@inproceedings{BertramJankeFlassigetal.2025, author = {Bertram, Hamun and Janke, Christian and Flassig, Robert and Flassig, Peter}, title = {Efficient ML-Based Prediction of Turbomachinery Blade Performance With B-Spline Surface Representation}, series = {ASME Turbo Expo 2025: Turbomachinery Technical Conference and Exposition, Memphis, Tennessee, USA, 2025}, booktitle = {ASME Turbo Expo 2025: Turbomachinery Technical Conference and Exposition, Memphis, Tennessee, USA, 2025}, publisher = {ASME}, isbn = {978-0-7918-8886-5}, doi = {10.1115/GT2025-152689}, pages = {13}, year = {2025}, abstract = {In turbomachinery blade design, rapid and accurate performance prediction is essential to accelerate optimization and reduce reliance on costly high-fidelity simulations. Traditional data-driven approaches often use dense surface point-cloud representations as input features, requiring extensive training datasets and computational resources. This work presents a more efficient methodology leveraging a compact B-Spline-based surface representation, where control points serve as input features, significantly reducing geometric dimensionality and computational overhead. A systematic Design of Experiments (DoE) is performed to generate a diverse set of blade geometries for NASA Rotor 67. Each design is evaluated via computational fluid dynamics (CFD) simulations in ANSYS CFX, providing key aerodynamic performance metrics such as isentropic efficiency. We train and compare Graph Convolutional Neural Networks (GCNN) and Random Forest Regression (RFR) models to predict blade performance directly from the reduced control-point parameterization. Incorporating first- and second-order geometric derivatives (gradients and Laplacians) into the feature set significantly enhances predictive accuracy and stability, capturing essential curvature-related flow physics. Results demonstrate that this B-Spline-based, CAD-centric methodology can achieve competitive accuracy in predictions with as few as 150-200 training simulations—comparable to other GCNN-based approaches. Consequently, the proposed framework reduces training overhead from days to minutes, enabling faster, more cost-effective turbomachinery design workflows and guiding optimization toward high-performing blade geometries.}, language = {en} } @inproceedings{MuellerMarkgrafVogeletal.2025, author = {M{\"u}ller, Katja and Markgraf, Klaus and Vogel, Andreas and Flassig, Peter and Flassig, Robert}, title = {Numerical Study of Ice Accretion on Fan Blades: Implications for the Design of Blade Geometries}, series = {ASME Turbo Expo 2025: Turbomachinery Technical Conference and Exposition, Memphis, Tennessee, USA, 2025}, booktitle = {ASME Turbo Expo 2025: Turbomachinery Technical Conference and Exposition, Memphis, Tennessee, USA, 2025}, publisher = {ASME}, isbn = {978-0-7918-8887-2}, doi = {10.1115/GT2025-152704}, pages = {12}, year = {2025}, abstract = {Ice formation on aircraft components due to the impact of supercooled droplets poses a severe safety risk. In particular, the formation of ice on the fan blades can lead to vibrations that affect the entire engine. While numerous studies have examined the effects of environmental conditions on ice accumulation, the influence of blade geometry has received little attention. This study investigates how variations in blade geometry affect ice accretion in a low-pressure compressor using a numerical approach. A Design of Experiments (DoE) is conducted on the NASA Rotor67, focusing on the sensitivity of ice formation to geometric modifications. The workflow includes geometry generation (ParaBlade), flow simulation (ANSYS CFX), and ice accretion modeling (ANSYS FENSAP-ICE) under rime ice conditions. The results reveal a strong correlation between the inlet metal angle and both accreted ice mass and maximum ice thickness. Furthermore, designs with good aerodynamic performance tend to exhibit higher ice accumulation. These findings enhance the understanding of icing behavior in low-pressure compressors and offer valuable insights for optimizing blade design in adverse environmental conditions.