Tabu Genetic Cat Swarm Algorithm Analysis of Optimization Arrangement on Mistuned Blades Based on CUDA

Abstract

Tabu genetic cat swarm optimization algorithm is proposed for optimization arrangement on mistuned blades. Furthermore, it is improved to be an innovative parallel algorithm based on Compute Unified Device Architecture (CUDA), whose performance is analyzed both in continuous and discrete solution space. The lumped parameter model and finite element model of the bladed-disk system are established for dynamics analysis and optimization verification. The complete mistuned parameter identification method and the improved mixed-interface prestressed substructure modal synthesis method are two other highlights. The results indicate that the algorithm in this paper has the advantages of low cost and high efficiency. The vibration localization and amplitude of the mistuned bladed-disk system are both reduced significantly. The optimization analysis method is proved to be applicable to the mistuned bladed-disk system of the aeroengine in engineering practice.