Code and data repositories
Open data sets
Geometry with performance and inter-row traverse measurements of a 4½-stage high-speed axial compressor (TFD-4AC)
Stoewer, M., Franke, P., Seume, J. R.; Mimic, D. (2025): 4½-stage high-speed axial compressor open test case of the Institute of Turbomachinery and Fluid Dynamics at Leibniz University Hannover.
Data set. LUIS. DOI: 10.25835/6cyjv3yq
URL: https://gitlab.uni-hannover.de/tfd_compressor_group/tfd-4ac_opentestcase
Steady-state and unsteady Reynolds-averaged Navier-Stokes simulations (TFD-4AC, quasi-3D model around mid-span)
Blechschmidt, D.; Mimic, D. (2025): Predicting Time-Averaged Unsteady Flows in Turbomachinery via Graph Neural Networks. Data set. LUIS. DOI: 10.25835/q7jqo97d
Code repositories
GitLab repository of my working group:
https://gitlab.uni-hannover.de/tfd_compressor_group
Tool for the preliminary design of mixed-flow, axial and radial compressors in fuel-cell propulsion:
https://gitlab.uni-hannover.de/tfd_compressor_group/marcel
High-fidelity graph neural network (GNN) for prediction of time-averaged unsteady flow effects in compressors:
https://gitlab.uni-hannover.de/tfd_compressor_group/published_codes/predicting-time-averaged-unsteady-flows-in-turbomachinery-via-graph-neural-networks
Low-fidelity deep neural network (DNN) for prediction of cooling impact on compressor performance:
https://gitlab.uni-hannover.de/tfd_compressor_group/published_codes/performance-prediction-of-cooled-compressors-using-neural-networks