Data-based autonomously discovering method for nonlinear aerodynamic force of quasi-flat plate
Teng Ma, Wei Cui, Ting-Ting Gao, Shengyuan Liu, Lin Zhao, Yaojun Ge
Abstract
Expression of nonlinear aerodynamic phenomena and calculation of nonlinear aeroelastic response require accurate and concise aeroelastic force function. In this paper, a group sparse regression method is used to reveal the nonlinear mapping aerodynamics relationship between motion and force from data. The aeroelastic force function discovered by this method balances modeling accuracy and simplicity. A quasi-flat plate in coupled vertical–torsional harmonic motion is employed as an experimental object in this work. Aerodynamic motion-force dataset is collected by forced motion test in wind tunnel, including 484 cases. The sparse regression analytic result shows that αα̇,α3,α̇3 (α is torsional displacement) can represent the nonlinearity in aerodynamic for all cases, even wind speed, amplitude, amplitude ratio, frequency ratio, and angle of attack are in different combinations.