Blade mistuning in blisks arises primarily from the scatters of blade geometry profiles caused by manufacturing tolerance, in-service wear, blade repairs, etc. There is a recent trend to capture the blade-to-blade geometry variances through precise geometry measurements by a 3D optical scanning system in order to obtain an improved blade geometric mistuning evaluation capability. However, this usually leads to prohibitive computational costs due to the large-scale, high-fidelity industrial blisk finite element models. This paper develops an original model reduction approach, Sector Mode Assembling Reduction Technique (SMART), specifically for the high-fidelity blisk model fully mistuned by blade geometric variances, with either topologically compatible or incompatible blade meshes. The basic idea of SMART is to construct the sector-level reduction mode basis by strategically assembling the truncated cyclic modes independently computed for each “isolated” sector with assumed cyclic symmetry at the sector interfaces. Benefiting from the block structure of the SMART mode basis, the reduced-order models are derived by a series of sector-level projections with a relatively low memory requirement and computational cost. Another hidden benefit is that the SMART approach enables efficient structural modification predictions of the global blisk modes because only the modes of the sectors undergoing blade modification need to be re-evaluated and replaced in the SMART mode basis. The SMART approach is applied into a high-fidelity “as-measured model” of a blended blisk, constructed upon the geometry measurement by the state-of-the-art 3D optical scanning technology. It is fully demonstrated that the reduced-order model derived by SMART, featured by a minimal size, is able to reproduce the dynamics of the full-order as-measured blisk model with high accuracy.


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    Title :

    Sector Mode Assembling Reduction Technique for High-Fidelity Blisk Models with Geometry Mistuning


    Contributors:
    Zhou, Biao (author) / Zhao, Jingchao (author) / Ye, Nan (author) / Berruti, Teresa M. (author)

    Published in:

    AIAA Journal ; 61 , 1 ; 406-415


    Publication date :

    2022-09-16


    Size :

    10 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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