Abstract
Hybrid simulation has emerged as a relatively accurate and efficient tool for the evaluation of structural response under earthquake loading. In conventional hybrid simulation the response of a few critical components is obtained by testing while the numerical module is assumed to follow an analytical idealization. Where there is a much larger number of analytical components compared to the experimental parts, the overall response may be dominated by the idealized parts hence the value of hybrid simulation is diminished. It is proposed to modify the material constitutive relationship of the numerical model during the test, based on the data obtained from the physically tested component. An approach based on genetic algorithms is utilized as an optimization tool to identify the constitutive relationship parameters used in updating the numerical model. The proposed model updating approach is verified through two analytical examples of steel and reinforced concrete frames. The results show the effectiveness of the updating process in minimizing the errors, compared to the assumed exact solution.
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