Abstract

This paper develops the Kron's substructuring method for updating large-scale nonlinear structures. The global structure is divided into linear and nonlinear substructures. By using a transform basis, the global vibration equation is reduced to the master modal responses of linear substructures and responses of nonlinear substructures only. The sensitivity-based nonlinear model updating is then conducted on the reduced vibration equation. The element parameters in the linear and nonlinear substructures can be adjusted simultaneously so that the predicted responses match the measurement ones in an optimal manner. Only the concerned substructures and the reduced equation are re-analyzed in the optimization process, thus reducing the computational load compared with the traditional model updating methods on the global structure. Application to a nine-story frame with nonlinear base isolations demonstrates that the proposed method is very accurate and efficient in updating the linear and nonlinear parameters simultaneously with a few measured responses. The effects of measurement noise and the number of measurement points on the updating results are also investigated.

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