}, language = {en} } @article{VogelWoelferRamirezDiazetal.2020, author = {Vogel, Sven and W{\"o}lfer, Christian and Ramirez-Diaz, Diego and Flassig, Robert and Sundmacher, Kai and Schwille, Petra}, title = {Symmetry Breaking and Emergence of Directional Flows in Minimal Actomyosin Cortices}, series = {Cells}, journal = {Cells}, publisher = {MDPI}, doi = {10.3390/cells9061432}, pages = {1 -- 10}, year = {2020}, abstract = {Cortical actomyosin flows, among other mechanisms, scale up spontaneous symmetry breaking and thus play pivotal roles in cell differentiation, division, and motility. According to many model systems, myosin motor-induced local contractions of initially isotropic actomyosin cortices are nucleation points for generating cortical flows. However, the positive feedback mechanisms by which spontaneous contractions can be amplified towards large-scale directed flows remain mostly speculative. To investigate such a process on spherical surfaces, we reconstituted and confined initially isotropic minimal actomyosin cortices to the interfaces of emulsion droplets. The presence of ATP leads to myosin-induced local contractions that self-organize and amplify into directed large-scale actomyosin flows. By combining our experiments with theory, we found that the feedback mechanism leading to a coordinated directional motion of actomyosin clusters can be described as asymmetric cluster vibrations, caused by intrinsic non-isotropic ATP consumption with spatial confinement. We identified fingerprints of vibrational states as the basis of directed motions by tracking individual actomyosin clusters. These vibrations may represent a generic key driver of directed actomyosin flows under spatial confinement in vitro and in living systems.}, language = {en} } @inproceedings{MuellerFlassigFlassig2024, author = {M{\"u}ller, Katja and Flassig, Peter and Flassig, Robert}, title = {Numerical Simulations and Sensitivity Analysis of Ice Formation on Fan Blades}, series = {ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition, London, 2024}, booktitle = {ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition, London, 2024}, publisher = {ASME}, isbn = {978-0-7918-8806-3}, doi = {10.1115/GT2024-125715}, pages = {10}, year = {2024}, abstract = {In-flight icing, the formation of ice during flight, poses risks to the safety and reliability of aircraft. Due to environmental conditions, ice accumulation occurs on the low-pressure compressor blades of an engine, diminishing aerodynamic performance and potentially causing damage to the engine. Numerical simulations of ice accretion are conducted on the blades of the NASA Rotor 67 utilizing the Computational Fluid Dynamics (CFD) software ANSYS CFX and the in-flight icing software FENSAP-ICE. One-dimensional and two-dimensional sensitivity studies aim to analyze the influences of temperature, droplet diameter and liquid water content (LWC) on the resulting ice build-up on the blade. The analyses reveal that ice accumulates predominantly at the leading edge of the blade, where collection efficiency is maximal. Additionally, an ice layer forms at the blade root on the pressure side. While LWC and temperature exerts a significant influence on the ice mass, only a marginal impact on droplet diameter is observed.}, language = {en} } @inproceedings{VogelGoschinFlassig2022, author = {Vogel, Mathias and Goschin, Tobias and Flassig, Robert}, title = {Techno-economic analysis of excess wind energy utilization in the energy supply of residential quarters}, series = {Konferenz: Symposium on Control of Power and Energy Systems (CPES), 2022/ Konferenzband:11th IFAC Symposium on Control of Power and Energy Systems (CPES 2022)}, booktitle = {Konferenz: Symposium on Control of Power and Energy Systems (CPES), 2022/ Konferenzband:11th IFAC Symposium on Control of Power and Energy Systems (CPES 2022)}, publisher = {Elsevier}, doi = {10.32479/ijeep.8067}, pages = {558}, year = {2022}, language = {en} } @article{GoschinVogelFlassig2022, author = {Goschin, Tobias and Vogel, Mathias and Flassig, Robert}, title = {Energy Technologies For Decarbonizing The Steel Processing Industry - A Numerical Study}, series = {IFAC-PapersOnLine}, volume = {55}, journal = {IFAC-PapersOnLine}, number = {9}, publisher = {Elsevier}, doi = {https://doi.org/10.1016/j.ifacol.2022.07.001}, pages = {1 -- 5}, year = {2022}, abstract = {This study analyzes approaches to decarbonize the energy supply of the secondary steel processing industry. Therefore, real data from a secondary steel production company is used in combination with state-of-the art low carbon energy supply technologies. Also, the use of waste heat from a pusher furnace for process integration is considered. The developed temporal process model allows holistic optimizing and expanding the steel making process system regarding techno-economic criteria. As we show, implementing the annual heat demand of a municipality shows that a nearly 100 \% self-sufficient heat supply is possible.}, language = {en} }