Future development of new modeling strategies for complex flows applications requires simulation data of specific benchmark problems which cover a wide range of flow problems. The need of such data is twofold. First, in classical method development, a wide range of validation data is required to test new models in different flow scenarios. Second, the model development based on machine learning (ML) not only necessitates an increasing amount of data for validation purposes but also for the training of new ML models. Thus, the goal of this project is to build up an open-source database in addition to the open-source flow solver FLEXI to provide a publicly accessible database of benchmark flow problems.
For more information check the project page of the associated project PN 1A-1.