Novel Frame Model for Mistuning Analysis of Bladed Disk Systems

Jie Yuan, Fabrizio Scarpa, Branislav Titurus, Giuliano Allegri , Sophoclis Patsias, Ramesh Rajasekaran

Research output: Contribution to journalArticle (Academic Journal)peer-review

11 Citations (Scopus)


The work investigates the application of a novel frame model to reduce the computational cost of the mistuning analysis of bladed disc systems. A full-scale finite element (FE) model of the bladed disc is considered as benchmark. The single blade frame configuration is identified via an optimization process. The individual blades are then assembled by 3D springs, whose parameters are determined via calibration process. The dynamics of the novel beam frame assembly is also compared to those obtained from three state-of-the-art FE-based reduced order models (ROMs): a lumped parameter approach; a Timoshenko beam assembly, and component mode synthesis (CMS) based techniques with free and fixed interfaces. The development of these classical ROMs to represent the bladed disc is also addressed in detail. A methodology to perform the mistuning analysis is then proposed and implemented. A comparison of the modal properties and forced response dynamics between the
aforementioned ROMs and the full-scale FE model is presented. The case study demonstrates that the beam frame assembly can predict the variations of the blade amplitude factors with results being in agreement with the full-scale FE model. The CMS based ROMs underestimate the maximum amplitude factor, while the results obtained from beam frame assembly are generally conservative.
The beam frame assembly is 4 times more computationally efficient than the CMS fixed-interface approach. This study proves that the beam frame assembly can efficiently predict the mistuning behavior of bladed discs when low order modes are of interest.
Original languageEnglish
Article number031016
Number of pages13
JournalJournal of Vibration and Acoustics
Issue number3
Early online date24 Apr 2017
Publication statusPublished - Jun 2017

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