TITLE:
Dynamic Similarity Optimization Design of an Aero-Engine
AUTHORS:
Zuxin Chen, Fei Wang, Shan Zeng, Yancong Lin
KEYWORDS:
Aero-Engine, Dynamic Similarity, Genetic Algorithm, Rotor System
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.15 No.4,
March
27,
2025
ABSTRACT: Aiming at the dynamic similarity design of an aero-engine rotor system, this study proposes a parameterized dynamic similarity design method based on a genetic algorithm, specifically addressing the dynamic equivalence issues between compressor and turbine disk structures. Taking the first three critical speeds of the prototype engine as objective functions, the thickness and diameter parameters of compressor stages and turbine disks were parameterized. Optimization design variables and constraints were established to formulate a dynamic similarity optimization model. By constructing a MATLAB-ANSYS cross-platform collaborative optimization framework, a genetic algorithm-driven single-objective parameter optimization mechanism was developed to iteratively optimize key structural parameters of the model rotor, ultimately obtaining a simplified rotor model dynamically equivalent to the prototype. Results demonstrate that the derived dynamic similarity model effectively predicts the dynamic characteristics of the prototype engine, with relative errors of 0.95%, 0.98%, and 0.28% for the first three critical speeds respectively. Moreover, the first three critical vibration modes show complete consistency, providing a reliable approach for subsequent vibration control in aero-engine rotor systems.