34 citations · 41 across the 9 of their papers we have counts for
4 papers · 1 filter
Spatio-Temporal Prediction of Unsteady Airfoil Aerodynamics Using Augmented Graph Neural Ordinary Differential Equations with Exogenous Controls
Henrik Lange, Reik Thormann, Philipp Bekemeyer
Unsteady aerodynamic phenomena, such as gusts, turbulence, and fluid-structure interactions affect an aircraft during flight. For design, optimisation and certification, it is indi…
Goal-Driven Adaptive Sampling Strategies for Machine Learning Models Predicting Fields
Jigar Parekh, Philipp Bekemeyer
Machine learning models are widely regarded as a way forward to tackle multi-query challenges that arise once expensive black-box simulations such as computational fluid dynamics a…
Fusing CFD and measurement data using transfer learning
Alexander Barklage, Philipp Bekemeyer
Aerodynamic analysis during aircraft design usually involves methods of varying accuracy and spatial resolution, which all have their advantages and disadvantages. It is therefore…
Predicting Onflow Parameters Using Transfer Learning for Domain and Task Adaptation
Emre Yilmaz, Philipp Bekemeyer
Determining onflow parameters is crucial from the perspectives of wind tunnel testing and regular flight and wind turbine operations. These parameters have traditionally been predi…