Year: 2021
Type: preprint
Abstract: A novel methodology of robust dynamic optimization of a dual-rotor system based on polynomial chaos expansion (PCE) is developed in this paper. The dual-rotor system model was built by the Timoshenko theory and the finite element method. Instead of the direct Monte Carlo simulation (MCS), the PCE of the present dual-rotor system under support stiffness uncertainty is generated to facilitate a rapid analysis of stochastic responses and yield desirable results in significantly less number of functional evaluations. The PCE is explored as a basis for robust optimization, focusing on the problem of minimizing the unbalance response at operating conditions while minimizing its sensitivity to uncertainty in the support stiffness. This strategy avoids the use of MCS in order to effectively increase the efficiency of the optimization and significantly reduce the computing cost and time spending. The robust dynamic optimization attempts to both optimize the mean performance and minimizes the variance of the performance simultaneously. The multi-objective optimization results show that vibration response can be decreased and is significantly less sensitive to the variation of design parameters compared with initial design case by matching of unbalance amplitude and phase angle differences. Implementation of the proposed robust dynamic optimization in the present dual-rotor system illustrates its potential for further complicated applications.
Source: Research Square
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3134057902