Abstract
This paper presents a two-step Bayesian optimization (BO) method for identifying the elastoplastic material parameters of structural steels subjected to multi-axial cyclic loading. A series of simple elastic and elastoplastic shaking table tests is conducted for a structure that has a steel specimen experiencing elastoplastic response. An inverse problem is formulated to identify the multi-axial material parameters of the specimen from the structural responses obtained by the shaking table tests. This is notable because it is more difficult to carry out multi-axial static cyclic material tests than to conduct dynamic cyclic structural tests. The inverse problem minimizes the error between the measured structural responses and those simulated by finite element (FE) analysis. The two-step BO devised for solving the inverse problem successfully offers a global optimization framework while considerably reducing the number of costly simulations. It first seeks to infer Young’s modulus values from the cyclic elastic responses of the structure, thereby validating the FE model in its elastic state. It then finds the parameters for the nonlinear combined isotropic/kinematic hardening model of the specimen using the cyclic elastoplastic responses of the structure. Verification results show that the parameters identified by the proposed method well reproduce the cyclic responses of the structure under different cyclic loading conditions.
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