In this paper, a sensitivity-based updating method is proposed to reduce the discrepancies between the finite-element model representation of a structure and its experimental counterpart, thus allowing engineers the use of such numerical representation for structural modification prediction, dynamic model synthesis, aeroelastic analysis, and system qualification. The proposed method iteratively minimizes a residual vector of correlation functions, defined on the frequency response functions, to find the mismodeled regions of the finite-element model through the identification of the unknown vector of the updating parameters. The approach provides an enhanced formulation of the Bayesian-based least-square solution technique and a proper numerical relaxation method, thus allowing the updated finite-element model to go beyond the dynamic equivalence with the experimental findings, that is the increase in the correlation between the corresponding modal parameters, by identifying updating parameters that well represent the physical properties of the structure under investigation. A formulation of the weighting matrices that takes into account the uncertainty of the experimental data and the use of the L-curve criterion to numerically relax the solution are presented in the paper. Results from both numerical analyses and experimental investigations are reported to validate the proposed approach and show its robustness.


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    Title :

    Finite-Element Structural Updating Using Frequency Response Functions


    Contributors:
    Arras, M. (author) / Coppotelli, G. (author)

    Published in:

    Journal of Aircraft ; 52 , 5 ; 1454-1468


    Publication date :

    2015-04-08


    Size :

    15 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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    Finite Element Structural Updating using FRFs (AIAA 2014-0492)

    Arras, M. / Coppotelli, G. / American Institute of Aeronautics and Astronautics | British Library Conference Proceedings | 2014