Project description
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.
Project information
Project title | Open-source simulation data for validation and machine learning |
Project leaders | Andrea Beck, Claus-Dieter Munz, Johan Larsson (University of Maryland) |
Project duration | January 2021 - December 2022 |
Project number | PN 1A-1 |

Andrea Beck
Prof. Dr.-Ing.Numerical Methods in Fluid Mechanics

Claus-Dieter Munz
Prof. Dr. rer. nat.Numerical Methods in Fluid Mechanics
[Image: SimTech/Max Kovalenko]