![]() ![]() You will design and develop a real-time, AI-based active flow control system able to control laminar-turbulent transition. (3) AI-based flow control for Transition Delay. You will use experimental and numerical data sets to develop and compare Artificial Neural Network surrogate models for wind-turbine blade unsteady surface pressures and tractions. (2) Artificial Neural Networks for unsteady wind turbine loads. Your role is to develop a large Direct Numerical Simulation database of transitional flows and use AI algorithms to extract informed and predictive models of the underlying physical processes. (1) Prediction of roughness-induced transition using AI. This research will lead to models that can be used to design more efficient aircraft and wind farms, and to the development of a new category of AI algorithms able to autonomously control sensors and actuators to manage complex flows and improve aerodynamic performance. Our objective is to combine human and machine insights to get to the essence of complex physical flows, be it in air, water or other media. Using AI algorithms, the AIFluids Lab will leverage numerical and experimental data to build interpretable models of transition and turbulence. New experimental techniques and high-fidelity flow simulations are providing larger and more detailed datasets. The AIFluids Lab is focused on two major challenges of fluid mechanics: the prediction and the control of complex, transitional and turbulent flows. Designing more efficient aircrafts and wind farms requires a deeper understanding of complex flows. The AIFluids lab was recently established to foster the use of AI in the Aerospace Sciences. ![]() TU Delft is a top tier university and is exceedingly active in the field of Artificial Intelligence. ![]()
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