Coarse Grid CFD for Fast Modeling of Indoor Environments: Why NOT?

Large-scale CFD analysis requires extended time and computing resource, and in recent years reduced order modeling techniques are developed. Among many of these techniques, proper orthogonal decomposition (POD) stands out as a preferable method. POD allows the processing of large amounts of high-dimensional data with the aim of obtaining low-dimensional descriptions that capture much of the analyzed phenomena. Here, we discuss how POD is used to overcome the issues addressed from the traditional CFD method and show how POD can be used for data center analyses. Both CFD and POD methods are compared in terms of running time and accuracy.