A New Aerodynamic Optimization Method with the Consideration of Dynamic Stability

Mi Baigang,Wang Xiangyu,Giacomo V Iungo

doi:10.1155/2021/5551094

Abstract

Dynamic stability is significantly important for flying quality evaluation and control system design of the advanced aircraft, and it should be considered in the initial aerodynamic design process. However, most of the conventional aerodynamic optimizations only focus on static performances and the dynamic motion has never been included. In this study, a new optimization method considering both dynamic stability and general lift-to-drag ratio performance has been developed. First, the longitudinal combined dynamic derivative based on the small amplitude oscillation method is calculated. Then, combined with the PSO (particle swarm optimization) algorithm, a dynamic stability derivative that must not be decreased is added to the constraints of optimization and the lift-drag ratio is chosen as the optimization objective. Finally, a new aerodynamic optimization method can be built. We take NACA0012 as an example to validate this method. The results show that the dynamic derivative calculation method is effective and conventional optimization design can significantly improve the lift-drag ratio. However, the dynamic stability is enormously changed at the same time. By contrast, the new optimization method can improve the lift-drag performance while maintaining the dynamic stability.

Highlights

As one type of the advanced transport systems, highperformance airfoil and aircraft configurations are increasingly important for the whole design cycle of advanced aircrafts
Panagant et al [17] investigated the comparative performance of fourteen new and established multiobjective metaheuristics when solving truss optimization problems, which gave us a brief introduction and comparison of the generally used algorithms. These previous studies indicates that the various improved optimization algorithms have been widely used on the aerodynamic design; these jobs only focus on the static aerodynamic performance; the aerodynamic optimization design combined with dynamic characteristics is rare
Based on the CFD calculation method, the dynamic derivative is identified in real time by using the small-amplitude forced vibration process, and combined with the particle swarm optimization (PSO) algorithm, the new optimization method considering both static and dynamic aerodynamic characteristics can be much more practical during the aerodynamic design of the advanced aircraft

Summary

Introduction

As one type of the advanced transport systems, highperformance airfoil and aircraft configurations are increasingly important for the whole design cycle of advanced aircrafts. Panagant et al [17] investigated the comparative performance of fourteen new and established multiobjective metaheuristics when solving truss optimization problems, which gave us a brief introduction and comparison of the generally used algorithms These previous studies indicates that the various improved optimization algorithms have been widely used on the aerodynamic design; these jobs only focus on the static aerodynamic performance; the aerodynamic optimization design combined with dynamic characteristics is rare. Based on the CFD calculation method, the dynamic derivative is identified in real time by using the small-amplitude forced vibration process, and combined with the particle swarm optimization (PSO) algorithm, the new optimization method considering both static and dynamic aerodynamic characteristics can be much more practical during the aerodynamic design of the advanced aircraft

Aerodynamic Optimization Methods

Calculation and Validation

Conclusions

Findings

Conflicts of Interest