The Thermofluiddynamics Project offers insights into current research topics in the Laboratory for Flow Instabilities and Dynamics. This includes questions from areas such as flow and flame dynamics, flow control, instabilities in reacting flows or special methods of data analysis.

This semester, there will be a focus on optimization methods and CFD. In the thermofluiddynamics project, students will get a deeper insight into this field and work on solutions for real-world research problems.

In two current research projects, we are interested in running a RANS simulation that matches high-fidelity reference data (from PIV measurements and LES data) as good as possible. To align RANS results to reference data different features of the simulation can be optimized (turbulence model, model constants, boundary conditions, etc.). The goal of the project is to write a python code that is capable to modify the OpenFoam case (adjust input parameters like turbulence model etc.), run the OpenFoam simulation, read results, compute an error measure and optimize the input parameters.

Ideally, these steps are performed iteratively by an algorithm that identifies optimal adjustments to fit the RANS results to reference data. We would like you to work in collaboration on one code repository using git. A short introduction to version control with git and the TU gitlab will be part of the project.

Relevant for this project is theoretical knowledge in Fluid Mechanics and CFD and practical experience in Python. Practical experience with OpenFoam would be helpful.

The project will take place in summer semester 2023. There will be weekly meetings and the project will be completed with a report and a presentation of the results.