| Autor: |
Tim De Troyer, Péter Zoltán Csurcsia, Muhammad Faheem Siddiqui, Mark Runacres |
| Přispěvatelé: |
Thermodynamics and Fluid Mechanics Group, Engineering Technology, Acoustics & Vibration Research Group, Faculty of Engineering |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Zdroj: |
Vrije Universiteit Brussel |
| Popis: |
Understanding unsteady aerodynamic forces on a lifting surface is crucial for many engineering applications. This work demonstrates the use of system identification techniques for the data-driven modelling of the aerodynamic lift force on a pitching wing. This lift force can be considered as a (nonlinear) dynamic function of the angle of attack. The proposed approach consists of multiple steps: 1) excitation by the means of broadband excitation, 2) pre-processing of the measurement, and 3) data-driven modelling techniques. The considered excitation signal is the so-called multisine (also known as periodic pseudo- random noise). However, dynamic stall is known to exhibit important cluster-to-cluster variations and this is no different when utilizing multisines. Therefore, we cluster the data before the actual data-driven Preliminary proceedings modeling and validation. We show that the obtained models can capture the nonlinear aerodynamic forces more accurately than the classical linear and semi-empirical models. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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