Finite element model updating based on response surface methodology

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This chapter presents the response-surface method for finite-element-model updating.The response-surface method was implemented by approximating the finite-element surface-response equation by a multi-layer perceptron, which is a neural-network technique.

The presented method is compared to existing methods that use simulated annealing and a genetic algorithm separately, with a full finite-element model for model updating.The results have been compared with those obtained from the traditional sensitivity-based FE model updating method.The real application to a full-size bridge has demonstrated that the FE model updating process is efficient and converges fast with the response surface to replace the original FE model.With the response surface at hand, an optimization problem is formulated explicitly.

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Hence, no FE calculation is required in each optimization iteration.

Based on sensitivity analysis, set of model parameters was selected for the model updating process.

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