Application of Incremental Proper Orthogonal Decomposition for the Reduction of Very Large Transient Flow Field Data

抄録

With the increase of available computer performance, unsteady Computational Fluid Dynamics (CFD) is now widely used for industrial applications. For the analysis of unsteady vehicle aerodynamics, massive data storage is required for saving time series of spatially highly resolved flow fields. The size of these transient datasets can be significantly reduced using the Incremental Proper Orthogonal Decomposition (POD) by computing POD modes in parallel to the CFD. In this paper, we present a successful approximation of the transient flow field using a reduced number of modes computed by Incremental POD.