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

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, and (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. Preprint submitted to Journal of Computational Physics 23 April 2008