Response Surface Method Based on Radial Basis Functions for Modeling Large‐Scale Structures in Model Updating

Abstract

The response surface (RS) method based on radial basis functions (RBFs) is proposed to model the input–output system of large‐scale structures for model updating in this article. As a methodology study, the complicated implicit relationships between the design parameters and response characteristics of cable‐stayed bridges are employed in the construction of an RS. The key issues for application of the proposed method are discussed, such as selecting the optimal shape parameters of RBFs, generating samples by using design of experiments, and evaluating the RS model. The RS methods based on RBFs of Gaussian, inverse quadratic, multiquadric, and inverse multiquadric are investigated. Meanwhile, the commonly used RS method based on polynomial function is also performed for comparison. The approximation accuracy of the RS methods is evaluated by multiple correlation coefficients and root mean squared errors. The antinoise ability of the proposed RS methods is also discussed. Results demonstrate that RS methods based on RBFs have high approximation accuracy and exhibit better performance than the RS method based on polynomial function. The proposed method is illustrated by model updating on a cable‐stayed bridge model. Simulation study shows that the updated results have high accuracy, and the model updating based on experimental data can achieve reasonable physical explanations. It is demonstrated that the proposed approach is valid for model updating of large and complicated structures such as long‐span cable‐stayed bridges.

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