Nonlinear model reduction with application to rapid thermal processing

The proper orthogonal decomposition, also called snapshot method, is a nonlinear model order reduction method where reduction of the size of the state space is achieved using a singular value decomposition of a matrix of snapshots of the state vector. This method has been shown to work well for a simple lumped physical model of a rapid thermal processing chamber. Although a substantial reduction of the number of states is achieved, some numerical computations still need to be performed in the high-dimensional state which is computationally expensive. In this paper we demonstrate how this can be avoided using aggregation of terms, resulting in a significant model simulation speed improvement