The reduction of noise and vibration of composite panels in aircraft through multi-dimensional particle swarm optimization

Abstract

The reduction of noise and vibrations on aircraft poses a unique challenge. This paper explores the use of multi-dimensional Particle Swarm Optimization (PSO) to reduce vibrations and transmitted noise in composite fuselage panels excited by turbulent boundary layer flow. Turbulent boundary layer Power Spectral Density (PSD) data is used to simulate the excitation of simply supported aircraft panels. A comparison is made between isotropic aluminum 2024-T3 panels and optimized composite panels of varying composition for the assessment of success in noise transmission reduction as well as structural function. The algorithm for PSO is implemented in Python and iterates through composites with varying thickness, ply makeup, ply orientation, and materials. Python allows for complex algorithms to be easily interfaced with Finite Element Analysis (FEA) programs. In the current study, ANSYS is used to determine the spectral response of the panels subject to turbulent flow using the superposition of the modes of vibration. During the optimization process, optimization parameters are updated in each iteration based on the success of reducing the spectral response of the panel without compromising its structural integrity or increasing its weight beyond a reasonable threshold.