Estimating a nonparametric data-driven model of the lift on a pitching wing. Issue 5 (September 2020)

• Record Type: Journal Article
• Authors: Siddiqui, M F; Decuyper, J; Csurcsia, P Z; Ertveldt, J; Troyer, T De; Schoukens, J; Runacres, M C
• Is Part Of: Journal of physics. Volume 1618:Issue 5(2020)
• Publication Date: 2020-09
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1618/5/052018
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In aerodynamics, as in many engineering applications, a parametrised mathematical model is used for design and control. Often, such models are directly estimated from experimental data. However, in some cases, it is better to first identify a so-called nonparametric model, before moving to a parametric model. Especially when nonlinear effects are present, a lot of information can be gained from the nonparametric model and the resulting parametric model will be better. In this article, we estimate a nonparametric model of the lift force acting on a pitching wing, using experimental data. The experiments are done using the Active Aeroelastic Test Bench (AATB) setup, which is capable of imposing a wide variety of motions to a wing. The input is the angle of attack and the output is the lift force acting on the NACA 0018 wing. The model is estimated for two different types of input signal, swept sine and odd-random multisine signals. The experiments are done at two different pitch offset angles (5° and 20°) with a pitch amplitude of 6°, covering both the linear and nonlinear aerodynamic flow regime. In the case of odd-random multisines nonlinearity on the FRF is also estimated. We show that the level and characterisation of the nonlinearity in the output can be resolved through a nonparametric model, and that it serves as a necessary step in estimating parametric models.