Acceleration techniques for reduced-order models based on proper orthogonal decomposition

Authors:
Paul G. A. Cizmas;Brian R. Richardson;Thomas A. Brenner;Thomas J. O'Brien;Ronald W. Breault
Affiliations:
Department of Aerospace Engineering, Texas A&M University, College Station, TX 77843-3141, USA;Department of Aerospace Engineering, Texas A&M University, College Station, TX 77843-3141, USA;Department of Aerospace Engineering, Texas A&M University, College Station, TX 77843-3141, USA;National Energy Technology Laboratory, Department of Energy, Morgantown, WV 26507-0880, USA;National Energy Technology Laboratory, Department of Energy, Morgantown, WV 26507-0880, USA
Venue:
Journal of Computational Physics
Year:
2008

Citing 3
Cited 1

Numerical recipes in FORTRAN (2nd ed.): the art of scientific computing

Numerical recipes in FORTRAN (2nd ed.): the art of scientific computing
Crout Versions of ILU for General Sparse Matrices

SIAM Journal on Scientific Computing
Error Estimation for Reduced-Order Models of Dynamical Systems

SIAM Journal on Numerical Analysis

Reduced order models based on local POD plus Galerkin projection

Journal of Computational Physics

Quantified Score

Hi-index	31.45

Visualization

Abstract

This paper presents several acceleration techniques for reduced-order models based on the proper orthogonal decomposition (POD) method. The techniques proposed herein are: (i) an algorithm for splitting the database of snapshots generated by the full-order model; (ii) a method for solving quasi-symmetrical matrices; (iii) a strategy for reducing the frequency of the projection. The acceleration techniques were applied to a POD-based reduced-order model of the two-phase flows in fluidized beds. This reduced-order model was developed using numerical results from a full-order computational fluid dynamics model of a two-dimensional fluidized bed. Using these acceleration techniques the computational time of the POD model was two orders of magnitude shorter than the full-order model.