Parallel intelligent algorithm analysis of optimization arrangement on mistuned blades based on compute unified device architecture

This paper sets up a parameterized model of engine-bladed disk system. Then a method of mistuned parameter identification is proposed, which consists of static frequency test of blades, dichotomy, and finite element analysis. Dynamic genetic ant colony optimization combined algorithm is presented which is used as a bladed arrangement optimization method. It combines the advantage of ant colony algorithm and genetic algorithm. By this way, the local and global search ability is introduced and the disadvantage of a single algorithm is overcome. The improved parallel algorithm comes up with graphics processing unit based on compute unified device architecture and its performance is analyzed. The results show that using optimization results can reduce the amplitude and localization of forced vibration response of bladed-disk system. At the same time, optimization based on compute unified device architecture framework can improve computing speed. Providing support for engineering application in terms of effectiveness and efficiency.