Optimization of steady spin prediction by nonlinear iterative inversion algorithm

Abstract

Purpose

Since the inception of aircraft, the phenomenon of spin has persistently accompanied aircraft, and research into spin has been ongoing. This paper aims to introduce an optimization technique to enhance the traditional geometric method for predicting steady spin, aiming to achieve more precise predictive outcomes.

Design/methodology/approach

To begin with, the force and moment equations used for motion analysis are initially presented, followed by the establishment of the motion model. Subsequently, the forward problem is set up, and the equilibrium solutions for the left and right spins of the aircraft are determined using the geometric method under the basic and wingtip configurations, thus solving the forward problem. In the final stage, nonlinear inversion is applied, and the inversion objective function is formulated based on the least squares approach. Through iterative processes, the measured data are interpolated, leading to the acquisition of the accurate equilibrium solution.

Findings

The findings indicate that the utilization of the nonlinear iterative inversion algorithm has effectively optimized the geometric method, yielding favorable outcomes. Postoptimization, the prediction accuracy has been enhanced, and the error has significantly diminished when compared to the preoptimization results.

Originality/value

The nonlinear inversion algorithm is used to refine the steady spin prediction for general aviation aircraft. This approach significantly mitigates the precision issues inherent in the forward problem. As demonstrated through the simulations provided, the application of the nonlinear iterative algorithm to resolve the inversion function yields promising optimization outcomes.

Citation

Yan, C. and Tu, L. (2024), "Optimization of steady spin prediction by nonlinear iterative inversion algorithm", Aircraft Engineering and Aerospace Technology, Vol. 96 No. 5, pp. 726-735. https://doi.org/10.1108/AEAT-08-2023-0210