Description:
This book initiates the new Series `Machine Learning Tools in Fluid Mechanics' published by the Technische Universität Braunschweig. The series focuses on machine learning tools for fluid mechanics tasks, like analysis, dynamic modeling, response modeling, control and closures. The tools comprise documentations of publicly available software packages, of good practices and of application studies. Our book introduces the software platform xROM, which is a freely available package for spectral analysis and reduced-order modeling. Initially, xROM was developed as a tool to quickly derive dynamic POD models from snapshot data and Galerkin projection using the Navier-Stokes equations. This purpose has since expanded, and xROM has become a platform that allows easy modular expansions and collaborations with partners worldwide. In this book, however, we focus on POD-based Galerkin modeling for reasons of simplicity.