2010), Iss. 2 : pp. 356–372

Published online:    2010-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    17

Keywords:    Model reduction proper orthogonal decomposition group finite element nonlinear.

Author Details

B. T. Dickinson

J. R. Singler