Improved approximations to the Wagner function using sparse identification of nonlinear dynamics

TL;DR

This paper introduces a novel method using sparse identification of nonlinear dynamics (SINDy) to accurately approximate the Wagner function across all time scales, improving upon existing approximations in unsteady aerodynamics.

Contribution

The paper develops a SINDy-based approach to model the Wagner function as a nonlinear differential equation, enhancing accuracy especially for long-time behavior.

Findings

SINDy-based models accurately approximate the Wagner function.

The method applies to realistic aerodynamic systems with finite thickness airfoils.

First- and second-order differential equations provide flexible modeling options.

Abstract

The Wagner function in classical unsteady aerodynamic theory represents the response in lift on an airfoil that is subject to a sudden change in conditions. While it plays a fundamental role in the development and application of unsteady aerodynamic methods, explicit expressions for this function are difficult to obtain. The Wagner function requires computation of an inverse Laplace transform, or similar inversion, of a non-rational function in the Laplace domain, which is closely related to the Theodorsen function. This has led to numerous proposed approximations to the Wagner function, which facilitate convenient and rapid computations. While these approximations can be sufficient for many purposes, their behavior is often noticeably different from the true Wagner function, especially for long-time asymptotic behavior. In particular, while many approximations have small maximum absolute error across all times, the relative error of the asymptotic behavior can be substantial. As well as documenting this error, we propose an alternative approximation methodology that is accurate for all times, for a variety of accuracy measures. This methodology casts the Wagner function as the solution of a nonlinear scalar ordinary differential equation, which is identified using a variant of the sparse identification of nonlinear dynamics (SINDy) algorithm. We show that this approach can give accurate approximations using either first- or second-order differential equations. We additionally show that this method can be applied to model the analogous lift response for a more realistic aerodynamic system, featuring a finite thickness airfoil and a nonplanar wake.