TY - GEN
T1 - Combinatorial optimization of mistuned blade rearrangement based on reduced-order FEA model
AU - Liu, Tianyuan
AU - Guo, Ding
AU - Zhang, Di
AU - Xie, Yonghui
N1 - Publisher Copyright:
© 2017 ASME.
PY - 2017
Y1 - 2017
N2 - This paper is focused on the optimization of mistuned blades assembling rearrangement under the forced response. First, in order to avoid the greatly increase of the calculation greatly by the whole circle bladed-disk finite element model, a reduced-order model is developed based on the component mode synthesis. CPU+GPU heterogeneous architecture parallel computation is used to accelerate modal analysis of the disk and blade sectors substructures. Second, a modified ant colony algorithm is applied to the combinatorial optimization to find the optimal rearrangement pattern of bladed-disk assembly. Different from classical algorithm, the individual mistuned information is used to construct heuristic function based on intentional mistuning pattern, which can avoid slow convergence of ant colony algorithm and increase the search speed efficiently. At last, a high-fidelity 3D FEM model with 43 mistuned blades is used to demonstrate the capabilities of the techniques in reducing the maximum displacement resonance response of the bladed-disk system. The numerical simulation showed that this program based on the reducedorder model proposed in this article gained 4.3 speedup compared with ANSYS full model under the scale of 500k nodes. The displacement response amplitude of the blades decreased by 32% with 60 steps (1200 times FEM calculation) by the new optimization method. The physical mechanism of reducing the bladed-disk response is explained by comparing the optimized and worst arrangement patterns. The results clearly demonstrate that the optimized rearrangement pattern of mistuned blades is able to reduce the response amplitude of the forced vibration significantly, and the algorithm proposed in this article is practical and effective.
AB - This paper is focused on the optimization of mistuned blades assembling rearrangement under the forced response. First, in order to avoid the greatly increase of the calculation greatly by the whole circle bladed-disk finite element model, a reduced-order model is developed based on the component mode synthesis. CPU+GPU heterogeneous architecture parallel computation is used to accelerate modal analysis of the disk and blade sectors substructures. Second, a modified ant colony algorithm is applied to the combinatorial optimization to find the optimal rearrangement pattern of bladed-disk assembly. Different from classical algorithm, the individual mistuned information is used to construct heuristic function based on intentional mistuning pattern, which can avoid slow convergence of ant colony algorithm and increase the search speed efficiently. At last, a high-fidelity 3D FEM model with 43 mistuned blades is used to demonstrate the capabilities of the techniques in reducing the maximum displacement resonance response of the bladed-disk system. The numerical simulation showed that this program based on the reducedorder model proposed in this article gained 4.3 speedup compared with ANSYS full model under the scale of 500k nodes. The displacement response amplitude of the blades decreased by 32% with 60 steps (1200 times FEM calculation) by the new optimization method. The physical mechanism of reducing the bladed-disk response is explained by comparing the optimized and worst arrangement patterns. The results clearly demonstrate that the optimized rearrangement pattern of mistuned blades is able to reduce the response amplitude of the forced vibration significantly, and the algorithm proposed in this article is practical and effective.
UR - https://www.scopus.com/pages/publications/85028966147
U2 - 10.1115/GT2017-63867
DO - 10.1115/GT2017-63867
M3 - 会议稿件
AN - SCOPUS:85028966147
T3 - Proceedings of the ASME Turbo Expo
BT - Structures and Dynamics
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition, GT 2017
Y2 - 26 June 2017 through 30 June 2017
ER -